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Abstract Background Lung adenocarcinoma (LUAD) is still one of the most prevalent malignancies. Interleukin factors are closely associated with the initiation and progression of cancer. However, the relationship between interleukin factors and LUAD has not been fully elucidated. This study aimed to use Mendelian randomization (MR) and RNA sequencing (RNA-seq) analyses to identify the interleukin factors associated with the onset and progression of LUAD. Methods Exposure-related instrumental variables were selected from interleukin factor summary datasets. The LUAD summary dataset from FINGENE served as the outcome. MR and sensitivity analyses were conducted to screen for interleukin factors associated with LUAD occurrence. Transcriptome analyses revealed the role of interleukin factors in lung tissues. The results were validated through Western blotting and further confirmed with driver gene-negative patients from multiple centers. Potential mechanisms influencing LUAD occurrence and development were explored using bulk RNA-seq and single-cell RNA-seq data. Results MR analysis indicated that elevated plasma levels of IL6RB, IL27RA, IL22RA1, and IL16 are causally associated with increased LUAD risk, while IL18R1 and IL11RA exhibit the opposite effect. Transcriptome analyses revealed that IL11RA, IL18R1, and IL16 were downregulated in tumor tissues compared with normal lung tissue, but only higher expression of IL11RA correlated with improved prognosis in patients with LUAD from different centers and persisted even in driver-gene negative patients. The IL11RA protein level was lower in various LUAD cell lines than in human bronchial epithelial cells. The genes co-expressed with IL11RA were enriched in the Ras signaling pathway and glycosylation processes. Fibroblasts were the primary IL11RA-expressing cell population, with IL11RA+fibroblasts exhibiting a more immature state. The genes differentially expressed between IL11RA+and IL11RA- fibroblasts were involved in the PI3K-Akt/TNF signaling pathway. Conclusion According to the MR and transcriptome analyses, the downregulation of IL11RA was closely related to the occurrence and development of LUAD. Graphical Abstract

Hypothyroidism has been suggested to play a role in tumor progression. However, the causal association between hypothyroidism and lung cancer remains unknow. To elucidate the potential association between hypothyroidism and lung cancer risk, we employ a Mendelian randomization (MR) approach. MR was performed to analyze pooled data from the International Lung Cancer Consortium (11,348 cases and 15,861 controls; European ancestry) to determine the causal relationship between hypothyroidism and lung cancer. We used 36, 83, and 14 single nucleotide polymorphisms as instrumental variables for hypothyroidism/myxoedema, hypothyroidism, and exercise, respectively. We further investigated the mechanisms involved in transcriptome analysis using data from The Cancer Genome Atlas and Genotype-Tissue Expression database. We conducted an initial validation of intermediary factor using a two-step MR analysis. Genetically predicted hypothyroidism was significantly related to the risk of overall lung cancer, specifically the risk of lung squamous cell cancer (LSCC) but not with the risk of lung adenocarcinoma (LUAD) as assessed using the inverse-variance weighted (IVM) method. A similar causal association was found between hypothyroidism/myxoedema and the risk of lung cancer, LSCC, and LUAD. Transcriptome analysis showed that genes associated with hypothyroidism, lung cancer, and LSCC were enriched in the PI3K/Akt signaling pathway and oxidative stress response. However, genes related to hypothyroidism and LUAD did not exhibit enrichment in these pathways. Hypothyroidism was significantly associated with strenuous sports or other exercises. Moreover, genetically predicted exercise was significantly related to the risk of overall lung cancer, and LSCC, but not LUAD. We detected no horizontal pleiotropy using the MR-PRESSO and MR Egger regression intercept. Hypothyroidism was causally associated with a lower risk of lung cancer, and these effects might be mediated by the oxidative stress response and the PI3K/Akt signaling pathway. Therefore, our study suggests that the potential factors and viable etiologies of hypothyroidism that contributed to lung cancer risk deserve further investigation.

Abstract Background This study aimed to identify the key genes involved in the development of multiple primary lung cancers. Methods Differential expression analysis was performed, followed by comparing the infiltration levels of 22 immune cell types between multiple and single primary lung adenocarcinomas. Marker genes for epithelial cells with different proportions between the two types of lung adenocarcinomas were identified. The common genes between the marker genes and differentially expressed genes were identified. Finally, the effects of the key genes were tested on the in vitro proliferation, migration and morphology. Results: The infiltration levels of helper follicular T cells, resting NK cells, activated NK cells, M2 macrophages and resting mast cells were higher in the patients with multiple than in those with single primary lung adenocarcinomas. A total of 1553 differentially expressed genes and 4414 marker genes of epithelial cells were identified. Logistic regression analysis was performed on the 164 resulting genes. The macrophage migration inhibitory factor expression was positively associated with the occurrence of multiple primary lung adenocarcinomas. Moreover, its signalling pathway was the key pathway among the epithelial cells and multiple and single primary lung adenocarcinoma cells, and it was upregulated in lung adenocarcinoma cells. It also increased the expression of lung cancer markers, including NES and CA125, induced morphological changes in alveolar epithelial type II cells, and promoted their proliferation, migration and invasion. Conclusions Multiple and single primary lung adenocarcinomas have different tumour immune microenvironments, and migration inhibitory factor may be a key factor in the occurrence of multiple primary lung adenocarcinomas.

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.

Abstract Background General transcription factor IIi (GTF2I) mutations are very common in thymic epithelial tumors (TETs) and are related to a more favorable prognosis in TET patients. However, limited research has been conducted on the role of GTF2I in the tumor immune microenvironment (TIME). Further, long non-coding RNAs (lncRNAs) have been associated with the survival of patients with TETs. Therefore, this study aimed to explore the relationship between GTF2I mutations and TIME and build a new potential signature for predicting tumor recurrence in the TETs. Research data was downloaded from The Cancer Genome Atlas database and the CIBERSORT algorithm was used to evaluate TIME differences between GTF2I mutant and wild-type TETs. Relevant differentially expressed lncRNAs based on differentially expressed immune-related genes were identified to establish lncRNA pairs. We constructed a signature using univariate and multivariate Cox regression analyses. Results GTF2I is the most commonly mutated gene in TETs, and is associated with an increased number of early-stage pathological types, as well as no history of myasthenia gravis or radiotherapy treatment. In the GTF2I wild-type group, immune score and immune cell infiltrations with M2 macrophages, activated mast cells, neutrophils, plasma, T helper follicular cells, and activated memory CD4 T cells were higher than the GTF2I mutant group. A risk model was built using five lncRNA pairs, and the 1-, 3-, and 5-year area under the curves were 0.782, 0.873, and 0.895, respectively. A higher risk score was related to more advanced histologic type. Conclusion We can define the GTF2I mutant-type TET as an immune stable type and the GTF2I wild-type as an immune stressed type. A signature based on lncRNA pairs was also constructed to effectively predict tumor recurrence.

Abstract Background Oxidative stress plays an important role in the progression of various types of tumors. However, its role in esophageal squamous cell carcinoma (ESCC) has seldom been explored. This study aimed to discover prognostic markers associated with oxidative stress in ESCC to improve the prediction of prognosis and help in the selection of effective immunotherapy for patients. Results A consensus cluster was constructed using 14 prognostic differentially expressed oxidative stress-related genes (DEOSGs) that were remarkably related to the prognosis of patients with ESCC. The infiltration levels of neutrophils, plasma cells, and activated mast cells, along with immune score, stromal score, and estimated score, were higher in cluster 1 than in cluster 2. A prognostic signature based on 10 prognostic DEOSGs was devised that could evaluate the prognosis of patients with ESCC. Calculated risk score proved to be an independent clinical prognostic factor in the training, testing, and entire sets. P53 signaling pathway was highly enriched in the high-risk group. The calculated risk score was positively related to the infiltration levels of resting mast cells, memory B cells, and activated natural killer (NK) cells and negatively associated with the infiltration levels of M1 and M2 macrophages. The relationship between clinical characteristics and risk score has not been certified. The half-maximal inhibitory concentration (IC50) values for sorafenib and gefitinib were lower for patients in the low-risk group. Conclusion Our prognostic signature based on 10 prognostic DEOSGs could predict the disease outcomes of patients with ESCC and had strong clinical value. Our study improves the understanding of oxidative stress in tumor immune microenvironment (TIME) and provides insights for developing improved and efficient immunotherapy strategies.

Abstract 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.

Abstract Objectives To develop and validate a radiomics model for evaluating treatment response to immune-checkpoint inhibitor plus chemotherapy (ICI + CT) in patients with advanced esophageal squamous cell carcinoma (ESCC). Methods A total of 64 patients with advance ESCC receiving first-line ICI + CT at two centers between January 2019 and June 2020 were enrolled in this study. Both 2D ROIs and 3D ROIs were segmented. ComBat correction was applied to minimize the potential bias on the results due to different scan protocols. A total of 788 features were extracted and radiomics models were built on corrected/uncorrected 2D and 3D features by using 5-fold cross-validation. The performance of the radiomics models was assessed by its discrimination, calibration and clinical usefulness with independent validation. Results Five features and support vector machine algorithm were selected to build the 2D uncorrected, 2D corrected, 3D uncorrected and 3D corrected radiomics models. The 2D radiomics models significantly outperformed the 3D radiomics models in both primary and validation cohorts. When ComBat correction was used, the performance of 2D models was better (p = 0.0059) in the training cohort, and significantly better (p

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.

Abstract Background As there is no consensus on the optimal surgery strategy for multiple primary lung cancer (MPLC), we conducted this study to address this issue by comparing the prognosis of MPLC patients underwent different surgical strategies including sublobar resection and the standard resection through a systemic review and meta-analysis. Methods Relevant literature was obtained from three databases including PubMed, Embase and Web of Science. Inclusion and exclusion criteria were set for the screening of articles to be selected for further conduction of systemic review and meta-analysis. The HRs of OS of the sublobar group compared with standard resection group were extracted directly or calculated indirectly from included researches. Results Ten researches published from 2000 to 2017 were included in this study, with 468 and 445 MPLC cases for the standard resection group and sublobar resection group respectively. The result suggested that OS of MPLC patients underwent sublobar resection (segmentectomy or wedge resection for at least one lesion) was comparable with those underwent standard resection approach (lobectomy or pneumonectomy for all lesions), with HR 1.07, 95% CI 0.67–1.71, p = 0.784. Further analysis found no difference in subgroups of synchronous and metachronous (from second metachronous lesion), different population region and dominant sex type. Conclusions This study may reveal that sublobar resection is acceptable for patients with MPLC at an early stage, because of the equivalent prognosis to the standard resection and better pulmonary function preservation. Further research is needed to validate these findings.