Cancer stem cells (CSCs) are tumor cells with initiating ability, self‐renewal potential, and intrinsic resistance to conventional therapeutics. Efficient isolation and characterization of CSCs pave the way for more comprehensive knowledge about tumorigenesis, heterogeneity, and chemoresistance. Also a better understanding of CSCs will lead to novel era of both basic and clinical cancer research, reclassification of human tumors, and development of innovative therapeutic strategies. Finding novel diagnostic and effective therapeutic strategies also enhance the success of treatment in cancer patients. There are various methods based on the characteristics of the CSCs to detect and isolate these cells, some of which have recently developed. This review summarized current techniques for effective isolation and characterization of CSCs with a focus on advantages and limitations of each method with clinical applications.

Hypoxia has an important role in tumor progression via the up-regulation of growth factors and cellular adaptation genes. These changes promote cell survival, proliferation, invasion, metastasis, angiogenesis, and energy metabolism in favor of cancer development. Hypoxia also plays a central role in determining the resistance of tumors to chemotherapy. Hypoxia of the tumor microenvironment provides an opportunity to develop new therapeutic strategies that may selectively induce apoptosis of the hypoxic cancer cells. Melatonin is well known for its role in the regulation of circadian rhythms and seasonal reproduction. Numerous studies have also documented the anti-cancer properties of melatonin, including anti-proliferation, anti-angiogenesis, and apoptosis promotion. In this paper, we hypothesized that melatonin exerts anti-cancer effects by inhibiting hypoxia-induced pathways. Considering this action, co-administration of melatonin in combination with other therapeutic medications might increase the effectiveness of anti-cancer drugs. In this review, we discussed the possible signaling pathways by which melatonin inhibits hypoxia-induced cancer cell survival, invasion, migration, and metabolism, as well as tumor angiogenesis.

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Objectives: In this study, we aimed to identify putative biomarkers for identification and characterization of these cells in liver cancer. Methods: We employed a supervised machine learning method, XGBoost, to data from 13 GEO data series to classify samples using gene expression data. Results.  Across the 376 samples (129 CSCs and 247 non-CSCs cases), XGBoost displayed high performance in the classification of data. XGBoost feature importance scores and SHAP (Shapley Additive explanation) values were used for the interpretation of results and analysis of individual gene importance. We confirmed that expression levels of a 10-gene set (PTGER3, AURKB, C15orf40, IDI2, OR8D1, NACA2, SERPINB6, L1CAM, SMC1A, and RASGRF1) were predictive. The results showed that these 10 genes can detect CSCs robustly with accuracy, sensitivity, and specificity of 97 %, 100 %, and 95 %, respectively. Conclusions. We suggest that the ten-gene set may be used as a biomarker set for detecting and characterizing CSCs using gene expression data.