Xiong Zou

Background. Immunity exerts momentous functions in the progression and treatment of kidney renal clear cell carcinoma (KIRC). A better understanding of the relationship between KIRC and immunity may make a great contribution to evaluating the prognosis and immune-related therapeutic response of KIRC. Methods. A series of information such as RNA sequence, clinical data, and tumor mutation burden (TMB) of KIRC patients were downloaded through The Cancer Genome Atlas (TCGA). Next, combining the survival information and gene expression data of TCGA and Gene Expression Omnibus (GEO), we established an immune gene-related prognosis model (IGRPM) and analyzed it. Then we constructed a nomogram which was convenient for clinicians to judge the prognosis of KIRC. Last but not the least, the expressions of some genes used to construct IGRPM in early KIRC, and adjacent normal tissues were verified through real-time fluorescence quantitative polymerase chain reaction (RT-qPCR). Perl (strawberry-perl-5.30.0.1-64bit), R software (4.0.3), and GraphPad Prism 7 were used to process the relevant data. Results. The single-sample gene set enrichment analysis (ssGSEA) showed that there were significant differences in StromalScore, ImmuneScore, ESTIMATEScore, TumorPurity, 22 kinds of human immune cells infiltration, and HLA genes expression between high immunity group (Immunity_H) and low immunity group (Immunity_L). The Immunity_H expressed more immune-related genes and enriched more immune-related functions than the Immunity_L. In addition, compared with the low-risk group, the high-risk group had worse survival outcome and higher TMB. Combining IGRPM-based risk characteristic and TMB, we found that low-TMB+low-risk was the most beneficial to the survival outcome of KIRC patients. The risk characteristic based on IGRPM could be used as an independent prognostic factor for KIRC, and the nomogram constructed for evaluating the prognosis of KIRC showed excellent predictive potential. The RT-qPCR results suggested that not all the genes used to construct IGRPM showed differential expression in early KIRC compared with adjacent normal tissues, but all these genes had significant influence on the prognosis of KIRC. Conclusion. These comprehensive immune assessments and survival predictions, integrating multiple aspects of data and clinical information, can provide additional value to the current Tumor Node Metastasis staging system for risk stratification of KIRC and may facilitate the development of KIRC immunotherapy.

Cytochrome P450 family 2 subfamily J member 2 (CYP2J2), a member of the monooxygenase cytochrome P450 (CYP) family and the only member of the human CYP2J subfamily, has many functions, including regulation of oxidative stress, inflammation, apoptosis, and immune responses. However, its role in cancer development has not been clearly elucidated. In this study, expression levels of CYP2J2 in various cancer types were determined using the Oncomine, the Gene Expression Profiling Interactive Analysis (GEIPA), DriverDBv3, UALCAN, and Tumor Immune Estimation Resource (TIMER) databases. The prognostic value of CYP2J2 for KIRC was analyzed using GEPIA, UALCAN, OSkirc, and DriverDBv3 databases. We evaluated the expression levels of CYP2J2 transcript, protein, and promoter methylation at different clinical characteristics in KIRC through the UALCAN database. Simultaneously, CYP2J2 network‐related functions were evaluated using the GeneMANIA interactive tool while the biological processes involved in CYP2J2 and its interactive genes were investigated through Metascape and FunRich. Then, we used TIMER to determine the correlation between CYP2J2 expression levels and immune infiltration levels in KIRC. In KIRC, the CYP2J2 gene, RNA, and protein were found to be overexpressed. However, the methylation level of CYP2J2 promoter in KIRC was lower than in normal tissues. Surprisingly, elevated expression levels of CYP2J2 exhibited better prognostic outcomes in KIRC. Evaluation of protein‐protein interaction networks and biological processes revealed that CYP2J2 was principally involved in immune responses, apoptosis, and other metabolic processes. Moreover, we found that the expression levels of CYP2J2 were positively correlated with infiltration levels of B cells, CD8 + T cells, neutrophils, and dendritic cells in KIRC. Therefore, we speculated that the overexpression of CYP2J2 prolonged the survival outcome of KIRC patients, which may be related to the change of tumor immune microenvironment. Moreover, all these new understandings of CYP2J2 may provide important value for the early diagnosis and new targeted drug therapy of KIRC.

Purpose: Metastasis is one of the most important causes of treatment failure in nasopharyngeal carcinoma (NPC). In T4 or N2-3 patients at high-risk of metastasis, concurrent chemoradiotherapy (CCRT) is inadequate and additional induction chemotherapy (IC) is controversial. There is a critical need to develop a better patient stratification to efficiently identify patients at high-risk of metastasis for additional IC. Recently, Sequestosome 1 (SQSTM1)/p62, an autophagy adaptor protein, was identified as one of the metastasis-related proteins in NPC. However, the mechanism by which SQSTM1 is involved in NPC metastasis was not investigated. Experimental Design: The effect of SQSTM1 on cell migration and invasion was examined in vitro and in vivo. SQSTM1 expression was analyzed in clinical NPC samples using IHC. Luciferase reporter analyses were conducted to identify the effects of SQSTM1 on NF-κB transcriptional activity. A prediction bio-model was constructed by Cox analysis. Retrospective and prospective randomized clinical data were adopted to build and test the model, respectively. Results: SQSTM1 mediated epithelial to mesenchymal transition (EMT) through the NF-κB pathway to promote NPC metastasis. Inhibiting SQSTM1 enhanced sensitivity to cisplatin in NPC cells. In NPC patients, high SQSTM1 expression was associated with increased risk of distant metastasis. Furthermore, we propose a prognostic bio-model based on SQSTM1 and N-stage to predict NPC metastasis. Most importantly, our prospective randomized study suggested that IC is beneficial for NPC patients with high metastasis risk. Conclusions: The prognostic bio-model identifies NPC patients at high-risk of metastasis for additional IC. Clin Cancer Res; 24(3); 648–58. ©2017 AACR.