RNA therapeutics in cancer treatment.

RNA therapeutics are a class of drugs that use RNA molecules to treat diseases, including cancer. RNA therapeutics work by targeting specific genes or proteins involved in the disease process, with the aim of blocking or altering their activity to ultimately halt or reverse the disease progression. The use of RNA therapeutics in cancer treatment has shown great potential, as they offer the ability to specifically target cancer cells while leaving healthy cells intact. This is in contrast to traditional chemotherapy and radiation treatments, which can damage healthy cells and cause unpleasant side effects. The field of RNA therapeutics is rapidly advancing, with several types of RNA molecules being developed for cancer treatment, including small interfering RNA, microRNA, mRNA, and RNA aptamers. Each type of RNA molecule has unique properties and mechanisms of action, allowing for targeted and personalized cancer treatments. In this chapter, we will explore the different types of RNA therapeutics used in cancer treatment, their mechanisms of action, and their potential applications in treating different types of cancer. We will also discuss the challenges and opportunities in the development and research of RNA therapeutics for cancer, as well as the future outlook for this promising field.

TOR1B: a predictor of bone metastasis in breast cancer patients.

Recent therapeutic advances in breast cancer (BC) have improved survival outcomes; however, the prognosis for patients with bone metastasis (BM) remains poor. Hence, novel clinical biomarkers are needed to accurately predict BC BM as well as to promote personalized medicine. Here, we discovered a novel biomarker, TOR1B, for BM in BC patients via analysis of BC gene expression data and clinical information downloaded from open public databases. In cancer cells, we found high expression levels of TOR1B in the nucleus and endoplasmic reticulum. Regarding gene expression, the level of TOR1B was significantly upregulated in BC patients with BM (p < 0.05), and the result was externally validated. In addition, gene expression clearly demonstrated two distinct types of prognoses in ER- and PR-positive patients. In multivariate regression, the gene could be an independent predictor of BM in BC patients, i.e., a low expression level of TOR1B was associated with delayed metastasis to bone in BC patients (HR, 0.28; 95% CI 0.094-0.84). Conclusively, TOR1B might be a useful biomarker for predicting BM; specifically, patients with ER- and PR-positive subtypes would benefit from the clinical use of this promising prognostic biomarker.

Genotypic diversity of CSFV field strains: A silent risk reduces vaccination efficacy of CSFV vaccines in Vietnam.

Classical swine fever (CSF) is a highly contagious, devastating, and transboundary viral disease that afflicts swine industries worldwide. Immunization with vaccines is one of the most effective strategies for controlling this disease. However, shifts in the antigenicity and pathogenicity of novel evolving viral strains have the potential to evade vaccination. In this study, 352 samples from swines exhibiting fever, hemorrhages, lethargy, and diarrhea in different pig farms located in 9 provinces of Vietnam were collected. CSFV was identified even within farms that had been vaccinated against CSFV. Several farms had swine which had been co-infection with CSFV and other pathogens. Copies of the E2 gene of 21 samples were isolated, cloned, sequenced, analyzed, and compared with copies of E2 in four vaccine strains. We identified a total of 42 amino acid substitutions in this glycoprotein, including 11 positions that affect the antigenic properties of E2 and 7 positions that are associated with neutralizing epitopes. The E2 glycoprotein of CSFV strains circulating in Vietnam and vaccine strains differ in their antigenicity. These findings provide deep insights into the molecular characteristics, genetic diversity, pathogenicity, antigenicity, and evolution of CSFV strains in Vietnam. Understanding the pathogenicity, antigenicity, and evolution of circulating CSFV strains will provide avenues for developing new vaccines and efficient approaches to control this disease.

Human papillomavirus prevalence and genotype distribution in Vietnamese male patients between 2016 and 2020.

Human papillomavirus (HPV) infection in men is a serious issue because it is associated with genital warts, anogenital cancers, and HPV transmission to their sex partners. This study aimed to investigate the prevalence and genotypes of HPVs in Vietnamese male patients hospitalized with sexually transmitted infection (STI) symptoms between 2016 and 2020 by using polymerase chain reaction and reverse dot blot hybridization analysis. HPV DNA was detected in 191/941 (20.3%) penile cell samples. The HPV patient's mean age was 30.3 in the range of 16- and 69-year-old. The highest HPV prevalence (84.7%) was found in patients between 20- and 39-year-old. A total of 313 HPV genotypes were identified. The multiple-infection rate was 42.9%. The most common high-risk (HR)-HPV genotypes were HPV-16 (8.0%), HPV-51 (7.7%), HPV-52 (4.8%), HPV-56 (4.2%), and HPV-18 (3.8%). Furthermore, HPV-11 and HPV-6 genotypes were the two most common low-risk (LR)-HPV genotypes with the rate of 36.7% and 21.4%, respectively. Notably, HPV-52 was found circulating in Vietnam for the first time. In conclusion, this study results showed that HPV prevalence in Vietnamese male patients was common and diverse. In addition, regarding public health and cancer prevention, the inclusion of the HPV vaccination into the national vaccination program for both men and women is recommended.

Genetic diversity and molecular characterization of classical swine fever virus envelope protein genes E2 and Erns circulating in Vietnam from 2017 to 2019.

Classical swine fever virus (CSFV) is an RNA virus that incurs severe economic costs to swine industries worldwide. This study was conducted to investigate the genetic diversity among CSFV strains circulating in Vietnam, with a focus on their genetic variants relative to four vaccine strains. Samples from clinical cases were collected from different provinces of Central and Southern Vietnam from 2017 to 2019. 21 CSFV-positive samples were selected for amplification and sequencing of the full-length Erns and E2 genes. Phylogenetic analyses of these two genes showed that most CSFV strains circulating in Central and Southern Vietnam from 2017 to 2019 belong to subgroup 2.1c, whereas the remaining strains cluster into subgroup 2.2. All CSFV field strains in this study were genetically distant from group 1 strains. Analysis of the E2 and Erns genes indicated that all CSFV field strains have low sequence identity with the vaccine strains (80-83.5% and 82.3-86% sequence identity for E2 and Erns, respectively). Likewise, amino acid-level sequence analysis showed 87.3-91.1% and 87.6-91.6% sequence identity for E2 and Erns, respectively. Together, our findings indicate that CSFV strains circulating in Vietnam belong to subtypes 2.2 and 2.1c, and we also provide novel insights into the epidemiology, molecular characteristics, genetic diversity, and evolution of these circulating CSFV strains.

Inflammatory conversion of quiescent osteoblasts by metastatic breast cancer cells through pERK1/2 aggravates cancer-induced bone destruction.

Disruption of bone homeostasis caused by metastatic osteolytic breast cancer cells increases inflammatory osteolysis and decreases bone formation, thereby predisposing patients to pathological fracture and cancer growth. Alteration of osteoblast function induces skeletal diseases due to the disruption of bone homeostasis. We observed increased activation of pERK1/2 in osteolytic breast cancer cells and osteoblasts in human pathological specimens with aggressive osteolytic breast cancer metastases. We confirmed that osteolytic breast cancers with high expression of pERK1/2 disrupt bone homeostasis via osteoblastic ERK1/2 activation at the bone-breast cancer interface. The process of inflammatory osteolysis modulates ERK1/2 activation in osteoblasts and breast cancer cells through dominant-negative MEK1 expression and constitutively active MEK1 expression to promote cancer growth within bone. Trametinib, an FDA-approved MEK inhibitor, not only reduced breast cancer-induced bone destruction but also dramatically reduced cancer growth in bone by inhibiting the inflammatory skeletal microenvironment. Taken together, these findings suggest that ERK1/2 activation in both breast cancer cells and osteoblasts is required for osteolytic breast cancer-induced inflammatory osteolysis and that ERK1/2 pathway inhibitors may represent a promising adjuvant therapy for patients with aggressive osteolytic breast cancers by altering the shared cancer and bone microenvironment.

Down-regulation of solute carrier family 10 member 1 is associated with early recurrence and poorer prognosis of hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is one of the most frequent malignancies and the fourth-leading cancer-related death worldwide. Most patients with HCC are diagnosed at a late stage in which curable therapies are limited. Thus, identifying biomarkers for early diagnosis and prognosis of HCC is essential for improving the treatment effectiveness in patients with HCC. In this paper, the SLC10A1 expression levels in the cells and the tissues and their correlation with HCC were analyzed using bioinformatics tools. Clinical information data and gene expression profiles were retrieved from the Gene Expression Omnibus and The Cancer Genome Atlas. Chi-square tests, log-rank tests, and Kaplan-Meier curves were performed using R packages. In all statistical analyses, a p-value of less than 0.05 was considered significant. We found that SLC10A1 primarily expresses in the liver, especially on the plasma membrane. The expression levels of SLC10A1 in tumors were consistently lower than that in normal tissue. Down-regulation of SLC10A1 was correlated with a poor survival outcome [p = 4.50e-05] and recurrence-free survival [p = 8.0e-04] in patients with HCC. In addition, multivariate analysis indicated that the expression of SLC10A1 was an independent predictor for survival outcome [p = 2.17e-05] and recurrence-free survival [p = 1.63e-04]. We concluded that SLC10A1 is a potential biomarker for the early diagnosis and prognosis of HCC in the era of personalized medicine.

A novel signature predicts recurrence risk and therapeutic response in breast cancer patients.

Acetylserotonin O-methyltransferase (ASMT) is a key enzyme in the synthesis of melatonin. Although melatonin has been shown to exhibit anticancer activity and prevents endocrine resistance in breast cancer, the role of ASMT in breast cancer progression remains unclear. In this retrospective study, we analyzed gene expression profiles in 27 data sets on 7244 patients from 11 countries. We found that ASMT expression was significantly reduced in breast cancer tumors relative to healthy tissue. Among breast cancer patients, those with higher levels of ASMT expression had better relapse-free survival outcomes and longer metastasis-free survival times. Following treatment with tamoxifen, patients with greater ASMT expression experienced longer periods before relapse or distance recurrence. Motivated by these results, we devised an ASMT gene signature that can correctly identify low-risk cases with a sensitivity and specificity of 0.997 and 0.916, respectively. This signature was robustly validated using 23 independent breast cancer mRNA array data sets from different platforms (consisting of 5800 patients) and an RNAseq data set from TCGA (comprising 1096 patients). Intriguingly, patients who are classified as high-risk by the signature benefit from adjuvant chemotherapy, and those with grade II tumors who are classified as low-risk exhibit improved overall survival and distance relapse-free outcomes following endocrine therapy. Together, our findings more clearly elucidate the roles of ASMT, provide strategies for improving the efficacy of tamoxifen treatment and help to identify those patients who may maximally benefit from adjuvant or endocrine therapies.

Bioinformatic identification and expression analysis of the chicken B cell lymphoma (BCL) gene.

BACKGROUND: B cell lymphoma (BCL) families play an important role in apoptosis as a growth factor, cell death programming, cytokine expression and immune-related genes expression. OBJECTIVES: In this study, to investigate the roles of BCLs, we performed genome-wide identification, expression and functional analyses of the BCL family in chicken. METHODS: Chicken BCLs genes were identified and analyzed by using bioinformatics approach. Expression profiles and Hierarchical cluster analysis of the BCLs genes in different chicken tissues were obtained from the genome-wide RNA-seq in the GEO, and Cluster and Java Treeview, respectively. RESULTS: A total of 16 BCLs genes were identified from the chicken genome, which could be further classified into five distinct groups in the phylogenetic tree. On the other hand, the interaction among BCLs proteins and between BCLs proteins with NF-κB subunits are limited, indicating that the remaining the functions of BCLs protein could be investigated in chicken. Moreover, KEGG pathway analysis indicated that BCL gene family was involved in regulation of apoptotic and immune response. Finally, BCL gene family was differentially expressed in chicken tissues, pathogen infection and growth stages of early chicken early embryo. CONCLUSION: This study provides significant insights into the potential functions of BCLs in chicken, including the regulation of apoptosis, cell death and expression of immune-related genes.

Cyclophilin B induces chemoresistance by degrading wild-type p53 via interaction with MDM2 in colorectal cancer.

Colorectal cancer (CRC) is one of the leading causes of cancer-related deaths worldwide. Chemoresistance is a major problem for effective therapy in CRC. Here, we investigated the mechanism by which peptidylprolyl isomerase B (PPIB; cyclophilin B, CypB) regulates chemoresistance in CRC. We found that CypB is a novel wild-type p53 (p53WT)-inducible gene but a negative regulator of p53WT in response to oxaliplatin treatment. Overexpression of CypB shortens the half-life of p53WT and inhibits oxaliplatin-induced apoptosis in CRC cells, whereas knockdown of CypB lengthens the half-life of p53WT and stimulates p53WT-dependent apoptosis. CypB interacts directly with MDM2, and enhances MDM2-dependent p53WT ubiquitination and degradation. Furthermore, we firmly validated, using bioinformatics analyses, that overexpression of CypB is associated with poor prognosis in CRC progression and chemoresistance. Hence, we suggest a novel mechanism of chemoresistance caused by overexpressed CypB, which may help to develop new anti-cancer drugs. We also propose that CypB may be utilized as a predictive biomarker in CRC patients. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

The Prognostic 97 Chemoresponse Gene Signature in Ovarian Cancer.

Patient diagnosis and care would be significantly improved by understanding the mechanisms underlying platinum and taxane resistance in ovarian cancer. Here, we aim to establish a gene signature that can identify molecular pathways/transcription factors involved in ovarian cancer progression, poor clinical outcome, and chemotherapy resistance. To validate the robustness of the gene signature, a meta-analysis approach was applied to 1,020 patients from 7 datasets. A 97-gene signature was identified as an independent predictor of patient survival in association with other clinicopathological factors in univariate [hazard ratio (HR): 3.0, 95% Confidence Interval (CI) 1.66-5.44, p = 2.7E-4] and multivariate [HR: 2.88, 95% CI 1.57-5.2, p = 0.001] analyses. Subset analyses demonstrated that the signature could predict patients who would attain complete or partial remission or no-response to first-line chemotherapy. Pathway analyses revealed that the signature was regulated by HIF1α and TP53 and included nine HIF1α-regulated genes, which were highly expressed in non-responders and partial remission patients than in complete remission patients. We present the 97-gene signature as an accurate prognostic predictor of overall survival and chemoresponse. Our signature also provides information on potential candidate target genes for future treatment efforts in ovarian cancer.

Inhibition of Carbonyl Reductase 1 Safely Improves the Efficacy of Doxorubicin in Breast Cancer Treatment.

AIMS: Doxorubicin (DOX) is a chemotherapeutic drug that is used to treat many cancers, but its use is limited by cardiotoxic side effect. Carbonyl reductase 1 (CBR1) is an NADPH-dependent oxidoreductase that reduces DOX to doxorubicinol (DOXOL), a less potent derivative that is responsible for DOX cardiotoxicity. Thus, we aimed to demonstrate that inhibition of CBR1 enhances the chemotherapeutic efficacy of DOX and attenuates cardiotoxicity. RESULTS: Pharmacological or genetic inhibition of CBR1 improved the anticancer effects of DOX in preclinical models of breast cancer. RNA interference or chemical inhibition of CBR1 improved the anticancer effect of DOX in breast cancer. Moreover, CBR1 overexpression enabled breast cancer cells to obtain chemotherapeutic resistance to DOX treatment. Intriguingly, inhibition of CBR1 decreased DOX-induced cardiotoxicity in animal model. Innovation and Conclusions: Inhibition of CBR1 increases chemotherapeutic efficacy of DOX and reduces cardiotoxicity by blocking DOX reduction to DOXOL. Therefore, we offer preclinical proof-of-concept for a combination strategy to safely leverage the efficacy of doxorubicin by blunting its cardiotoxic effects that limit use of this cytotoxic agent used widely in the oncology clinic. Antioxid. Redox Signal. 26, 70-83.

An 8-gene signature for prediction of prognosis and chemoresponse in non-small cell lung cancer.

Identification of a potential gene signature for improved diagnosis in non-small cell lung cancer (NSCLC) patient is necessary. Here, we aim to establish and validate the prognostic efficacy of a gene set that can predict prognosis and benefits of adjuvant chemotherapy (ACT) in NSCLC patients from various ethnicities. An 8-gene signature was calculated from the gene expression of 181 patients using univariate Cox proportional hazard regression analysis. The prognostic value of the signature was robustly validated in 1,477 patients from five microarray independent data sets and one RNA-seq data set. The 8-gene signature was identified as an independent predictor of patient survival in the presence of clinical parameters in univariate and multivariate analyses [hazard ratio (HR): 2.84, 95% confidence interval CI (1.74-4.65), p=3.06e-05, [HR] 2.62, 95% CI (1.51-4.53), p=0.001], respectively. Subset analysis demonstrated that the 8-gene signature could identify high-risk patients in stage II-III with improved survival from ACT [(HR) 1.47, 95% CI (1.01-2.14), p=0.044]. The 8-gene signature also stratified risk groups in EGFR-mutated and wild-type patients. In conclusion, the 8-gene signature is a strong and independent predictor that can significantly stratify patients into low- and high-risk groups. Our gene signature also has the potential to predict patients in stage II-III that are likely to benefit from ACT.

Prognostic value and their clinical implication of 89-gene signature in glioma.

Gliomas are the most common and aggressive primary tumors in adults. The current approaches, such as histological classification and molecular genetics, have limitation in prediction of individual therapeutic outcomes due to heterogeneity within the tumor groups. Recent studies have proposed several gene signatures to predict glioma's prognosis. However, most of the gene expression profiling studies have been performed on relatively small number of patients and combined probes from diverse microarray chips. Here, we identified prognostic 89 common genes from diverse microarray chips. The 89-gene signature classified patients into good and bad prognostic groups which differed in the overall survival significantly, reflecting the biological characteristics and heterogeneity. The robustness and accuracy of the gene signature as an independent prognostic factor was validated in three microarray and one RNA-seq data sets independently. By incorporating into histological classification and molecular marker, the 89-gene signature could further stratify patients with 1p/19q co-deletion and IDH1 mutation. Additionally, subset analyses suggested that the 89-gene signature could predict patients who would benefit from adjuvant chemotherapy. Conclusively, we propose that the 89-gene signature would have an independent and accurate prognostic value for clinical use. This study also offers opportunities for novel targeted treatment of individual patients.

CRC-113 gene expression signature for predicting prognosis in patients with colorectal cancer.

Colorectal cancer (CRC) is the third leading cause of global cancer mortality. Recent studies have proposed several gene signatures to predict CRC prognosis, but none of those have proven reliable for predicting prognosis in clinical practice yet due to poor reproducibility and molecular heterogeneity. Here, we have established a prognostic signature of 113 probe sets (CRC-113) that include potential biomarkers and reflect the biological and clinical characteristics. Robustness and accuracy were significantly validated in external data sets from 19 centers in five countries. In multivariate analysis, CRC-113 gene signature showed a stronger prognostic value for survival and disease recurrence in CRC patients than current clinicopathological risk factors and molecular alterations. We also demonstrated that the CRC-113 gene signature reflected both genetic and epigenetic molecular heterogeneity in CRC patients. Furthermore, incorporation of the CRC-113 gene signature into a clinical context and molecular markers further refined the selection of the CRC patients who might benefit from postoperative chemotherapy. Conclusively, CRC-113 gene signature provides new possibilities for improving prognostic models and personalized therapeutic strategies.

Prognostic value of a 92-probe signature in breast cancer.

Clinical applications of gene expression signatures in breast cancer prognosis still remain limited due to poor predictive strength of single training datasets and appropriate invariable platforms. We proposed a gene expression signature by reducing baseline differences and analyzing common probes among three recent Affymetrix U133 plus 2 microarray data sets. Using a newly developed supervised method, a 92-probe signature found in this study was associated with overall survival. It was robustly validated in four independent data sets and then repeated on three subgroups by incorporating 17 breast cancer microarray datasets. The signature was an independent predictor of patients' survival in univariate analysis [(HR) 1.927, 95% CI (1.237-3.002); p < 0.01] as well as multivariate analysis after adjustment of clinical variables [(HR) 7.125, 95% CI (2.462-20.618); p < 0.001]. Consistent predictive performance was found in different multivariate models in increased patient population (p = 0.002). The survival signature predicted a late metastatic feature through 5-year disease free survival (p = 0.006). We identified subtypes within the lymph node positive (p < 0.001) and ER positive (p = 0.01) patients that best reflected the invasive breast cancer biology. In conclusion using the Common Probe Approach, we present a novel prognostic signature as a predictor in breast cancer late recurrences.