Proteins Found in the Triple-Negative Breast Cancer Secretome and Their Therapeutic Potential

Targeted therapy approaches for epithelial-mesenchymal transition in triple negative breast cancer

Triple-negative breast cancer (TNBC) is distinguished by negative expression of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2), making it an aggressive subtype of breast cancer and contributes to 15-20% of the total incidence. TNBC is a diverse disease with various genetic variations and molecular subtypes. The tumor microenvironment involves multiple cells, including immune cells, fibroblast cells, extracellular matrix (ECM), and blood vessels that constantly interact with tumor cells and influence each other. The ECM undergoes significant structural changes, leading to induced cell proliferation, migration, adhesion, invasion, and epithelial-to-mesenchymal transition (EMT). The involvement of EMT in the occurrence and development of tumors through invasion and metastasis in TNBC has been a matter of concern. Therefore, EMT markers could be prognostic predictors and potential therapeutic targets in TNBC. Chemotherapy has been one of the primary options for treating patients with TNBC, but its efficacy against TNBC is still limited. Targeted therapy is a critical emerging option with enhanced efficacy and less adverse effects on patients. Various targeted therapy approaches have been developed based on the specific molecules and the signaling pathways involved in TNBC. These include inhibitors of signaling pathways such as TGF-β, Wnt/β-catenin, Notch, TNF-α/NF-κB and EGFR, as well as immune checkpoint inhibitors, such as pembrolizumab, 2laparib, and talazoparib have been widely explored. This article reviews recent developments in EMT in TNBC invasion and metastasis and potential targeted therapy strategies.

The treatment landscape of triple-negative breast cancer

Triple-negative breast cancer (TNBC) tumors are biologically aggressive breast cancer. On the molecular level, TNBC is a highly heterogeneous disease; more biotechnologies are gradually being used to advance the understanding of TNBC subtypes and help establish more targeted therapies. Multiple TNBC target-related agents are already approved by the Food and Drug Administration for clinical use, including PI3K/AKT/mTOR inhibitors, PRAP inhibitors, and antibody-drug conjugates. Some innovative approaches, like peptide strategies, also promise to treat TNBC. Currently, the interplay between TNBC tumors and their tumor microenvironment provides a promising prospect for improving the efficacy of immunotherapy. In this review, we summarize the prevalent TNBC subtype methodologies, discuss the evolving therapeutic strategies, and propose new therapeutic possibilities based on existing foundational theories, with the attempt to serve as a reference to further advance tailoring treatment of TNBC.

The intersection of the nervous system and breast cancer

Breast cancer (BC) represents a paradigm of heterogeneity, manifesting as a spectrum of molecular subtypes with divergent clinical trajectories. It is fundamentally characterized by the aberrant proliferation of malignant cells within breast tissue, a process modulated by a myriad of factors that govern its progression. Recent endeavors outline the interplay between BC and the nervous system, illuminate the complex symbiosis between neural structures and neoplastic cells, and elucidate nerve dependence as a cornerstone of BC progression. This includes the neural modulations on immune response, neurovascular formation, and multisystem interactions. Such insights have unveiled the critical impact of neural elements on tumor dynamics and patient prognosis. This revelation beckons a deeper exploration into the neuro-oncological interface, potentially unlocking novel therapeutic vistas. This review endeavors to delineate the intricate mechanisms between the nervous system and BC, aiming to accentuate the implications and therapeutic strategies of this intersection for tumor evolution and the formulation of innovative therapeutic approaches.

Precision unveiled: Synergistic genomic landscapes in breast cancer-Integrating single-cell analysis and decoding drug toxicity for elite prognostication and tailored therapeutics

BACKGROUND

Globally, breast cancer, with diverse subtypes and prognoses, necessitates tailored therapies for enhanced survival rates. A key focus is glutamine metabolism, governed by select genes. This study explored genes associated with T cells and linked them to glutamine metabolism to construct a prognostic staging index for breast cancer patients for more precise medical treatment.

METHODS

Two frameworks, T-cell related genes (TRG) and glutamine metabolism (GM), stratified breast cancer patients. TRG analysis identified key genes via hdWGCNA and machine learning. T-cell communication and spatial transcriptomics emphasized TRG's clinical value. GM was defined using Cox analyses and the Lasso algorithm. Scores categorized patients as TRG_high+GM_high (HH), TRG_high+GM_low (HL), TRG_low+GM_high (LH), or TRG_low+GM_low (LL). Similarities between HL and LH birthed a "Mixed" class and the TRG_GM classifier. This classifier illuminated gene variations, immune profiles, mutations, and drug responses.

RESULTS

Utilizing a composite of two distinct criteria, we devised a typification index termed TRG_GM classifier, which exhibited robust prognostic potential for breast cancer patients. Our analysis elucidated distinct immunological attributes across the classifiers. Moreover, by scrutinizing the genetic variations across groups, we illuminated their unique genetic profiles. Insights into drug sensitivity further underscored avenues for tailored therapeutic interventions.

CONCLUSION

Utilizing TRG and GM, a robust TRG_GM classifier was developed, integrating clinical indicators to create an accurate predictive diagnostic map. Analysis of enrichment disparities, immune responses, and mutation patterns across different subtypes yields crucial subtype-specific characteristics essential for prognostic assessment, clinical decision-making, and personalized therapies. Further exploration is warranted into multiple fusions between metrics to uncover prognostic presentations across various dimensions.

Secretome processing for proteomics: A methods comparison

The cancer cell secretome comprises a treasure-trove for biomarkers since it reflects cross-talk between tumor cells and their surrounding environment with high detectability in biofluids. In this study, we evaluated six secretome sample processing workflows coupled to single-shot mass spectrometry: (1) Protein concentration by ultrafiltration with a molecular weight cut-off (MWCO) filter and sample preparation through in-gel digestion (IGD); (2) Acetone protein precipitation coupled to IGD; (3) MWCO filter-based protein concentration followed by to in-solution digestion (ISD); (4) Acetone protein precipitation coupled to ISD; (5) Direct ISD; (6) Secretome lyophilization and ISD. To this end, we assessed workflow triplicates in terms of total number of protein identifications, unique identifications, reproducibility of protein identification and quantification and detectability of small proteins with important functions in cancer biology such as cytokines, chemokines, and growth factors. Our findings revealed that acetone protein precipitation coupled to ISD outperformed the other methods in terms of the number of identified proteins (2246) and method reproducibility (correlation coefficient between replicates (r = 0.94, CV = 19%). Overall, especially small proteins such as those from the classes mentioned above were better identified using ISD workflows. Concluding, herein we report that secretome protein precipitation coupled to ISD is the method of choice for high-throughput secretome proteomics via single shot nanoLC-MS/MS.

Single-cell RNA sequencing reveals distinct transcriptomic profiles and evolutionary patterns in lung cancer brain metastasis

Background

Lung cancer metastasis to the brain presents significant clinical challenges. Therefore, elucidating its underlying mechanisms and characterizing its transcriptomic landscape is essential for developing therapeutic interventions.

Methods

We analyzed two distinct single-cell RNA sequencing datasets of lung cancer metastasis to analyze the evolutionary trajectory of brain metastatic tumors. In addition, a systematic comparison of cell-cell interaction between tumor cells and lymphocytes was conducted within primary and brain metastatic tumors.

Results

The brain metastatic tumors showed greater transcriptomic changes (reflected by a higher pseudotime) than tumors in the lymph nodes and primary tumors. Furthermore, our investigation has not only revealed specific shared ligand-receptor pairs in both mLN and mBrain, exemplified by the interaction between SPP1 and CD99 in T cells, but has also unveiled a diverse array of ligand-receptor pairs exclusive to the mBrain. Notably, this includes distinctive pairs such as APP and IL1 observed specifically in myeloid cells.

Conclusion

The distinct microenvironment in the brain may influence the observed transcriptomic changes in tumors, emphasizing the significance of the specific environment in determining tumor behavior and therapeutic response.

Omics-Based Investigations of Breast Cancer

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.

Impact of the Cancer Cell Secretome in Driving Breast Cancer Progression

Breast cancer is a complex and heterogeneous disease resulting from the accumulation of genetic and epigenetic alterations in breast epithelial cells. Despite remarkable progress in diagnosis and treatment, breast cancer continues to be the most prevalent cancer affecting women worldwide. Recent research has uncovered a compelling link between breast cancer onset and the extracellular environment enveloping tumor cells. The complex network of proteins secreted by cancer cells and other cellular components within the tumor microenvironment has emerged as a critical player in driving the disease's metastatic properties. Specifically, the proteins released by the tumor cells termed the secretome, can significantly influence the progression and metastasis of breast cancer. The breast cancer cell secretome promotes tumorigenesis through its ability to modulate growth-associated signaling pathways, reshaping the tumor microenvironment, supporting pre-metastatic niche formation, and facilitating immunosurveillance evasion. Additionally, the secretome has been shown to play a crucial role in drug resistance development, making it an attractive target for cancer therapy. Understanding the intricate role of the cancer cell secretome in breast cancer progression will provide new insights into the underlying mechanisms of this disease and aid in the development of more innovative therapeutic interventions. Hence, this review provides a nuanced analysis of the impact of the cancer cell secretome on breast cancer progression, elucidates the complex reciprocal interaction with the components of the tumor microenvironment and highlights emerging therapeutic opportunities for targeting the constituents of the secretome.

The Variety of 3D Breast Cancer Models for the Study of Tumor Physiology and Drug Screening

Breast cancer is the most common cancer in women and responsible for multiple deaths worldwide. 3D cancer models enable a better representation of tumor physiology than the conventional 2D cultures. This review summarizes the important components of physiologically relevant 3D models and describes the spectrum of 3D breast cancer models, e.g., spheroids, organoids, breast cancer on a chip and bioprinted tissues. The generation of spheroids is relatively standardized and easy to perform. Microfluidic systems allow control over the environment and the inclusion of sensors and can be combined with spheroids or bioprinted models. The strength of bioprinting relies on the spatial control of the cells and the modulation of the extracellular matrix. Except for the predominant use of breast cancer cell lines, the models differ in stromal cell composition, matrices and fluid flow. Organoids are most appropriate for personalized treatment, but all technologies can mimic most aspects of breast cancer physiology. Fetal bovine serum as a culture supplement and Matrigel as a scaffold limit the reproducibility and standardization of the listed 3D models. The integration of adipocytes is needed because they possess an important role in breast cancer.

The Potential of PSMA as a Vascular Target in TNBC

Recent studies proving prostate-specific membrane antigen (PSMA) expression on triple-negative breast cancer (TNBC) cells and adjacent endothelial cells suggest PSMA as a promising target for therapy of until now not-targetable cancer entities. In this study, PSMA and its isoform expression were analyzed in different TNBC cells, breast cancer stem cells (BCSCs), and tumor-associated endothelial cells. PSMA expression was detected in 91% of the investigated TNBC cell lines. The PSMA splice isoforms were predominantly found in the BCSCs. Tumor-conditioned media from two TNBC cell lines, BT-20 (high full-length PSMA expression, PSMAΔ18 expression) and Hs578T (low full-length PSMA expression, no isoform expression), showed significant pro-angiogenic effect with induction of tube formation in endothelial cells. All TNBC cell lines induced PSMA expression in human umbilical vein endothelial cells (HUVEC). Significant uptake of radiolabeled ligand [⁶⁸Ga]Ga-PSMA was detected in BCSC1 (4.2%), corresponding to the high PSMA expression. Moreover, hypoxic conditions increased the uptake of radiolabeled ligand [¹⁷⁷Lu]Lu-PSMA in MDA-MB-231 (0.4% vs. 3.4%, under hypoxia and normoxia, respectively) and MCF-10A (0.3% vs. 3.0%, under normoxia and hypoxia, respectively) significantly (p < 0.001). [¹⁷⁷Lu]Lu-PSMA-induced apoptosis rates were highest in BT-20 and MDA-MB-231 associated endothelial cells. Together, these findings demonstrate the potential of PSMA-targeted therapy in TNBC.