Breast cancer (BC) is characterized by an extensive genotypic and phenotypic heterogeneity. In-depth investigations into the molecular bases of BC phenotypes, carcinogenesis, progression, and metastasis are necessary for accurate diagnoses, prognoses, and therapy assessments in predictive, precision, and personalized oncology. This review discusses both classic as well as several novel omics fields that are involved or should be used in modern BC investigations, which may be integrated as a holistic term, onco-breastomics. Rapid and recent advances in molecular profiling strategies and analytical techniques based on high-throughput sequencing and mass spectrometry (MS) development have generated large-scale multi-omics datasets, mainly emerging from the three ”big omics”, based on the central dogma of molecular biology: genomics, transcriptomics, and proteomics. Metabolomics-based approaches also reflect the dynamic response of BC cells to genetic modifications. Interactomics promotes a holistic view in BC research by constructing and characterizing protein–protein interaction (PPI) networks that provide a novel hypothesis for the pathophysiological processes involved in BC progression and subtyping. The emergence of new omics- and epiomics-based multidimensional approaches provide opportunities to gain insights into BC heterogeneity and its underlying mechanisms. The three main epiomics fields (epigenomics, epitranscriptomics, and epiproteomics) are focused on the epigenetic DNA changes, RNAs modifications, and posttranslational modifications (PTMs) affecting protein functions for an in-depth understanding of cancer cell proliferation, migration, and invasion. Novel omics fields, such as epichaperomics or epimetabolomics, could investigate the modifications in the interactome induced by stressors and provide PPI changes, as well as in metabolites, as drivers of BC-causing phenotypes. Over the last years, several proteomics-derived omics, such as matrisomics, exosomics, secretomics, kinomics, phosphoproteomics, or immunomics, provided valuable data for a deep understanding of dysregulated pathways in BC cells and their tumor microenvironment (TME) or tumor immune microenvironment (TIMW). Most of these omics datasets are still assessed individually using distinct approches and do not generate the desired and expected global-integrative knowledge with applications in clinical diagnostics. However, several hyphenated omics approaches, such as proteo-genomics, proteo-transcriptomics, and phosphoproteomics-exosomics are useful for the identification of putative BC biomarkers and therapeutic targets. To develop non-invasive diagnostic tests and to discover new biomarkers for BC, classic and novel omics-based strategies allow for significant advances in blood/plasma-based omics. Salivaomics, urinomics, and milkomics appear as integrative omics that may develop a high potential for early and non-invasive diagnoses in BC. Thus, the analysis of the tumor circulome is considered a novel frontier in liquid biopsy. Omics-based investigations have applications in BC modeling, as well as accurate BC classification and subtype characterization. The future in omics-based investigations of BC may be also focused on multi-omics single-cell analyses.

Cancer detection has made significant progress, moving from conventional methods to innovative, non-invasive or minimally invasive approaches aimed at improving early diagnosis, precision, and treatment outcomes. This review examines current and emerging diagnostic technologies, including liquid biopsy (LB), molecular biomarkers, and artificial intelligence (AI). LB analyzes biomarkers in bodily fluids, showing promise in detecting tumors at molecular levels, monitoring cancer progression, and predicting treatment responses. The assignment of specific proteoforms, often linked to tumor subtype, stage, and therapy resistance, adds another layer of diagnostic precision, offering valuable insights for personalized oncology. However, the clinical application of LB faces challenges related to sensitivity, specificity, tumor heterogeneity, and a lack of standardized protocols. Relatively high costs, complex result interpretation, and privacy concerns also hinder its widespread adoption in clinical practice. Despite these challenges, advancements in AI, nanotechnology, and multi-omics strategies offer opportunities to enhance cancer diagnostic accuracy. Future developments, including wearable biosensors and lab-on-a-chip technologies, could lead to personalized, real-time cancer detection with improved patient outcomes, potentially redefining cancer care and fostering a more proactive, patient-centered healthcare approach.

Proteins are the most common types of biomarkers used in breast cancer (BC) theranostics and management. By definition, a biomarker must be a relevant, objective, stable, and quantifiable biomolecule or other parameter, but proteins are known to exhibit the most variate and profound structural and functional variation. Thus, the proteome is highly dynamic and permanently reshaped and readapted, according to changing microenvironments, to maintain the local cell and tissue homeostasis. It is known that protein posttranslational modifications (PTMs) can affect all aspects of protein function. In this review, we focused our analysis on the different types of PTMs of histological biomarkers in BC. Thus, we analyzed the most common PTMs, including phosphorylation, acetylation, methylation, ubiquitination, SUMOylation, neddylation, palmitoylation, myristoylation, and glycosylation/sialylation/fucosylation of transcription factors, proliferation marker Ki-67, plasma membrane proteins, and histone modifications. Most of these PTMs occur in the presence of cellular stress. We emphasized that these PTMs interfere with these biomarkers maintenance, turnover and lifespan, nuclear or subcellular localization, structure and function, stabilization or inactivation, initiation or silencing of genomic and non-genomic pathways, including transcriptional activities or signaling pathways, mitosis, proteostasis, cell–cell and cell–extracellular matrix (ECM) interactions, membrane trafficking, and PPIs. Moreover, PTMs of these biomarkers orchestrate all hallmark pathways that are dysregulated in BC, playing both pro- and/or antitumoral and context-specific roles in DNA damage, repair and genomic stability, inactivation/activation of tumor-suppressor genes and oncogenes, phenotypic plasticity, epigenetic regulation of gene expression and non-mutational reprogramming, proliferative signaling, endocytosis, cell death, dysregulated TME, invasion and metastasis, including epithelial–mesenchymal/mesenchymal–epithelial transition (EMT/MET), and resistance to therapy or reversal of multidrug therapy resistance. PTMs occur in the nucleus but also at the plasma membrane and cytoplasmic level and induce biomarker translocation with opposite effects. Analysis of protein PTMs allows for the discovery and validation of new biomarkers in BC, mainly for early diagnosis, like extracellular vesicle glycosylation, which may be considered as a potential source of circulating cancer biomarkers.

Known as a diverse collection of neoplastic diseases, breast cancer (BC) can be hyperbolically characterized as a dynamic pseudo-organ, a living organism able to build a complex, open, hierarchically organized, self-sustainable, and self-renewable tumor system, a population, a species, a local community, a biocenosis, or an evolving dynamical ecosystem (i.e., immune or metabolic ecosystem) that emphasizes both developmental continuity and spatio-temporal change. Moreover, a cancer cell community, also known as an oncobiota, has been described as non-sexually reproducing species, as well as a migratory or invasive species that expresses intelligent behavior, or an endangered or parasite species that fights to survive, to optimize its features inside the host’s ecosystem, or that is able to exploit or to disrupt its host circadian cycle for improving the own proliferation and spreading. BC tumorigenesis has also been compared with the early embryo and placenta development that may suggest new strategies for research and therapy. Furthermore, BC has also been characterized as an environmental disease or as an ecological disorder. Many mechanisms of cancer progression have been explained by principles of ecology, developmental biology, and evolutionary paradigms. Many authors have discussed ecological, developmental, and evolutionary strategies for more successful anti-cancer therapies, or for understanding the ecological, developmental, and evolutionary bases of BC exploitable vulnerabilities. Herein, we used the integrated framework of three well known ecological theories: the Bronfenbrenner’s theory of human development, the Vannote’s River Continuum Concept (RCC), and the Ecological Evolutionary Developmental Biology (Eco-Evo-Devo) theory, to explain and understand several eco-evo-devo-based principles that govern BC progression. Multi-omics fields, taken together as onco-breastomics, offer better opportunities to integrate, analyze, and interpret large amounts of complex heterogeneous data, such as various and big-omics data obtained by multiple investigative modalities, for understanding the eco-evo-devo-based principles that drive BC progression and treatment. These integrative eco-evo-devo theories can help clinicians better diagnose and treat BC, for example, by using non-invasive biomarkers in liquid-biopsies that have emerged from integrated omics-based data that accurately reflect the biomolecular landscape of the primary tumor in order to avoid mutilating preventive surgery, like bilateral mastectomy. From the perspective of preventive, personalized, and participatory medicine, these hypotheses may help patients to think about this disease as a process governed by natural rules, to understand the possible causes of the disease, and to gain control on their own health.