C1orf64 is a novel androgen receptor target gene and coregulator that interacts with 14-3-3 protein in breast cancer

Exploring the molecular mechanisms of asthma across multiple datasets

BACKGROUND

Asthma, a prevalent chronic respiratory disorder, remains enigmatic, notwithstanding considerable advancements in our comprehension. Continuous efforts are crucial for discovering novel molecular targets and gaining a comprehensive understanding of its pathogenesis.

MATERIALS AND METHODS

In this study, we analyzed gene expression data from 212 individuals, including asthma patients and healthy controls, to identify 267 differentially expressed genes, among which C1orf64 and C7orf26 emerged as potential key genes in asthma pathogenesis. Various bioinformatics tools, including differential gene expression analysis, pathway enrichment, drug target prediction, and single-cell analysis, were employed to explore the potential roles of the genes.

RESULTS

Quantitative PCR demonstrated differential expression of C1orf64 and C7orf26 in the asthmatic airway epithelial tissue, implying their potential involvement in asthma pathogenesis. GSEA enrichment analysis revealed significant enrichment of these genes in signaling pathways associated with asthma progression, such as ABC transporters, cell cycle, CAMs, DNA replication, and the Notch signaling pathway. Drug target prediction, based on upregulated and downregulated differential expression, highlighted potential asthma treatments, including Tyrphostin-AG-126, Cephalin, Verrucarin-a, and Emetine. The selection of these drugs was based on their significance in the analysis and their established anti-inflammatory and antiviral invasion properties. Utilizing Seurat and Celldex packages for single-cell sequencing analysis unveiled disease-specific gene expression patterns and cell types. Expression of C1orf64 and C7orf26 in T cells, NK cells, and B cells, instrumental in promoting hallmark features of asthma, was observed, suggesting their potential influence on asthma development and progression.

CONCLUSION

This study uncovers novel genetic aspects of asthma, highlighting potential therapeutic pathways. It exemplifies the power of integrative bioinformatics in decoding complex disease patterns. However, these findings require further validation, and the precise roles of C1orf64 and C7orf26 in asthma warrant additional investigation to validate their therapeutic potential.

Characterization of Wnt Signaling Pathway Aberrations in Metastatic Prostate Cancer

Wnt (wingless-type) signaling pathway (WSP) alterations have been identified in patients with prostate cancer and are implicated in disease progression and hormonal resistance. In this study, we utilized a multi-institutional dataset to characterize molecular alterations in the canonical and noncanonical WSPs in prostate cancer. Patients with prostate cancer who underwent tissue-based genomic sequencing were investigated. Tumors with somatic activating mutations in CTNNB1 or RSPO2 or inactivating mutations in either APC or RNF43 were characterized as having aberrant canonical Wnt signaling (WSP-activated). Overall survival analyses were restricted to microsatellite-stable (MSS) tumors lacking RNF43 G659fs* mutations. We also investigated noncanonical WSP by evaluation of ROR1, ROR2, and WNT5 in WSP-activated versus WSP wild-type (WSP-WT) tumors. Of 4,138 prostate cancer samples, 3,684 were MSS. Among MSS tumors, 42.4% were from metastatic sites, of which 19.1% were WSP activated, and 57.6% were from the prostate, of which 10.1% were WSP activated. WSP-activated tumors were more prevalent in metastatic sites than in primary prostate cancer. WSP-activated prostate cancer exhibited more SPOP mutations and higher expression of canonical WSP activators than WSP-WT tumors. ROR1 gene expression was elevated in WSP-activated tumors from both primary and metastatic sites. M2 macrophages predominated the tumor microenvironment in WSP-activated tumors. There was no significant difference in overall survival between patients with WSP-activated and WSP-WT prostate cancer. WSP-activated prostate cancer demonstrated a more immunosuppressed tumor microenvironment and a pronounced upregulation of ROR1 gene expression, underscoring its potential involvement in the crosstalk between canonical and noncanonical WSPs. Implications: Our findings may provide a rationale for developing novel therapeutic strategies targeting Wnt-activated prostate cancer.

Role of steroid receptor-associated and regulated protein in tumor progression and progesterone receptor signaling in endometrial cancer

BACKGROUND

Steroid receptor-associated and regulated protein (SRARP) suppresses tumor progression and modulates steroid receptor signaling by interacting with estrogen receptors and androgen receptors in breast cancer. In endometrial cancer (EC), progesterone receptor (PR) signaling is crucial for responsiveness to progestin therapy. The aim of this study was to investigate the role of SRARP in tumor progression and PR signaling in EC.

METHODS

Ribonucleic acid sequencing data from the Cancer Genome Atlas, Clinical Proteomic Tumor Analysis Consortium, and Gene Expression Omnibus were used to analyze the clinical significance of SRARP and its correlation with PR expression in EC. The correlation between SRARP and PR expression was validated in EC samples obtained from Peking University People's Hospital. SRARP function was investigated by lentivirus-mediated overexpression in Ishikawa and HEC-50B cells. Cell Counting Kit-8 assays, cell cycle analyses, wound healing assays, and Transwell assays were used to evaluate cell proliferation, migration, and invasion. Western blotting and quantitative real-time polymerase chain reaction were used to evaluate gene expression. The effects of SRARP on the regulation of PR signaling were determined by co-immunoprecipitation, PR response element (PRE) luciferase reporter assay, and PR downstream gene detection.

RESULTS

Higher SRARP expression was significantly associated with better overall survival and disease-free survival and less aggressive EC types. SRARP overexpression suppressed growth, migration, and invasion in EC cells, increased E-cadherin expression, and decreased N-cadherin and Wnt family member 7A ( WNT7A ) expression. SRARP expression was positively correlated with PR expression in EC tissues. In SRARP -overexpressing cells, PR isoform B (PRB) was upregulated and SRARP bound to PRB. Significant increases in PRE-based luciferase activity and expression levels of PR target genes were observed in response to medroxyprogesterone acetate.

CONCLUSIONS

This study illustrates that SRARP exerts a tumor-suppressive effect by inhibiting the epithelial-mesenchymal transition via Wnt signaling in EC. In addition, SRARP positively modulates PR expression and interacts with PR to regulate PR downstream target genes.

Novel gene signature for predicting biochemical recurrence-free survival of prostate cancer and PRAME modulates prostate cancer progression

Biochemical recurrence (BCR) is considered as an early sign of prostate cancer (PCa) progression after initial treatment, such as radical prostatectomy and radiotherapy; hence, it is important to stratify patients at risk of BCR. In this study, we established a robust 8-gene signature (APOF, Clorf64, RPE65, SEMG1, ARHGDIG, COMP, MKI67 and PRAME) based on the PCa transcriptome profiles in the Cancer Genome Atlas (TCGA) for predicting BCR-free survival of PCa, which was further validated in the MSK-IMPACT Clinical Sequencing Cohort (MSKCC) PCa cohort. Moreover, we found that one risk-related gene (PRAME) was upregulated in tumor samples, particularly in high-risk group was well as in patients metastatic tumor and was correlated with chemotherapeutic drug response. In vitro experiments showed that knocking down PRAME reduced the proliferation, migration, and invasion of PCa cells. Therefore, our study established a new 8-gene signature that could accurately predict the BCR risk of PCa. Inhibition of PRAME attenuated the proliferation, invasion, and migration of PCa cells. These findings provide a novel tool for stratifying high-risk PCa patient and shed light on the mechanism of PCa progression.

Biomarkers of Castrate Resistance in Prostate Cancer: Androgen Receptor Amplification and T877A Mutation Detection by Multiplex Droplet Digital PCR

Androgen Receptor (AR) alterations (amplification, point mutations, and splice variants) are master players in metastatic castration resistant prostate cancer (CRPC) progression and central therapeutic targets for patient management. Here, we have developed two multiplexed droplet digital PCR (ddPCR) assays to detect AR copy number (CN) and the key point mutation T877A. Overcoming challenges of determining gene amplification from liquid biopsies, these assays cross-validate each other to produce reliable AR amplification and mutation data from plasma cell free DNA (cfDNA) of advanced prostate cancer (PC) patients. Analyzing a mixed PC patient cohort consisting of CRPC and hormone sensitive prostate cancer (HSPC) patients showed that 19% (9/47) patients had AR CN amplification. As expected, only CRPC patients were positive for AR amplification, while interestingly the T877A mutation was identified in two patients still considered HSPC at the time. The ddPCR based analysis of AR alterations in cfDNA is highly economic, feasible, and informative to provide biomarker detection that may help to decide on the best follow-up therapy for CRPC patients.

Joint eQTL mapping and inference of gene regulatory network improves power of detecting both cis- and trans-eQTLs

MOTIVATION

Genetic variations of expression quantitative trait loci (eQTLs) play a critical role in influencing complex traits and diseases development. Two main factors that affect the statistical power of detecting eQTLs are: (i) relatively small size of samples available, and (ii) heavy burden of multiple testing due to a very large number of variants to be tested. The later issue is particularly severe when one tries to identify trans-eQTLs that are far away from the genes they influence. If one can exploit co-expressed genes jointly in eQTL-mapping, effective sample size can be increased. Furthermore, using the structure of the gene regulatory network (GRN) may help to identify trans-eQTLs without increasing multiple testing burden.

RESULTS

In this article, we use the structure equation model (SEM) to model both GRN and effect of eQTLs on gene expression, and then develop a novel algorithm, named sparse SEM for eQTL mapping (SSEMQ), to conduct joint eQTL mapping and GRN inference. The SEM can exploit co-expressed genes jointly in eQTL mapping and also use GRN to determine trans-eQTLs. Computer simulations demonstrate that our SSEMQ significantly outperforms nine existing eQTL mapping methods. SSEMQ is further used to analyze two real datasets of human breast and whole blood tissues, yielding a number of cis- and trans-eQTLs.

AVAILABILITY AND IMPLEMENTATION

R package ssemQr is available at https://github.com/Ivis4ml/ssemQr.git.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Genomic and epigenetic aberrations of chromosome 1p36.13 have prognostic implications in malignancies

Deletions of chromosome 1p36 are common in malignancies; however, there is limited information regarding the biological and prognostic implications of 1p36 in cancer. Steroid Receptor-Associated and Regulated Protein (SRARP) is a tumor suppressor on chromosome 1p36.13 that its inactivation predicts poor cancer outcome, indicating that the 1p36.13 segment requires further studies. Therefore, a comprehensive multi-omics analysis of The Cancer Genome Atlas (TCGA), the Pan-Cancer Analysis of Whole Genomes (PCAWD), the International Cancer Genome Consortium (ICGC), and the Genomic Data Commons (GDC) Pan-Cancer datasets was conducted to investigate the prognostic implications of 1p36.13 in malignancies. This study revealed that expression and DNA methylation of multiple genes on 1p36.13 are significantly associated with survival in primary tumors and normal adjacent tissues. In addition, copy-number loss in every gene on 1p36.13 predicts poor cancer outcome. Importantly, copy-number loss and somatic mutations of chromosome 1p36.13 segment are associated with worse survival in primary tumors, and DNA hypermethylation of 1p36.13 predicts poor outcome in normal adjacent tissues. Therefore, genomic and epigenetic aberrations of chromosome 1p36.13 have promising prognostic implications in cancer.

Steroid receptor-associated and regulated protein is a biomarker in predicting the clinical outcome and treatment response in malignancies

BACKGROUND

Steroid receptor-associated and regulated protein (SRARP) has recently been identified as a novel tumor suppressor in malignancies of multiple tissue origins. SRARP is located on chromosome 1p36.13 and is widely inactivated by deletions and epigenetic silencing in malignancies. Therefore, additional studies are required to explore SRARP as a potential cancer biomarker.

AIM

This study explores the application of SRARP as a novel biomarker in malignancies of multiple tissue origins using the analysis of large genomic datasets.

METHODS AND RESULTS

A comprehensive genomic analysis of large cancer datasets was carried out to examine the association of SRARP expression and copy-number with molecular and clinical features in malignancies of multiple tissue origins. This study demonstrated that SRARP under-expression and copy-number loss are strongly associated with the loss of other tumor suppressors such as TP53 and NF1 mutations and oncogenic gains, including N-MYC amplification and ERG rearrangement, suggesting that SRARP inactivation is associated with wider genomic instability in malignancies. Importantly, SRARP under-expression and copy-number loss are strong predictors of poor clinical and/or pathological features in breast, colorectal, lung, prostate, gastric, endometrial, cervical, brain, ovarian, bladder, thyroid, and hepatocellular cancers as well as neuroblastoma, uveal melanoma, and acute myeloid leukemia with highly significant odds ratios. Finally, higher SRARP expression and copy-number predict a better response to several cancer drugs.

CONCLUSION

This study suggests that the SRARP inactivation presents a robust biomarker in predicting molecular and clinicopathological features, and treatment response in malignancies.

Identification of retinoid acid induced 16 as a novel androgen receptor target in prostate cancer cells

BACKGROUND

Retinoid acid induced 16 (RAI16) was reported to enhance tumorigenesis in hepatocellular carcinoma (HCC). The androgen receptor (AR) is a nuclear hormone receptor that functions as a critical oncogene in several cancer progressions. However, whether RAI16 is a candidate AR target gene that may involve in prostate cancer progression was unclear.

MATERIALS & METHODS

RAI16 expression was detected in prostate cancer cells with or without the AR agonist R1881 treatment by quantitative RT-PCR and Western blot. Direct AR binding to the RAI16 promoter was tested using AR chromatin immunoprecipitation (ChIP) and luciferase assay. Cell viability and colony formation assays in response to R1881 were analyzed in cells with RAI16 knockdown by specific siRNA.

RESULTS

The expression of RAI16 was high in LNCaP(AI), LNCaP(AD), C4-2 expressing AR, but low in Du145 and Pc-3 cells without AR expressing. In addition, the expression of RAI16 could be induced by 10 nM R1881 treatment LNCaP(AD) and C4-2 cells, but inhibited by AR specific siRNA treatment. Furthermore, AR binds directly to ARE3 (-2003~-1982bp) of RAI16 promoter region by ChIP and luciferase assay. RAI16 knockdown inhibited the enhancement of cell viability and colony formation of AR stimulation.

CONCLUSIONS

We demonstrate for the first time that RAI16 is a direct target gene of AR. RAI16 may involved in cell growth of prostate cancer cells in response to AR signaling.

CAncer bioMarker Prediction Pipeline (CAMPP)-A standardized framework for the analysis of quantitative biological data

With the improvement of -omics and next-generation sequencing (NGS) methodologies, along with the lowered cost of generating these types of data, the analysis of high-throughput biological data has become standard both for forming and testing biomedical hypotheses. Our knowledge of how to normalize datasets to remove latent undesirable variances has grown extensively, making for standardized data that are easily compared between studies. Here we present the CAncer bioMarker Prediction Pipeline (CAMPP), an open-source R-based wrapper (https://github.com/ELELAB/CAncer-bioMarker-Prediction-Pipeline -CAMPP) intended to aid bioinformatic software-users with data analyses. CAMPP is called from a terminal command line and is supported by a user-friendly manual. The pipeline may be run on a local computer and requires little or no knowledge of programming. To avoid issues relating to R-package updates, a renv .lock file is provided to ensure R-package stability. Data-management includes missing value imputation, data normalization, and distributional checks. CAMPP performs (I) k-means clustering, (II) differential expression/abundance analysis, (III) elastic-net regression, (IV) correlation and co-expression network analyses, (V) survival analysis, and (VI) protein-protein/miRNA-gene interaction networks. The pipeline returns tabular files and graphical representations of the results. We hope that CAMPP will assist in streamlining bioinformatic analysis of quantitative biological data, whilst ensuring an appropriate bio-statistical framework.

SRARP and HSPB7 are epigenetically regulated gene pairs that function as tumor suppressors and predict clinical outcome in malignancies

Deletions of chromosome 1p36 are common in cancers; however, despite extensive studies, there has been limited success for discovering candidate tumor suppressors in this region. SRARP has recently been identified as a novel corepressor of the androgen receptor (AR) and is located on chromosome 1p36. Here, bioinformatics analysis of large tumor datasets was performed to study SRARP and its gene pair, HSPB7. In addition, using cancer cell lines, mechanisms of SRARP and HSPB7 regulation and their molecular functions were investigated. This study demonstrated that SRARP and HSPB7 are a gene pair located 5.2 kb apart on 1p36.13 and are inactivated by deletions and epigenetic silencing in malignancies. Importantly, SRARP and HSPB7 have tumor suppressor functions in clonogenicity and cell viability associated with the downregulation of Akt and ERK. SRARP expression is inversely correlated with genes that promote cell proliferation and signal transduction, which supports its functions as a tumor suppressor. In addition, AR exerts dual regulatory effects on SRARP, and although an increased AR activity suppresses SRARP transcription, a minimum level of AR activity is required to maintain baseline SRARP expression in AR+ cancer cells. Furthermore, as observed with SRARP, HSPB7 interacts with the 14-3-3 protein, presenting a shared molecular feature between SRARP and HSPB7. Of note, genome- and epigenome-wide associations of SRARP and HSPB7 with survival strongly support their tumor suppressor functions. In particular, DNA hypermethylation, lower expression, somatic mutations, and lower copy numbers of SRARP are associated with worse cancer outcome. Moreover, DNA hypermethylation and lower expression of SRARP in normal adjacent tissues predict poor survival, suggesting that SRARP inactivation is an early event in carcinogenesis. In summary, SRARP and HSPB7 are tumor suppressors that are commonly inactivated in malignancies. SRARP inactivation is an early event in carcinogenesis that is strongly associated with worse survival, presenting potential translational applications.