PLUS: Predicting cancer metastasis potential based on positive and unlabeled learning

Beta-blocker adjunct therapy as a prospective anti-metastatic with cardio-oncologic regulation

The prevailing treatment stratagem in cancer therapy still challenges the dilemma of a probable metastatic spread following an initial diagnosis. Including an anti-metastatic agent demands a significant focus to overrule the incidence of treatment failures. Adrenergic stimulation underlying the metastatic spread paved the way for beta blockers as a breakthrough in repurposing as an anti-metastatic agent. However, the current treatment approach fails to fully harness the versatile potential of the drug in inhibiting probable metastasis. The beta blockers were seen to show a myriad of grip over the pro-metastatic and prognostic parameters of the patient. Novel interventions in immune therapy, onco-hypertension, surgery-induced stress, induction of apoptosis and angiogenesis inhibition have been used as evidence to interpret our objective of discussing the potential adjuvant role of the drug in the existing anti-cancer regimens. Adding weight to the relative incidence of onco-hypertension as an unavoidable side effect from chemotherapy, the slot for an anti-hypertensive agent is necessitated, and we try to suggest beta-blockers to fill this position. However, pointing out the paucity in the clinical study, we aim to review the current status of beta blockers under this interest to state how the drug should be included as a drug of choice in every patient undergoing cancer treatment.

Harnessing immunotherapy to enhance the systemic anti-tumor effects of thermosensitive liposomes

Chemotherapy plays an important role in debulking tumors in advance of surgery and/or radiotherapy, tackling residual disease, and treating metastatic disease. In recent years many promising advanced drug delivery strategies have emerged that offer more targeted delivery approaches to chemotherapy treatment. For example, thermosensitive liposome-mediated drug delivery in combination with localized mild hyperthermia can increase local drug concentrations resulting in a reduction in systemic toxicity and an improvement in local disease control. However, the majority of solid tumor-associated deaths are due to metastatic spread. A therapeutic approach focused on a localized target area harbors the risk of overlooking and undertreating potential metastatic spread. Previous studies reported systemic, albeit limited, anti-tumor effects following treatment with thermosensitive liposomal chemotherapy and localized mild hyperthermia. This work explores the systemic treatment capabilities of a thermosensitive liposome formulation of the vinca alkaloid vinorelbine in combination with mild hyperthermia in an immunocompetent murine model of rhabdomyosarcoma. This treatment approach was found to be highly effective at heated, primary tumor sites. However, it demonstrated limited anti-tumor effects in secondary, distant tumors. As a result, the addition of immune checkpoint inhibition therapy was pursued to further enhance the systemic anti-tumor effect of this treatment approach. Once combined with immune checkpoint inhibition therapy, a significant improvement in systemic treatment capability was achieved. We believe this is one of the first studies to demonstrate that a triple combination of thermosensitive liposomes, localized mild hyperthermia, and immune checkpoint inhibition therapy can enhance the systemic treatment capabilities of thermosensitive liposomes.

Finding miRNA-RNA Network Biomarkers for Predicting Metastasis and Prognosis in Cancer

Despite remarkable progress in cancer research and treatment over the past decades, cancer ranks as a leading cause of death worldwide. In particular, metastasis is the major cause of cancer deaths. After an extensive analysis of miRNAs and RNAs in tumor tissue samples, we derived miRNA-RNA pairs with substantially different correlations from those in normal tissue samples. Using the differential miRNA-RNA correlations, we constructed models for predicting metastasis. A comparison of our model to other models with the same data sets of solid cancer showed that our model is much better than the others in both lymph node metastasis and distant metastasis. The miRNA-RNA correlations were also used in finding prognostic network biomarkers in cancer patients. The results of our study showed that miRNA-RNA correlations and networks consisting of miRNA-RNA pairs were more powerful in predicting prognosis as well as metastasis. Our method and the biomarkers obtained using the method will be useful for predicting metastasis and prognosis, which in turn will help select treatment options for cancer patients and targets of anti-cancer drug discovery.