Cyclin D type does not influence cell cycle response to DNA damage caused by ionizing radiation in multiple myeloma tumours

Glaucocalyxin A suppresses multiple myeloma progression in vitro and in vivo through inhibiting the activation of STAT3 signaling pathway

Background

Multiple myeloma (MM) is the most common malignant hematological disease in the people worldwide. Glaucocalyxin A (GLA) is a bioactive ent-kauranoid diterpenoid, that is derived from Rabdosia japonica var. GLA has been demonstrated that it had various pharmacological activities, such as anti-coagulation, anti-bacterial, anti-tumor, anti-inflammation, antioxidant activities. Although GLA has effective anti-tumor properties, its effects on multiple myeloma remain unclear. The aim of this study was to examine the possible anti-cancer effects of GLA and their molecular mechanisms on MM cells in vitro and in vivo.

Methods

To evaluate the role of GLA on the proliferation of MM cells in vitro and in vivo, we used MTT method to detect the role of GLA on the proliferation of MM cells. Cell apoptosis and cell cycle assay were evaluated by flow cytometry. Protein expressions in GLA-treated and untreated MM cells were evaluated by western blot analyses. MM xenograft nude mice model was used to investigate the role of GLA on the proliferation of MM cells in vivo. IHC assay was used to examine the role of GLA on the MM xenograft model in vivo.

Results

In the present study, we firstly reported the potent anti-myeloma activity of GLA on MM cells. We found that GLA could induce apoptosis in vitro and in vivo. GLA could inhibit the phosphorylation of the signal transducer and activator of transcription 3 (STAT3) and downregulate interleukin IL-6 induced STAT3 phosphorylation in MM. Overexpression of STAT3 could significantly prevent apoptosis induced by GLA; while knockdown of STAT3 enhanced it. Moreover, GLA could inhibit cell proliferation by inducing the cell cycle arrest. GLA reduced the expression of cell cycle-related proteins CCNB1, CCND1, CCND2, and CCND3 and increased the expression of p21 in MM cell lines. In addition, in the MM xenograft nude mice model, GLA exhibited very good anti-myeloma activity. Administration of GLA almost completely inhibited tumor growth within 19 days without physical toxicity. And the IHC results showed GLA significantly inhibited cell proliferation and interfered STAT3 pathway on MM xenograft model tumor tissues.

Conclusions

Taken together, our present research indicated that GLA inhibits the MM cell proliferation, induces MM cell apoptosis and cell cycle arrest through blocking the activation of STAT3 pathway. Thus, GLA may be a potential therapeutic candidate for MM patients in the future.

Mining Natural Products with Anticancer Biological Activity through a Systems Biology Approach

Natural products, like turmeric, are considered powerful antioxidants which exhibit tumor-inhibiting activity and chemoradioprotective properties. Nowadays, there is a great demand for developing novel, affordable, efficacious, and effective anticancer drugs from natural resources. In the present study, we have employed a stringent in silico methodology to mine and finally propose a number of natural products, retrieved from the biomedical literature. Our main target was the systematic search of anticancer products as anticancer agents compatible to the human organism for future use. In this case and due to the great plethora of such products, we have followed stringent bioinformatics methodologies. Our results taken together suggest that natural products of a great diverse may exert cytotoxic effects in a maximum of the studied cancer cell lines. These natural compounds and active ingredients could possibly be combined to exert potential chemopreventive effects. Furthermore, in order to substantiate our findings and their application potency at a systems biology level, we have developed a representative, user-friendly, publicly accessible biodatabase, NaturaProDB, containing the retrieved natural resources, their active ingredients/fractional mixtures, the types of cancers that they affect, and the corresponding experimentally verified target genes.

Investigating Molecular Determinants of Cancer Cell Resistance to Ionizing Radiation Through an Integrative Bioinformatics Approach

Eradication of cancer cells through exposure to high doses of ionizing radiation (IR) is a widely used therapeutic strategy in the clinical setting. However, in many cases, cancer cells can develop remarkable resistance to radiation. Radioresistance represents a prominent obstacle in the effective treatment of cancer. Therefore, elucidation of the molecular mechanisms and pathways related to radioresistance in cancer cells is of paramount importance. In the present study, an integrative bioinformatics approach was applied to three publicly available RNA sequencing and microarray transcriptome datasets of human cancer cells of different tissue origins treated with ionizing radiation. These data were investigated in order to identify genes with a significantly altered expression between radioresistant and corresponding radiosensitive cancer cells. Through rigorous statistical and biological analyses, 36 genes were identified as potential biomarkers of radioresistance. These genes, which are primarily implicated in DNA damage repair, oxidative stress, cell pro-survival, and apoptotic pathways, could serve as potential diagnostic/prognostic markers cancer cell resistance to radiation treatment, as well as for therapy outcome and cancer patient survival. In addition, our findings could be potentially utilized in the laboratory and clinical setting for enhancing cancer cell susceptibility to radiation therapy protocols.

Mouse serum protects against total body irradiation-induced hematopoietic system injury by improving the systemic environment after radiation

Reactive oxygen species (ROS) play a critical role in total body irradiation (TBI)-induced hematopoietic system injury. However, the mechanisms involved in ROS production in hematopoietic stem cells (HSCs) post TBI need to be further explored. In this study, we demonstrated that hematopoietic system injury in mice radiated with TBI was effectively alleviated when the blood circulation environment was changed via the injection of serum from non-radiated mice. Serum injection increased the survival of radiated mice and ameliorated TBI-induced hematopoietic system injury through attenuating myeloid skew, increasing HSC frequency, and promoting the reconstitution of radiated HSCs. Serum injection also decreased ROS levels in HSCs and regulated oxidative stress-related proteins. A serum proteome sequence array showed that proteins related to tissue injury and oxidative stress were regulated, and a serum-derived exosome microRNA sequence assay showed that the PI3K-Akt and Hippo signaling pathways were affected in radiated mice injected with serum from non-radiated mice. Furthermore, a significant increase in cell viability and a decrease in ROS were observed in radiated lineage^-c-kit⁺ cells treated with serum-derived exosomes. Similarly, an improvement in the impaired differentiation of HSCs was observed in radiated mice injected with serum-derived exosomes. Taken together, our observations suggest that serum from non-radiated mice alleviates HSC injury in radiated mice by improving the systemic environment after radiation, and exosomes contribute to this radioprotective effect as important serum active component.

Potential prognostic long non-coding RNA identification and their validation in predicting survival of patients with multiple myeloma

Multiple myeloma, a typical hematological malignancy, is characterized by malignant proliferation of plasma cells. This study was to identify differently expressed long non-coding RNAs to predict the survival of patients with multiple myeloma efficiently. Gene expressing profiles of diagnosed patients with multiple myeloma, GSE24080 (559 samples) and GSE57317 (55 samples), were downloaded from Gene Expression Omnibus database. After processing, survival-related long non-coding RNAs were identified by Cox regression analysis. The prognosis of multiple myeloma patients with differently expressed long non-coding RNAs was predicted by Kaplan–Meier analysis. Meanwhile, stratified analysis was performed based on the concentrations of serum beta 2-microglobulin (S-beta 2m), albumin, and lactate dehydrogenase of multiple myeloma patients. Gene set enrichment analysis was performed to further explore the functions of identified long non-coding RNAs. A total of 176 long non-coding RNAs significantly related to the survival of multiple myeloma patients (p < 0.05) were identified. In dataset GSE24080 and GSE57317, there were 558 and 55 patients being clustered into two groups with significant differences, respectively. Stratified analysis indicated that prediction of the prognoses with these long non-coding RNAs was independent from other clinical phenotype of multiple myeloma. Gene set enrichment analysis–identified pathways of cell cycle, focal adhesion, and G2-M checkpoint were associated with these long non-coding RNAs. A total of 176 long non-coding RNAs, especially RP1-286D6.1, AC008875.2, MTMR9L, AC069360.2, and AL512791.1, were potential biomarkers to evaluate the prognosis of multiple myeloma patients. These long non-coding RNAs participated indispensably in many pathways associated to the development of multiple myeloma; however, the molecular mechanisms need to be further studied.