Novel molecular-targeted treatments show great prospects for radioiodine-refractory and surgically inoperable thyroid carcinomas. While aberrations in protein-coding genes are a focus in molecular thyroid cancer medicine, the impact of oncogenes on the expression of long noncoding RNAs (lncRNAs) has been largely uncharacterized. We aimed to identify the expression patterns of lncRNAs and mRNAs in high-throughput molecular profiles of 18 papillary thyroid cancer (PTC) patients. We identified 452 mRNAs and 240 unannotated lncRNAs that were differentially expressed in PTC. Significantly enriched GO terms and pathways were identified, many of which were linked to cancer. By integrating the predicted lncRNA target genes with differentially expressed mRNAs, we identified 20 candidate lncRNAs in 45 PTC patients. Five lncRNAs (CTD-3193O13.11, RP5-1024C24.1, AC007255.8, HOXD-AS1, and RP11-402L6.1) were verified to be differentially expressed in PTC and to exhibit specific topological characteristics in the lncRNA–mRNA co-expression network. LncRNA CTD-3193O13.11 was determined to comprise a node of co-regulation with the other lncRNAs in PTC tumorigenesis. LncRNA RP5-1024C24.1, AC007255.8, and HOXD-AS1 expression was significantly related to clinical stage, lncRNA RP11-402L6.1 expression was associated with lymph node metastasis, lncRNA CTD-3193O13.11 expression was proportional to tumor size, and lncRNA AC007255.8 expression was proportional to patient age. Therefore, our study provides a genome-wide screening and analysis of lncRNA expression in PTC, which brings novel insights into the roles of lncRNAs in PTC progression.

Purpose: This systematic review and meta-analysis was carried out with the aim of investigating the relationship between Foxp3 polymorphisms (rs3761547, r3761548, and rs3761549) and the risk of Graves' disease (GD). Methods: Four online database including PubMed, EMBASE, ISI Web of Science, and CNKI were searched to identify observational studies that evaluated the association between Foxp3 polymorphisms and risk of GD. The strength of associations was indicated as odds ratio (OR) and corresponding 95% confidence interval (95%CI) under the allelic model. The Newcastle-Ottawa Scale was used to assess the methodological quality. Pre-specified subgroup analysis and sensitivity analysis were performed using RevMan 5.3 software. Publication bias was detected by Egger's and Begg's tests. Results: Eight case control studies involving 3,104 GD patients and 3,599 healthy controls were included. The methodological quality of included studies was considered to be moderate to high. The results of our meta-analysis supported no association of rs3761547 and risk of GD in Asians (OR: 1.07, 95%CI 0.97, 1.19, P = 0.18). Evidence for rs3761547 and GD risk among Caucasians was still limited because only one study reported marginally increased risk of GD with the minor allele of rs3761547 (P = 0.04). The variant allele of both rs3761548 (OR: 1.31, 95%CI 1.04, 1.64; P = 0.02) and rs3761549 (OR: 1.30, 95%CI 1.03, 1.64; P = 0.03) was associated with increased risk of GD among Asians, but neither polymorphism turned out to be related with GD among Caucasians. Conclusion: Rs3761548 and rs3761549 polymorphisms in Foxp3 were associated with risk of GD among Asians, possibly due to suppressed function of regulatory T cells and augmented autoimmune response. Their genetic effect among Caucasians remained to be confirmed by future large-scale and well-designed studies.

Breast cancer (BC) poses one of the major threats to female's health worldwide. Immune infiltration in BC is a key representative of the tumor microenvironment and has been proven highly relevant for prognosis. The role of the FREM1 (FRAS1‐Related Extracellular Matrix 1) gene in carcinoma has not studied, moreover, the underlying mechanism remains largely unknown. This study aims to investigate the expression profile and potential action of FREM1 on BC progression. We applied series of bioinformatic methods as well as immunohistochemistry (IHC) and immunofluorescence (IF) to analyze FREM1 expression profile, its relationship with clinicopathological characteristics, impact on clinical outcomes, relevant functions, correlation with immune infiltration in BC. The results demonstrated that FREM1 had a dramatically reduced expression in BC tissues, possessed an inverse correlation with stage, age, and metastasis, and exhibited a higher level in invasive lobular breast carcinoma than in ductal one. Furthermore, decreased FREM1 expression was often associated with estrogen receptor (ER)/progesterone receptor (PR) negative and triple negative breast carcinoma (TNBC) status while human epidermal growth factor 2 (Her‐2) positive status, and considerably correlated with a worse overall survival (OS) and recurrence‐free survival (RFS). Meanwhile, the univariate/multivariate Cox model revealed that low‐FREM1 expression can be an independent prognostic factor for BC. Additionally, FREM1 was mainly involved in the cell metabolism and immune cells infiltration. Moreover, IHC and IF demonstrated a positive correlation of its expression with the immune infiltrating levels of CD4⁺, CD8⁺ T cells, and CD86⁺ M1 macrophages while a negative correlation with CD68⁺ pan‐macrophages and CD163⁺ M2 macrophages. These findings suggest that FREM1 can be a potential biomarker for evaluating the immune infiltrating status, and the BC prognosis.

Triple-negative breast cancer (TNBC) is a relatively aggressive breast cancer subtype due to tumor relapse, drug resistance, and multi-organ metastatic properties. Identifying reliable biomarkers to predict prognosis and precisely guide TNBC immunotherapy is still an unmet clinical need. To address this issue, we successfully constructed a novel 25 machine learning (ML) algorithms-based immune infiltrating cell (IIC) associated signature of TNBC (MLIIC), achieved by multiple transcriptome data of purified immune cells, TNBC cell lines, and TNBC entities. The TSI index was employed to determine IIC-RNAs that were accompanied by an expression pattern of upregulation in immune cells and downregulation in TNBC cells. LassoLR, Boruta, Xgboost, SVM, RF, and Pamr were utilized for further obtaining the optimal IIC-RNAs. Following univariate Cox regression analysis, LassoCox, CoxBoost, and RSF were utilized for the dimensionality reduction of IIC-RNAs from a prognostic perspective. RSF, Ranger, ObliqueRSF, Rpart, CoxPH, SurvivalSVM, CoxBoost, GlmBoost, SuperPC, StepwiseCox, Enet, LassoCox, CForest, Akritas, BlackBoost, PlsRcox, SurvReg, GBM, and CTree were used for determining the most potent MLIIC signature. Consequently, this MLIIC signature was correlated significantly with survival status validated by four independent TNBC cohorts. Also, the MLIIC signature had a superior predictive capability for TNBC prognosis, compared with 148 previously reported signatures. In addition, MLIIC signature scores developed by immunofluorescent staining of tissue arrays from TNBC patients showed a substantial prognostic value. In TNBC immunotherapy, the low MLIIC profile demonstrated significant immune-responsive efficacy in a dataset of multiple cancer types. MLIIC signature could also predict m6A epigenetic regulation which controls T cell homeostasis. Therefore, this well-established MLIIC signature is a robust predictive indicator for TNBC prognosis and the benefit of immunotherapy, thus providing an efficient tool for combating TNBC.

Increasing evidence indicates that the abnormal expression of N6-methyladenosine (m6A) modification is closely related to the epigenetic regulation of immune response in breast cancer (BC). However, the potential roles of m6A modification in the tumor microenvironment (TME) of BC remain unclear. For addressing this issue, we comprehensively analyzed the m6A modification patterns in 983 samples and correlated these modification patterns with TME immune cell infiltration, based on 23 kinds of m6A regulators. Principal component analysis (PCA) was used to construct the m6A scoring system to quantify the modification pattern of m6A of BC individuals. Consequently, three different m6A modification patterns were identified, and the infiltrating characteristics of TME cells were consistent with the three immune phenotypes, including immune rejection, immune inflammation, and immune desert. Besides, our analysis showed that the prognosis of patients could be predicted by evaluating the m6A modification pattern in the tumor. The low m6Ascore corresponded to increased mutation burden and immune activation, while stroma activation and lack of immune infiltration were observed in high m6Ascore subtypes. In addition, a low m6Ascore was associated with enhanced response to anti-PD-1/PD-L1 immunotherapy. In conclusion, the m6A modification pattern was closely related to the BC immune landscape. This well-validated score model of the m6A modification patterns will provide a valuable tool to depict the tumor immune state and guide effective tumor immunotherapy for combating BC.

γ‐Glutamine cyclotransferase (GGCT) is an enzyme involved in the metabolic cycle of glutathione (GSH). Abnormal GSH metabolism is mostly related to ferroptosis. However, the mechanisms supporting aberrant GGCT expression in PTC remain to be investigated. In this study, we found that GGCT knockdown inhibited GSH synthesis and promoted malondialdehyde (MDA) and reactive oxygen species (ROS) accumulation, thereby promoting ferroptosis in papillary thyroid cancer cells. Pro‐GA, the specific inhibitor of GGCT, inhibited the subcutaneous tumor formation of K1 cells. IP combined with LC–MS/MS showed an interaction between GGCT and RPS15A. RPS15A is highly expressed in PTC tissues and cells, and GGCT promotes the stability of RPS15A. Knockdown of RPS15A promoted p53 expression, which in turn inhibited SLC7A11 expression, resulting in ferroptosis, while overexpression of RPS15A reversed GGCT‐induced ferroptosis. In addition, miR‐205‐5p targeted the 3’ UTR of GGCT to inhibit GGCT‐mediated ferroptosis, tumor growth, and lung metastasis. In conclusion, we found that knockdown of GGCT promoted ferroptosis in PTC cells. Mechanistically, GGCT interacts with RPS15A, and GGCT promotes the protein stability of RPS15A. Knockdown of RPS15A promotes p53 expression and inhibits SLC7A11 expression, thereby inhibiting GSH synthesis. The upstream mechanism of GGCT regulation showed that miR‐205‐5p inhibited GGCT protein expression by targeting the 3′ UTR of GGCT.