Identification of Five Cytotoxicity-Related Genes Involved in the Progression of Triple-Negative Breast Cancer

MammOnc-DB, an integrative breast cancer data analysis platform for target discovery

Breast cancer (BCa), a leading malignancy among women, is characterized by morphological and molecular heterogeneity. While early-stage, hormone receptor, and HER2-positive BCa are treatable, triple-negative BCa and metastatic BCa remains largely untreatable. Advances in sequencing and proteomic technologies have improved our understanding of the molecular alterations that occur during BCa initiation and progression and enabled identification of subclass-specific biomarkers and therapeutic targets. Despite the availability of abundant omics data in public repositories, user-friendly tools for multi-omics data analysis and integration are scarce. To address this, we developed a comprehensive BCa data analysis platform called MammOnc-DB ( http://resource.path.uab.edu/MammOnc-Home.html ), comprising data from more than 20,000 BCa samples. MammOnc-DB facilitates hypothesis generation and testing, biomarker discovery, and therapeutic targets identification. The platform also includes pre- and post-treatment data, which can help users identify treatment resistance markers and support combination therapy strategies, offering researchers and clinicians a comprehensive tool for BCa data analysis and visualization.

MammOnc-DB, an integrative breast cancer data analysis platform for target discovery

Breast cancer (BCa) is one of the most common malignancies among women worldwide. It is a complex disease that is characterized by morphological and molecular heterogeneity. In the early stages of the disease, most BCa cases are treatable, particularly hormone receptor-positive and HER2-positive tumors. Unfortunately, triple-negative BCa and metastases to distant organs are largely untreatable with current medical interventions. Recent advances in sequencing and proteomic technologies have improved our understanding of the molecular changes that occur during breast cancer initiation and progression. In this era of precision medicine, researchers and clinicians aim to identify subclass-specific BCa biomarkers and develop new targets and drugs to guide treatment. Although vast amounts of omics data including single cell sequencing data, can be accessed through public repositories, there is a lack of user-friendly platforms that integrate information from multiple studies. Thus, to meet the need for a simple yet effective and integrative BCa tool for multi-omics data analysis and visualization, we developed a comprehensive BCa data analysis platform called MammOnc-DB (http://resource.path.uab.edu/MammOnc-Home.html), comprising data from more than 20,000 BCa samples. MammOnc-DB was developed to provide a unique resource for hypothesis generation and testing, as well as for the discovery of biomarkers and therapeutic targets. The platform also provides pre- and post-treatment data, which can help users identify treatment resistance markers and patient groups that may benefit from combination therapy.

MLIP and Its Potential Influence on Key Oncogenic Pathways

Muscle-enriched A-type lamin-interacting protein (MLIP) is an emerging protein involved in cellular homeostasis and stress adaptation. Eukaryotic cells regulate various cellular processes, including metabolism, DNA repair, and cell cycle progression, to maintain cellular homeostasis. Disruptions in this homeostasis can lead to diseases such as cancer, characterized by uncontrolled cell growth and division. This review aims to explore for the first time the unique role MLIP may play in cancer development and progression, given its interactions with the PI3K/Akt/mTOR pathway, p53, MAPK9, and FOXO transcription factors, all critical regulators of cellular homeostasis and tumor suppression. We discuss the current understanding of MLIP's involvement in pro-survival pathways and its potential implications in cancer cells' metabolic remodeling and dysregulated homeostasis. Additionally, we examine the potential of MLIP as a novel therapeutic target for cancer treatment. This review aims to shed light on MLIP's potential impact on cancer biology and contribute to developing innovative therapeutic strategies.

Globally invariant behavior of oncogenes and random genes at population but not at single cell level

Cancer is widely considered a genetic disease. Notably, recent works have highlighted that every human gene may possibly be associated with cancer. Thus, the distinction between genes that drive oncogenesis and those that are associated to the disease, but do not play a role, requires attention. Here we investigated single cells and bulk (cell-population) datasets of several cancer transcriptomes and proteomes in relation to their healthy counterparts. When analyzed by machine learning and statistical approaches in bulk datasets, both general and cancer-specific oncogenes, as defined by the Cancer Genes Census, show invariant behavior to randomly selected gene sets of the same size for all cancers. However, when protein-protein interaction analyses were performed, the oncogenes-derived networks show higher connectivity than those relative to random genes. Moreover, at single-cell scale, we observe variant behavior in a subset of oncogenes for each considered cancer type. Moving forward, we concur that the role of oncogenes needs to be further scrutinized by adopting protein causality and higher-resolution single-cell analyses.

Identification of a NACC1-Regulated Gene Signature Implicated in the Features of Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC), characterized by a deficiency in estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor2 (HER2), is among the most lethal subtypes of breast cancer (BC). Nevertheless, the molecular determinants that contribute to its malignant phenotypes such as tumor heterogeneity and therapy resistance, remain elusive. In this study, we sought to identify the stemness-associated genes involved in TNBC progression. Using bioinformatics approaches, we found 55 up- and 9 downregulated genes in TNBC. Out of the 55 upregulated genes, a 5 gene-signature (CDK1, EZH2, CCNB1, CCNA2, and AURKA) involved in cell regeneration was positively correlated with the status of tumor hypoxia and clustered with stemness-associated genes, as recognized by Parametric Gene Set Enrichment Analysis (PGSEA). Enhanced infiltration of immunosuppressive cells was also positively correlated with the expression of these five genes. Moreover, our experiments showed that depletion of the transcriptional co-factor nucleus accumbens-associated protein 1 (NAC1), which is highly expressed in TNBC, reduced the expression of these genes. Thus, the five genes signature identified by this study warrants further exploration as a potential new biomarker of TNBC heterogeneity/stemness characterized by high hypoxia, stemness enrichment, and immune-suppressive tumor microenvironment.

Antioxidant Capacity, Antitumor Activity and Metabolomic Profile of a Beetroot Peel Flour

In this study, a beetroot peel flour was made, and its in vitro antioxidant activity was determined in aqueous (BPFw) and ethanolic (BPFe) extracts. The influence of BPFw on breast cancer cell viability was also determined. A targeted betalain profile was obtained using high-resolution Q-Extractive Plus Orbitrap mass spectrometry (Obrtitrap-HRMS) alongside untargeted chemical profiling of BPFw using Ultra-High-Performance Liquid Chromatography with High-Resolution Mass Spectrometry (UHPLC-HRMS). BPFw and BPFe presented satisfactory antioxidant activities, with emphasis on the total phenolic compounds and ORAC results for BPFw (301.64 ± 0.20 mg GAE/100 g and 3032.78 ± 55.00 µmol T/100 g, respectively). The MCF-7 and MDA-MB-231 breast cancer cells presented reductions in viability when treated with BPFw, showing dose-dependent behavior, with MDA-MB-231 also showing time-dependent behavior. The chemical profiling of BPFw led to the identification of 9 betalains and 59 other compounds distributed amongst 28 chemical classes, with flavonoids and their derivates and coumarins being the most abundant. Three forms of betalain generated via thermal degradation were identified. However, regardless of thermal processing, the BPF still presented satisfactory antioxidant and anticancer activities, possibly due to synergism with other identified molecules with reported anticancer activities via different metabolic pathways.