RNA sequencing (RNA-Seq) and its application in ovarian cancer

The oncogenic role and regulatory mechanism of ACAA2 in human ovarian cancer

Acetyl-CoAacyltransferase2 (ACAA2) is a key enzyme in the fatty acid oxidation pathway that catalyzes the final step of mitochondrial β oxidation, which plays an important role in fatty acid metabolism. The expression of ACAA2 is closely related to the occurrence and malignant progression of tumors. However, the function of ACAA2 in ovarian cancer is unclear. The expression level and prognostic value of ACAA2 were analyzed by databases. Gain and loss of function were carried out to explore the function of ACAA2 in ovarian cancer. RNA-seq and bioinformatics methods were applied to illustrate the regulatory mechanism of ACAA2. ACAA2 overexpression promoted the growth, proliferation, migration, and invasion of ovarian cancer, and ACAA2 knockdown inhibited the malignant progression of ovarian cancer as well as the ability of subcutaneous tumor formation in nude mice. At the same time, we found that OGT can induce glycosylation modification of ACAA2 and regulate the karyoplasmic distribution of ACAA2. OGT plays a vital role in ovarian cancer as a function of oncogenes. In addition, through RNA-seq sequencing, we found that ACAA2 regulates the expression of DIXDC1. ACAA2 regulated the malignant progression of ovarian cancer through the WNT/β-Catenin signaling pathway probably. ACAA2 is an oncogene in ovarian cancer and has the potential to be a target for ovarian cancer therapy.

Comparative transcriptomic study on the ovarian cancer between chicken and human

The laying hen is the spontaneous model of ovarian tumor. A comprehensive comparison based on RNA-seq from hens and women may shed light on the molecular mechanisms of ovarian cancer. We performed next-generation sequencing of microRNA and mRNA expression profiles in 9 chicken ovarian cancers and 4 normal ovaries, which has been deposited in GSE246604. Together with 6 public datasets (GSE21706, GSE40376, GSE18520, GSE27651, GSE66957, TCGA-OV), we conducted a comparative transcriptomics study between chicken and human. In the present study, miR-451, miR-2188-5p, and miR-10b-5p were differentially expressed in normal ovaries, early- and late-stage ovarian cancers. We also disclosed 499 up-regulated genes and 1,061 down-regulated genes in chicken ovarian cancer. The molecular signals from 9 cancer hallmarks, 25 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and 369 Gene Ontology (GO) pathways exhibited abnormalities in ovarian cancer compared to normal ovaries via Gene Set Enrichment Analysis (GSEA). In the comparative analysis across species, we have uncovered the conservation of 5 KEGG and 76 GO pathways between chicken and human including the mismatch repair and ECM receptor interaction pathways. Moreover, a total of 174 genes contributed to the core enrichment for these KEGG and GO pathways were identified. Among these genes, the 22 genes were found to be associated with overall survival in patients with ovarian cancer. In general, we revealed the microRNA profiles of ovarian cancers in hens and updated the mRNA profiles previously derived from microarrays. And we also disclosed the molecular pathways and core genes of ovarian cancer shared between hens and women, which informs model animal studies and gene-targeted drug development.

Omics-based molecular classifications empowering in precision oncology

BACKGROUND

In the past decades, cancer enigmatical heterogeneity at distinct expression levels could interpret disparities in therapeutic response and prognosis. It built hindrances to precision medicine, a tactic to tailor customized treatment informed by the tumors' molecular profile. Single-omics analysis dissected the biological features associated with carcinogenesis to some extent but still failed to revolutionize cancer treatment as expected. Integrated omics analysis incorporated tumor biological networks from diverse layers and deciphered a holistic overview of cancer behaviors, yielding precise molecular classification to facilitate the evolution and refinement of precision medicine.

CONCLUSION

This review outlined the biomarkers at multiple expression layers to tutor molecular classification and pinpoint tumor diagnosis, and explored the paradigm shift in precision therapy: from single- to multi-omics-based subtyping to optimize therapeutic regimens. Ultimately, we firmly believe that by parsing molecular characteristics, omics-based typing will be a powerful assistant for precision oncology.

Nanoscale dihydroartemisinin@zeolitic imidazolate frameworks for enhanced antigiardial activity and mechanism analysis

An artificial semisynthetic material can be derived from artemisinin (ART) called dihydroartemisinin (DHA). Although DHA has enhanced antigiardial potential, its clinical application is limited because of its poor selectivity and low solubility. The drug's absorption has a direct impact on the cell, and mechanism research is limited to its destruction of the cytoskeleton. In this study, we used the zeolitic imidazolate framework-8 and loaded it with DHA (DHA@Zif-8) to improve its antigiardial potential. DHA@Zif-8 can enhance cellular uptake, increase antigiardial proliferation and encystation, and expand the endoplasmic reticulum compared with the DHA-treated group. We used RNA sequencing (RNA-seq) to investigate the antigiardial mechanism. We found that 126 genes were downregulated and 123 genes were upregulated. According to the KEGG and GO pathway analysis, the metabolic functions in G. lamblia are affected by DHA@Zif-8 NPs. We used real-time quantitative reverse transcription polymerase chain reaction to verify our results using the RNA-seq data. DHA@Zif-8 NPs significantly enhanced the eradication of the parasite from the stool in vivo. In addition, the intestinal mucosal injury caused by G. lamblia trophozoites markedly improved in the intestine. This research provided the potential of utilizing DHA@Zif-8 to develop an antiprotozoan drug for clinical applications.

The pivotal role of long non-coding RNAs as potential biomarkers and modulators of chemoresistance in ovarian cancer (OC)

Ovarian cancer (OC) is a fatal gynecological disease that is often diagnosed at later stages due to its asymptomatic nature and the absence of efficient early-stage biomarkers. Previous studies have identified genes with abnormal expression in OC that couldn't be explained by methylation or mutation, indicating alternative mechanisms of gene regulation. Recent advances in human transcriptome studies have led to research on non-coding RNAs (ncRNAs) as regulators of cancer gene expression. Long non-coding RNAs (lncRNAs), a class of ncRNAs with a length greater than 200 nucleotides, have been identified as crucial regulators of physiological processes and human diseases, including cancer. Dysregulated lncRNA expression has also been found to play a crucial role in ovarian carcinogenesis, indicating their potential as novel and non-invasive biomarkers for improving OC management. However, despite the discovery of several thousand lncRNAs, only one has been approved for clinical use as a biomarker in cancer, highlighting the importance of further research in this field. In addition to their potential as biomarkers, lncRNAs have been implicated in modulating chemoresistance, a major problem in OC. Several studies have identified altered lncRNA expression upon drug treatment, further emphasizing their potential to modulate chemoresistance. In this review, we highlight the characteristics of lncRNAs, their function, and their potential to serve as tumor markers in OC. We also discuss a few databases providing detailed information on lncRNAs in various cancer types. Despite the promising potential of lncRNAs, further research is necessary to fully understand their role in cancer and develop effective strategies to combat this devastating disease.

Single-cell landscape identifies the immunophenotypes and microenvironments of HBV-positive and HBV-negative liver cancer

BACKGROUND

HBV infection leads to HCC and affects immunotherapy. We are exploring the tumor ecosystem in HCC to help gain a deeper understanding and design more effective immunotherapy strategies for patients with HCC with or without HBV infection.

METHODS

Single-cell RNA sequencing series were integrated as a discovery cohort to interrogate the tumor microenvironment of HBV-positive (HBV+) HCC and HBV-negative (HBV-) HCC. We further dissect the intratumoral immune status of HBV+ HCC and HBV- HCC. An independent cohort, including samples treated with immune checkpoint blockade therapy, was used to validate the major finding and investigate the effect of HBV infection on response to immunotherapy.

RESULTS

The interrogation of tumor microenvironment indicated that regulatory T cells, exhausted CD8+ T cells, and M1-like Macrophage_MMP9 were enriched in HBV+ HCC, while mucosa-associated invariant T cells were enriched in HBV- HCC. All subclusters of T cells showed high expression of immune checkpoint genes in HBV+ HCC. Regulatory T cells enriched in HBV+ HCC also showed more robust immunosuppressive properties, which was confirmed by cross talk between immune cell subsets. The ability of antigen presentation with major histocompatibility complex-II was downregulated in HBV+ HCC and this phenomenon can be reversed by immunotherapy. Two types of HCC also present different responses to immunotherapy.

CONCLUSIONS

There is a more immunosuppressive and exhausted tumor microenvironment in HBV+ HCC than in HBV- HCC. This in-depth immunophenotyping strategy is critical to understanding the impact of HBV and the HCC immune microenvironment and helping develop more effective treatments in patients with HCC.

The Putative Effects of Neoadjuvant Chemotherapy on the Immune System of Advanced Epithelial Ovarian Carcinoma

The epithelial ovarian carcinoma (EOC) is one of leading causes of cancer-related mortality in females. For some patients, complete resection cannot be achieved, thus neoadjuvant chemotherapy (NACT) following interval debulking surgery (IDS) could be an alternative choice. In general-held belief, cytotoxic chemotherapy is assumed to be immunosuppressive, because of its toxicity to dividing cells in the bone marrow and peripheral lymphoid tissues. However, increasing evidence highlighted that the anticancer activity of chemotherapy may also be related to its ability to act as an immune modulator. NACT not only changed the morphology of cancer cells, but also changed the transcriptomic and genomic profile of EOC, induced proliferation of cancer stem-like cells, gene mutation, and tumor-related adaptive immune response. This review will provide a comprehensive overview of recent studies evaluating the impact of NACT on cancer cells and immune system of advanced EOC and their relationship to clinical outcome. This information could help us understand the change of immune system during NACT, which might provide new strategies in future investigation of immuno-therapy for maintenance treatment of EOC.

Germline and somatic testing for ovarian Cancer: An SGO clinical practice statement

Germline and somatic genetic testing have become critical components of care for people with ovarian cancer. The identification of germline and somatic pathogenic variants as well as homologous recombination deficiency can contribute to the prediction of treatment response, prognostic outcome, and suitability for targeted agents (e.g. poly (ADP-ribose) polymerase (PARP) inhibitors). Furthermore, identifying germline pathogenic variants can prompt cascade genetic testing for at-risk relatives. Despite the clinical benefits and consensus recommendations from several organizations calling for universal genetic testing in ovarian cancer, only about one third of patients complete germline or somatic genetic testing. The members of the Society of Gynecologic Oncology (SGO) Clinical Practice Committee have composed this statement to provide an overview of germline and somatic genetic testing for patients with epithelial ovarian cancer, focusing on available testing modalities and options for care delivery.

Next-generation sequencing-based analysis of homologous recombination repair gene variant in ovarian cancer

Background

Ovarian cancer is the leading cause of death from gynecological malignancies. Investigating the HRR-related gene status, notably BRCA1/2 in different regions and populations is of great significance for formulating accurate target therapy.

Methods

We collected 124 ovarian cancer cases from the Affiliated Hospital of.Qingdao University, detected the genomic alteration of 32 genes by NGS, including.19 HRR-related genes, 9 proto-oncogenes and 4 tumor suppressor genes. Clinicopathological characteristics, variants, clinical significance, and correlation with prognosis were analyzed.

Results

The incidence of HRR-related gene mutation was 59.68 % and no statistical significance was found with multiple clinicopathological characteristics. BRCA1/2 (27.42 %) were the most frequent mutated HRR genes. 23 (18.55 %) cases harbored gBRCA1/2 mutation, with all BRCA1 mutations were pathogenic/likely pathogenic and 2 cases of BRCA2 mutation was variant of uncertain significance. Somatic BRCA1/2 mutations were found in 12 (9.68 %) cases, and sBRCA1/2 had a higher frequency in less common ovarian cancer than high-grade serous carcinoma. HRR-related gene mutation status was associated with better prognosis than HRR wild-type.

Conclusions

Somatic BRCA1/2 mutation has higher incidence in less common ovarian cancer. HRR gene mutation status is an independent prognosis factor in ovarian cancer. Clarifying the HRR gene status is important for the selection of target therapy as well as the evaluation of prognosis.

Anoikis related genes may be novel markers associated with prognosis for ovarian cancer

The aim of this study was to determine the prognostic significance of anoikis related genes (ARGs) in ovarian cancer (OC) and to develop a prognostic signature based on ARG expression. We analyzed cohorts of OC patients and used nonnegative matrix factorization (NMF) for clustering. Single-sample gene-set enrichment analysis (ssGSEA) was employed to quantify immune infiltration. Survival analyses were performed using the Kaplan-Meier method, and differences in survival were determined using the log-rank test. The extent of anoikis modification was quantified using a risk score generated from ARG expression. The analysis of single-cell sequencing data was performed by the Tumor Immune Single Cell Hub (TISCH). Our analyses revealed two distinct patterns of anoikis modification. The risk score was used to evaluate the anoikis modification patterns in individual tumors. Three hub-genes were screened using the LASSO (Least Absolute Shrinkage and Selection Operator) method and patients were classified into different risk groups based on their individual score and the median score. The low-risk subtype was characterized by decreased expression of hub-genes and better overall survival. The risk score, along with patient age and gender, were considered to identify the prognostic signature, which was visualized using a nomogram. Our findings suggest that ARGs may play a novel role in the prognosis of OC. Based on ARG expression, we have developed a prognostic signature for OC that can aid in patient stratification and treatment decision-making. Further studies are needed to validate these results and to explore the underlying mechanisms.

Identification of key genes and regulatory mechanisms in adult degenerative scoliosis

BACKGROUND

Adult degenerative scoliosis (ADS) is a spinal disorder, but its pathogenesis remain unclear. Therefore, in this study, we utilized data from the GEO database and explored the key genes and regulatory mechanisms involved in ADS.

METHODS

We performed bioinformatics analysis on the GSE209825 dataset of GEO database. Weighted gene co-expression network analysis (WGCNA) was used to identify ADS-related gene modules, and we performed gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. We constructed a protein-protein interaction (PPI) network using the STRING database. We validated the specificity of hub genes in ADS using the GSE34095 dataset and plotted ROC curves for the identification of different degenerative spinal diseases based on the hub genes expression RESULTS: We identified 113 differentially expressed lncRNAs. WGCNA identified the MEblack module had the strongest correlation to ADS. GO and KEGG analyses of target genes in lncRNAs revealed their involvement in immune responses, inflammation, cellular processes, and metabolic pathways. Through PPI and ROC analysis, 10 hub genes linked to ADS diseases with certain specificity were found: ELANE, LTF, DEFA1B, SLC2A4, DEFA1, FAXDC2, LCN2, CTSB, FDFT1, and AURKA.

CONCLUSIONS

We identified 10 potential hub genes associated with ADS and constructed a transcription factors (TFs)-lncRNAs-hub genes regulatory network. These findings provide a new direction and research basis for the targeted treatment and mechanism research of ADS.

Unveiling the novel immune and molecular signatures of ovarian cancer: insights and innovations from single-cell sequencing

Ovarian cancer is a highly heterogeneous and lethal malignancy with limited treatment options. Over the past decade, single-cell sequencing has emerged as an advanced biological technology capable of decoding the landscape of ovarian cancer at the single-cell resolution. It operates at the level of genes, transcriptomes, proteins, epigenomes, and metabolisms, providing detailed information that is distinct from bulk sequencing methods, which only offer average data for specific lesions. Single-cell sequencing technology provides detailed insights into the immune and molecular mechanisms underlying tumor occurrence, development, drug resistance, and immune escape. These insights can guide the development of innovative diagnostic markers, therapeutic strategies, and prognostic indicators. Overall, this review provides a comprehensive summary of the diverse applications of single-cell sequencing in ovarian cancer. It encompasses the identification and characterization of novel cell subpopulations, the elucidation of tumor heterogeneity, the investigation of the tumor microenvironment, the analysis of mechanisms underlying metastasis, and the integration of innovative approaches such as organoid models and multi-omics analysis.

Proteogenomics in Cancer: Then and Now

For years, the paths of sequencing technologies and mass spectrometry have occurred in isolation, with each developing its own unique culture and expertise. These two technologies are crucial for inspecting complementary aspects of the molecular phenotype across the central dogma. Integrative multiomics strives to bridge the analysis gap among different fields to complete more comprehensive mechanisms of life events and diseases. Proteogenomics is one integrated multiomics field. Here in this review, we mainly summarize and discuss three aspects: workflow of proteogenomics, proteogenomics applications in cancer research, and the SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis of proteogenomics in cancer research. In conclusion, proteogenomics has a promising future as it clarifies the functional consequences of many unannotated genomic abnormalities or noncanonical variants and identifies driver genes and novel therapeutic targets across cancers, which would substantially accelerate the development of precision oncology.

TAGET: a toolkit for analyzing full-length transcripts from long-read sequencing

Single-molecule Real-time Isoform Sequencing (Iso-seq) of transcriptomes by PacBio can generate very long and accurate reads, thus providing an ideal platform for full-length transcriptome analysis. We present an integrated computational toolkit named TAGET for Iso-seq full-length transcript data analyses, including transcript alignment, annotation, gene fusion detection, and quantification analyses such as differential expression gene analysis and differential isoform usage analysis. We evaluate the performance of TAGET using a public Iso-seq dataset and newly sequenced Iso-seq datasets from tumor patients. TAGET gives significantly more precise novel splice site prediction and enables more accurate novel isoform and gene fusion discoveries, as validated by experimental validations and comparisons with RNA-seq data. We identify and experimentally validate a differential isoform usage gene ECM1, and further show that its isoform ECM1b may be a tumor-suppressor in laryngocarcinoma. Our results demonstrate that TAGET provides a valuable computational toolkit and can be applied to many full-length transcriptome studies.

Particulate matter impairs immune system function by up-regulating inflammatory pathways and decreasing pathogen response gene expression

Airborne particulate matter produced by industrial sources and automobiles has been linked to increased susceptibility to infectious diseases and it is known to be recognized by cells of the immune system. The molecular mechanisms and changes in gene expression profiles induced in immune cells by PM have not been fully mapped out or systematically integrated. Here, we use RNA-seq to analyze mRNA profiles of human peripheral blood mononuclear cells after exposure to coarse particulate matter (PM10). Our analyses showed that PM10 was able to reprogram the expression of 1,196 genes in immune cells, including activation of a proinflammatory state with an increase in cytokines and chemokines. Activation of the IL-36 signaling pathway and upregulation of chemokines involved in neutrophil and monocyte recruitment suggest mechanisms for inflammation upon PM exposure, while NK cell-recruiting chemokines are repressed. PM exposure also increases transcription factors associated with inflammatory pathways (e.g., JUN, RELB, NFKB2, etc.) and reduces expression of RNases and pathogen response genes CAMP, DEFAs, AZU1, APOBEC3A and LYZ. Our analysis across gene regulatory and signaling pathways suggests that PM plays a role in the dysregulation of immune cell functions, relevant for antiviral responses and general host defense against pathogens.

Decoding Oncofusions: Unveiling Mechanisms, Clinical Impact, and Prospects for Personalized Cancer Therapies

Cancer-associated gene fusions, also known as oncofusions, have emerged as influential drivers of oncogenesis across a diverse range of cancer types. These genetic events occur via chromosomal translocations, deletions, and inversions, leading to the fusion of previously separate genes. Due to the drastic nature of these mutations, they often result in profound alterations of cellular behavior. The identification of oncofusions has revolutionized cancer research, with advancements in sequencing technologies facilitating the discovery of novel fusion events at an accelerated pace. Oncofusions exert their effects through the manipulation of critical cellular signaling pathways that regulate processes such as proliferation, differentiation, and survival. Extensive investigations have been conducted to understand the roles of oncofusions in solid tumors, leukemias, and lymphomas. Large-scale initiatives, including the Cancer Genome Atlas, have played a pivotal role in unraveling the landscape of oncofusions by characterizing a vast number of cancer samples across different tumor types. While validating the functional relevance of oncofusions remains a challenge, even non-driver mutations can hold significance in cancer treatment. Oncofusions have demonstrated potential value in the context of immunotherapy through the production of neoantigens. Their clinical importance has been observed in both treatment and diagnostic settings, with specific fusion events serving as therapeutic targets or diagnostic markers. However, despite the progress made, there is still considerable untapped potential within the field of oncofusions. Further research and validation efforts are necessary to understand their effects on a functional basis and to exploit the new targeted treatment avenues offered by oncofusions. Through further functional and clinical studies, oncofusions will enable the advancement of precision medicine and the drive towards more effective and specific treatments for cancer patients.

Identification and Validation of a Metabolism-Related Prognostic Signature Associated with M2 Macrophage Infiltration in Gastric Cancer

High levels of M2 macrophage infiltration invariably contribute to poor cancer prognosis and can be manipulated by metabolic reprogramming in the tumor microenvironment. However, the metabolism-related genes (MRGs) affecting M2 macrophage infiltration and their clinical implications are not fully understood. In this study, we identified 173 MRGs associated with M2 macrophage infiltration in cases of gastric cancer (GC) using the TCGA and GEO databases. Twelve MRGs were eventually adopted as the prognostic signature to develop a risk model. In the high-risk group, the patients showed poorer survival outcomes than patients in the low-risk group. Additionally, the patients in the high-risk group were less sensitive to certain drugs, such as 5-Fluorouracil, Oxaliplatin, and Cisplatin. Risk scores were positively correlated with the infiltration of multiple immune cells, including CD8+ T cells and M2 macrophages. Furthermore, a difference was observed in the expression and distribution between the 12 signature genes in the tumor microenvironment through single-cell sequencing analysis. In vitro experiments proved that the M2 polarization of macrophages was suppressed by Sorcin-knockdown GC cells, thereby hindering the proliferation and migration of GC cells. These findings provide a valuable prognostic signature for evaluating clinical outcomes and corresponding treatment options and identifying potential targets for GC treatment.

MNQ derivative D21 protects against LPS-induced inflammatory damage in bovine ovarian follicular GCs in vitro via the steroid biosynthesis signaling pathway

Bacterial infections of the reproductive system of dairy cows lead to inflammation, and lipopolysaccharide (LPS) of the cell wall of Gram-negative bacteria is the main pathogenic component of inflammation. LPS inhibits follicular growth and development and alters the expression of follicular granulosa cells (GCs) genes in the ovary, leading to their functional disorders. Naphthoquinones have anti-inflammatory effects. In this experiment, 2-methoxy-1,4-naphthoquinone (MNQ), an extract of Impatiens balsamina L, and its derivative D₂₁ were used to eliminate the inflammatory response of GCs exposed to LPS in vitro and to restore functional disorders in GCs. The anti-inflammatory effects of the two compounds were compared and their mechanism of action was investigated. The cytotoxicity of MNQ and its derivative D₂₁ on follicular GCs was determined by MTT method. The relative expression of inflammatory factors and steroid synthesis-related genes were determined by qRT-PCR. The protective effects of MNQ and D₂₁ on cellular inflammatory damage were observed by TEM. ELISA were performed to detect the levels of estradiol (E₂) and progesterone (P₄) in the culture supernatant. The expression of differential genes was analyzed by RNA-seq, and GO and KEGG enrichment analysis of differential genes were performed to investigate the mechanism of anti-inflammatory effect of D₂₁. The results showed that the maximum no-cytotoxic concentrations of MNQ and D₂₁ acting on GCs for 12 h were 4 μM and 64 μM, respectively. LPS concentration of 10 μg/mL had little effect on the survival of follicular GCs, but the relative expressions of IL-6, IL-1β and TNF-α were significantly higher (P < 0.05). The results of qRT-PCR, ELISA and TEM observations showed that the anti-inflammatory effect of D₂₁ was stronger than that of MNQ. RNA-seq analysis revealed a total of 341 differential genes between the LPS vs CK group (Control group) and the D₂₁+L vs LPS group, which were mainly enriched in signaling pathways such as steroid biosynthesis. Nine genes in this signaling pathway were analyzed, and the RNA-seq and qRT-PCR results were found to be basically consistent. In this study, we confirmed that derivative D₂₁ has stronger in vitro anti-inflammatory effects and better efficacy in protecting bovine follicular GCs from inflammatory damage than MNQ and acts through the steroid biosynthesis signaling pathway.

Screening of potential hub genes and key pathways associated with breast cancer by bioinformatics tools

Breast cancer (BC) remains the leading cause of cancer-related death in women worldwide. The development of new targeted therapies that may improve patient survival remains an area of growing interest. This study aimed to identify new biomarkers involved in BC progression that could be used as potential targeted therapies. DEGs were selected from three gene expression profiles, GSE55715, GSE124646, and GSE87049, using the GEO2R tool and Venn diagram software. Gene Ontology and KEGG pathways were then performed using DAVID software. Next, the PPI network was constructed using STRING and visualized using Cytoscape software, and hub genes were extracted using the cytoHubba plug-in. Survival analysis was performed using the Kaplan-Meier Plotter, while the expression of hub genes in BC was verified using the GEPIA2 tool. Finally, transcription the factors of hub genes were determined using the NetworkAnalyst database, and the TIMER tool was employed to explore the infiltration levels of tumor immune cells with related genes. A total of 146 DEGs were identified in the three datasets, including 60 upregulated genes that were enriched in the cell cycle, and 86 downregulated genes that were mainly enriched in the TNF signaling pathway and pathways in cancer. Ten genes were identified: BUB1, CDK1, HMMR, MAD2L1, CEP55, AURKA, CCNB2, TPX2, MELK, and KIF20A. The overexpression of hub genes, except CDK1, was associated with poor survival in BC and was regulated by several transcription factors involved in DNA binding activity and transcription regulation. The infiltration levels of immune cells were positively correlated with hub genes, particularly macrophages and CD4+ T cells. This study identified new reliable molecular biomarkers that can serve as potential therapeutic targets for BC treatment.

Identifying tumour microenvironment-related signature that correlates with prognosis and immunotherapy response in breast cancer

Tumor microenvironment (TME) plays important roles in prognosis and immune evasion. However, the relationship between TME-related genes and clinical prognosis, immune cell infiltration, and immunotherapy response in breast cancer (BRCA) remains unclear. This study described the TME pattern to construct a TME-related prognosis signature, including risk factors PXDNL, LINC02038 and protective factors SLC27A2, KLRB1, IGHV1-12 and IGKV1OR2-108, as an independent prognostic factor for BRCA. We found that the prognosis signature was negatively correlated with the survival time of BRCA patients, infiltration of immune cells and the expression of immune checkpoints, while positively correlated with tumor mutation burden and adverse treatment effects of immunotherapy. Upregulation of PXDNL and LINC02038 and downregulation of SLC27A2, KLRB1, IGHV1-12 and IGKV1OR2-108 in high-risk score group synergistically contribute to immunosuppressive microenvironment which characterized by immunosuppressive neutrophils, impaired cytotoxic T lymphocytes migration and natural killer cell cytotoxicity. In summary, we identified a TME-related prognostic signature in BRCA, which was connected with immune cell infiltration, immune checkpoints, immunotherapy response and could be developed for immunotherapy targets.

Immunotherapeutic Approaches in Ovarian Cancer

Ovarian cancer (OC) is gynecological cancer, and diagnosis and treatment are continuously advancing. Next-generation sequencing (NGS)-based diagnoses have emerged as novel methods for identifying molecules and pathways in cancer research. The NGS-based applications have expanded in OC research for early detection and identification of aberrant genes and dysregulation pathways, demonstrating comprehensive views of the entire transcriptome, such as fusion genes, genetic mutations, and gene expression profiling. Coinciding with advances in NGS-based diagnosis, treatment strategies for OC, such as molecular targeted therapy and immunotherapy, have also advanced. Immunotherapy is effective against many other cancers, and its efficacy against OC has also been demonstrated at the clinical phase. In this review, we describe several NGS-based applications for therapeutic targets of OC, and introduce current immunotherapeutic strategies, including vaccines, checkpoint inhibitors, and chimeric antigen receptor (CAR)-T cell transplantation, for effective diagnosis and treatment of OC.

Screening for diagnostic targets in tuberculosis and study on its pathogenic mechanism based on mRNA sequencing technology and miRNA-mRNA-pathway regulatory network

Purpose

Tuberculosis is common infectious diseases, characterized by infectivity, concealment and chronicity, and the early diagnosis is helpful to block the spread of tuberculosis and reduce the resistance of Mycobacterium tuberculosis to anti-tuberculosis drugs. At present, there are obvious limitations in the application of clinical detection methods used for the early diagnosis of tuberculosis. RNA sequencing (RNA-Seq) has become an economical and accurate gene sequencing method for quantifying transcripts and detecting unknown RNA species.

Methods

A peripheral blood mRNA sequencing was used to screen the differentially expressed genes between healthy people and tuberculosis patients. A protein-protein interaction (PPI) network of differentially expressed genes was constructed through Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. The potential diagnostic targets of tuberculosis were screened by the calculation of degree, betweenness and closeness in Cytoscape 3.9.1 software. Finally, the functional pathways and the molecular mechanism of tuberculosis were clarified in combination of the prediction results of key gene miRNAs, and by Gene Ontology (GO) enrichment analysis and the Kyoto Encyclopedia Genes and Genomes (KEGG) pathway annotation analysis.

Results

556 Differential genes of tuberculosis were screened out by mRNA sequencing. Six key genes (AKT1, TP53, EGF, ARF1, CD274 and PRKCZ) were screened as the potential diagnostic targets for tuberculosis by analyzing the PPI regulatory network and using three algorithms. Three pathways related to the pathogenesis of tuberculosis were identified by KEGG pathway analysis, and two key miRNAs (has-miR-150-5p and has-miR-25-3p) that might participate in the pathogenesis of tuberculosis were screened out by constructing a miRNA-mRNA pathway regulatory network.

Conclusion

Six key genes and two important miRNAs that could regulate them were screened out by mRNA sequencing. The 6 key genes and 2 important miRNAs may participate in the pathogenesis of infection and invasion of Mycobacterium tuberculosis through herpes simplex virus 1 infection, endocytosis and B cell receptor signaling pathways.

Benchmark study for evaluating the quality of reference genomes and gene annotations in 114 species

Introduction

For reference genomes and gene annotations are key materials that can determine the limits of the molecular biology research of a species; however, systematic research on their quality assessment remains insufficient.

Methods

We collected reference assemblies, gene annotations, and 3,420 RNA-sequencing (RNA-seq) data from 114 species and selected effective indicators to simultaneously evaluate the reference genome quality of various species, including statistics that can be obtained empirically during the mapping process of short reads. Furthermore, we newly presented and applied transcript diversity and quantification success rates that can relatively evaluate the quality of gene annotations of various species. Finally, we proposed a next-generation sequencing (NGS) applicability index by integrating a total of 10 effective indicators that can evaluate the genome and gene annotation of a specific species.

Results and discussion

Based on these effective evaluation indicators, we successfully evaluated and demonstrated the relative accessibility of NGS applications in all species, which will directly contribute to determining the technological boundaries in each species. Simultaneously, we expect that it will be a key indicator to examine the direction of future development through relative quality evaluation of genomes and gene annotations in each species, including countless organisms whose genomes and gene annotations will be constructed in the future.

The coming decade in precision oncology: six riddles

High-throughput methods to investigate tumour omic landscapes have quickly catapulted cancer specialists into the precision oncology era. The singular lesson of precision oncology might be that, for it to be precise, treatment must be personalized, as each cancer's complex molecular and immune landscape differs from patient to patient. Transformative therapies include those that are targeted at the sequelae of molecular abnormalities or at immune mechanisms, and, increasingly, pathways previously thought to be undruggable have become druggable. Critical to applying precision medicine is the concept that the right combination of drugs must be chosen for each patient and used at the right stage of the disease. Multiple puzzles remain that complicate therapy choice, including evidence that deleterious mutations are common in normal tissues and non-malignant conditions. The host's role is also likely to be key in determining treatment response, especially for immunotherapy. Indeed, maximizing the impact of immunotherapy will require omic analyses to match the right immune-targeted drugs to the individualized patient and tumour setting. In this Perspective, we discuss six key riddles that must be solved to optimize the application of precision oncology to otherwise lethal malignancies.

Whole-transcriptome sequencing revealed differentially expressed mRNAs and non-coding RNAs played crucial roles in NiONPs-induced liver fibrosis

Nickel oxide nanoparticles (NiONPs) induced liver fibrosis, while its mechanisms associated with transcriptome remained unclear. This study aimed to investigate the roles of differentially expressed (DE) messenger RNAs (mRNAs) and non-coding RNAs (ncRNAs) in NiONPs-induced liver fibrosis, and further confirm whether JNK/c-Jun pathway enriched by the DE RNAs was involved in the regulation of the disease. A liver fibrosis rat model was established by intratracheal perfusion of NiONPs twice a week for 9 weeks. Whole-transcriptome sequencing was applied to obtain expression profiles of mRNAs, long non-coding RNAs (lncRNAs), microRNAs (miRNAs), and circular RNAs (circRNAs) in the model rat and control liver tissues. Comparing the RNA expression profiles of the model and control liver tissues, we identified 324 DE mRNAs, 129 DE lncRNAs, 24 DE miRNAs and 33 DE circRNAs, and the potential interactions among them were revealed by constructing two co-expression networks, including lncRNA-miRNA-mRNA and circRNA-miRNA-mRNA networks. Using RT-qPCR, we verified the sequencing results of some RNAs in the networks and obtained similar expression profiles, indicating our sequencing results were reliable and referable. Through Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, we predicted the biological functions and signaling pathways potentially related to NiONPs-induced liver fibrosis, such as "positive regulation of JNK cascade", "inflammatory response", "transcription factor binding", and MAPK, Wnt, PI3K-Akt signaling pathways. JNK/c-Jun pathway, a subclass of MAPK signal, was selected for further investigation because it was significantly enriched by fibrosis-related DE genes and activated in animal models. In vitro, we detected the cytotoxicity of NiONPs on LX-2 cells and treated the cells with 5 μg/ml NiONPs for 12 h. The results showed NiONPs induced the up-regulated protein expression of fibrotic factors collagen-1a1 (Col-1a1) and matrix metalloproteinas2 (MMP2) and JNK/c-Jun pathway activation. While these effects were reversed after JNK/c-Jun pathway was blocked by SP600125 (JNK pathway inhibitor), indicating the pathway was involved in NiONPs-induced excessive collagen formation. In conclusion, our results revealed the DE mRNAs and ncRNAs played crucial roles in NiONPs-induced liver fibrosis, and JNK/c-Jun pathway mediated the development of the disease.

An RNA-seq transcriptome analysis for investigating the anti-lung cancer activity of medicinal Cuscuta chinensis Lam plant

Cuscuta chinensis Lam. is a traditional medicinal herb used to treat female sterility and male reproductive system disorders. However, the anti-lung cancer properties of Cuscuta chinensis Lam. and possible molecular mechanisms have yet to be explored. Thus, the study’s main purpose was to evaluate in vitro and in vivo anti-lung cancer properties of C. chinensis water extract (CLW) in human lung adenocarcinomas and the underlying molecular mechanism involved. Our results demonstrated that CLW caused a significant inhibition of cell viability and induced G1 cycle arrest in lung cancer cells. Furthermore, RNA-seq transcriptome analysis revealed 602 common genes with a significant expression in A549 and H1650 cells under CLW treatment. Functional enrichment analysis suggested that these common genes regulated by CLW mainly involve lung cancer cell proliferation, metastases and apoptosis processes. In addition, forty-six common genes (> 2-fold change) regulated by CLW in A549 and H1650 cells were selected for further validation. In vitro quantitative real-time PCR results confirmed that twelve genes were up-regulated, and four genes were down-regulated in A549 and H1650 cells. The in vivo experiment demonstrated CLW could significantly decrease tumour volume and tumour weight of mice compared with the control group. Moreover, in vivo quantitative real-time PCR results revealed that C11orf96, FGFBP1, FOSB and NPTX1 genes were up-regulated and EGR1, GBP4 and MAP2K6 genes were down-regulated in tumour tissues compared with the control group. These data strongly suggest that CLW could be developed as an efficacious drug for lung cancer treatment.

RNA m6A methyltransferase METTL14 promotes the procession of non-small cell lung cancer by targeted CSF1R

BACKGROUND

Non-small cell lung cancer (NSCLC) is one of the most malignant cancer types, characterized by a poor prognosis. N6-methyladenosine (m6A) is a prevalent internal modification of mRNA. METTL14, an RNA methyltransferase that mediates m6A modification, is implicated in mRNA biogenesis. However, the biomechanism of METTL14 in NSCLC is not very clear.

METHODS

Here, immunohistochemical (IHC) assay was employed to detect METTL14 in NSCLC tissues. The biological functions of METTL14 were demonstrated using cell transfection, cell proliferation assay, cell clone formation assay, cell cycle analysis, cell death analysis, transwell and wound healing assays. Transcriptome and methylated RNA immunoprecipitation (MERIP)-sequencing were used to explore the pathways and potential mechanism of METTL14 in NSCLC. RNA sequencing, METTL14 rip-sequencing, and METTL14 merip-sequencing were conducted to identify the potential targets of METTL14.

RESULTS

METTL14 was significantly correlated with clinical pathological parameters of differentiation and M stage. Additionally, METTL14 promotes cell proliferation, induces cell death, and enhances cell migration and invasion in vitro. Transcriptome and MeRIP-sequencing reveal oncogenic mechanism of METTL14. RIP-sequencing highlights CSF1R and AKR1C1 as targets of METTL14. After validation with TCGA dataset, colony stimulating factor 1 receptor (CSF1R) showed significant positive coefficient with METTL14, and was presumed to be one target of METTl14 in lung cancer and verified by the cellular experiments.

CONCLUSION

In conclusion, our results revealed the clinical significance of m6A RNA modification atlas, the function, and molecular targets CSF1R of METTL14 in NSCLC cell lines. The RNA m6A methyltransferase METTL14 promotes the progression of NSCLC by targeted CSF1R.

Comparative Genomic Hybridization and Transcriptome Sequencing Reveal Genes with Gain in Acute Lymphoblastic Leukemia: JUP Expression Emerges as a Survival-Related Gene

Acute lymphoblastic leukemia (ALL) in children or adults is characterized by structural and numeric aberrations in chromosomes; these anomalies strongly correlate with prognosis and clinical outcome. Therefore, this work aimed to identify the genes present in chromosomal gain regions found more frequently in patients with acute lymphoblastic leukemia (ALL) and ALL-derived cell lines using comparative genomic hybridization (CGH). In addition, validation of the genes found in these regions was performed utilizing RNAseq from JURKAT, CEM, and SUP-B15 cell lines, as well as expression microarrays derived from a MILE study. Chromosomes with common gain zones that were maintained in six or more samples were 14, 17, and 22, in which a total of 22 genes were identified. From them, NT5C3B, CNP, ACLY, and GNB1L maintained overexpression at the mRNA level in the cell lines and in patients with ALL. It is noteworthy that SALL2 showed very high expression in T-ALL, while JUP was highly expressed in B-ALL lineages. Interestingly, the latter correlated with worse survival in patients. This provided evidence that the measurement of these genes has high potential for clinical utility; however, their expressions should first be evaluated with a sensitive test in a more significant number of patients.

Integration of artificial intelligence and precision oncology in Latin America

Next-generation medicine encompasses different concepts related to healthcare models and technological developments. In Latin America and the Caribbean, healthcare systems are quite different between countries, and cancer control is known to be insufficient and inefficient considering socioeconomically discrepancies. Despite advancements in knowledge about the biology of different oncological diseases, the disease remains a challenge in terms of diagnosis, treatment, and prognosis for clinicians and researchers. With the development of molecular biology, better diagnosis methods, and therapeutic tools in the last years, artificial intelligence (AI) has become important, because it could improve different clinical scenarios: predicting clinically relevant parameters, cancer diagnosis, cancer research, and accelerating the growth of personalized medicine. The incorporation of AI represents an important challenge in terms of diagnosis, treatment, and prognosis for clinicians and researchers in cancer care. Therefore, some studies about AI in Latin America and the Caribbean are being conducted with the aim to improve the performance of AI in those countries. This review introduces AI in cancer care in Latin America and the Caribbean, and the advantages and promising results that it has shown in this socio-demographic context.

Biomarker screening in preeclampsia: an RNA-sequencing approach based on data from multiple studies

OBJECTIVE

Biomarkers have become important in the prognosis and diagnosis of various diseases. High-throughput methods, such as RNA sequencing facilitate the detection of differentially expressed genes (DEGs), hence potential biomarker candidates. Individual studies suggest long lists of DEGs, hampering the identification of clinically relevant ones. Concerning preeclampsia - a major obstetric burden with high risk for adverse maternal and/or neonatal outcomes - limitations in diagnosis and prediction are still important issues. We, therefore, developed a workflow to facilitate the screening for biomarkers.

METHODS

On the basis of the tool DESeq2, a comprehensive workflow for identifying DEGs was established, analyzing data from several publicly available RNA-sequencing studies. We applied it to four RNA-sequencing datasets (one blood, three placenta) analyzing patients with preeclampsia and normotensive controls. We compared our results with other published approaches and evaluated their performance.

RESULTS

We identified 110 genes that are dysregulated in preeclampsia, observed in at least three of the studies analyzed, six even in all four studies. These included FLT-1, TREM-1, and FN1, which either represent established biomarkers at protein level, or promising candidates based on recent studies. For comparison, using a published meta-analysis approach, 5240 DEGs were obtained.

CONCLUSION

This study presents a data analysis workflow for preeclampsia biomarker screening, capable of identifying promising biomarker candidates, while drastically reducing the numbers of candidates. Moreover, we were also able to confirm its performance for heart failure. This approach can be applied to additional diseases for biomarker identification, and the set of DEGs identified in preeclampsia represents a resource for further studies.

Bioinformatics analysis reveals potential biomarkers associated with the occurrence of intracranial aneurysms

To better understand the molecular mechanisms of intracranial aneurysm (IA) pathogenesis, we used gene coexpression networks to identify hub genes and functional pathways associated with IA onset. Two Gene Expression Omnibus (GEO) datasets encompassing intracranial aneurysm tissue samples and cerebral artery control samples were included. To discover functional pathways and potential biomarkers, weighted gene coexpression network analysis was employed. Next, single-gene gene set enrichment analysis was employed to investigate the putative biological roles of the chosen genes. We also used receiver operating characteristic analysis to confirm the diagnostic results. Finally, we used a rat model to confirm the hub genes in the module of interest. The module of interest, which was designated the green module and included 115 hub genes, was the key module that was most strongly and negatively associated with IA formation. According to gene set variation analysis results, 15 immune-related pathways were significantly activated in the IA group, whereas 7 metabolic pathways were suppressed. In two GEO datasets, SLC2A12 could distinguish IAs from control samples. Twenty-nine hub genes in the green module might be biomarkers for the occurrence of cerebral aneurysms. SLC2A12 expression was significantly downregulated in both human and rat IA tissue. In the present study, we identified 115 hub genes related to the pathogenesis of IA onset and deduced their potential roles in various molecular pathways; this new information may contribute to the diagnosis and treatment of IAs. By external validation, the SLC2A12 gene may play an important role. The molecular function of SLC2A12 in the process of IA occurrence can be further studied in a rat model.

Inhibitory Effects and Gene Expression Analysis of Chemotherapeutic Photodynamic Therapy by using a Liposomally Formulated Indocyanine Green Derivative

BACKGROUND

Photodynamic therapy (PDT) utilizes the enhanced permeability retention effect of photosensitizers and is less invasive and more selective than traditional chemotherapy. We constructed a chemotherapeutic PDT (chemo-PDT) nanoscale drug delivery system using a liposomally formulated indocyanine green derivative (ICG-Lipo) that encapsulated carboplatin and docetaxel (ICG-Lipo-C&D).

METHODS

The antitumor effect of chemo-PDT mediated by ICG-Lipo-C&D was evaluated in a murine colon 26 CDF1 mouse model. Gene expression in tumor tissues was analyzed by RNA sequencing.

RESULTS

Chemo-PDT using ICG-Lipo-C&D demonstrated an even stronger PDT-enhancing effect than did ICG-Lipo due to the synergistic effect of carboplatin and docetaxel. In addition, gene expression analysis showed that PDT with ICG-Lipo-C&D increased the expression of immune-related genes and decreased the expression of cytoskeleton-related genes.

CONCLUSIONS

Chemo-PDT using ICG-Lipo as a photosensitizer as well as a drug delivery system with an enhanced permeability retention effect may be a promising cancer therapy.

Mitochondria-Targeted Mesoporous Organic Silica Nanoplatforms for Overcoming Cisplatin Resistance by Disturbing Mitochondrial Redox Homeostasis

Cisplatin (also known as DDP) resistance is one of the biggest challenges in the treatment of ovarian cancer. Recent studies have found that mitochondrion, as a potential target of DDP, participates in drug-related apoptosis and resistance. Overexpressed glutathione (GSH) in resistant cells is involved in protecting mitochondria from DDP or DDP-induced ROS. In this work, triphenylphosphonium (TPP) modified disulfide bond-rich (S-S) mesoporous organic silica nanoplatforms (DMON) were developed to deliver DDP (TPP-DMON@DDP) to mitochondria for overcoming DDP resistance. TPP supported the migration of nanoplatforms to the mitochondria, with consequent depletion of mitochondrial GSH by the S-S bond of DMON, leading to mitochondria in redox dyshomeostasis. These treated cells seemed more susceptible to the DDP released from the nanoplatforms. Significantly increased ROS production, mitochondrial damage, and apoptosis were observed in TPP-DMON@DDP-treated cells. Overall, interference of mitochondrial redox homeostasis provides a new opportunity for improving DDP cytotoxicity against resistant cells.

Unravelling of the comparative Transcriptomic Profile of Gallbladder Cancer using mRNA sequencing

BACKGROUND

Gallbladder cancer (GBC) represents a wide geographical diversity as well as heterogeneity in clinical and genomic landscape. There seems to be little progress in the development of diagnostic biomarkers, targeted therapies or individualized approaches to GBC management. In this study, we investigated the whole transcriptome profile of GBC patients using RNA sequencing and identified key genes and pathways associated with gallbladder cancer using bioinformatics.

METHODOLOGY

A total of 10 cases of GBC were collected and sequenced. The raw reads of the gallbladder sample was compared with the gallbladder normal control (SRA Database ID: ERX288537: HPA RNA-seq normal tissues gallbladder). Using Gene ontology analysis the differentially expressed genes were categorized into the biological pathway, cellular component, and molecular function. Pathway enrichment analyses, protein-protein interaction, transcription factor and miRNA interaction that regulate the expression of hub genes were conducted using bioinformatics tool.

RESULTS

A total of 954 differentially expressed mRNA transcripts were identified, including overexpression of REG4, TMEM238, S100A2, LYPD2, and KRT17, as well as underexpressed genes like CCKAR, IGSF10, CHRM2, CRISP3, and FGF19. Enrichment analysis showed the metabolic pathways to be the top five cancer pathways in gallbladder carcinogenesis besides PI3k-Akt signalling pathway, cAMP signalling pathway, miRNAs in cancer, and cell adhesion profile of GBC.

CONCLUSIONS

CCKAR, CDKN2A and LRRK2 were found to be most involved genes in its progression and development through different regulatory pathways. Further, most of the genes were significantly involved in PI3k-Akt, Wnt and hedgehog signaling pathways which have a key role in gallbladder cancer development.

Next Generation Sequencing and Molecular Biomarkers in Ovarian Cancer—An Opportunity for Targeted Therapy

Ovarian cancer is the deadliest of all gynecologic malignancies claiming the lives of nearly 14,000 women in the United States annually. Despite therapeutic advances, the ovarian cancer mortality rate has remained stagnant since the 1980’s. The molecular heterogeneity of ovarian cancers suggest they may be more effectively treated via precision medicine. Current guidelines recommend germline and somatic testing for all new epithelial ovarian cancer diagnoses to assist providers in identifying candidates for targeted therapies. Next generation sequencing (NGS) identifies targetable, driver, and novel mutations used to guide treatment decisions. Performing NGS is standard of care in many other malignancies, but for ovarian cancer the use of NGS in daily practice is still emerging. This review discusses the targetable genetic mutations and role of NGS and molecular biomarker testing in the treatment of ovarian cancer.

COVID-19 Biomarkers Recognition & Classification Using Intelligent Systems

Background:

SARS-CoV-2 has paralyzed mankind due to its high transmissibility and its associated mortality, causing millions of infections and deaths worldwide. The search for gene expression biomarkers from the host transcriptional response to infection may help understand the underlying mechanisms by which the virus causes COVID-19. This research proposes a smart methodology integrating different RNA-Seq datasets from SARS-CoV-2, other respiratory diseases, and healthy patients.

Methods:

The proposed pipeline exploits the functionality of the ‘KnowSeq’ R/Bioc package, integrating different data sources and attaining a significantly larger gene expression dataset, thus endowing the results with higher statistical significance and robustness in comparison with previous studies in the literature. A detailed preprocessing step was carried out to homogenize the samples and build a clinical decision system for SARS-CoV-2. It uses machine learning techniques such as feature selection algorithm and supervised classification system. This clinical decision system uses the most differentially expressed genes among different diseases (including SARS-Cov-2) to develop a four-class classifier.

Results:

The multiclass classifier designed can discern SARS-CoV-2 samples, reaching an accuracy equal to 91.5%, a mean F1-Score equal to 88.5%, and a SARS-CoV-2 AUC equal to 94% by using only 15 genes as predictors. A biological interpretation of the gene signature extracted reveals relations with processes involved in viral responses.

Conclusion:

This work proposes a COVID-19 gene signature composed of 15 genes, selected after applying the feature selection ‘minimum Redundancy Maximum Relevance’ algorithm. The integration among several RNA-Seq datasets was a success, allowing for a considerable large number of samples and therefore providing greater statistical significance to the results than previous studies. Biological interpretation of the selected genes was also provided.

Ovarian cancer-specific dysregulated genes with prognostic significance: scRNA-Seq with bulk RNA-Seq data and experimental validation

A major cause of gynecological cancer -related deaths worldwide, ovarian cancer is characterized by heterogeneity in both tumor cells and the tumor microenvironment (TME). Our study aimed to characterize tumor cell heterogeneity and the infiltration of M2 tumor-associated macrophages (TAMs) in the ovarian cancer TME by single-cell RNA-Seq (scRNA-Seq) analysis combined with bulk RNA sequencing (bulk RNA-Seq). Several highly variable genes were identified in ovarian cancer tissues, and tumor cell heterogeneity and infiltrating immune tumor cell heterogeneity were characterized in ovarian cancer cells. M2 TAMs in the TME were the predominant phenotype of TAM. Further, M2 TAM infiltration in the TME was negatively correlated with poor prognosis of ovarian cancer patients. Four M2 TAM-associated genes (SLAMF7, GNAS, TBX2-AS1, and LYPD6) correlated with the prognostic survival of ovarian cancer patients. Knockdown of SLAMF7 or GNAS mRNA repressed malignancy and cisplatin resistance of ovarian cancer cells. ScRNA-Seq combined with bulk RNA-Seq identified the same four genes associated with M2 TAMs. The prognostic risk score model based on these four genes may hold favorable predictive value for the prognosis of ovarian cancer patients.

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.

Metabolic alterations and WNT signaling impact immune response in HGSOC

PURPOSE

Our study used transcriptomic and metabolomic strategies to determine the molecular profiles of HGSOC patient samples derived from primary tumor and ascites cells. These data identified clinically relevant heterogeneity among and within patients and highlighted global and patient-specific cellular responses to neoadjuvant chemotherapy (NACT).

EXPERIMENTAL DESIGN

Tissue from 61 treatment naïve patients with HGSOC were collected. In addition, 11 benign, 32 ascites, and 18 post-NACT samples (matched to the individual patient's pre-NACT sample) were collected. RNA-sequencing (RNA-seq) was performed on all samples collected. Two-dimensional spatial proteomic data was collected for two pairs of pre-and post-NACT. Untargeted metabolomics data using GCxGC-MS was generated for 30 treatment-naive tissues. Consensus clustering, analysis of differential expression, pathway enrichment, and survival analyses were performed.

RESULTS

Treatment-naïve HGSOC tissues had distinct transcriptomic and metabolomic profiles. The mesenchymal subtype harbored a metabolomic profile distinct from the other subtypes. Compared to primary tumor tissue, ascites showed significant changes in immune response and signaling pathways. NACT caused significant alterations in gene expression and WNT activity, and this corresponded to altered immune response. Overall, WNT signaling levels were inversely correlated with immune cell infiltration in HGSOC tissues and WNT signaling post-NACT was inversely correlated with progression-free survival.

CONCLUSIONS

Our study concluded that HGSOC is a heterogenous disease at baseline and growing molecular differences can be observed between primary tumor and ascites cells or within tumors in response to treatment. Our data reveal potential exploratory biomarkers relevant for treatment selection and predicting patient outcomes that warrant further research.

Long Noncoding RNA LIFR-AS1: A New Player in Human Cancers

Emerging evidence has indicated that aberrantly expressed long noncoding RNAs (lncRNAs) play a vital role in various biological processes associated with tumorigenesis. Leukemia inhibitory factor receptor antisense RNA1 (LIFR-AS1) is a recently identified lncRNA transcribed in an antisense manner from the LIFR gene located on human chromosome 5p13.1. LIFR-AS1 regulates tumor proliferation, migration, invasion, apoptosis, and drug resistance through different mechanisms. Its expression level is related to the clinicopathological characteristics of tumors and plays a key role in tumor occurrence and development. In this review, we summarize the role of LIFR-AS1 in the development and progression of different cancers and highlight the potential for LIFR-AS1 to serve as a biomarker and therapeutic target for a variety of human cancers.

Prognostic Value and Immune Infiltration Analysis of Nuclear Factor Erythroid-2 Family Members in Ovarian Cancer

Ovarian cancer (OC) often presents at an advanced stage and is still one of the most frequent causes of gynecological cancer-related mortality worldwide. The nuclear factor erythroid-2 (NFE2) transcription factors include nuclear factor, erythroid 2 like 1 (NFE2L1), NFE2L2, and NFE2L3. NFE2 members bind to the antioxidant-response element (ARE) region and activate the expression of targeted genes. The distinct functions of NFE2 members in OC remain poorly elucidated. Several online bioinformatics databases were applied to determine gene expression, prognosis, mutations, and immune infiltration correlation in OC patients. NFE2L1 and NFE2L2 were decreased in OC, whereas NFE2L3 was increased. NFE2L2 and NFE2L3 were significantly correlated with the clinical stages of OC. High NFE2L1 level was significantly associated with short progression-free survival (PFS) in patients with OC ( $\text{HR}=1.18$ , $P=0.021$ ), while high NFE2L2 expression strongly correlated with long PFS ( $\text{HR}=0.77$ , $P=0.00067$ ). High NFE2L3 expression was associated with better overall survival and postprogression survival in OC. Functional analysis showed that NFE2 members mainly focused on transcription coactivator activities. Genetic alterations of NFE2 members were found in 13% of OC patients, and amplification ranked the top. The expression of NFE2 members was significantly correlated with immune infiltration of CD4+ T cells, CD8+ T cells, B cells, macrophages, and neutrophils in OC. Our study provides novel insights into the roles and prognostic potential of NFE2 family members in OC.

Identification of a Novel Oncogenic Fusion Gene SPON1-TRIM29 in Clinical Ovarian Cancer That Promotes Cell and Tumor Growth and Enhances Chemoresistance in A2780 Cells

Gene structure alterations, such as chromosomal rearrangements that develop fusion genes, often contribute to tumorigenesis. It has been shown that the fusion genes identified in public RNA-sequencing datasets are mainly derived from intrachromosomal rearrangements. In this study, we explored fusion transcripts in clinical ovarian cancer specimens based on our RNA-sequencing data. We successfully identified an in-frame fusion transcript SPON1-TRIM29 in chromosome 11 from a recurrent tumor specimen of high-grade serous carcinoma (HGSC), which was not detected in the corresponding primary carcinoma, and validated the expression of the identical fusion transcript in another tumor from a distinct HGSC patient. Ovarian cancer A2780 cells stably expressing SPON1-TRIM29 exhibited an increase in cell growth, whereas a decrease in apoptosis was observed, even in the presence of anticancer drugs. The siRNA-mediated silencing of SPON1-TRIM29 fusion transcript substantially impaired the enhanced growth of A2780 cells expressing the chimeric gene treated with anticancer drugs. Moreover, a subcutaneous xenograft model using athymic mice indicated that SPON1-TRIM29-expressing A2780 cells rapidly generated tumors in vivo compared to control cells, whose growth was significantly repressed by the fusion-specific siRNA administration. Overall, the SPON1-TRIM29 fusion gene could be involved in carcinogenesis and chemotherapy resistance in ovarian cancer, and offers potential use as a diagnostic and therapeutic target for the disease with the fusion transcript.

Identification of the Recombinant Plasmodium vivax Surface-Related Antigen as a Possible Immune Evasion Factor Against Human Splenic Fibroblasts by Targeting ITGB1

Plasmodium vivax–infected erythrocytes can enter the spleen and evade spleen clearance to establish chronic infections. However, the mechanism underlying P. vivax immune evasion in the spleen is still unclear. Human splenic fibroblasts (HSF), also known as barrier cells, play an essential role in the immune function of spleen. A hypothesis holds that P. vivax—infected erythrocytes induce spleen structural remodeling to form barrier cells. Subsequently, these infected erythrocytes can selectively cytoadhere to these barrier cells to escape spleen clearance. In this work, we found that P. vivax surface-related antigen (PvSRA; PlasmoDB ID: PVX_084970), an exported protein on infected erythrocyte membrane, could bind with HSF. Considering the above hypothesis, we speculated that PvSRA might be involved in P. vivax immune evasion by changing HSF cell performance. To investigate this speculation, RNA sequencing, protein microarray, and bioinformatics analysis technologies were applied, and in vitro validations were further performed. The results showed that the recombinant PvSRA attracted HSF migration and interacted with HSF by targeting integrin β1 (ITGB1) along with changes in HSF cell performance, such as focal adhesion, extracellular matrix, actin cytoskeleton, and cell cycle. This study indicated that PvSRA might indeed participate in the immune evasion of P. vivax in the spleen by changing HSF function through PvSRA–ITGB1 axis.

Does the "Devil" originate from the fallopian tubes?

Epithelial ovarian cancer (OC) is a heterogeneous disease and continues to be mostly diagnosed in advanced stages. The high lethality, the high rate of platinum-resistance, and the poor survival outcomes are the principal factors for categorizing OC among the most aggressive gynecological cancers. Only recently, a substantial progress has been made in our latest understanding of the origins of OC, particularly of high-grade serous histology. For a long time, the accumulation of genetic alterations in epithelial single layer cells of ovarian cysts caused by cyclic ovulations was considered as the most important driver and the long-standing dogma of ovarian tumorigenesis. Besides, the unique biological features and high histological heterogeneity of OC did not support this hypothesis. Indeed, various extra-ovarian cells of origin and multiple sites to each histotype were proposed, supported by cogent evidence from clinical cohorts and animal studies. In light of this enigma, this review was conducted to discuss the recent evidence supporting the revised origins of ovarian carcinoma histotypes with a particular focus on high-grade serous OC which may impact diagnostic and preventive approaches.

Uncovering the stability status of the reputed reference genes in breast and hepatic cancer cell lines

Accurate and reliable relative gene expression analysis via the Reverse Transcription-quantitative Real Time PCR (RT-qPCR) method strongly depends on employing several stable reference genes as normalizers. Utilization of the reference genes without analyzing their expression stability under each experimental condition causes RT-qPCR analysis error as well as false output. Similar to cancerous tissues, cancer cell lines also exhibit various gene expression profiles. It is crucial to recognize stable reference genes for well-known cancer cell lines to minimize RT-qPCR analysis error. In this study, we showed the expression level and investigated the expression stability of eight common reference genes that are ACTB, YWHAZ, HPRT1, RNA18S, TBP, GAPDH, UBC, and B2M, in two sets of cancerous cell lines. One set contains MCF7, SKBR3, and MDA-MB231 as breast cancer cell lines. Another set includes three hepatic cancer cell lines, including Huh7, HepG2, and PLC-PRF5. Three excel-based softwares comprising geNorm, BestKeeper, and NormFinder, and an online tool, namely RefFinder were used for stability analysis. Although all four algorithms did not show the same stability ranking of nominee genes, the overall results showed B2M and ACTB as the least stable reference genes for the studied breast cancer cell lines. While TBP had the lowest expression stability in the three hepatic cancer cell lines. Moreover, YWHAZ, UBC, and GAPDH showed the highest stability in breast cancer cell lines. Besides that, a panel of five nominees, including ACTB, HPRT1, UBC, YWHAZ, and B2M showed higher stability than others in hepatic cancer cell lines. We believe that our results would help researchers to find and to select the best combination of the reference genes for their own experiments involving the studied breast and hepatic cancer cell lines. To further analyze the reference genes stability for each experimental condition, we suggest researchers to consider the provided stability ranking emphasizing the unstable reference genes.

Transcriptomic landscape of gene expression profiles and pathways in JORRP tumor tissues and HPV6/11 E6-E7-overexpressing HNSCC cell lines

Juvenile-onset recurrent respiratory papillomatosis (JORRP) is the most common benign laryngeal neoplasm in children and is considered to be primarily caused by human papillomavirus (HPV) types 6 and 11. In the present study, we performed RNA sequencing (RNA-seq) of 8 tumors and 4 adjacent nontumor tissues to explore the transcriptional profiles of JORRP tumors. A total of 1151 upregulated genes involved in the IL-17 signaling pathway and 1620 downregulated genes involved in dysregulated inflammatory responses were reported. Immunohistochemistry (IHC) assays confirmed the upregulation of IL-17C in JORRP tumors compared with paired adjacent nontumor tissues. Real-time PCR (RT-PCR) assays showed positive correlations between CXCL1 and CXCL8 and the Derkay Clinic Score of JORRP patients. We further overexpressed the HPV6 or HPV11 E6 and E7 oncogenes in SNU-1076 head and neck squamous cell carcinoma (HNSCC) cell lines and carried out RNA-seq. We found that HPV6-E6-E7 gene overexpression resulted in only 16 upregulated genes and 1 downregulated gene; however, HPV11-E6-E7 gene overexpression resulted in 1776 upregulated genes and 461 downregulated genes compared with the control cell lines. The DEGs of HPV11-E6-E7 gene overexpression were positively enriched in the DNA replication-related terms by Gene Ontology (GO) analysis and the IL-17 signaling pathway by Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Taken together, our present findings revealed IL-17 signaling pathway-related gene profiles that might contribute to disease pathogenesis and that the HPV11 E6 and E7 oncogenes promote disease progression by enhancing tumor growth and activating the IL-17 signaling pathway in JORRP patients. Importance JORRP is primarily caused by HPV 6 and HPV11 infection, however, the gene signatures of tumor are less understood currently. In the present study, we performed RNA-sequencing and found up-regulated genes associated with "IL-17 signaling pathway" and down-regulated genes associated with inflammatory-related pathways. Further RNA-sequencing was performed in HPV6-E6-E7 or HPV11-E6-E7 over-expressing SNU-1076 HNSCC cells lines to explore the potential pathogenic molecular mechanisms of HPV virus. We found HPV11-E6-E7 over-expression resulted in gene expressions related to DNA replication and IL-17 signaling pathway. Our results suggested enriched IL-17 signaling pathway resulted from HPV11 infection might contribute to JORRP pathogenesis.

CXCL2-mediated ATR/CHK1 signaling pathway and platinum resistance in epithelial ovarian cancer

Tumor microenvironment and chemokines play a significant role in cancer chemoresistance. This study was designed to reveal the important role of CXCL2 in platinum resistance in epithelial ovarian cancer (EOC). Differently expressed (DE) genes were screen out based on analysis of GSE114206 dataset in GEO database. The expression of DE chemokines was further validated in platinum- resistant and sensitive EOC. Cell viability assay and cell apoptosis assay were performed to explore the roles of CXCL2 in EOC. Cell stemness characteristics and the signaling pathway regulated by CXCL2 were also investigated in this study. As the results showed, CXCL2 was identified up-regulated in platinum-resistant EOC. The functional assays showed overexpressing CXCL2 or co-culturing with recombinant human CXCL2 promoted cell resistance to cisplatin. Conversely, knocking down CXCL2 or co-culturing with neutralizing antibody to CXCL2 increased cell response to cisplatin. CXCL2 overexpressing maintained cell stemness and activated ATR/CHK1 signaling pathway in EOC. Moreover, we further demonstrated that CXCL2-mediated resistance to cisplatin could be saved by SB225002, the inhibitor of CXCL2 receptor, as well as be rescued by SAR-020106, the inhibitor of ATR/CHK1 signaling pathway. This study identified a CXCL2-mediated mechanism in EOC platinum resistance. Our findings provided a novel target for chemoresistance prevention in EOC.

ARMT: An automatic RNA-seq data mining tool based on comprehensive and integrative analysis in cancer research

The comprehensive and integrative analysis of RNA-seq data, in different molecular layers from diverse samples, holds promise to address the full-scale complexity of biological systems. Recent advances in gene set variant analysis (GSVA) are providing exciting opportunities for revealing the specific biological processes of cancer samples. However, it is still urgently needed to develop a tool, which combines GSVA and different molecular characteristic analysis, as well as prognostic characteristics of cancer patients to reveal the biological processes of disease comprehensively. Here, we develop ARMT, an automatic tool for RNA-Seq data analysis. ARMT is an efficient and integrative tool with user-friendly interface to analyze related molecular characters of single gene and gene set comprehensively based on transcriptome and genomic data, which builds the bridge for deeper information between genes and pathways, to further accelerate scientific findings. ARMT can be installed easily from https://github.com/Dulab2020/ARMT.

Recent Advancements in Biosensing Approaches for Screening and Diagnostic Applications

Recent advancements in molecular recognition have provided additional diagnostic and treatment approaches for multiple diseases, including autoimmune disorders and cancers. Research investigating how the composition of biological fluids is altered during disease progression, including differences in the expression of the small molecules, proteins, RNAs, and other components present in patient tears, saliva, blood, urine, or other fluids, has provided a wealth of potential candidates for early disease screening; however, adoption of biomarker screening into clinical settings has been challenged by the need for more robust, low-cost, and high-throughput assays. This review examines current approaches in molecular recognition and biosensing for the quantification of biomarkers for disease screening and diagnostic outcomes.