Breast-Specific Epigenetic Regulation of DeltaNp73 and Its Role in DNA-Damage-Response of BRCA1-Mutated Human Mammary Epithelial Cells

Epigenetic oncogenesis, biomarkers and emerging chemotherapeutics for breast cancer

Breast cancer remains one of the leading causes of cancer-related deaths globally and the most prominent among females, yet with limited effective therapeutic options. Most of the current medications are challenged by various factors including low efficacy, incessant resistance, immune evasion and frequent recurrence of the disease. Further understanding of the prognosis and identification of plausible therapeutic channels thus requires multimodal approaches. In this review, epigenetics studies of several pathways to BC oncogenesis via the inducement of oncogenic changes on relevant markers have been overviewed. Similarly, the counter-epigenetic mechanisms to reverse such changes as effective therapeutic strategies were surveyed. The epigenetic oncogenesis occurs through several pathways, notably, DNMT-mediated hypermethylation of DNA, dysregulated expression for ERα, HER2/ERBB and PR, histone modification, overexpression of transcription factors including the CDK9-cyclin T1 complex and suppression of tumour suppressor genes. Scientifically, the regulatory reversal of the mechanisms constitutes effective epigenetic approaches for mitigating BC initiation, progression and metastasis. These were exhibited at various experimental levels by classical chemotherapeutic agents including some repurposable drugs, endocrine inhibitors, monoclonal antibodies and miRNAs, natural products, metal complexes and nanoparticles. Dozens of the potential candidates are currently in clinical trials while others are still at preclinical experimental stages showing promising anti-BC efficacy. The review presents a model for a wider understanding of epigenetic oncogenic pathways to BC and reveals plausible channels for reversing the unpleasant changes through epigenetic modifications. It advances the science of therapeutic designs for ameliorating the global burden of BC upon further translational studies.

The p53 family member p73 in the regulation of cell stress response

During oncogenesis, cells become unrestrictedly proliferative thereby altering the tissue homeostasis and resulting in subsequent hyperplasia. This process is paralleled by resumption of cell cycle, aberrant DNA repair and blunting the apoptotic program in response to DNA damage. In most human cancers these processes are associated with malfunctioning of tumor suppressor p53. Intriguingly, in some cases two other members of the p53 family of proteins, transcription factors p63 and p73, can compensate for loss of p53. Although both p63 and p73 can bind the same DNA sequences as p53 and their transcriptionally active isoforms are able to regulate the expression of p53-dependent genes, the strongest overlap with p53 functions was detected for p73. Surprisingly, unlike p53, the p73 is rarely lost or mutated in cancers. On the contrary, its inactive isoforms are often overexpressed in cancer. In this review, we discuss several lines of evidence that cancer cells develop various mechanisms to repress p73-mediated cell death. Moreover, p73 isoforms may promote cancer growth by enhancing an anti-oxidative response, the Warburg effect and by repressing senescence. Thus, we speculate that the role of p73 in tumorigenesis can be ambivalent and hence, requires new therapeutic strategies that would specifically repress the oncogenic functions of p73, while keeping its tumor suppressive properties intact.

Analyzing cancer gene expression data through the lens of normal tissue-specificity

The genetic alterations that underlie cancer development are highly tissue-specific with the majority of driving alterations occurring in only a few cancer types and with alterations common to multiple cancer types often showing a tissue-specific functional impact. This tissue-specificity means that the biology of normal tissues carries important information regarding the pathophysiology of the associated cancers, information that can be leveraged to improve the power and accuracy of cancer genomic analyses. Research exploring the use of normal tissue data for the analysis of cancer genomics has primarily focused on the paired analysis of tumor and adjacent normal samples. Efforts to leverage the general characteristics of normal tissue for cancer analysis has received less attention with most investigations focusing on understanding the tissue-specific factors that lead to individual genomic alterations or dysregulated pathways within a single cancer type. To address this gap and support scenarios where adjacent normal tissue samples are not available, we explored the genome-wide association between the transcriptomes of 21 solid human cancers and their associated normal tissues as profiled in healthy individuals. While the average gene expression profiles of normal and cancerous tissue may appear distinct, with normal tissues more similar to other normal tissues than to the associated cancer types, when transformed into relative expression values, i.e., the ratio of expression in one tissue or cancer relative to the mean in other tissues or cancers, the close association between gene activity in normal tissues and related cancers is revealed. As we demonstrate through an analysis of tumor data from The Cancer Genome Atlas and normal tissue data from the Human Protein Atlas, this association between tissue-specific and cancer-specific expression values can be leveraged to improve the prognostic modeling of cancer, the comparative analysis of different cancer types, and the analysis of cancer and normal tissue pairs.

The frequency and functional impact of the genetic alterations that drive human cancer are highly tissue-specific. This tissue-specificity implies that important information about cancer biology can be extracted from the features of associated normal tissues. The use of normal tissue genomic data for cancer analysis has primarily focused on paired tumor and adjacent normal samples. Less attention has been paid to pan-cancer approaches that use the general characteristics of normal tissue for cancer genomic analysis. To address this research gap, we explored the genome-wide association between the transcriptomes of 21 solid human cancers and their associated normal tissues as profiled in healthy individuals. We found a strong association between tissue-specific and cancer-specific expression, an association that can be leveraged to improve the prognostic modeling of cancer, the comparative analysis of different cancer types, and the analysis of cancer and normal tissue pairs.