Oesophageal squamous cell carcinoma (ESCC) remains a clinically challenging disease with high morbidity rates and poor prognosis. ESCC is also the most common pathological type of oesophageal cancer (EC) in China. Ras-related genes are one of the most frequently mutated gene families in cancer and regulate tumour development and progression. Given this, we investigated the Ras-related gene expression profiles and their values in ESCC prognosis, using data from the Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) databases. We found that we could identify three distinct oesophageal cancer clusters based on their unique expression profile for 11 differentially expressed Ras-related genes with each of these demonstrating some prognostic value when, evaluated using univariate Cox analysis. We then used multivariate Cox analysis to identify relevant independent prognostic indicators and used these to build a new prognostic prediction model for oesophageal cancer patients using these three Ras-related genes. These evaluations produced an area under the curve (AUC) of 0.932. We found that our Ras-related signatures could also act as independent factors in ESCC prognosis and that patients with low Ras scores showed a higher overall expression levels of various immune checkpoint genes, including TNFSF4, TNFRSF8, TNFRSF9, NRP1, CD28, CD70, CD200, CD276, METTL16, METTL14, ZC3H13, YTHDF3, VIRMA, FTO, and RBM15, as well as a higher CSMD3, FLG, DNAH5, MUC4, PLCO, EYS, and ZNF804B mutation rates, and better sensitivity to drugs such as erlotinib, paclitaxel, and gefitinib. In conclusion, we were able to use the unique expression profiles of several Ras-related genes to produce a novel disease signature which might facilitate improved prognosis in ESCC, providing new insight into both diagnosis and treatment in these cancers.

Objective Examining the role of immune‐related genes (IRGs) in “driver gene negative” lung adenocarcinoma (LUAD) may provide new ideas for the treatment and study for this LUAD subgroup. We aimed to find the hub immune‐related gene pairs can stratify the risk of “driver‐gene‐negative” LUAD. Materials and Methods IRGs were identified according to ImmPort database based on RNA sequencing results of tumors and normal tissues from 46 patients with “driver gene negative” LUAD at The First Affiliated Hospital of Sun Yat‐sen University and cyclically singly paired as immune‐related gene pairs (IRGPs). Multivariate Cox analysis was used to construct an immune risk model and a prognostic nomogram combining was also been developed. Immune microenvironment landscape described by CIBERSORT and drug sensitivity calculated by pRRophetic algorithm were used to explore possible treatment improvements. Results A novel immune risk model with 5‐IRGPs (CD1A|CXCL135, CD1A|S100A7L2, IFNA7|CMTM2, IFNA7|CSF3, CAMP|TFR2) can accurately distinguish patients in the high‐ and low‐risk groups. Risk score act as an independent prognostic factor and is related to clinical stage. There are significant differences in tumor immune microenvironment and PD‐1/PD‐L1/CTLA‐4 expression between groups. The low‐risk patient may benefit more from the commonly used chemotherapy regimens such as gemcitabine and paclitaxel. Conclusion This study constructed 5‐IRGPs as a reliable prognostic tool and may represent genes pairs that are potential rationale for choice of treatment for “driver gene negative” LUAD.

Esophageal squamous cell carcinoma (ESCC) is a common malignant tumor with high mortality and poor prognosis. Ferroptosis is a newly discovered form of cell death induced by iron-catalyzed excessive peroxidation of polyunsaturated fatty acids (PUFAs). However, the prognostic value of ferroptosis-related genes (FRGs) for ESCC remains unclear. Based on the ESCC dataset from the Gene Expression Omnibus (GEO) database, we identified 39 prognostic FRGs through univariate Cox regression analysis. After LASSO regression and multivariate Cox regression analyses, a multigene signature based on 10 prognostic FRGs was constructed and successfully divided ESCC patients into two risk groups. Patients in the low-risk group showed a significantly better prognosis than patients in the high-risk group. In addition, we combined the risk score with clinical predictors to construct a nomogram for ESCC. The predictive ability of the nomogram was further verified by ROC curves and calibration plots in both the training and validation sets. The predictive power of the nomogram was demonstrated to be better than that of either the risk score or clinical variable alone. Furthermore, functional analysis revealed that the 10-FRG signature was mainly associated with ferroptosis, differentiation and immune response. Connectivity map analysis identified potential compounds capable of targeting FRGs in ESCC. Finally, we demonstrated the prognostic value of SRC gene in ESCC using the clinical samples and found that SRC inhibition sensitized ESCC cells to ferroptosis inducers by in vitro experiments. In conclusion, we identified and verified a 10-FRG prognostic signature and a nomogram, which provide individualized prognosis prediction and provide insight into potential therapeutic targets for ESCC.

Single-agent concurrent chemoradiotherapy is commonly used to treat older or low Karnofsky Performance Scores patients with unresectable esophageal squamous cell carcinoma in China. But it is not clear if the clinical efficacy is equivalent between single-agent and dual-agent concurrent chemoradiotherapy. The main purpose of this study was to compare the clinical efficacy of single-agent and dual-agent concurrent chemoradiotherapy for patients with unresectable esophageal squamous cell carcinoma by retrospectively analyzed. Materials/Methods: This study enrolled 133 patients who had undergone definitive concurrent chemoradiotherapy for locally advanced unresectable esophageal squamous carcinoma at 10 hospital between 2010 and 2015. The KaplaneMeier method was used to compare the progression-free survival (PFS) and overall survival (OS) between the different treatment groups. A Cox proportional hazards regression model was used in a multivariate analysis of the impact of prognostic factors on survival. Results: In this study, 81 patients (60.9%) received single-agent concurrent chemoradiotherapy and 52 patients (39.1%) received dual-agent combination chemoradiotherapy. Univariate analysis revealed no significant difference in OS and PFS between patients receiving single-agent and those receiving double-agent combination chemoradiotherapy (P values were 0.260, 0.387, respectively). The median OS of single-agent and dualagent group were 20 months and 20 months, respectively, and median PFS were 18.0 months and 18.5 months, respectively. Multivariate analysis showed that independent prognostic factor of OS and PFS was only stages (P values were 0.007, 0.006, respectively). Conclusion: The clinical efficacy of single-agent concurrent chemoradiotherapy is equivalent to dual-agent concurrent chemoradiotherapy for patients with locally advanced unresectable esophageal squamous cell carcinoma. We will start a prospective randomized study to confirm our findings

The improvement of treatment for patients with ‘driver‐gene‐negative’ lung adenocarcinoma (LUAD) remains a critical problem to be solved. We aimed to explore the role of methylation of N6 adenosine (m6A)‐related long noncoding RNA (lncRNA) in stratifying ‘driver‐gene‐negative’ LUAD risk. Patients negative for mutations in EGFR , KRAS , BRAF , HER2 , MET , ALK , RET , and ROS1 were identified as ‘driver‐gene‐negative’ cases. RNA sequencing was performed in 46 paired tumors and adjacent normal tissues from patients with ‘driver‐gene‐negative’ LUAD. Twenty‐three m6A regulators and relevant lncRNAs were identified using Pearson's correlation analysis. K‐means cluster analysis was used to stratify patients, and a prognostic nomogram was developed. The CIBERSORT and pRRophetic algorithms were employed to quantify the immune microenvironment and chemosensitivity. We identified two clusters highly consistent with the prognosis based on their unique expression profiles for 46 m6AlncRNAs. A risk model constructed from nine m6A lncRNAs could stratify patients into high‐ and low‐risk groups with promising predictive power (C‐index = 0.824), and the risk score was an independent prognostic factor. The clusters and risk models were closely related to immune characteristics and chemosensitivity. Additional pan‐cancer analysis using the nine m6AlncRNAs showed that the expression of DIO3 opposite strand upstream RNA ( DIO3OS ) is closely related to the immune/stromal score and tumor stemness in a variety of cancers. Our results show that m6AlncRNAs are a reliable prognostic tool and can aid treatment decision‐making in ‘driver‐gene‐negative’ LUAD. DIO3OS is associated with the development of various cancers and has potential clinical applications.