Motivation for Launching a Cancer Metastasis Inhibition (CMI) Program

Repurposing N-acetylcysteine for management of non-acetaminophen induced acute liver failure: an evidence scan from a global health perspective

Background

The World Health Organization (WHO)'s Essential Medicines List (EML) plays an important role in advocating for access to key treatments for conditions affecting people in all geographic settings. We applied our established drug repurposing methods to one EML agent, N-acetylcysteine (NAC), to identify additional uses of relevance to the global health community beyond its existing EML indication (acetaminophen toxicity).

Methods

We undertook a phenome-wide association study (PheWAS) of a variant in the glutathione synthetase (GSS) gene in approximately 35,000 patients to explore novel indications for use of NAC, which targets glutathione. We then evaluated the evidence regarding biologic plausibility, efficacy, and safety of NAC use in the new phenotype candidates.

Results

PheWAS of GSS variant R418Q revealed increased risk of several phenotypes related to non-acetaminophen induced acute liver failure (ALF), indicating that NAC may represent a therapeutic option for treating this condition. Evidence review identified practice guidelines, systematic reviews, clinical trials, retrospective cohorts and case series, and case reports. This evidence suggesting benefit of NAC use in this subset of ALF patients. The safety profile of NAC in this literature was also concordant with existing evidence on safety of this agent in acetaminophen-induced ALF.

Conclusions

This body of literature indicates efficacy and safety of NAC in non-acetaminophen induced ALF. Given the presence of NAC on the EML, this medication is likely to be available across a range of resource settings; promulgating its use in this novel subset of ALF can provide healthcare professionals and patients with a valuable and safe complement to supportive care for this disease.

Thromboxane biosynthesis in cancer patients and its inhibition by aspirin: a sub-study of the Add-Aspirin trial

BACKGROUND

Pre-clinical models demonstrate that platelet activation is involved in the spread of malignancy. Ongoing clinical trials are assessing whether aspirin, which inhibits platelet activation, can prevent or delay metastases.

METHODS

Urinary 11-dehydro-thromboxane B2 (U-TXM), a biomarker of in vivo platelet activation, was measured after radical cancer therapy and correlated with patient demographics, tumour type, recent treatment, and aspirin use (100 mg, 300 mg or placebo daily) using multivariable linear regression models with log-transformed values.

RESULTS

In total, 716 patients (breast 260, colorectal 192, gastro-oesophageal 53, prostate 211) median age 61 years, 50% male were studied. Baseline median U-TXM were breast 782; colorectal 1060; gastro-oesophageal 1675 and prostate 826 pg/mg creatinine; higher than healthy individuals (~500 pg/mg creatinine). Higher levels were associated with raised body mass index, inflammatory markers, and in the colorectal and gastro-oesophageal participants compared to breast participants (P < 0.001) independent of other baseline characteristics. Aspirin 100 mg daily decreased U-TXM similarly across all tumour types (median reductions: 77-82%). Aspirin 300 mg daily provided no additional suppression of U-TXM compared with 100 mg.

CONCLUSIONS

Persistently increased thromboxane biosynthesis was detected after radical cancer therapy, particularly in colorectal and gastro-oesophageal patients. Thromboxane biosynthesis should be explored further as a biomarker of active malignancy and may identify patients likely to benefit from aspirin.

Inhibition of human oral squamous cell carcinoma proliferation and migration by prodrug-activating suicide gene therapies

Head and neck squamous cell carcinoma (HNSCC), which originates from mucosal epithelium in the oral cavity, pharynx and larynx, is the sixth most common malignancy in the world. The prognosis of HNSCC is not satisfactory due to metastasis, resulting in 5-year survival rates ranging from 65.9 to 67.2%. Previously, we developed a method to evaluate the effect prodrug-activating suicide gene (PA-SG) therapy on the proliferation of HNSCC. The present study investigated PA-SG therapy on metastatic HNSCC by wound-healing assay and our previously established method. HSC-3 cells with stable expression of suicide genes thymidine kinase (TK) or cytosine deaminase (CD) were treated with prodrugs ganciclovir (GCV) or 5-fluorocytosine (5-FC), respectively. Both GCV and 5-FC inhibited HSC-3 proliferation while the bystander effect of CD/5-FC was greater compared with that of TK/GCV. GCV showed a greater anti-migration effect compared with that of 5-FC. To the best of our knowledge, the present study is the first to evaluate the anti-migratory and anti-proliferative effects of PA-SG therapies on metastatic HNSCC. This may also serve as a general method to quantify other types of PA-SC therapy. The present results demonstrated that PA-SG therapy is a promising treatment for anti-metastatic HNSCC therapy development.

A Novel Platelet-Related Gene Signature for Predicting the Prognosis of Triple-Negative Breast Cancer

Regarded as the most invasive subtype, triple-negative breast cancer (TNBC) lacks the expression of estrogen receptors (ERs), progesterone receptors (PRs), and human epidermal growth factor receptor 2 (HER2) proteins. Platelets have recently been shown to be associated with metastasis of malignant tumors. Nevertheless, the status of platelet-related genes in TNBC and their correlation with patient prognosis remain unknown. In this study, the expression and variation levels of platelet-related genes were identified and patients with TNBC were divided into three subtypes. We collected cohorts from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. By applying the least absolute shrinkage and selection operator (LASSO) Cox regression method, we constructed a seven-gene signature which classified the two cohorts of patients with TNBC into low- or high-risk groups. Patients in the high-risk group were more likely to have lower survival rates than those in the low-risk group. The risk score, incorporated with the clinical features, was confirmed as an independent factor for predicting the overall survival (OS) time. Functional enrichment analyses revealed the involvement of a variety of vital biological processes and classical cancer-related pathways that could be important to the ultimate prognosis of TNBC. We then built a nomogram that performed well. Moreover, we tested the model in other cohorts and obtained positive outcomes. In conclusion, platelet-related genes were closely related to TNBC, and this novel signature could serve as a tool for the assessment of clinical prognosis.

Human and Machine Intelligence Together Drive Drug Repurposing in Rare Diseases

Repurposing is an increasingly attractive method within the field of drug development for its efficiency at identifying new therapeutic opportunities among approved drugs at greatly reduced cost and time of more traditional methods. Repurposing has generated significant interest in the realm of rare disease treatment as an innovative strategy for finding ways to manage these complex conditions. The selection of which agents should be tested in which conditions is currently informed by both human and machine discovery, yet the appropriate balance between these approaches, including the role of artificial intelligence (AI), remains a significant topic of discussion in drug discovery for rare diseases and other conditions. Our drug repurposing team at Vanderbilt University Medical Center synergizes machine learning techniques like phenome-wide association study-a powerful regression method for generating hypotheses about new indications for an approved drug-with the knowledge and creativity of scientific, legal, and clinical domain experts. While our computational approaches generate drug repurposing hits with a high probability of success in a clinical trial, human knowledge remains essential for the hypothesis creation, interpretation, "go-no go" decisions with which machines continue to struggle. Here, we reflect on our experience synergizing AI and human knowledge toward realizable patient outcomes, providing case studies from our portfolio that inform how we balance human knowledge and machine intelligence for drug repurposing in rare disease.

Use of signals of positive and negative selection to distinguish cancer genes and passenger genes

A major goal of cancer genomics is to identify all genes that play critical roles in carcinogenesis. Most approaches focused on genes positively selected for mutations that drive carcinogenesis and neglected the role of negative selection. Some studies have actually concluded that negative selection has no role in cancer evolution. We have re-examined the role of negative selection in tumor evolution through the analysis of the patterns of somatic mutations affecting the coding sequences of human genes. Our analyses have confirmed that tumor suppressor genes are positively selected for inactivating mutations, oncogenes, however, were found to display signals of both negative selection for inactivating mutations and positive selection for activating mutations. Significantly, we have identified numerous human genes that show signs of strong negative selection during tumor evolution, suggesting that their functional integrity is essential for the growth and survival of tumor cells.

Repurposing of a Thromboxane Receptor Inhibitor Based on a Novel Role in Metastasis Identified by Phenome-Wide Association Study

Although new drug discoveries are revolutionizing cancer treatments, repurposing existing drugs would accelerate the timeline and lower the cost for bringing treatments to cancer patients. Our goal was to repurpose CPI211, a potent and selective antagonist of the thromboxane A₂-prostanoid receptor (TPr), a G-protein-coupled receptor that regulates coagulation, blood pressure, and cardiovascular homeostasis. To identify potential new clinical indications for CPI211, we performed a phenome-wide association study (PheWAS) of the gene encoding TPr, TBXA2R, using robust deidentified health records and matched genomic data from more than 29,000 patients. Specifically, PheWAS was used to identify clinical manifestations correlating with a TBXA2R single-nucleotide polymorphism (rs200445019), which generates a T399A substitution within TPr that enhances TPr signaling. Previous studies have correlated 200445019 with chronic venous hypertension, which was recapitulated by this PheWAS analysis. Unexpectedly, PheWAS uncovered an rs200445019 correlation with cancer metastasis across several cancer types. When tested in several mouse models of metastasis, TPr inhibition using CPI211 potently blocked spontaneous metastasis from primary tumors, without affecting tumor cell proliferation, motility, or tumor growth. Further, metastasis following intravenous tumor cell delivery was blocked in mice treated with CPI211. Interestingly, TPr signaling in vascular endothelial cells induced VE-cadherin internalization, diminished endothelial barrier function, and enhanced transendothelial migration by tumor cells, phenotypes that were decreased by CPI211. These studies provide evidence that TPr signaling promotes cancer metastasis, supporting the study of TPr inhibitors as antimetastatic agents and highlighting the use of PheWAS as an approach to accelerate drug repurposing.

Anti-Cancer Activities of Diterpenoids Derived from Euphorbia fischeriana Steud

Euphorbia fischeriana Steud is an essential oriental folk medicine used for healing cancer, edema and tuberculosis. Recently, its anticancer activitity has attracted more attention. A volume of research has indicated that diterpenoids are the major anticancer active constituents from this medicinal herb. In this review, we aimed to provide a summary of the promising anticancer diterpenoids from this plant; many diterpenoids mentioned in this article are newly discovered diterpenoids. According to the carbon skeleton and substituents, they can be classified into eight subtypes: ent-abietane, daphnane, tigliane, ingenane, ent-atisane, ent-rosane, ent-kaurane, and lathyrane. Futhermore, their key anticancer mechanisms and protein targets of these compounds will be discussed. These natural diterpenoids could provide a reservoir for drug discovery.