ABSTRACT
This article examines the hype generated around the term "stem cell", and the capitalization of the stem cell craze by the cosmetic industry. It started by introducing product lines containing active ingredients derived from plant stem cells. Then, evolved to using own cells for skin regeneration and hair loss treatment, and allogenic cells for the manufacturing of stem cell-derived products. This article also discusses the missing links for safe and reliable stem cell applications in cosmetics, and why local regulatory bodies, members of the industry and consumers must all work together to stop the illegitimate use of the "stem cell" good name in unsafe or fraudulent commercial practices.
ABSTRACT
Application software is utilized to aid in the diagnosis of breast cancer. Yet, recent advances in artificial intelligence (AI) are addressing challenges related to the detection, classification, and monitoring of different types of tumors. AI can apply deep learning algorithms to perform automated analysis on mammographic or histologic examinations. Large volume of data generated by digitalized mammogram or whole-slide images can be interoperated through advanced machine learning. This enables fast evaluation of every tissue patch on an image, resulting in a quicker more sensitivity, and more reproducible diagnoses compared to human performance. On the other hand, cancer cell-exosomes which are extracellular vesicles released by cancer cells into the blood circulation, are being explored as cancer biomarker. Recent studies on cancer-exosome-content revealed that the encapsulated miRNA and other biomolecules are indicative of tumor sub-type, possible metastasis and prognosis. Thus, theoretically, through nanogenomicas, a profile of each breast tumor sub-type, estrogen receptor status, and potential metastasis site can be constructed. Then, a laboratory instrument, fitted with an AI program, can be used to diagnose suspected patients by matching their sera miRNA and biomolecules composition with the available template profiles. In this paper, we discuss the advantages of establishing a nanogenomics-AI-based breast cancer diagnostic approach, compared to the gold standard radiology or histology based approaches that are currently being adapted to AI. Also, we discuss the advantages of building the diagnostic and prognostic biomolecular profiles for breast cancers based on the exosome encapsulated content, rather than the free circulating miRNA and other biomolecules.
ABSTRACT
In an attempt to conceptualize the process of cancer formation, Hanahan and Weinberg [2000] have outlined six universal characteristics of tumorigenesis, and labelled them as the "hallmarks of cancer". These hallmarks include; unlimited proliferation, evading growth suppressors, resisting cell death, replicative immortality, inducing angiogenesis, initiating invasion and metastasis. Cancer cell signalling is crucial for initiating and controlling cellular pathways that are involved in these hallmarks. The intricate network of communication between cancer cells and other cancer or non-cancer cells is still being investigated, and is yet to be fully understood. Initially it was proposed that the main form of communication between cells within the tumour microenvironment are soluble growth factors, and gap junctions. Then, researchers reported another form of cell-to-cell communication, through the release of spherical particles called exosomes. It is believed that these exosomes enable communication through the transfer of active components from the releasing cell, and off-loading it into the recipient cell. As researchers continue to examine the development of the cancer hallmarks and the pathways involved, it became evident that cancer cell-derived exosomes play a major role in almost all of them. This review will examine the role played by cancer cell-derived exosomes in development of cancer.
