Genomic analysis: Toward a new approach in breast cancer management

Progress in triple negative breast carcinoma pathophysiology: Potential therapeutic targets

Triple-negative breast carcinoma (TNBC) is a subtype of breast carcinoma defined by negativity for estrogen receptor (ER) or progesterone receptor (PR) by immunohistochemical analysis and negativity for human epidermal growth factor receptor (Her2) by immunohistochemistry or in situ hybridization. TNBC is clinically marked by its high aggressiveness, particularly poor outcomes including a low survival rate, and the lack of specific and effective treatments. Therefore, new potential targets for the treatment of TNBC must be identified. This review summarizes recent evidence supporting novel targets and possible therapeutic regimens in the treatment of TNBC.

The Promise of Digital Biopsy for the Prediction of Tumor Molecular Features and Clinical Outcomes Associated With Immunotherapy

Immunotherapy by immune checkpoint inhibitors has emerged as an effective treatment for a slight proportion of patients with aggressive tumors. Currently, some molecular determinants, such as the expression of the programmed cell death ligand-1 (PD-L1) or the tumor mutational burden (TMB) have been used in the clinical practice as predictive biomarkers, although they fail in consistency, applicability, or reliability to precisely identify the responding patients mainly because of their spatial intratumoral heterogeneity. Therefore, new biomarkers for early prediction of patient response to immunotherapy, that could integrate several approaches, are eagerly sought. Novel methods of quantitative image analysis (such as radiomics or pathomics) might offer a comprehensive approach providing spatial and temporal information from macroscopic imaging features potentially predictive of underlying molecular drivers, tumor-immune microenvironment, tumor-related prognosis, and clinical outcome (in terms of response or toxicity) following immunotherapy. Preliminary results from radiomics and pathomics analysis have demonstrated their ability to correlate image features with PD-L1 tumor expression, high CD3 cell infiltration or CD8 cell expression, or to produce an image signature concordant with gene expression. Furthermore, the predictive power of radiomics and pathomics can be improved by combining information from other modalities, such as blood values or molecular features, leading to increase the accuracy of these models. Thus, “digital biopsy,” which could be defined by non-invasive and non-consuming digital techniques provided by radiomics and pathomics, may have the potential to allow for personalized approach for cancer patients treated with immunotherapy.

The trophic effect of nerve growth factor in primary cultures of rat hippocampal neurons is associated to an anti-inflammatory and immunosuppressive transcriptional program

Nerve growth factor, the prototype of a family of neurotrophins, elicits differentiation and survival of peripheral and central neuronal cells. Although its neural mechanisms have been studied extensively, relatively little is known about the transcriptional regulation governing its effects. We have previously observed that in primary cultures of rat hippocampal neurons treatment with nerve growth factor for 72 hr increases neurite outgrowth and cell survival. To obtain a comprehensive view of the underlying transcriptional program, we performed whole-genome expression analysis by microarray technology. We identified 541 differentially expressed genes and characterized dysregulated pathways related to innate immunity: the complement system and neuro-inflammatory signaling. The exploitation of such genes and pathways may help interfering with the intracellular mechanisms involved in neuronal survival and guide novel therapeutic strategies for neurodegenerative diseases.

Molecular Classification of Breast Cancer

Breast cancer is a heterogeneous disease, observed traditionally by morphology and protein expression but, more recently with the advent of modern molecular technologies, at the genomic and transcriptomic level. This review describes the association between the different molecular subtypes with the histologic subtypes of breast cancer alongside some of their major genomic characteristics and illustrates how these subtypes may affect the appearance of tumors on imaging studies. The authors aim to show how molecular stratification can be used to augment traditional methods to improve our understanding of breast cancers and their clinical management.

Application of pharmacometrics and quantitative systems pharmacology to cancer therapy: The example of luminal a breast cancer

Breast cancer (BC) is the most common cancer in women, and the second most frequent cause of cancer-related deaths in women worldwide. It is a heterogeneous disease composed of multiple subtypes with distinct morphologies and clinical implications. Quantitative systems pharmacology (QSP) is an emerging discipline bridging systems biology with pharmacokinetics (PK) and pharmacodynamics (PD) leveraging the systematic understanding of drugs' efficacy and toxicity. Despite numerous challenges in applying computational methodologies for QSP and mechanism-based PK/PD models to biological, physiological, and pharmacological data, bridging these disciplines has the potential to enhance our understanding of complex disease systems such as BC. In QSP/PK/PD models, various sources of data are combined including large, multi-scale experimental data such as -omics (i.e. genomics, transcriptomics, proteomics, and metabolomics), biomarkers (circulating and bound), PK, and PD endpoints. This offers a means for a translational application from pre-clinical mathematical models to patients, bridging the bench to bedside paradigm. Not only can these models be applied to inform and advance BC drug development, but they also could aid in optimizing combination therapies and rational dosing regimens for BC patients. Here, we review the current literature pertaining to the application of QSP and pharmacometrics-based pharmacotherapy in BC including bottom-up and top-down modeling approaches. Bottom-up modeling approaches employ mechanistic signal transduction pathways to predict the behavior of a biological system. The ones that are addressed in this review include signal transduction and homeostatic feedback modeling approaches. Alternatively, top-down modeling techniques are bioinformatics reconstruction techniques that infer static connections between molecules that make up a biological network and include (1) Bayesian networks, (2) co-expression networks, and (3) module-based approaches. This review also addresses novel techniques which utilize the principles of systems biology, synthetic lethality and tumor priming, both of which are discussed in relationship to novel drug targets and existing BC therapies. By utilizing QSP approaches, clinicians may develop a platform for improved dose individualization for subpopulation of BC patients, strengthen rationale in treatment designs, and explore mechanism elucidation for improving future treatments in BC medicine.

Selection and Prioritization of Candidate Drug Targets for Amyotrophic Lateral Sclerosis Through a Meta-Analysis Approach

Amyotrophic lateral sclerosis (ALS) is a progressive and incurable neurodegenerative disease. Although several compounds have shown promising results in preclinical studies, their translation into clinical trials has failed. This clinical failure is likely due to the inadequacy of the animal models that do not sufficiently reflect the human disease. Therefore, it is important to optimize drug target selection by identifying those that overlap in human and mouse pathology. We have recently characterized the transcriptional profiles of motor cortex samples from sporadic ALS (SALS) patients and differentiated these into two subgroups based on differentially expressed genes, which encode 70 potential therapeutic targets. To prioritize drug target selection, we investigated their degree of conservation in superoxide dismutase 1 (SOD1) G93A transgenic mice, the most widely used ALS animal model. Interspecies comparison of our human expression data with those of eight different SOD1^G93A datasets present in public repositories revealed the presence of commonly deregulated targets and related biological processes. Moreover, deregulated expression of the majority of our candidate targets occurred at the onset of the disease, offering the possibility to use them for an early and more effective diagnosis and therapy. In addition to highlighting the existence of common key drivers in human and mouse pathology, our study represents the basis for a rational preclinical drug development.

Evaluation of miRNA-binding-site SNPs of MRE11A, NBS1, RAD51 and RAD52 involved in HRR pathway genes and risk of breast cancer in China

MiRNA-binding-site single nucleotide polymorphisms (SNPs) in homologous recombination repair (HRR) pathway genes may change DNA repair capacity and affect susceptibility to cancer though complex gene-gene and gene-reproductive factors interactions. However, these SNPs associated with breast cancer (BC) are still unclear in Chinese women. Therefore, we conducted a case-control study to evaluate the genetic susceptibility of the five miRNA-binding-site SNPs in HRR pathway genes (MRE11A rs2155209, NBS1 rs2735383, RAD51 rs963917 and rs963918 and RAD52 rs7963551) in the development of BC. MRE11A rs2155209 and RAD52 rs7963551 were found to be associated with BC risk (ORadjusted: 1.87; 95 % CI: 1.23-2.86 and ORadjusted: 0.36; 95 % CI: 0.24-0.58). NBS1 rs2735383, RAD51 rs963917 and rs963918 were associated with BC risk after stratification according to reproductive factors. Haplotypes of Crs963917Ars963918 decreased the risk of BC (ORadjusted: 0.53; 95 % CI: 0.4-0.68), while the Trs963917Ars963918 and Trs963917Grs963918 haplotypes could increase the risk of BC (ORadjusted: 1.28; 95 % CI: 1.05-1.57 and ORadjusted: 1.31; 95 % CI: 1.09-1.62). Combined effect of risk alleles showed that the five SNPs were associated with increased BC risk in a dose-dependent manner (P trend = 0.003). The GC genotype of rs2735383, AG + GG genotype of rs963918 and AC + CC genotype of rs7963551 were associated with PR positivity of BC patients. These findings suggest that the miRNA-binding-site SNPs involved in HRR pathway genes may affect susceptibility of BC in Chinese women; moreover, the interactions of gene-gene and gene-reproductive factors play vital roles in the progression of BC. Further functional studies with larger sample are needed to support and validate these findings.

Functional MDM4 rs4245739 genetic variant, alone and in combination with P53 Arg72Pro polymorphism, contributes to breast cancer susceptibility

The oncoprotein MDM4 plays an essential role in P53 tumor suppressor pathway through negative regulation of P53 function. It has been reported that the rs4245739 A > C polymorphism located in the MDM4 3'-untranslated region creates a miR-191 target site and results in decreased MDM4 expression. Therefore, we investigated the association of the MDM4 rs4245739 polymorphism as well as the P53 Arg72Pro genetic variant with the breast cancer risk. Genotypes were determined in two independent case-control sets consisting of 1100 breast cancer cases and 1400 controls from two regions of China. Odds ratios (ORs) and 95 % confidence intervals (CIs) were estimated by logistic regression. Our results demonstrated that the MDM4 rs4245739 AC and CC genotypes were significantly associated with decreased breast cancer risk compared to the AA genotype in both the case-control sets (Jinan set: OR = 0.55, 95 % CI 0.40-0.76, P = 2.3 × 10(-4); Huaian set: OR = 0.41, 95 % CI 0.25-0.67, P = 3.1 × 10(-4)). The P53 Arg/Pro genotype or Pro/Pro genotype was significantly associated with an increased risk of developing breast cancer, compared to the P53 Arg/Arg genotype in both the case-control sets (all P < 0.05). Interestingly, we observed a combinational effect between MDM4 rs4245739 and P53 Arg72Pro variants in attenuating breast cancer risk, highlighting the importance of the P53 tumor suppressor pathway genes during malignant transformation. Our results also support the hypothesis that genetic variants interrupting miRNA-mediated gene regulation might be important genetic modifiers of breast cancer risk.

Genomic approaches in breast cancer research

Microarray technologies provide high-throughput analysis of genes that are differentially expressed in humans and other species, and thereby provide a means to measure how biological systems are altered during development or disease states. Within, we review how high-throughput genomic technologies have increased our understanding about the molecular complexity of breast cancer, identified distinct molecular phenotypes and how they can be used to increase the accuracy of predicted clinical outcome.

P53 mutations in triple negative breast cancer upregulate endosomal recycling of epidermal growth factor receptor (EGFR) increasing its oncogenic potency

There is no available targeted therapy for triple-negative or its more aggressive subtype, basal-like breast cancer. Multiple therapeutic strategies based on translational knowledge have not improved the treatment options for triple negative patients. As understanding of molecular pathways that drive tumor development is rapidly increasing, it is imperative to adapt our treatment strategies to perturbations in molecular pathways driving the malignant process. Basal-like breast cancers over-express EGFR (without mutations or EGFR gene amplifications) and have p53 mutations. While EGFR drives the malignant behavior in triple negative breast cancer (TNBC), anti-EGFR therapies have fallen short of the expected results in clinical trials. Here we bring evidence that the less than optimal results of the anti-EGFR therapies may be explained in part by the increased potency of the EGFR signaling due to increased endosomal recycling. The functional connection between EGFR and endosomal trafficking in TNBC is mutant p53 found in the most aggressive forms of TNBC. Mutant p53 acquires oncogenic functions and binds p63 protein, a member of p53 family with tumor suppressor activities. In the absence of functional p63 there is an upregulation of endosomal recycling EGFR and integrin to the membrane with increased proinvasive abilities of cancer cells. Blocking endosomal trafficking combined with anti-EGFR treatments may result in better clinical outcomes in TNBC.