Background: Esophageal squamous cell cancer (ESCC) patients with the potentially resectable disease most would experience relapse after surgery. Immunotherapy has been reported to improve the prognosis of advanced esophageal cancer and may be a new strategy to prevent this urgent condition's recurrence. We first evaluated the efficacy and safety of neoadjuvant chemotherapy combined with immunotherapy in patients with resectable ESCC.Methods: All patients with resectable locally advanced ESCC (clinical stage III-IVB). Received at least 1 cycle of neoadjuvant chemotherapy combined with immunotherapy (NACI), and the interval between each cycle and the operation should be at least 3 weeks. All patients were treated with standard surgery. The tumor imaginations were obtained at baseline and within a week before surgery. The efficacy endpoint was the rate of major pathologic response (MPR, 10% viable tumor cells). Expression of immunohistochemicalrelated molecules was investigated in surgical samples. Results: A total of 38 patients with ESCC were included (36 males, median age 61 years), and most of them used Pembrolizumab (55.26%) and Camrelizumab (31.58%). We analyzed 19 patients and found that 13 patients (68.42%) achieved radiological partial response (PR) by CT images. R0 resection was performed in 35 patients (92.11%), and 10 patients (26.32%) developed postoperative complications. Through postoperative pathology, we found 13 (34.21%) patients had complete pathologic response (cPR), and 16 (42.11%) patients achieved MPR. We also found that none of the factors had a statistically significant impact on MPR. Still, the regression rate of Sum of lesion diameter (SLD) was significantly positively correlated with the pathological remission rate (P=0.012, r=0.565). Conclusions: The rate of MPR in ESCC patients reached 42.11%. The use of the NACI regimen did not increase the occurrence of complications in neoadjuvant treatment and operation, and the SLD regression rate has a certain guiding significance for the effect of immunotherapy.

As the most abundant noncoding RNA in cells, tRNA plays an important role in tumorigenesis and development. The report of tRNA on the pathogenesis of lung adenocarcinoma is rare. It is of great clinical significance to explore the relationship between tRNA expression and prognosis of lung adenocarcinoma. The expression level of tRNAs in lung adenocarcinoma tissues and paracarcinoma tissues was detected using a tRNA RT‐qPCR array. A total of 104 lung adenocarcinomas were included in the analysis of the correlation between candidate tRNAs expression and prognosis. A tRNA‐based prognostic model was constructed and validated using Cox proportional hazards regression. A nomogram was built to help clinicians develop treatment strategies. We screened a series of differentially expressed tRNAs between lung adenocarcinoma tissues and paracarcinoma tissues. Among these tRNAs, tRNAAsnATT, tRNAIleAAT, tRNALeuTAA, mt‐tRNATrpTCA, mt‐tRNALeuTAA, tRNAProAGG, tRNALysCTT‐1 and tRNALeuAAG were associated with the clinicopathological characteristics of lung adenocarcinoma. tRNALysCTT‐1, mt‐tRNASerGCT and tRNATyrATA were associated with cancer‐specific survival. We constructed a prognostic model for lung adenocarcinoma using specific tRNA expression levels as reference factors. Multivariate analyses showed that tRNA‐based prognostic score was a significant and important prognostic factor. The prognostic model based on the tRNAs expression signatures can help predict the prognosis of patients with lung adenocarcinoma.

Background Lung adenocarcinoma (LUAD) is a highly malignant and heterogeneous tumor that involves various oncogenic genetic alterations. Epigenetic processes play important roles in lung cancer development. However, the variation in enhancer and super-enhancer landscapes of LUAD patients remains largely unknown. To provide an in-depth understanding of the epigenomic heterogeneity of LUAD, we investigate the H3K27ac histone modification profiles of tumors and adjacent normal lung tissues from 42 LUAD patients and explore the role of epigenetic alterations in LUAD progression. Results A high intertumoral epigenetic heterogeneity is observed across the LUAD H3K27ac profiles. We quantitatively model the intertumoral variability of H3K27ac levels at proximal gene promoters and distal enhancers and propose a new epigenetic classification of LUAD patients. Our classification defines two LUAD subgroups which are highly related to histological subtypes. Group II patients have significantly worse prognosis than group I, which is further confirmed in the public TCGA-LUAD cohort. Differential RNA-seq analysis between group I and group II groups reveals that those genes upregulated in group II group tend to promote cell proliferation and induce cell de-differentiation. We construct the gene co-expression networks and identify group-specific core regulators. Most of these core regulators are linked with group-specific regulatory elements, such as super-enhancers. We further show that CLU is regulated by 3 group I-specific core regulators and works as a novel tumor suppressor in LUAD. Conclusions Our study systematically characterizes the epigenetic alterations during LUAD progression and provides a new classification model that is helpful for predicting patient prognosis.

Background: Intratumoral heterogeneity is a crucial factor to the outcome of patients and resistance to therapies, in which structural variants play an indispensable but undiscovered role. Methods:We performed an integrated analysis of optical mapping and whole-genome sequencing on a primary tumor (PT) and matched metastases including lymph node metastasis (LNM) and tumor thrombus in the pulmonary vein (TPV). Single nucleotide variants, indels and structural variants were analyzed to reveal intratumoral genetic heterogeneity among tumor cells in different sites.Results: Our results demonstrated there were less nonsynonymous somatic variants shared with PT in LNM than in TPV, while there were more structural variants shared with PT in LNM than in TPV. More private variants and its affected genes associated with tumorigenesis and progression were identified in TPV than in LNM. It should be noticed that optical mapping detected an average of 77.1% (74.5-78.5%) large structural variants (>5,000 bp) not detected by whole-genome sequencing and identified several structural variants private to metastases.Conclusions: Our study does demonstrate structural variants, especially large structural variants play a crucial role in intratumoral genetic heterogeneity and optical mapping could make up for the deficiency of whole-genome sequencing to identify structural variants.

BackgroundIt is difficult to distinguish benign pulmonary nodules (PNs) from malignant PNs by conventional examination. Therefore, novel biomarkers that can identify the nature of PNs are needed. Exosomes have recently been identified as an attractive alternative approach since tumor-specific molecules can be found in exosomes isolated from biological fluids.MethodsPlasma exosomes were extracted via the exoEasy reagent method. The major proteins from plasma exosomes in patients with PNs were identified via labelfree analysis and screened for differentially expressed proteins. A GO classification analysis and KEGG pathway analysis were performed on plasma exosomal protein from patients with benign and malignant PNs.ResultsWestern blot confirmed that protein expression of CD63 and CD9 could be detected in the exosome extract. Via a search of the human Uniprot database, 736 plasma exosome proteins from patients with PNs were detected using high-confidence peptides. There were 33 differentially expressed proteins in the benign and malignant PNs. Of these, 12 proteins were only expressed in the benign PNs group, while 9 proteins were only expressed in the malignant PNs group. We further obtained important information on signaling pathways and nodal proteins related to differential benign and malignant PNs via bioinformatic analysis methods such as GO, KEGG, and String.ConclusionsThis study provides a new perspective on the identification of novel detection strategies for benign and malignant PNs. We hope our findings can provide clues for the identification of benign and malignant PNs.Electronic supplementary materialThe online version of this article (10.1186/s12014-019-9225-5) contains supplementary material, which is available to authorized users.

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Background: Young patients with non-small cell lung cancer (NSCLC) represent a distinct subgroup of patients with this disease. This study aimed to construct nomograms to predict the overall survival (OS) and cancer-specific survival (CSS) of young patients with NSCLC.Methods: NSCLC patients under 50 years old diagnosed between 2010 and 2016 were selected from the Surveillance, Epidemiology, and End Results (SEER) database and randomly divided into training (n=1,357) and validation (n=678) cohorts at a ratio of 2:1. Independent prognostic factors for OS or CSS were identified through the log-rank test, Cox proportional hazards models or competing risk model and further integrated to construct nomograms. The predictive capability of the nomogram was assessed by Harrell's concordance index (C-index), the calibration curve and risk group stratification.Results: A total of 2,035 patients were enrolled. In the training cohort, insurance, marital status, histological type, grade, T stage, N stage and surgery were identified as independent prognostic for OS and CSS. The C-index value were 0.759 [95% confidence interval (CI): 0.731-0.787] for OS and 0.810 (95% CI: 0.803-0.818) for BCSS in the training cohort and 0.751 (95% CI: 0.711-0.790) for OS and 0.807 (95% CI: 0.795-0.819) for CSS in the validation cohort. The calibration curves showed optimal agreement between the predicted and actual survival both in internal and external validation. In addition, patients in the validation cohort within different risk groups exhibited significantly different survival even in each TNM stage.Conclusions: Nomograms were developed and validated to predict OS and CSS of young patients with NSCLC in our study. A prospective study with more potential prognostic factors and the latest TNM classification is required to ameliorate this model.