Nanogenomics and Artificial Intelligence: A Dynamic Duo for the Fight Against Breast Cancer

Decoding the secrets of small extracellular vesicle communications: exploring the inhibition of vesicle-associated pathways and interception strategies for cancer treatment

Cancer disease is the second leading cause of death worldwide. In 2023, about 2 million new cancer cases and 609,820 cancer deaths are projected to occur in the United States. The driving forces of cancer progression and metastasis are widely varied and comprise multifactorial events. Although there is significant success in treating cancer, patients still present with tumors at advanced stages. Therefore, the discovery of novel oncologic pathways has been widely developed. Tumor cells communicate with each other through small extracellular vesicles (sEVs), which contribute to tumor-stromal interaction and promote tumor growth and metastasis. sEV-specific inhibitors are being investigated as a next-generation cancer therapy. A literature search was conducted to discuss different options for targeting sEV pathways in cancer cells. However, there are some challenges that need to be addressed in targeting sEVs: i) specificity and toxicity of sEV inhibitor, ii) targeted delivery of sEV inhibitors, iii) combination of sEV inhibitors with current standard chemotherapy to improve patients' clinical outcomes, and iv) data reproducibility and applicability at distinct levels of the disease. Despite these challenges, sEV inhibitors have immense potential for effectively treating cancer patients.

Machine Learning-Assisted FTIR Analysis of Circulating Extracellular Vesicles for Cancer Liquid Biopsy

Extracellular vesicles (EVs) are abundantly released into the systemic circulation, where they show remarkable stability and harbor molecular constituents that provide biochemical information about their cells of origin. Due to this characteristic, EVs are attracting increasing attention as a source of circulating biomarkers for cancer liquid biopsy and personalized medicine. Despite this potential, none of the discovered biomarkers has entered the clinical practice so far, and novel approaches for the label-free characterization of EVs are highly demanded. In this regard, Fourier Transform Infrared Spectroscopy (FTIR) has great potential as it provides a quick, reproducible, and informative biomolecular fingerprint of EVs. In this pilot study, we investigated, for the first time in the literature, the capability of FTIR spectroscopy to distinguish between EVs extracted from sera of cancer patients and controls based on their mid-IR spectral response. For this purpose, EV-enriched suspensions were obtained from the serum of patients diagnosed with Hepatocellular Carcinoma (HCC) of nonviral origin and noncancer subjects. Our data point out the presence of statistically significant differences in the integrated intensities of major mid-IR absorption bands, including the carbohydrate and nucleic acids band, the protein amide I and II bands, and the lipid CH stretching band. Additionally, we used Principal Component Analysis combined with Linear Discriminant Analysis (PCA-LDA) for the automated classification of spectral data according to the shape of specific mid-IR spectral signatures. The diagnostic performances of the proposed spectral biomarkers, alone and combined, were evaluated using multivariate logistic regression followed by a Receiving Operator Curve analysis, obtaining large Areas Under the Curve (AUC = 0.91, 95% CI 0.81–1.0). Very interestingly, our analyses suggest that the discussed spectral biomarkers can outperform the classification ability of two widely used circulating HCC markers measured on the same groups of subjects, namely alpha-fetoprotein (AFP), and protein induced by the absence of vitamin K or antagonist-II (PIVKA-II).

Advances of Exosomal miRNAs in Breast Cancer Progression and Diagnosis

Breast cancer is one of the most commonly diagnosed malignancies and the leading cause of cancer death in women worldwide. Although many factors associated with breast cancer have been identified, the definite etiology of breast cancer is still unclear. In addition, early diagnosis of breast cancer remains challenging. Exosomes are membrane-bound nanovesicles secreted by most types of cells and contain a series of biologically important molecules, such as lipids, proteins, and miRNAs, etc. Emerging evidence shows that exosomes can affect the status of cells by transmitting substances and messages among cells and are involved in various physiological and pathological processes. In breast cancer, exosomes play a significant role in breast tumorigenesis and progression through transfer miRNAs which can be potential biomarkers for early diagnosis of breast cancer. This review discusses the potential utility of exosomal miRNAs in breast cancer progression such as tumorigenesis, metastasis, immune regulation and drug resistance, and further in breast cancer diagnosis.

The Roles of Exosomes as Future Therapeutic Agents and Diagnostic Tools for Glioma

Glioma is a common type of tumor originating in the brain. Glioma develops in the gluey supporting cells (glial cells) that surround and support nerve cells. Exosomes are extracellular vesicles that contain microRNAs, messenger RNA, and proteins. Exosomes are the most prominent mediators of intercellular communication, regulating, instructing, and re-educating their surrounding milieu targeting different organs. As exosomes' diameter is in the nano range, the ability to cross the blood-brain barrier, a crucial obstacle in developing therapeutics against brain diseases, including glioma, makes the exosomes a potential candidate for delivering therapeutic agents for targeting malignant glioma. This review communicates the current knowledge of exosomes' significant roles that make them crucial future therapeutic agents and diagnostic tools for glioma.