SOX14 activates the p53 signaling pathway and induces apoptosis in a cervical carcinoma cell line

Expression and gene regulatory network of S100A16 protein in cervical cancer cells based on data mining

S100A16 protein belongs to the S100 family of calcium-binding proteins, which is widely distributed in human tissues and highly conserved. S100 calcium-binding proteins possess broad biological functions, such as cancer cell proliferation, apoptosis, tumor metastasis, and inflammation (Nat Rev Cancer 15:96-109, 2015). The S100A16 protein was initially isolated from a cell line derived from astrocytoma. The S100A16 protein, consisting of 103 amino acids, is a small acidic protein with a molecular weight of 11,801.4 Da and an isoelectric point (pI) of 6.28 (Biochem Biophys Res Commun 313:237-244, 2004). This protein exhibits high conservation among mammals and is widely expressed in various human tissues (Biochem Biophys Res Commun 322:1111-1122, 2004). Like other S100 proteins, S100A16 contains two EF-hand motifs that form a helix-loop-helix structural domain. The N-terminal domain and the C-terminal domain of S100A16 are connected by a "hinge" linker.S100A16 protein exhibits distinct characteristics that distinguish it from other S100 proteins. A notable feature is the presence of a single functional Ca2 + binding site located in the C-terminal EF-hand, consisting of 12 amino acids per protein monomer (J Biol Chem 281:38905-38917, 2006). In contrast, the N-terminal EF-hand of S100A16 comprises 15 amino acids instead of the typical 14, and it lacks the conserved glutamate residue at the final position. This unique attribute may contribute to the impaired Ca2 + binding capability in the N-terminal region (J Biol Chem 281:38905-38917, 2006). Studies have shown an integral role of S100 calcium-binding proteins in the diagnosis, treatment, and prognosis of certain diseases (Cancers 12:2037, 2020). Abnormal expression of S100A16 protein is implicated in the progression of breast and prostate cancer, but an inhibitor of oral cancer and acute lymphoblastic leukemia tumor cell proliferation (BMC Cancer 15:53, 2015; BMC Cancer 15:631, 2015). Tu et al. (Front Cell Dev Biol 9:645641, 2021) indicate that the overexpression of S100A16 mRNA in cervical cancer(CC) such as cervical squamous cell carcinoma and endocervical adenocarcinoma as compared to the control specimens. Tomiyama N. and co-workers (Oncol Lett 15:9929-9933, 2018) (Tomiyama, N) investigated the role of S100A16 in cancer stem cells using Yumoto cells (a CC cell line),The authors found upregulation of S100A16 in Yumoto cells following sphere formation as compared to monolayer culture.Despite a certain degree of understanding, the exact biological function of S100A16 in CC is still unclear. This article explores the role of S100A16 in CC through a bioinformatics analysis. Referencing the mRNA expression and SNP data of cervical cancer available through The Cancer Genome Atlas (TCGA) database, we analyzed S100A16 and its associated regulatory gene expression network in cervical cancer. We further screened genes co-expressed with S100A16 to hypothesize their function and relationship to the S100A16 cervical cancer phenotype.Our results showed that data mining can effectively elucidate the expression and gene regulatory network of S100A16 in cervical cancer, laying the foundation for further investigations into S100A16 cervical tumorigenesis.

Identification and validation of a novel prognostic circadian rhythm-related gene signature for stomach adenocarcinoma

Circadian rhythm genes were reported to be strongly associated with the development and prognosis of circadian rhythm disorders related to stomach adenocarcinoma (STAD), which is one of the most prevalent cancers. This study aimed to identify a circadian rhythm-related gene signature that could help predict STAD outcome. Using bioinformatics analysis approaches, 105 genes were examined in 350 patients with STAD. Overall, six hub-type circadian rhythm-associated genes (GNA11, PER1, SOX14, EZH2, MAGED1, and NR1D1) were identified using univariate and multivariate Cox regression analyses. These genes were then used to build a genetic predictive model, which was further validated using a publicly available dataset (GSE26899). Overall, genes associated with the circadian rhythm were found to be substantially correlated with the characteristics of the STAD patients (grade, sex, and M stage). In addition, the circadian rhythm-related gene signature was significantly associated with the MAPK and Notch signaling pathways, which are known risk factors for poorer STAD outcome. Taken together, these findings suggest that the herein proposed prognostic model based on six circadian rhythm-associated genes may have predictive value and potential application for clinical decision-making and for personalized treatment of STAD.

Genotype-environment interaction for milk production of Gyr cattle in Brazil and Colombia

BACKGROUND

Genotype by environment interactions (G × E) can play an important role in cattle populations and should be included in breeding programs in order to select the best animals for different environments.

OBJECTIVE

The aim of this study was to investigate the G × E for milk production of Gyr cattle in Brazil and Colombia by applying a reaction norm model used genomics information, and to identify genomic regions associated with milk production in the two countries.

METHODS

The Brazilian and Colombian database included 464 animals (273 cows and 33 sires from Brazil and 158 cows from Colombia) and 27,505 SNPs. A two-trait animal model was used for milk yield adjusted to 305 days in Brazil and Colombia as a function of country of origin, which included genomic information obtained with a single-step genomic reaction norm model. The GIBBS3F90 and POSTGSf90 programs were used.

RESULTS

The results obtained indicate G × E based on the reranking of bulls between Brazil and Colombia, demonstrating environmental differences between the two countries. The findings highlight the importance of considering the environment when choosing breeding animals in order to ensure the adequate performance of their progeny. Within this context, the reranking of bulls and the different SNPs associated with milk production in the two countries suggest that G × E is an important effect that should be included in the genetic evaluation of Dairy Gyr cattle in Brazil and Colombia.

CONCLUSION

The Gyr breeding program can be optimized by choosing a selection environment that will allow maximum genetic progress in milk production in different environments within and between countries.

The Role of SOX Transcription Factors in Ageing and Age-Related Diseases

The quest for eternal youth and immortality is as old as humankind. Ageing is an inevitable physiological process accompanied by many functional declines that are driving factors for age-related diseases. Stem cell exhaustion is one of the major hallmarks of ageing. The SOX transcription factors play well-known roles in self-renewal and differentiation of both embryonic and adult stem cells. As a consequence of ageing, the repertoire of adult stem cells present in various organs steadily declines, and their dysfunction/death could lead to reduced regenerative potential and development of age-related diseases. Thus, restoring the function of aged stem cells, inducing their regenerative potential, and slowing down the ageing process are critical for improving the health span and, consequently, the lifespan of humans. Reprograming factors, including SOX family members, emerge as crucial players in rejuvenation. This review focuses on the roles of SOX transcription factors in stem cell exhaustion and age-related diseases, including neurodegenerative diseases, visual deterioration, chronic obstructive pulmonary disease, osteoporosis, and age-related cancers. A better understanding of the molecular mechanisms of ageing and the roles of SOX transcription factors in this process could open new avenues for developing novel strategies that will delay ageing and prevent age-related diseases.

Tumor DNA Methylation Profiles Enable Diagnosis, Prognosis Prediction, and Screening for Cervical Cancer

Background

DNA-methylation-based machine learning algorithms have demonstrated powerful diagnostic capabilities, and these tools are currently emerging in many fields of tumor diagnosis and patient prognosis prediction. This work aimed to identify novel DNA methylation diagnostic biomarkers for differentiating cervical cancer (CC) from normal tissues, as well as a prognostic prediction model to predict survival of CC patients.

Methods

The methylation profiles with the available clinical characteristics were downloaded from the Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA) program. We first screened out the differential methylation sites in CC and normal tissues and performed multiple statistical analyses to discover DNA methylation diagnostic markers that are used to distinguish CC and normal control. Then, we developed a methylation-based survival model to improve risk stratification.

Results

A diagnostic prediction panel consists of five CpG markers that could predict cervical cancer versus normal tissue with highly correct rate of 100%, and cg16428251, cg22341310, and cg23316360 which in diagnostic prediction panel all could yield high sensitivity and specificity for detection of CC and normal in six cohorts (area under curve [AUC] > 0.8), in addition to excellent performance in discriminating between CC and normal sample. The diagnostic marker panel also effectively predicted the CIN3 versus normal tissue with high accuracy in two datasets (AUC = 0.80, 0.789, respectively). Furthermore, a prognostic prediction model aggregated two CpG markers that effectively stratified the prognosis of high-risk and low-risk groups (training cohort: hazard ratio [HR] 4, 95% CI: 1.7–9.6, P = 0.0021; testing cohort: hazard ratio [HR] 1.9, 95% CI: 1.2–3.1, P = 0.0072).

Conclusion

The findings of our study showed that DNA methylation markers are of great value in the diagnosis and prognosis of CC.

SOX9: Advances in Gynecological Malignancies

Transcription factors of the SOX family were first discovered in mammals in 1990. The sex-determining region Y box 9 belongs to the SOX transcription factor family. It plays an important role in inducing tissue and cell morphogenesis, survival, and many developmental processes. Furthermore, it has been shown to be an oncogene in many tumors. Gynecological malignancies are tumors that occur in the female reproductive system and seriously threaten the lives of patients. Common gynecological malignancies include ovarian cancer, cervical cancer, and endometrial cancer. So far, the molecular mechanisms related to the incidence and development of gynecological malignancies remain unclear. This makes it particularly important to discover their common causative molecule and thus provide an effective therapeutic target. In recent years, studies have found that multiple mechanisms are involved in regulating the expression of the sex-determining region Y box 9, leading to the occurrence and development of gynecological malignancies. In this review, we discuss the prognostic value of SOX9 expression and the potential of targeting SOX9 for gynecological malignancy treatment. We also discuss progress regarding the role of SOX9 in gynecological malignancy pathogenesis through its mediation of important mechanisms, including tumor initiation and proliferation, apoptosis, migration, invasion, chemoresistance, and stem cell maintenance.

Sox14 is essential for initiation of neuronal differentiation in the chick spinal cord

BACKGROUND

The neural tube comprises several different types of progenitors and postmitotic neurons that co-ordinately act with each other to play integrated functions. Its development consists of two phases: proliferation of progenitor cells and differentiation into postmitotic neurons. How progenitor cells differentiate into each corresponding neuron is an important question for understanding the mechanisms of neuronal development.

RESULTS

Here we introduce one of the Sox transcription factors, Sox14, which plays an essential role in the promotion of neuronal differentiation. Sox14 belongs to the SoxB2 subclass and its expression starts in the progenitor regions before neuronal differentiation is initiated at the trunk level of the neural tube. After neuronal differentiation is initiated, Sox14 expression gradually becomes confined to the V2a region of the neural tube, where Chx10 is co-expressed. Overexpression of Sox14 restricts progenitor cell proliferation. Conversely, the blockade of Sox14 expression by the RNAi strategy inhibits V2a neuron differentiation and causes expansion of the progenitor domain. We further found that Sox14 acted as a transcriptional activator.

CONCLUSIONS

Sox14 acts as a modulator of cell proliferation and is essential for initiation of neuronal differentiation in the chick neural tube.

SOX14 hypermethylation as a tumour biomarker in cervical cancer

BACKGROUND

The association between SOX14 and cancer has been reported. The aim of this study was to identify and validate the potential value of SOX14 methylation in the early detection of cervical cancer.

METHODS

First, we extracted the data for SOX14 methylation and expression within cervical cancer from The Cancer Genome Atlas (TCGA) database and analysed them via UALCAN, Wanderer, MEXPRESS and LinkedOmics. Subsequently, according to the bioinformatics findings, primers and probes were designed for the most significantly differentiated methylation CpG site and synthesized for methylation-specific PCR (MSP) and quantitative methylation-specific PCR (QMSP) to verify SOX14 methylation in both cervical tissuses and liquid-based cell samples. Eventually, the clinical diagnostic efficacy of SOX14 methylation in the normal, cervical intraepithelial neoplasia, and cancer groups was analysed by ROCAUC.

RESULTS

Pooled analysis demonstrated that SOX14 methylation levels were significantly increased in cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) compared to normal tissues (P < 0.001). Both the verification and validation cohorts indicated that the methylation level and the positive rate of SOX14 gradually increased with increasing severity from normal to cancer samples (P < 0.01). When the cut-off value was set as 128.45, the sensitivity and specificity of SOX14 hypermethylation in the diagnosis of cervical cancer were 94.12 and 86.46%, respectively. When taken as a screening biomarker (>CINII), the sensitivity was 74.42% and the specificity was 81.48%, with a cut-off value of 10.37.

CONCLUSION

SOX14 hypermethylation is associated with cervical cancer and has the potential to be a molecular biomarker for the screening and early diagnosis of cervical cancer.

Identification of a Goat Intersexuality-Associated Novel Variant Through Genome-Wide Resequencing and Hi-C

Background: Polled intersex syndrome (PIS) leads to reproductive disorders in goats and exerts a heavy influence on goat breeding. Since 2001, the core variant of an 11.7 kb deletion at ~129 Mb on chromosome 1 (CHI1) has been widely used as a genetic diagnostic criterion. In 2020, a ~0.48 Mb insertion within the PIS deletion was identified by sequencing in XX intersex goats. However, the suitability of this variation for the diagnosis of intersex goats worldwide and its further molecular genetic mechanism need to be clarified.

Results: The whole-genome selective sweep of intersex goats from China was performed with whole-genome next-generation sequencing technology for large sample populations and a case–control study on interbreeds. A series of candidate genes related to the goat intersexuality phenotype were found. We further confirmed that a ~0.48 Mb duplicated fragment (including ERG and KCNJ15) downstream of the ~20 Mb PIS region was reversely inserted into the PIS locus in intersex Chinese goats and was consistent with that in European Saanen and Valais black-necked goats. High-throughput chromosome conformation capture (Hi-C) technology was then used to compare the 3D structures of the PIS variant neighborhood in CHI1 between intersex and non-intersex goats. A newly found structure was validated as an intrachromosomal rearrangement. This inserted duplication changed the original spatial structure of goat CHI1 and caused the appearance of several specific loop structures in the adjacent ~20 kb downstream region of FOXL2.

Conclusions: Results suggested that the novel complex PIS variant genome was sufficient as a broad-spectrum clinical diagnostic marker of XX intersexuality in goats from Europe and China. A series of private dense loop structures caused by segment insertion into the PIS deletion might affect the expression of FOXL2 or other neighboring novel candidate genes. However, these structures require further in-depth molecular biological experimental verification. In general, this study provided new insights for future research on the molecular genetic mechanism underlying female-to-male sex reversal in goats.

Genomics Score Based on Genome-Wide Network Analysis for Prediction of Survival in Gastric Cancer: A Novel Prognostic Signature

Purpose

Gastric cancer (GC) is a product of multiple genetic abnormalities, including genetic and epigenetic modifications. This study aimed to integrate various biomolecules, such as miRNAs, mRNA, and DNA methylation, into a genome-wide network and develop a nomogram for predicting the overall survival (OS) of GC.

Materials and Methods

A total of 329 GC cases, as a training cohort with a random of 150 examples included as a validation cohort, were screened from The Cancer Genome Atlas database. A genome-wide network was constructed based on a combination of univariate Cox regression and least absolute shrinkage and selection operator analyses, and a nomogram was established to predict 1-, 3-, and 5-year OS in the training cohort. The nomogram was then assessed in terms of calibration, discrimination, and clinical usefulness in the validation cohort. Afterward, in order to confirm the superiority of the whole gene network model and further reduce the biomarkers for the improvement of clinical usefulness, we also constructed eight other models according to the different combinations of miRNAs, mRNA, and DNA methylation sites and made corresponding comparisons. Finally, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were also performed to describe the function of this genome-wide network.

Results

A multivariate analysis revealed a novel prognostic factor, a genomics score (GS) comprising seven miRNAs, eight mRNA, and 19 DNA methylation sites. In the validation cohort, comparing to patients with low GS, high-GS patients (HR, 12.886; P < 0.001) were significantly associated with increased all-cause mortality. Furthermore, after stratification of the TNM stage (I, II, III, and IV), there were significant differences revealed in the survival rates between the high-GS and low-GS groups as well (P < 0.001). The 1-, 3-, and 5-year C-index of whole genomics-based nomogram were 0.868, 0.895, and 0.928, respectively. The other models have comparable or relatively poor comprehensive performance, while they had fewer biomarkers. Besides that, DAVID 6.8 further revealed multiple molecules and pathways related to the genome-wide network, such as cytomembranes, cell cycle, and adipocytokine signaling.

Conclusion

We successfully developed a GS based on genome-wide network, which may represent a novel prognostic factor for GC. A combination of GS and TNM staging provides additional precision in stratifying patients with different OS prognoses, constituting a more comprehensive sub-typing system. This could potentially play an important role in future clinical practice.

GWAS of five gynecologic diseases and cross-trait analysis in Japanese

We performed genome-wide association studies of five gynecologic diseases using data of 46,837 subjects (5236 uterine fibroid, 645 endometriosis, 647 ovarian cancer (OC), 909 uterine endometrial cancer (UEC), and 538 uterine cervical cancer (UCC) cases allowing overlaps, and 39,556 shared female controls) from Biobank Japan Project. We used the population-specific imputation reference panel (n = 3541), yielding 7,645,193 imputed variants. Analyses performed under logistic model, linear mixed model, and model incorporating correlations identified nine significant associations with three gynecologic diseases including four novel findings (rs79219469:C > T, LINC02183, P = 3.3 × 10⁻⁸ and rs567534295:C > T, BRCA1, P = 3.1 × 10⁻⁸ with OC, rs150806792:C > T, INS-IGF2, P = 4.9 × 10⁻⁸ and rs140991990:A > G, SOX9, P = 3.3 × 10⁻⁸ with UCC). Random-effect meta-analysis of the five GWASs correcting for the overlapping subjects suggested one novel shared risk locus (rs937380553:A > G, LOC730100, P = 2.0 × 10⁻⁸). Reverse regression analysis identified three additional novel associations (rs73494486:C > T, GABBR2, P = 4.8 × 10⁻⁸, rs145152209:A > G, SH3GL3/BNC1, P = 3.3 × 10⁻⁸, and rs147427629:G > A, LOC107985484, P = 3.8 × 10⁻⁸). Estimated heritability ranged from 0.026 for OC to 0.220 for endometriosis. Genetic correlations were relatively strong between OC and UEC, endometriosis and OC, and uterine fibroid and OC (r_g > 0.79) compared with relatively weak correlations between UCC and the other four (r_g = −0.08 ~ 0.25). We successfully identified genetic associations with gynecologic diseases in the Japanese population. Shared genetic effects among multiple related diseases may help understanding the pathophysiology.

Transcription factors in SOX family: Potent regulators for cancer initiation and development in the human body

Transcription factors (TFs) have a key role in controlling the gene regulatory network that sustains explicit cell states in humans. However, an uncontrolled regulation of these genes potentially results in a wide range of diseases, including cancer. Genes of the SOX family are indeed crucial as deregulation of SOX family TFs can potentially lead to changes in cell fate as well as irregular cell growth. SOX TFs are a conserved group of transcriptional regulators that mediate DNA binding through a highly conserved high-mobility group (HMG) domain. Accumulating evidence demonstrates that cell fate and differentiation in major developmental processes are controlled by SOX TFs. Besides; numerous reports indicate that both up- and down-regulation of SOX TFs may induce cancer progression. In this review, we discuss the involvement of key TFs of SOX family in human cancers.

The role of SOX family members in solid tumours and metastasis

Cancer is a heavy burden for humans across the world with high morbidity and mortality. Transcription factors including sex determining region Y (SRY)-related high-mobility group (HMG) box (SOX) proteins are thought to be involved in the regulation of specific biological processes. The deregulation of gene expression programs can lead to cancer development. Here, we review the role of the SOX family in breast cancer, prostate cancer, renal cell carcinoma, thyroid cancer, brain tumours, gastrointestinal and lung tumours as well as the entailing therapeutic implications. The SOX family consists of more than 20 members that mediate DNA binding by the HMG domain and have regulatory functions in development, cell-fate decision, and differentiation. SOX2, SOX4, SOX5, SOX8, SOX9, and SOX18 are up-regulated in different cancer types and have been found to be associated with poor prognosis, while the up-regulation of SOX11 and SOX30 appears to be favourable for the outcome in other cancer types. SOX2, SOX4, SOX5 and other SOX members are involved in tumorigenesis, e.g. SOX2 is markedly up-regulated in chemotherapy resistant cells. The SoxF family (SOX7, SOX17, SOX18) plays an important role in angio- and lymphangiogenesis, with SOX18 seemingly being an attractive target for anti-angiogenic therapy and the treatment of metastatic disease in cancer. In summary, SOX transcription factors play an important role in cancer progression, including tumorigenesis, changes in the tumour microenvironment, and metastasis. Certain SOX proteins are potential molecular markers for cancer prognosis and putative potential therapeutic targets, but further investigations are required to understand their physiological functions.

Comparative transcriptomic analysis of bovine papillomatosis

BACKGROUND

Bovine papillomavirus (BPV) belongs to the Papillomaviridae family and infects epithelial cells of bovines and closely related animals, causing hyperproliferative lesions known as warts or papillomas, which may regress or progress to form benign or malignant tumors. The virus enters the host cell and interacts with it by altering the regulation of genes that are responsible for controlling the cell cycle, thus triggering lesion formation. It is not yet known which host genes are regulated by viral infection. Therefore, the objective of this study was to make use of next-generation RNA sequencing methods to identify differentially expressed genes associated with BPV infection, which might elucidate possible marker genes that could be used to control the disease.

RESULTS

Transcriptome analysis revealed that 1343 genes were differentially regulated (FDR < 0.05). A comparison of gene expression in infected and noninfected cows indicated that 655 genes were significantly upregulated, and 688 genes were significantly downregulated. Most differentially expressed genes were associated with BPV infection pathways, which supports the hypothesis that viral infection was the mechanism associated with this regulation.

CONCLUSIONS

This is the first study that focused on a large-scale evaluation of gene expression associated with BPV infection, which is important to identify possible metabolic pathways regulated by host genes for lesion development. In addition, novel targets could be identified in order to find ligands that interact with BPV, with the aim of interrupting the infection cycle.