PRR4: A novel downregulated gene in laryngeal cancer

Identification of a two metastasis-related prognostic signature in the process of predicting the survival of laryngeal squamous cell carcinoma

Metastasis is a major cause of treatment failure and poor outcomes in cancer patients. The data used in the current study was downloaded from TCGA and GEO databases. Differentially expressed metastasis-related genes were identified and the biological functions were implemented. Kaplan-Meier analysis univariate, and, multivariate Cox regression analyses were performed to identify robust prognostic biomarkers, followed by construction of the risk model and nomogram. Gene set enrichment analysis was performed to identify pathways enriched in low- and high-risk groups. POLR2J3 and MYH11 were treated as prognostic biomarkers in LSCC and the risk model was constructed. Receiver operating characteristic curves revealed the good performance of the risk model. A nomogram with high accuracy was constructed, as evidenced by calibration and decision curves. Moreover, we found that the expressions of POLR2J3 and MYH11 was significantly higher in metastasis tissues compared with those in non-metastasis tissues by RT-qPCR and IHC. Our study identified novel metastasis-related prognostic biomarkers in LSCC and constructed a unique nomogram for predicting the prognosis of LSCC patients. Moreover, we explored the related mechanisms of metastasis-related genes in regulating LSCC.

Screening of biomarkers associated with diagnosis and prognosis of colorectal cancer

We aimed to explore biomarkers associated with diagnosis and prognosis of colorectal cancer. Differentially expressed protein (DEP) genes were obtained and validated. Moreover, co-expressed genes were screened and their prognostic value was evaluated. In addition, miRNAs that were negatively correlated with DEP genes were identified and used to construct a competitive endogenous RNA network. Furthermore, a support vector machine model was built using DEP genes, and a receiver operating characteristic curve was implemented to confirm its prediction performance. The results showed that only one DEP gene, CCL26, was obtained. Moreover, 43 genes co-expressed with CCL26 were identified, among which six (AP3M2, DAPK1, ISYNA1, PPM1K, PRR4 and RNF122) were linked with the prognosis of colorectal cancer. Besides, the axis RP11-47122.2/RP11-527N22.1-hsa-miR-3192-5p-CCL26 was identified as an lncRNA-miRNA-target gene network. Support vector machine model analysis showed that the area under the curve of CCL26 reached 0.878 based on GEO data and 0.743 based on our protein data. In conclusion, AP3M2, DAPK1, ISYNA1, PPM1K, PRR4, RNF122, CCL26 and hsa-miR-3192-5p appear to be related to the progression of colorectal cancer.

Gender-affirming hormone therapy induces specific DNA methylation changes in blood

Background

DNA methylation is an epigenetic mark that is influenced by underlying genetic profile, environment, and ageing. In addition to X-linked DNA methylation, sex-specific methylation patterns are widespread across autosomal chromosomes and can be present from birth or arise over time. In individuals where gender identity and sex assigned at birth are markedly incongruent, as in the case of transgender people, feminization or masculinization may be sought through gender-affirming hormone therapy (GAHT). GAHT is a cornerstone of transgender care, yet no studies to date have investigated its effect on genome-wide methylation. We profiled genome-wide DNA methylation in blood of transgender women (n = 13) and transgender men (n = 13) before and during GAHT (6 months and 12 months into feminizing or masculinizing hormone therapy).

Results

We identified several thousand differentially methylated CpG sites (DMPs) (Δβ ≥ 0.02, unadjusted p value < 0.05) and several differentially methylated regions (DMRs) in both people undergoing feminizing and masculinizing GAHT, the vast majority of which were progressive changes over time. X chromosome and sex-specific autosomal DNA methylation patterns established in early development are largely refractory to change in association with GAHT, with only 3% affected (Δβ ≥ 0.02, unadjusted p value < 0.05). The small number of sex-specific DMPs that were affected by GAHT were those that become sex-specific during the lifetime, known as sex-and-age DMPs, including DMRs in PRR4 and VMP1 genes. The GAHT-induced changes at these sex-associated probes consistently demonstrated a shift towards the methylation signature of the GAHT-naïve opposite sex, and we observed enrichment of previously reported adolescence-associated methylation changes.

Conclusion

We provide evidence for GAHT inducing a unique blood methylation signature in transgender people. This study advances our understanding of the complex interplay between sex hormones, sex chromosomes, and DNA methylation in the context of immunity. We highlight the need to broaden the field of ‘sex-specific’ immunity beyond cisgender males and cisgender females, as transgender people on GAHT exhibit a unique molecular profile.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-022-01236-4.

Identification of ZG16B as a prognostic biomarker in breast cancer

Zymogen granule protein 16B (ZG16B) has been identified in various cancers, while so far the association between ZG16B and breast cancer hasn’t been explored. Our aim is to confirm whether it can serve as a prognostic biomarker in breast cancer. In this study, Oncomine, Cancer Cell Line Encyclopedia (CCLE), Ualcan, and STRING database analyses were conducted to detect the expression level of ZG16B in breast cancer with different types. Kaplan–Meier plotter was used to analyze the prognosis of patients with high or low expression of ZG16B. We found that ZG16B was significantly upregulated in breast cancer. Moreover, ZG16B was closely associated with foregone biomarkers and crucial factors in breast cancer. In the survival analysis, high expression of ZG16B represents a favorable prognosis in patients. Our work demonstrates the latent capacity of ZG16B to be a biomarker for prognosis of breast cancer.