Abstract RNA modifications have become hot topics recently. By influencing RNA processes, including generation, transportation, function, and metabolization, they act as critical regulators of cell biology. The immune cell abnormality in human diseases is also a research focus and progressing rapidly these years. Studies have demonstrated that RNA modifications participate in the multiple biological processes of immune cells, including development, differentiation, activation, migration, and polarization, thereby modulating the immune responses and are involved in some immune related diseases. In this review, we present existing knowledge of the biological functions and underlying mechanisms of RNA modifications, including N 6 -methyladenosine (m 6 A), 5-methylcytosine (m 5 C), N 1 -methyladenosine (m 1 A), N 7 -methylguanosine (m 7 G), N 4 -acetylcytosine (ac 4 C), pseudouridine (Ψ), uridylation, and adenosine-to-inosine (A-to-I) RNA editing, and summarize their critical roles in immune cell biology. Via regulating the biological processes of immune cells, RNA modifications can participate in the pathogenesis of immune related diseases, such as cancers, infection, inflammatory and autoimmune diseases. We further highlight the challenges and future directions based on the existing knowledge. All in all, this review will provide helpful knowledge as well as novel ideas for the researchers in this area. 

https://www.nature.com/articles/s41392-022-01175-9.pdf

RNA modifications: importance in immune cell biology and related diseases

Background Prostate cancer is the second most common cancer with a high risk of biochemical recurrence (BCR) among men. Recently, 5-methylcytosine (m5C) modification has attracted more attention as a new layer of RNA post-transcriptional regulation. Hence, we aimed at investigating the potential roles of m5C modification regulators in the BCR of prostate adenocarcinoma (PRAD). Methods CNV data, mutation annotation data, mRNA expression profiles, and clinical data were downloaded from TCGA and GEO databases. Kaplan-Meier curves analysis, log-rank test, univariate and multivariate Cox regression, and time-dependent ROC curves analysis were performed to evaluate the prognostic factors. Principal components analysis (PCA) was applied to validate the distinction between subgroups. Gene set variation analysis (GSVA) was used to investigate the underlying pathways associated with m5C modification patterns. Single sample gene set enrichment analysis (ssGSEA) was utilized to assess the infiltration of distinct immune cells. Tumor Immune Dysfunction and Exclusion (TIDE) prediction was carried out to assess the potential response to immune checkpoint blockade (ICB) therapy. The m5C modification signature was constructed via LASSO Cox’s proportional hazards regression method. Results After comprehensively analyzing various types of data from TCGA dataset, and exploring the differential expression and prognostic value of each m5C regulator, we identified m5C modification patterns based on 17 m5C regulators. Two patterns presented a significant difference in the risk of BCR, the tumor microenvironment (TME), and immunotherapy response in PRAD. We found that TET2, which was highly expressed in adjacent normal tissues compared to tumor tissues, was closely associated with many infiltrating immune cells. The m5C modification signature was constructed for the clinical application. Risk score calculated by m5C signature was associated with T stage, N stage, Gleason score, and the possibility of BCR (HR, 4.197; 95% CI, 3.016-5.842; p < 0.001). A higher risk score also represented the possibility of immunotherapy response. Finally, the potential roles of m5C modification signature were validated in the testing dataset. Conclusions Our study revealed the potential roles of m5C modification in the PRAD BCR and TME diversity, which may provide new insight into the field of prostate cancer in future research.

https://www.frontiersin.org/articles/10.3389/fimmu.2022.869759/pdf

Roles of m5C RNA Modification Patterns in Biochemical Recurrence and Tumor Microenvironment Characterization of Prostate Adenocarcinoma

Non-coding RNAs (ncRNAs) account for the majority of the widespread transcripts of mammalian genomes. They rarely encode proteins and peptides, but their regulatory role is crucial in numerous physiological and pathological processes. The m6A (N6-methyladenosine) modification is one of the most common internal RNA modifications in eukaryotes and is associated with all aspects of RNA metabolism. Accumulating researches have indicated a close association between m6A modification and ncRNAs, and suggested m6A-modified ncRNAs played a crucial role in tumor progression. The correlation between m6A modification and ncRNAs offers a novel perspective for investigating the potential mechanisms of cancer pathological processes, which suggests that both m6A modification and ncRNAs are critical prognostic markers and therapeutic targets in numerous malignancies. In the present report, we summarized the interaction between m6A modification and ncRNA, emphasizing how their interaction regulates pathological processes in cancer. 

/pdf/the-role-of-n6-methyladenosine-modified-non-coding-rnas-in-18dngp8u.pdf

The role of N6-methyladenosine-modified non-coding RNAs in the pathological process of human cancer

/pdf/the-role-of-n6-methyladenosine-modified-non-coding-rnas-in-1tosuase.pdf

Thyroid-stimulating hormone (TSH) is a growth factor associated with the initiation and progression of well-differentiated thyroid cancer (WDTC). Atypia of undetermined significance and follicular lesion of undetermined significance (AUS/FLUS) are the most uncertain cytological diagnoses of thyroid nodules. The aim of the study was to determine the association of histopathological diagnosis with preoperative serum TSH levels in patients with AUS/FLUS thyroid nodule diagnosis. Among 5028 individuals with thyroid nodules, 342 (6.8%) with AUS/FLUS diagnoses were analyzed. The frequency of all histopathology diagnoses was assessed for associations with preoperative serum TSH levels. The median TSH concentration was significantly higher in patients with AUS/FLUS diagnosis and histopathology of WDTC than in patients with the same cytology result and histopathology of a benign tumor (p < 0.0001). The diagnostic potential of serum TSH level was determined to evaluate risk of malignancy in patients with thyroid nodules classified into the Bethesda III category. ROC analysis showed the TSH concentration at a cutoff point of 2.5 mIU/L to be an acceptable prognostic factor for WDTC. For this optimal cutoff point, the AUC was 0.877, the sensitivity was 0.830, and the specificity was 0.902. Preoperative serum TSH levels in patients with AUS/FLUS thyroid tumor diagnosis should be taken into consideration in the decision-making process and clinical management.

/pdf/assessment-of-preoperative-tsh-serum-level-and-thyroid-34ta9z4w.pdf

Assessment of Preoperative TSH Serum Level and Thyroid Cancer Occurrence in Patients with AUS/FLUS Thyroid Nodule Diagnosis

Given the relatively poor understanding of the expression and functional effects of the N6-methyladenosine (m6A) RNA methylation on colorectal cancer (CRC), we attempted to measure its prognostic value and clinical significance. We comprehensively screened 37 m6A-related prognostic long non-coding RNAs (lncRNAs) with significant differences in expression based on 21 acknowledged regulators of m6A modification and data on 473 colorectal cancer tissues and 41 para-cancer tissues obtained from the TCGA database. Accordingly, we classified 473 CRC patients into two clusters by consensus clustering on the basis of significantly different survival outcomes. We also found a potential correlation between m6A-related prognostic lncRNAs and BRAF-KRAS expression, as well as immune cell infiltration. Then, we established a prognostic model by selecting 16 m6A-related prognostic lncRNAs via LASSO Cox analysis and grouped the CRC patients into low- and high-risk groups to calculate risk scores. Then, we performed stratified sampling to validate and confirm our model by categorising the 473 samples into a training group (N = 208) and a testing group (N = 205) in a 1:1 ratio. The survival curve showed a distinct clinical outcome in the low- and high-risk subgroups. We reconfirmed the reliability and independence of the prognostic model through various measures: risk curve, heat map and univariate and multivariate Cox analyses. To ensure that the outcomes were applicable to clinical settings, we performed stratified analyses on different clinical features, such as age, lymph node status and clinical stage. CRC patients with downregulated m6A-related gene expression, lower immune score, distant metastasis, lymph node metastasis or more advanced clinical staging had higher risk scores, indicating less-desirable outcomes. Moreover, we explored the immunology of colorectal cancer cells. The risk score showed positive correlations with eosinophils, M2 macrophages and neutrophils. In summary, our effort revealed the significance of m6A RNA methylation regulators in colorectal cancer, and the prognostic model we constructed may be used as an essential reference for predicting the outcome of CRC patients.

/pdf/construction-and-analysis-of-a-colorectal-cancer-prognostic-rypw4o1lo1.pdf

Construction and Analysis of a Colorectal Cancer Prognostic Model Based on N6-Methyladenosine-Related lncRNAs.

Objective To explore the relationship between thyroid-stimulating hormone (TSH) levels in the serum and postoperative recurrence and lymph node metastasis (LNM) in papillary thyroid cancer (PTC) patients after surgery. Methods We selected 272 patients diagnosed with PTC from June 2011 to July 2014. The clinical and pathological data of 272 PTC patients were collected at the First Affiliated Hospital of Wenzhou Medical University and analysed retrospectively. All PTC patients were tested for the BRAFV600E gene mutation before surgery by fine-needle aspiration (FNA) cytology, and TSH levels in the serum were determined one month after surgery. The optimal cut-off value of thyroid-stimulating hormone (TSH) for predicting the recurrence or metastasis of PTC after surgery was determined by the establishment of a receiver operating characteristic (ROC) curve. Kaplan-Meier and Cox regression analyses were used to evaluate the correlation between the optimal cut-off value of TSH and disease-free survival rate and prognosis. Results Of 272 patients, only 182 (73 BRAFV600E+, 109 BRAFV600E-) met the final study criteria. Among them, 60 cases had recurrence or metastasis, and 122 cases were controls. The optimal cut-off value of TSH for the prediction of recurrence or metastasis of PTC after surgery was 2.615 mlU/L. In our study, a high TSH level (> 2.615 mlU/L) was correlated with the BRAFV600E mutation, multifocality, lymph node metastasis, recurrence, and metastasis. In all 182 patients, those with high TSH levels had worse disease-free survival. This result was more obvious in the 73 BRAFV600E+ patients. The univariate analysis showed that lymph node metastasis, multifocality, lymph node dissection, tumour size, sex, BRAFV600E mutation, and a high postoperative TSH level were all significantly correlated with recurrence or metastasis in PTC patients (all P Conclusion PTC patients with high TSH levels (> 2.615 mlU/L) have worse disease-free survival, which is more obvious in the BRAFV600E+ population.

Serum TSH levels are associated with postoperative recurrence and lymph node metastasis of papillary thyroid carcinoma.

Background: It is necessary to identify patients at risk of developing lymph node metastasis prior to papillary thyroid carcinoma (PTC) surgery. This can be challenging due to limiting factors, and an artificial intelligence algorithm may be a viable option. Objective: In this study, we aimed to evaluate whether combining an artificial intelligence algorithm (support vector machine and probabilistic neural network) and clinico-pathologic data can preoperatively predict lymph node metastasis of papillary thyroid carcinoma (PTC). Methods: We retrospectively examined 251 PTCs with lymph node metastasis and 194 PTCs without lymph node metastasis. The artificial intelligence algorithm included the support vector machine (SVM) and the probabilistic neural network (PNN). Results: The ACR TI-RADS (Thyroid Imaging, Reporting and Data System), number of tumours, no well-defined margin, lymph node status and rim calcification on ultrasonography (US), age, sex, tumour size, and presence of Hashimoto’s thyroiditis were significantly more frequent among PTCs with central lymph node metastasis than those without metastasis (P<0.05). The PNN classifier revealed an F1 score of 0.88 on the central lymph node metastasis test set. The SVM classifier revealed an F1 score of 0.93 on the lateral lymph node metastasis test set. Our study demonstrates that combining artificial intelligence algorithms and clinico-pathologic data can effectively predict the lymph node metastasis of papillary thyroid carcinoma prior to surgery.

Yanyan Shen

Papers

Construction and Analysis of a Colorectal Cancer Prognostic Model Based on N6-Methyladenosine-Related lncRNAs.

Serum TSH levels are associated with postoperative recurrence and lymph node metastasis of papillary thyroid carcinoma.

Preoperative prediction of lymph node metastasis in patients with papillary thyroid carcinoma by an artificial intelligence algorithm.