Dynamic genome and transcriptional network-based biomarkers and drugs: precision in breast cancer therapy

Prognostic insights, immune infiltration, and therapeutic response: Cytoplasmic poly(A) tail regulators in hepatocellular carcinoma

The presence of a poly(A) tail is indispensable for the post-transcriptional regulation of gene expression in cancer. This dynamic and modifiable feature of transcripts is under the control of various nuclear and cytoplasmic proteins. This study aimed to develop a novel cytoplasmic poly(A)-related signature for predicting prognosis, clinical attributes, tumor immune microenvironment (TIME), and treatment response in hepatocellular carcinoma (HCC). Utilizing RNA sequencing (RNA-seq) data from The Cancer Genome Atlas (TCGA), non-negative matrix factorization (NMF), and principal-component analysis (PCA) were employed to categorize HCC patients into three clusters, thus demonstrating the pivotal prognostic role of cytoplasmic poly(A) tail regulators. Furthermore, machine learning algorithms such as least absolute shrinkage and selection operator (LASSO), survival analysis, and Cox proportional hazards modeling were able to distinguish distinct cytoplasmic poly(A) subtypes. As a result, a 5-gene signature derived from TCGA was developed and validated using International Cancer Genome Consortium (ICGC) HCC datasets. This novel classification based on cytoplasmic poly(A) regulators has the potential to improve prognostic predictions and provide guidance for chemotherapy, immunotherapy, and transarterial chemoembolization (TACE) in HCC.

Diversity of interpretations of the concept "patient-centered care for breast cancer patients"; a scoping review of current literature

RATIONALE, AIMS AND OBJECTIVES

Patient-centered care is considered a vital component of good quality care for breast cancer patients. Nevertheless, the implementation of this valuable concept in clinical practice appears to be difficult. The goal of this study is to bridge the gap between theoretical elaboration of "patient-centered care" and clinical practice. To that purpose, a scoping analysis was performed of the application of the term "patient-centered care in breast cancer treatment" in present-day literature.

METHOD

For data-extraction, a literature search was performed extracting references that were published in 2018 and included the terms "patient-centered care" and "breast cancer". The articles were systematically traced for answers to the following three questions: "What is patient-centered care?", "Why perform patient-centered care?", and "How to realize patient-centered care?". For the content analysis, these answers were coded and assembled into meaningful clusters until separate themes arose which concur with various interpretations of the term "patient-centered care".

RESULTS

A total of 60 publications were retained for analysis. Traced answers to the three questions "what", "why", and "how" varied considerably in recent literature concerning breast cancer treatment. Despite the inconsistent use of the term "patient-centered care," we did not find any critical consideration about the nature of the concept, regardless of the applied interpretation. Interventions that are supposed to contribute to the heterogeneous concept of patient-centered care as such, seem to be judged desirable, virtually without empirical justification.

CONCLUSIONS

We propose, contrary to previous efforts to define "patient-centered care" more accurately, to embrace the heterogeneity of the concept and apply "patient-centered care" as an umbrella-term for all healthcare that intends to contribute to the acknowledgement of the person in the patient. For the justification of measures to realize patient-centered care for breast cancer patients, instead of a mere contribution to the abstract concept, we insist on the demonstration of desirable real-world effects.

Tin-loaded mesoporous silica nanoparticles: Antineoplastic properties and genotoxicity assessment

Nanotechnology has immensely advanced the field of cancer diagnostics and treatment by introducing potential delivery vehicles as carriers for drugs or therapeutic agents. In due course, mesoporous silica nanoparticles (MSNs) have emerged as excellent vehicles for delivering drugs, biomolecules, and biomaterials, attributed to their solid framework and porosity providing a higher surface area for decorating with various functional ligands. Recently, the metal tin (Sn) has gained huge importance in cancer research owing to its excellent cytotoxicity and ability to kill cancer cells. In the present work, we synthesized MSNs, conjugated them with organotin compounds, and characterized them using various physicochemical techniques. Subsequently, the biological evaluation of MSN (S1), MSN-MP (S2) and tin-conjugated MSNs (S3: MSN-MP-SnPh3) (MP = 3-mercaptopropyltriethoxysilane) revealed that these nanoconjugates induced cytotoxicity, necrosis, and apoptosis in MCF-7 cells. Moreover, these nanoconjugates exhibited anti-angiogenic properties as demonstrated in the chick embryo model. The increase of reactive oxygen species (ROS) was found as a one of the plausible mechanisms underlying cancer cell cytotoxicity induced by these nanoconjugates, encouraging their application for the treatment of cancer. The tin-conjugated MSNs demonstrated less toxicity to normal cells compared to cancer cells. Furthermore, the genotoxicity studies revealed the clastogenic and aneugenic effects of these nanoconjugates in CHO cells mostly at high concentrations. These interesting observations are behind the idea of developing tin-conjugated MSNs as prospective candidates for anticancer therapy.

A Novel Signature Integrated of Immunoglobulin, Glycosylation and Anti-Viral Genes to Predict Prognosis for Breast Cancer

Background: Aberrant glycosylation is significantly related to the occurrence, progression, metastasis, and drug resistance of tumors. It is essential to identify glycosylation and related genes with prognostic value for breast cancer.

Objective: We aimed to construct and validate a prognostic model based on glycosylation and related genes, and further investigate its prognosis values in validation set and external independent cohorts.

Materials and Methods: The transcriptome and clinical data of breast cancer patients were downloaded from The Cancer Genome Atlas (TCGA, n = 1072), Molecular Taxonomy of Breast Cancer International Consortium (METABRIC, n = 1451), and GSE2741 (n = 120). Glycosylation-related genes were downloaded from the Genecards website. Differentially expressed glycosylation-related geneswere identified by comparing the tumor tissues with the adjacent tissues. The TCGA data were randomly divided into training set and validation set in a 1:1 ratio for further analysis. The glycosylation risk-scoring prognosis model was constructed by univariate and multivariate Cox regression analysis, followed by confirmation in TCGA validation, METABRIC, and GEO datasets. Gene set enrichment analysis (GSEA) and Gene ontology analysis for identifying the affected pathways in the high- and low-risk groups were performed.

Results: We attained 1072 breast cancer samples from the TCGA database and 786 glycosylation genes from the Genecards website. A signature contains immunoglobulin, glycosylation and anti-viral related genes was constructed to separate BRCA patients into two risk groups. Low-risk patients had better overall survival than high-risk patients (p < 0.001). A nomogram was constructed with risk scores and clinical characteristics. The area under time-dependent ROC curve reached 0.764 at 1 year, 0.744 at 3 years, and 0.765 at 5 years in the training set. Subgroup analysis showed differences in OS between the high- and low-risk patients in different subgroups. Moreover, the risk score was confirmed as an independent prognostic indicator of BRCA patients and was potentially correlated with immunotherapy response and drug sensitivity.

Conclusion: We identified a novel signature integrated of immunoglobulin (IGHA2), glycosylation-related (SLC35A2) and anti-viral gene (BST2) that was an independent prognostic indicator for BRCA patients. The risk-scoring model could be used for predicting prognosis and immunotherapy in BRCA, thus providing a powerful instrument for combating BRCA.

Prediction of Hepatocellular Carcinoma Prognosis and Immune Cell Infiltration Using Gene Signature Associated with Inflammatory Response

It has been demonstrated that the inflammatory response influences cancer development and can be used as a prognostic biomarker in various tumors. However, the relevance of genes associated with inflammatory responses in hepatocellular carcinoma (HCC) remains unknown. The Cancer Genome Atlas (TCGA) database was analyzed using weighted gene coexpression network analysis (WGCNA) and differential analysis to discover essential inflammatory response-related genes (IFRGs). Cox regression studies, both univariate and multivariate, were employed to develop a prognostic IFRGs signature. Additionally, Gene Set Enrichment Analysis (GSEA) was used to deduce the biological function of the IFRGs signature. Finally, we estimated immune cell infiltration using a single sample GSEA (ssGSEA) and x-cell. Our results revealed that, among the major HCC IFRGs, two (DNASE1L3 and KLKB1) were employed to create a predictive IFRG signature. The IFRG signature could correctly predict overall survival (O.S) as per Kaplan-Meier time-dependent roc curves analysis. It was also linked to pathological tumor stage and T stage and might be used as a prognostic predictor in HCC. GSEA analysis concluded that the IFRG signature might influence the immune response in HCC. Immunological cell infiltration and immune checkpoint molecule expression differed in the high-risk and low-risk groups. As a result of our findings, DNASILE may play a role in the tumor microenvironment. However, more research is necessary to confirm the role of DNASE1L3 and KLKB1.

Analysis of dynamic molecular networks: the progression from colorectal adenoma to cancer

BACKGROUND

Colorectal cancer (CRC) is one of the deadliest cancers worldwide. It is the fourth most deadly cancer in the world with nearly 900,000 people die every year, the progression of polyps into cancer as one of its most common developmental pathways.

METHODS

This study obtained gene chip data collections from the Gene Expression Omnibus for colorectal adenoma (GSE8671) and colorectal cancer (GSE32323). Differentially expressed genes (DEGs) in normal tissue and different stages of CRC were analyzed for clustering, comparison, and visualization using R software. The Cytoscape plugin DyNetViewer was used to construct a dynamic protein-protein interaction network. Subsequently, through the Database for Annotation, Visualization and Integrated Discovery, the DEGs were functionally annotated and path enriched.

RESULTS

Our study found that the matrix metalloprotein family and chemokines were the key regulatory genes that drove CRC progression. The Wnt signaling pathway, chemokine signaling pathway, and CRC pathway were the pathological pathways for CRC. Maintenance played an important role in this process. In addition, the related nodes and pathways at various stages may be potential mechanisms for promoting dynamic CRC progression.

CONCLUSIONS

Our study provides a better understanding of the dynamic pattern of molecular interaction networks during CRC progression and provides relevant markers for more accurate screening of cancer in polyps.

Molecular pathogenesis of breast cancer: impact of miR-99a-5p and miR-99a-3p regulation on oncogenic genes

Our recent research has revealed that passenger strands of certain microRNAs (miRNAs) function as tumor-suppressive miRNAs in cancer cells, e.g., miR-101-5p, miR-143-5p, miR-144-5p, miR-145-3p, and miR-150-3p. Thus, they are important in cancer pathogenesis. Analysis of the miRNA expression signature of breast cancer (BrCa) showed that the expression levels of two miRNAs derived from pre-miR-99a (miR-99a-5p and miR-99a-3p) were suppressed in cancerous tissues. The aim of this study was to identify oncogenic genes controlled by pre-miR-99a that are closely involved in the molecular pathogenesis of BrCa. A total of 113 genes were identified as targets of pre-miR-99a regulation (19 genes modulated by miR-99a-5p, and 95 genes regulated by miR-99a-3p) in BrCa cells. Notably, FAM64A was targeted by both of the miRNAs. Among these targets, high expression of 16 genes (C5orf22, YOD1, SLBP, F11R, C12orf49, SRPK1, ZNF250, ZNF695, CDK1, DNMT3B, TRIM25, MCM4, CDKN3, PRPS, FAM64A, and DESI2) significantly predicted reduced survival of BrCa patients based upon The Cancer Genome Atlas (TCGA) database. In this study, we focused on FAM64A and investigated the relationship between FAM64A expression and molecular pathogenesis of BrCa subtypes. The upregulation of FAM64A was confirmed in BrCa clinical specimens. Importantly, the expression of FAM64A significantly differed between patients with Luminal-A and Luminal-B subtypes. Our data strongly suggest that the aberrant expression of FAM64A is involved in the malignant transformation of BrCa. Our miRNA-based approaches (identification of tumor-suppressive miRNAs and their controlled targets) will provide novel information regarding the molecular pathogenesis of BrCa.

PI3K/AKT pathway as a key link modulates the multidrug resistance of cancers

Multidrug resistance (MDR) is the dominant challenge in the failure of chemotherapy in cancers. Phosphatidylinositol 3-kinase (PI3K) is a lipid kinase that spreads intracellular signal cascades and regulates a variety of cellular processes. PI3Ks are considered significant causes of chemoresistance in cancer therapy. Protein kinase B (AKT) is also a significant downstream effecter of PI3K signaling, and it modulates several pathways, including inhibition of apoptosis, stimulation of cell growth, and modulation of cellular metabolism. This review highlights the aberrant activation of PI3K/AKT as a key link that modulates MDR. We summarize the regulation of numerous major targets correlated with the PI3K/AKT pathway, which is further related to MDR, including the expression of apoptosis-related protein, ABC transport and glycogen synthase kinase-3 beta (GSK-3β), synergism with nuclear factor kappa beta (NF-κB) and mammalian target of rapamycin (mTOR), and the regulation of glycolysis.

Connecting the Missing Dots: ncRNAs as Critical Regulators of Therapeutic Susceptibility in Breast Cancer

Whether acquired or de novo, drug resistance remains a significant hurdle in achieving therapeutic success in breast cancer (BC). Thus, there is an urge to find reliable biomarkers that will help in predicting the therapeutic response. Stable and easily accessible molecules such as microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) are regarded as valuable prognostic biomarkers and therapeutic targets since they act as crucial regulators of the various mechanisms involved in BC drug resistance. Here, we reviewed the current literature on ncRNAs as mediators of resistance to systemic therapies in BC. Interestingly, upon integrating data results from individual studies, we concluded that miR-221, miR-222, miR-451, Urothelial Carcinoma Associated 1 (UCA1), and Growth arrest-specific 5 (GAS5) are strong candidates as prognostic biomarkers and therapeutic targets since they are regulating multiple drug resistance phenotypes in BC. However, further research around their clinical implications is needed to validate and integrate them into therapeutic applications. Therefore, we believe that our review may provide relevant evidence for the selection of novel therapeutic targets and prognostic biomarkers for BC and will serve as a foundation for future translational research in the field.

A hypoxia-related signature for clinically predicting diagnosis, prognosis and immune microenvironment of hepatocellular carcinoma patients

BACKGROUND

Hypoxia plays an indispensable role in the development of hepatocellular carcinoma (HCC). However, there are few studies on the application of hypoxia molecules in the prognosis predicting of HCC. We aim to identify the hypoxia-related genes in HCC and construct reliable models for diagnosis, prognosis and recurrence of HCC patients as well as exploring the potential mechanism.

METHODS

Differentially expressed genes (DEGs) analysis was performed using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database and four clusters were determined by a consistent clustering analysis. Three DEGs closely related to overall survival (OS) were identified using Cox regression and LASSO analysis. Then the hypoxia-related signature was developed and validated in TCGA and International Cancer Genome Consortium (ICGC) database. The Gene Set Enrichment Analysis (GSEA) was performed to explore signaling pathways regulated by the signature. CIBERSORT was used for estimating the fractions of immune cell types.

RESULTS

A total of 397 hypoxia-related DEGs in HCC were detected and three genes (PDSS1, CDCA8 and SLC7A11) among them were selected to construct a prognosis, recurrence and diagnosis model. Then patients were divided into high- and low-risk groups. Our hypoxia-related signature was significantly associated with worse prognosis and higher recurrence rate. The diagnostic model also accurately distinguished HCC from normal samples and nodules. Furthermore, the hypoxia-related signature could positively regulate immune response. Meanwhile, the high-risk group had higher fractions of macrophages, B memory cells and follicle-helper T cells, and exhibited higher expression of immunocheckpoints such as PD1and PDL1.

CONCLUSIONS

Altogether, our study showed that hypoxia-related signature is a potential biomarker for diagnosis, prognosis and recurrence of HCC, and it provided an immunological perspective for developing personalized therapies.

Aconitine induces cardiomyocyte damage by mitigating BNIP3-dependent mitophagy and the TNFα-NLRP3 signalling axis

Objectives

Aconitine, the natural product extracted from Aconitum species, is widely used for the treatment of various diseases, including rheumatism, arthritis, bruises, fractures and pains. However, many studies have reported cardiotoxicity and neurotoxicity caused by aconitine, but the detailed mechanism underlying aconitine's effect on these processes remains unclear.

Materials and methods

The effects of aconitine on the inflammation, apoptosis and viability of H9c2 rat cardiomyocytes were evaluated by flow cytometry, Western blot, RNA sequencing and bioinformatics analysis.

Results

Aconitine suppressed cardiomyocyte proliferation and induced inflammation and apoptosis in a dose‐ and time‐dependent manner. These inflammatory damages could be reversed by a TNFα inhibitor and BNIP3‐mediated mitophagy. Consistent with the in vitro results, overexpression of BNIP3 in heart tissue partially suppressed the cardiotoxicity of aconitine by inhibiting apoptosis and the NLRP3 inflammasome.

Conclusions

Our findings lay a foundation for the application of a TNFα inhibitor and BNIP3 to aconitine‐induced cardiac toxicity prevention and therapy, thereby demonstrating potential for further investigation.

Specific glioblastoma multiforme prognostic-subtype distinctions based on DNA methylation patterns

DNA methylation is an important regulator of gene expression, and plays a significant role in carcinogenesis in the brain. Here, we explored specific prognosis-subtypes based on DNA methylation status using 138 Glioblastoma Multiforme (GBM) samples from The Cancer Genome Atlas (TCGA) database. The methylation profiles of 11,637 CpG sites that significantly correlated with survival in the training set were employed for consensus clustering. We identified three GBM molecular subtypes, and their survival curves were distinct from each other. Furthermore, ten feature CpG sites were obtained on conducting a weighted gene co-expression network analysis (WGCNA) of the CpG sites. We were able to classify the samples into high- and low-methylation groups, and classified the prognosis information of the samples after cluster analysis of the training set samples using the hierarchical clustering algorithm. Similar results were obtained in the test set and clinical GBM specimens. Finally, we found that a positive relationship existed between methylation level and sensitivity to temozolomide (or radiotherapy) or anti-migration ability of GBM cells. Taken together, these results suggest that the model constructed in this study could help explain the heterogeneity of previous molecular subgroups in GBM and can provide guidance to clinicians regarding the prognosis of GBM.

Drug resistance: origins, evolution and characterization of genomic clones and the tumor ecosystem to optimize precise individualized therapy

Progress in understanding and overcoming fatal intrinsic and acquired resistance is slow, with only a few exceptions. Despite advances in modern genome and transcriptome analysis, the controversy of the three different theories on drug resistance and tumor progression, namely dynamic intratumor heterogeneity, pre-existing minor genomic clones and tumor ecosystem, is unresolved. Moreover, evidence on transcriptional heterogeneity suggests the necessity of a drug bank for individualized, precise drug-sensitivity prediction. We propose a cancer type- and stage-specific clinicogenomic and tumor ecosystemic concept toward cancer precision medicine, focusing on early therapeutic resistance and relapse.