Processing and Analysis of RNA-seq Data from Public Resources

CXCL14 in prostate cancer: complex interactions in the tumor microenvironment and future prospects

CXCL14 is a highly conserved chemokine expressed in various cell types, playing crucial roles in both physiological and pathological processes, including immune regulation and tumorigenesis. Recently, the role of CXCL14 in tumors has attracted considerable attention. However, previous pan-cancer studies have reported inconsistencies regarding the effects of CXCL14 on tumors, particularly concerning its expression levels in tumor tissues and its influence on various phenotypes of cancer cells. This variability is believed to stem from the context-dependent nature of CXCL14, as different sources of CXCL14 and its secretion within distinct tumor microenvironments may mediate diverse biological effects. Such phenomena have also been observed in prostate cancer research. Despite a foundational understanding of CXCL14 in prostate cancer, there remains a lack of comprehensive reviews summarizing the specific roles of this chemokine and systematically analyzing the reasons behind its complex effects. Therefore, this article aims to discuss the role of CXCL14 in the tumor microenvironment of prostate cancer and explore future research directions and potential applications.

Reliable RNA-seq analysis from FFPE specimens as a means to accelerate cancer-related health disparities research

Whole transcriptome sequencing (WTS/ RNA-Seq) is a ubiquitous tool for investigating cancer biology. RNA isolated from frozen sources limits possible studies for analysis of associations with phenotypes or clinical variables requiring long-term follow-up. Although good correlations are reported in RNA-Seq data from paired frozen and formalin fixed paraffin embedded (FFPE) samples, uncertainties regarding RNA quality, methods of extraction, and data reliability are hurdles to utilization of archival samples. We compared three different platforms for performing RNA-seq using archival FFPE oropharyngeal squamous carcinoma (OPSCC) specimens stored up to 20 years, as part of an investigation of transcriptional profiles related to health disparities. We developed guidelines to purify DNA and RNA from FFPE tissue and perform downstream RNA-seq and DNA SNP arrays. RNA was extracted from 150 specimens, with an average yield of 401.8 ng/cm 2 of tissue. Most samples yielded sufficient RNA reads >13,000 protein coding genes which could be used to differentiate HPV-associated from HPV-independent OPSCCs. Co-isolated DNA was used to identify patient ancestry. Utilizing the methods described in this study provides a robust, reliable, and standardized means of DNA & RNA extraction from FFPE as well as a means by which to assure the quality of the data generated.

Circular RNAs in human diseases

Circular RNAs (circRNAs) are a unique class of RNA molecules formed through back-splicing rather than linear splicing. As an emerging field in molecular biology, circRNAs have garnered significant attention due to their distinct structure and potential functional implications. A comprehensive understanding of circRNAs' functions and potential clinical applications remains elusive despite accumulating evidence of their involvement in disease pathogenesis. Recent research highlights their significant roles in various human diseases, but comprehensive reviews on their functions and applications remain scarce. This review provides an in-depth examination of circRNAs, focusing first on their involvement in non-neoplastic diseases such as respiratory, endocrine, metabolic, musculoskeletal, cardiovascular, and renal disorders. We then explore their roles in tumors, with particular emphasis on exosomal circular RNAs, which are crucial for cancer initiation, progression, and resistance to treatment. By detailing their biogenesis, functions, and impact on disease mechanisms, this review underscores the potential of circRNAs as diagnostic biomarkers and therapeutic targets. The review not only enhances our understanding of circRNAs' roles in specific diseases and tumor types but also highlights their potential as novel diagnostic and therapeutic tools, thereby paving the way for future clinical investigations and potential therapeutic interventions.

Identification of allograft inflammatory factor-1 suppressing the progression and indicating good prognosis of osteosarcoma

BACKGROUND

Osteosarcoma is one of the most common cancers worldwide. Intense efforts have been made to elucidate the pathogeny, but the mechanisms of osteosarcoma are still not well understood. We aimed to investigate the potential biomarker, allograft inflammatory factor-1 (AIF1), affecting the progression and prognosis of osteosarcoma.

METHODS

Three microarray datasets were downloaded from GEO datasets and one was obtained from the TCGA dataset. The differentially expressed genes (DEGs) were identified. GO and KEGG functional enrichment analyses of overlapped DEGs were performed. The PPI network of overlapped DEGs was constructed by STRING and visualized with Cytoscape. Overall survival (OS) and Metastasis free survival (MFS) were analyzed from GSE21257. Finally, the effect of the most relevant core gene affecting the progression of osteosarcoma was examined in vitro.

RESULTS

One hundred twenty six DEGs were identified, consisting of 65 upregulated and 61 downregulated genes. Only AIF1 was significantly associated with OS and MFS. It was found that AIF1 could be enriched into the NF-κB signaling pathway. GSEA and ssGSEA analyses showed that AIF1 was associated with the immune invasion of tumors. Cell experiments showed that AIF1 was underexpressed in osteosarcoma cell lines, while the malignant propriety was attenuated after overexpressing the expression of AIF1. Moreover, AIF1 also affects the expression of the NF-κB pathway.

CONCLUSION

In conclusion, DEGs and hub genes identified in the present study help us understand the molecular mechanisms underlying the carcinogenesis and progression of osteosarcoma, and provide candidate targets for diagnosis and treatment of osteosarcoma.

Transcriptome Analysis Reveals the Molecular Mechanisms of BR Negative Regulatory Factor StBIN2 Maintaining Tuber Dormancy

Potato is an important food crop. After harvest, these tubers will undergo a period of dormancy. Brassinosteroids (BRs) are a new class of plant hormones that regulate plant growth and seed germination. In this study, 500 nM of BR was able to break the dormancy of tubers. Additionally, exogenous BR also upregulated BR signal transduction genes, except for StBIN2. StBIN2 is a negative regulator of BR, but its specific role in tuber dormancy remains unclear. Transgenic methods were used to regulate the expression level of StBIN2 in tubers. It was demonstrated that the overexpression of StBIN2 significantly prolonged tuber dormancy while silencing StBIN2 led to premature sprouting. To further investigate the effect of StBIN2 on tuber dormancy, RNA-Seq was used to analyze the differentially expressed genes in OE-StBIN2, RNAi-StBIN2, and WT tubers. The results showed that StBIN2 upregulated the expression of ABA signal transduction genes but inhibited the expression of lignin synthesis key genes. Meanwhile, it was also found that StBIN2 physically interacted with StSnRK2.2 and StCCJ9. These results indicate that StBIN2 maintains tuber dormancy by mediating ABA signal transduction and lignin synthesis. The findings of this study will help us better understand the molecular mechanisms underlying potato tuber dormancy and provide theoretical support for the development of new varieties using related genes.

Circular RNAs in renal cell carcinoma: from mechanistic to clinical perspective

CircRNAs, a special type of noncoding RNAs characterized by their stable structure and unique abilities to form backsplicing loops, have recently attracted the interest of scientists. These RNAs are abundant throughout the body and play important roles such as microRNA sponges, templates for transcription, and regulation of protein translation and RNA-binding proteins. Renal cancer development is highly correlated with abnormal circRNA expression in vivo. CircRNAs are currently considered promising targets for novel therapeutic approaches as well as possible biomarkers for prognosis and diagnosis of various malignancies. Despite our growing understanding of circRNA, numerous questions remain unanswered. Here, we address the characteristics of circRNAs and their function, focusing in particular on their impact on drug resistance, metabolic processes, metastasis, cell growth, and programmed cell death in renal cancer. In addition, the application of circRNAs as prognostic and diagnostic biomarkers will be discussed.

The function and mechanisms of action of circular RNAs in Urologic Cancer

Kidney, bladder, and prostate cancer are the three major tumor types of the urologic system that seriously threaten human health. Circular RNAs (CircRNAs), special non-coding RNAs with a stabile structure and a unique back-splicing loop-forming ability, have received recent scientific attention. CircRNAs are widely distributed within the body, with important biologic functions such as sponges for microRNAs, as RNA binding proteins, and as templates for regulation of transcription and protein translation. The abnormal expression of circRNAs in vivo is significantly associated with the development of urologic tumors. CircRNAs have now emerged as potential biomarkers for the diagnosis and prognosis of urologic tumors, as well as targets for the development of new therapies. Although we have gained a better understanding of circRNA, there are still many questions to be answered. In this review, we summarize the properties of circRNAs and detail their function, focusing on the effects of circRNA on proliferation, metastasis, apoptosis, metabolism, and drug resistance in kidney, bladder, and prostate cancers.

Angiogenesis-related gene signatures reveal the prognosis of cervical cancer based on single cell sequencing and co-expression network analysis

Cervical cancer ranks first in female reproductive tract tumors in terms of morbidity and mortality. Yet the curative effect of patients with persistent, recurrent or metastatic cervical cancer remains unsatisfactory. Although antitumor angiogenic drugs have been recommended as the first-line treatment options for cervical cancer, there are no comprehensive prognostic indicators for cervical cancer based on angiogenic signature genes. In this study, we aimed to develop a model to assess the prognosis of cervical cancer based on angiogenesis-related (AG) signature genes, and to provide some reference for the comprehensive treatment of cervical cancer in the clinical setting. First we screened the AG gene set from GeneCard website, and then performed angiogenesis-related scores (AGS) per cell from single cell sequencing dataset GSE168652, followed by performing weighted gene co-expression network analysis (WGCNA) for cervical cancer patients according to angiogenesis phenotype. Thus, we established a prognostic model based on AGS by taking the intersection of WGCNA angiogenic module gene and differential gene (DEGs) of GSE168652. The GSE44001 was selected as an external validation set, followed by performing ROC curve analysis to assess its accuracy. The results showed that we successfully constructed a prognostic model related to the AG genes. Patients in the high-AGS group in both the train, test and the validation sets had a worse prognosis than those in the low-AGS group, had lower expression of most immune checkpoint-associated genes and lower tumor mutational burden as well. Patients in the low-AGS group were more sensitive to AMG.706, Bosutinib, and Lenalidomide while Imatinib, Pazopanib, and Sorafenib were more recommended to patients in the high-AGS group. Finally, TXNDC12 and ZC3H13, which have high hazard ratio and poor prognosis in the model, were highly expressed in cervical cancer cell lines and tissue. Meanwhile, the results showed that TXNDC12 promoted the migration of cervical cancer cells and the tubule-forming ability of endothelial cells. In conclusion, our model based on genes with AG features can effectively assess the prognosis of cervical cancer, and can also provide reference for clinicians to choose immune-related treatments.

Comparative Analysis of the Liver Transcriptome of Beijing You Chickens and Guang Ming Broilers under Salmonella enterica Serovar Typhimurium Infection

Salmonella enterica serovar Typhimurium (ST) is a food-borne pathogen that can infect animals and humans. It is currently the most common bacterial pathogen that negatively affects the poultry industry. Although different chicken breeds have been observed to exhibit diverse resistance to ST infection, the underlying genetic mechanisms remain unclear and the genes involved in this differential disease resistance need to be identified. To overcome this knowledge gap, we used a liver transcriptome analysis to screen differentially expressed genes (DEGs) in two different chicken breeds (local Beijing You (BY) and commercial Guang Ming No. 2 broiler line B (GM)) before and after ST infection. We also performed weighted gene co-expression network analysis (WGCNA) to detect hub genes, and employed selection signal analysis of candidate genes. Three promising genes (EGR1, JUN and FOS) were eventually identified, and were significantly and differentially expressed in the same breed under different conditions, and in the two breeds after ST infection. Hub genes, such as PPFIA4 and ZNF395, were identified using WGCNA, and were associated with the ratio of heterophils to lymphocytes (H/L), an indicator of disease resistance. the present study identified several genes and pathways associated with resistance to ST infection, and found that BY had greater resistance to ST infection than GM. The results obtained provide valuable resources for investigating the mechanisms of resistance to ST infection in different chicken breeds.

On taming the effect of transcript level intra-condition count variation during differential expression analysis: A story of dogs, foxes and wolves

The evolution of RNA-seq technologies has yielded datasets of scientific value that are often generated as condition associated biological replicates within expression studies. With expanding data archives opportunity arises to augment replicate numbers when conditions of interest overlap. Despite correction procedures for estimating transcript abundance, a source of ambiguity is transcript level intra-condition count variation; as indicated by disjointed results between analysis tools. We present TVscript, a tool that removes reference-based transcripts associated with intra-condition count variation above specified thresholds and we explore the effects of such variation on differential expression analysis. Initially iterative differential expression analysis involving simulated counts, where levels of intra-condition variation and sets of over represented transcripts are explicitly specified, was performed. Then counts derived from inter- and intra-study data representing brain samples of dogs, wolves and foxes (wolves vs. dogs and aggressive vs. tame foxes) were used. For simulations, the sensitivity in detecting differentially expressed transcripts increased after removing hyper-variable transcripts, although at levels of intra-condition variation above 5% detection became unreliable. For real data, prior to applying TVscript, ≈20% of the transcripts identified as being differentially expressed were associated with high levels of intra-condition variation, an over representation relative to the reference set. As transcripts harbouring such variation were removed pre-analysis, a discordance from 26 to 40% in the lists of differentially expressed transcripts is observed when compared to those obtained using the non-filtered reference. The removal of transcripts possessing intra-condition variation values within (and above) the 97^th and 95^th percentiles, for wolves vs. dogs and aggressive vs. tame foxes, maximized the sensitivity in detecting differentially expressed transcripts as a result of alterations within gene-wise dispersion estimates. Through analysis of our real data the support for seven genes with potential for being involved with selection for tameness is provided. TVscript is available at: https://sourceforge.net/projects/tvscript/.

SMARCB1 expression is a novel diagnostic and prognostic biomarker for osteosarcoma

BACKGROUND

Although weak SWI/SNF related matrix-associated actin-dependent regulator of chromatin subfamily B member 1 (SMARCB1) expression is a known diagnostic and prognostic biomarker in several malignancies, its expression and clinical significance in osteosarcoma remain unknown. The aim of the present study was to investigate SMARCB1 expression in osteosarcoma and its clinical significance with respect to chemosensitivity and prognosis.

METHODS

We obtained 114 specimens from 70 osteosarcoma patients to construct a tissue microarray (TMA) and assess SMARCB1 protein expression via immunohistochemistry (IHC). The mRNA expression of SMARCB1 was in-silico analyzed using open-access RNA sequencing (RNA-Seq) and clinicopathological data provided by the Therapeutically Applicable Research to Generate Effective Treatments on Osteosarcoma (TARGET-OS) project. The correlations between SMARCB1 expression and clinical features were statistically analyzed.

RESULTS

Weak SMARCB1 expression occurred in 70% of the osteosarcoma patient specimens in the TMA, and significantly correlated with poor neoadjuvant response as well as shorter overall and progression-free survival (PFS). In addition, mRNA in-silico analysis confirmed that SMARCB1 expression correlates with chemotherapeutic response and prognosis in osteosarcoma patients.

CONCLUSION

To our knowledge, the present study is the first to analyze SMARCB1 expression in osteosarcoma. SMARCB1 may serve as a novel diagnostic and prognostic biomarker in osteosarcoma.

RKC-B1 Blocks Activation of NF-κB and NLRP3 Signaling Pathways to Suppress Neuroinflammation in LPS-Stimulated Mice

RKC-B1 is a novel fermentation product obtained from the marine micromonospora FIM02-523A. Thus far, there have been few reports about the pharmacological activity of RKC-B1. In our present study, we investigated the anti-neuroinflammatory effects and the possible mechanism of RKC-B1 in LPS-stimulated mice. After treatment with RKC-B1, RNA-seq transcriptome of the cerebral cortex tissue was conducted to find the differentially expressed genes (DEGs). Inflammatory cytokines and proteins were evaluated by ELISA and WB. In RNA-seq analysis, there were 193 genes screened as core genes of RKC-B1 for treatment with neuroinflammation. The significant KEGG enrichment signaling pathways of these core genes were mainly included TNF signaling pathway, IL-17 signaling pathway, NOD-like receptor signaling pathway, NF-κB signaling pathway and others. The corresponding top five KEGG enrichment pathways of three main clusters in PPI network of core genes were closely related to human immune system and immune disease. The results showed that RKC-B1 reduced the levels of pro-inflammatory factors (IL-6, IL-1β, MCP-1, and ICAM-1) and the expression of COX2 in cerebral cortex tissue. Additionally, we found that the anti-neuroinflammation activity of RKC-B1 might be related to suppress activating of NF-κB and NLRP3/cleaved caspase-1 signaling pathways. The current findings suggested that RKC-B1 might be a promising anti-neuroinflammatory agent.