Multi-omics data integration reveals correlated regulatory features of triple negative breast cancer

Multi-omic analysis of dysregulated pathways in triple negative breast cancer

The aggressive characteristics of triple-negative breast cancer (TNBC) and the absence of targeted medicines make TNBC a challenging clinical case. The molecular landscape of TNBC has been well-understood thanks to recent developments in multi-omic analysis, which have also revealed dysregulated pathways and possible treatment targets. This review summarizes the utilization of multi-omic approaches in elucidating TNBC's complex biology and therapeutic avenues. Dysregulated pathways including cell cycle progression, immunological modulation, and DNA damage response have been uncovered in TNBC by multi-omic investigations that integrate genomes, transcriptomics, proteomics, and metabolomics data. Methods like this pave the door for the discovery of new therapeutic targets, such as the EGFR, PARP, and mTOR pathways, which in turn direct the creation of more precise treatments. Recent developments in TNBC treatment strategies, including immunotherapy, PARP inhibitors, and antibody-drug conjugates, show promise in clinical trials. Emerging biomarkers like MUC1, YB-1, and immune-related markers offer insights into personalized treatment approaches and prognosis prediction. Despite the strengths of multi-omic analysis in offering a more comprehensive view and personalized treatment strategies, challenges exist. Large sample sizes and ensuring high-quality data remain crucial for reliable findings. Multi-omic analysis has revolutionized TNBC research, shedding light on dysregulated pathways, potential targets, and emerging biomarkers. Continued research efforts are imperative to translate these insights into improved outcomes for TNBC patients.

One-pot method for preparing DNA, RNA, and protein for multiomics analysis

Typical multiomics studies employ separate methods for DNA, RNA, and protein sample preparation, which is labor intensive, costly, and prone to sampling bias. We describe a method for preparing high-quality, sequencing-ready DNA and RNA, and either intact proteins or mass-spectrometry-ready peptides for whole proteome analysis from a single sample. This method utilizes a reversible protein tagging scheme to covalently link all proteins in a lysate to a bead-based matrix and nucleic acid precipitation and selective solubilization to yield separate pools of protein and nucleic acids. We demonstrate the utility of this method to compare the genomes, transcriptomes, and proteomes of four triple-negative breast cancer cell lines with different degrees of malignancy. These data show the involvement of both RNA and associated proteins, and protein-only dependent pathways that distinguish these cell lines. We also demonstrate the utility of this multiomics workflow for tissue analysis using mouse brain, liver, and lung tissue.

Quercetin@Gd3+ doped Prussian blue nanocubes induce the pyroptotic death of MDA-MB-231 cells: combinational targeted multimodal therapy, dual modal MRI, intuitive modelling of r1-r2 relaxivities

Quercetin (Qu), a potential bioflavonoid has gained considerable interest as a promising chemotherapeutic drug which can inhibit the proliferation of triple-negative breast cancer (TNBC) cells due to its regulation of the expression of tumor-suppressor gene metastasis and antioxidant property. Notably, Qu exhibits a very negligible cytotoxic effect on normal cells, even with high-dose treatment, while it is shows high affinity to TNBC. However, the efficiency of Qu is limited clinically due to its poor bioavailability, caused by its low aqueous solubility (2.15 μg mL^-1 at 25 °C), rapid gastrointestinal digestion and chemical instability in alkaline and neutral media. Herein, polydopamine (PDA)-coated, NH₂-PEG-NH₂ and hyaluronic acid (HA)-functionalized Gd³⁺-doped Prussian blue nanocubes (GPBNC) are reported as a multifunctional platform for the codelivery of Qu as a chemotherapeutic agent and GPBNC as a photodynamic (PDT) and photothermal (PTT) agent with improved therapeutic efficiency to overcome theses barriers. PDA, NH₂-PEG-NH₂ and HA stabilize GPBNC@Qu and facilitate bioavailability and active-targeting, while absorption of near infrared (NIR) (808 nm; 1 W cm^-2) induces PDT and PTT activities and dual T₁-T₂-weighted magnetic resonance imaging (MRI) with high relaxometric parameters (r₁ 10.06 mM^-1 s^-1 and r₂ 24.96 mM^-1 s^-1 at a magnetic field of 3 T). The designed platform shows a pH-responsive Qu release profile and NIR-induced therapeutic efficiency of ∼79% in 20 minutes of irradiation, wherein N-terminal gardermin D (N-GSDMD) and a P2X7-receptor-mediated pyroptosis pathway induces cell death, corroborating the up-regulation of NLRP3, caspase-1, caspase-5, N-GSDMD, IL-1β, cleaved Pannexin-1 and P2X7 proteins. More interestingly, the increasing relaxivity values of Prussian blue nanocubes with Gd³⁺ doping have been explained on the basis of Solomon-Bloembergen-Morgan theory, considering inner- and outer-sphere relaxivity, wherein crystal defects, coordinated water molecules, tumbling rate, metal to water proton distance, correlation time, magnetisation value etc. play a significant role. In summary, our study suggests that GPBNC could be a beneficial nanocarrier for theranostic purposes against TNBC, while our conceptual study clearly demonstrates the role of various factors in increasing relaxometric parameters.

Comprehensive proteome, phosphoproteome and kinome characterization of luminal A breast cancer

Background

Breast cancer is one of the most frequently occurring malignant cancers worldwide. Invasive ductal carcinoma (IDC) and invasive lobular carcinoma (ILC) are the two most common histological subtypes of breast cancer. In this study, we aimed to deeply explore molecular characteristics and the relationship between IDC and ILC subtypes in luminal A subgroup of breast cancer using comprehensive proteomics and phosphoproteomics analysis.

Methods

Cancer tissues and noncancerous adjacent tissues (NATs) with the luminal A subtype (ER- and PR-positive, HER2-negative) were obtained from paired IDC and ILC patients respectively. Label-free quantitative proteomics and phosphoproteomics methods were used to detect differential proteins and the phosphorylation status between 10 paired breast cancer and NATs. Then, the difference in protein expression and its phosphorylation between IDC and ILC subtypes were explored. Meanwhile, the activation of kinases and their substrates was also revealed by Kinase-Substrate Enrichment Analysis (KSEA).

Results

In the luminal A breast cancer, a total of 5,044 high-confidence proteins and 3,808 phosphoproteins were identified from 10 paired tissues. The protein phosphorylation level in ILC tissues was higher than that in IDC tissues. Histone H1.10 was significantly increased in IDC but decreased in ILC, Conversely, complement C4-B and Crk-like protein were significantly decreased in IDC but increased in ILC. Moreover, the increased protein expression of Septin-2, Septin-9, Heterogeneous nuclear ribonucleoprotein A1 and Kinectin but reduce of their phosphorylation could clearly distinguish IDC from ILC. In addition, IDC was primarily related to energy metabolism and MAPK pathway, while ILC was more closely involved in the AMPK and p53/p21 pathways. Furthermore, the kinomes in IDC were primarily significantly activated in the CMGC groups.

Conclusions

Our research provides insights into the molecular characterization of IDC and ILC and contributes to discovering novel targets for further drug development and targeted treatment.

Functional impact of multi-omic interactions in breast cancer subtypes

Multi-omic approaches are expected to deliver a broader molecular view of cancer. However, the promised mechanistic explanations have not quite settled yet. Here, we propose a theoretical and computational analysis framework to semi-automatically produce network models of the regulatory constraints influencing a biological function. This way, we identified functions significantly enriched on the analyzed omics and described associated features, for each of the four breast cancer molecular subtypes. For instance, we identified functions sustaining over-representation of invasion-related processes in the basal subtype and DNA modification processes in the normal tissue. We found limited overlap on the omics-associated functions between subtypes; however, a startling feature intersection within subtype functions also emerged. The examples presented highlight new, potentially regulatory features, with sound biological reasons to expect a connection with the functions. Multi-omic regulatory networks thus constitute reliable models of the way omics are connected, demonstrating a capability for systematic generation of mechanistic hypothesis.

Multifocal organoids reveal clonal associations between synchronous intestinal tumors with pervasive heterogeneous drug responses

Multifocal colorectal cancer (CRC) comprises both clonally independent primary tumors caused by inherited predisposition and clonally related tumors mainly due to intraluminal spreading along an intact basement membrane. The distinction between these multifocal CRCs is essential because therapeutic strategies vary according to the clonal association of multiple tumor masses. Here, we report one unique case of synchronous intestinal cancer (SIC) with tumors occurring along the entire bowel tract, including the small intestine. We established six patient-derived organoids (PDOs), and patient-derived cell lines (PDCs) from each site of the SIC, which were subjected to extensive genomic, transcriptomic, and epigenomic sequencing. We also estimated the drug responses of each multifocal SIC to 25 clinically relevant therapeutic compounds to validate how the clinically actionable alternations between SICs were associated with drug sensitivity. Our data demonstrated distinct clonal associations across different organs, which were consistently supported by multi-omics analysis, as well as the accordant responses to various therapeutic compounds. Our results indicated the imminent drawback of a single tumor-based diagnosis of multifocal CRC and suggested the necessity of an in-depth molecular analysis of all tumor regions to avoid unexpected resistance to the currently available targeted therapies.

XIST loss impairs mammary stem cell differentiation and increases tumorigenicity through Mediator hyperactivation

X inactivation (XCI) is triggered by upregulation of XIST, which coats the chromosome in cis, promoting formation of a heterochromatic domain (Xi). XIST role beyond initiation of XCI is only beginning to be elucidated. Here, we demonstrate that XIST loss impairs differentiation of human mammary stem cells (MaSCs) and promotes emergence of highly tumorigenic and metastatic carcinomas. On the Xi, XIST deficiency triggers epigenetic changes and reactivation of genes overlapping Polycomb domains, including Mediator subunit MED14. MED14 overdosage results in increased Mediator levels and hyperactivation of the MaSC enhancer landscape and transcriptional program, making differentiation less favorable. We further demonstrate that loss of XIST and Xi transcriptional instability is common among human breast tumors of poor prognosis. We conclude that XIST is a gatekeeper of human mammary epithelium homeostasis, thus unveiling a paradigm in the control of somatic cell identity with potential consequences for our understanding of gender-specific malignancies.

Screening and Identification of Human Endogenous Retrovirus-K mRNAs for Breast Cancer Through Integrative Analysis of Multiple Datasets

Objective

Human endogenous retroviruses (HERVs) make up 8% of the human genome. HERVs are biologically active elements related to multiple diseases. HERV-K, a subfamily of HERVs, has been associated with certain types of cancer and suggested as an immunologic target in some tumors. The expression levels of HERV-K in breast cancer (BCa) have been studied as biomarkers and immunologic therapeutic targets. However, HERV-K has multiple copies in the human genome, and few studies determined the transcriptional profile of HERV-K copies across the human genome for BCa.

Methods

Ninety-one HERV-K indexes with entire proviral sequences were used as the reference database. Nine raw sequencing datasets with 243 BCa and 137 control samples were mapped to this database by Salmon software. The differential proviral expression across several groups was analyzed by DESeq2 software.

Results

First, the clustering of each dataset demonstrated that these 91 HERV-K proviruses could well cluster the BCa and control samples when the normal controls were normal cells or healthy donor tissues. Second, several common HERV-K proviruses that are closely related with BCa risk were significantly differentially expressed (p_adj < 0.05 and absolute log2FC > 1.5) in the tissues and cell lines. Additionally, almost all the HERV-K proviruses had higher expression in BCa tissue than in healthy donor tissue. Notably, we first found the expression of 17p13.1 provirus that located with TP53 should regulate TP53 expression in ER+ and HER2+ BCa.

Conclusion

The expression profiling of these 91 HERV-K proviruses can be used as biomarkers to distinguish individuals with BCa and healthy controls. Some proviruses, especially 17p13.1, were strongly associated with BCa risk. The results suggest that HERV-K expression profiles may be appropriate biomarkers and targets for BCa.