ALS Drug Discovery via High-Throughput Phenotypic Screening Using iPSC-Derived Human Motor Neurons

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease primarily affecting motor neurons. Unfortunately, there are only two drugs approved to treat the condition, neither of which increases patient survival by more than a few months. This sobering reality highlights the urgent need for new ALS therapeutic development, which has been plagued by the high failure rate of drug candidates during clinical trials. This high failure rate suggests that preclinical screening strategies need to be re-evaluated.
One of the markers of disease in ALS patients is the aberrantly low expression of neurofilament light chain (NFL) in motor neurons. Further, the recovery of the NFL to normal levels prevents hallmark phenotypic changes in ALS neurons.
Therefore, we wanted to establish a clinically relevant screening platform to identify compounds that return the expression of NFL to normal levels in ALS patient-derived motor neurons. At BrainXell, we established new technologies to rapidly differentiate ALS patient induced pluripotent stem cells (iPSCs) into large quantities of neurons. We then used genome editing techniques to endogenously fuse NFL with a nanoluciferase (NLuc) reporter, thus enabling a high-throughput screening (HTS) system that monitors the expression levels of NFL after 72 h exposure to each compound. The assay was adapted to meet HTS requirements, including large batch sizes, 1536-well format, and minimal well-to-well variation, short-term culture, plating by an automated dispenser, and low reagent volumes.
Applying a quantitative HTS approach, we screened the LOPAC, NPC, and MIPE libraries (>6,000 compounds) in a dose-dependent manner. Compounds that increase NFL expression by >30% (to approximately normal levels) were considered hits. From these screens, we identified 80 hit compounds that are currently going through secondary validation. Preliminary data look promising. For example, two of these hits restore normal expression of NFL with no observed toxicity.

Using a common anticonvulsant to counteract inflammation:

Serious conditions, including sepsis, stem from inflammation in the body, and there is a lack of effective medication for sepsis. A chromosomal protein called high-mobility group box 1 (HMGB1), secreted by immune and dying cells, binds to a specific cellular receptor—named receptor for advanced glycation end-products (RAGE)—and triggers the process of inflammation in the body. Through a computer software-based docking study with a structural similarity-based strategy, scientists from Japan, led by senior researcher Prof Sei-ichi Tanuma from Tokyo University of Science (TUS), discovered that the popular anticonvulsant drug papaverine blocks the binding of HMGB1 to this receptor.

This kind of “drug repositioning” can be used to find other merits for existing drugs whose safety profiles are known. This novel approach used for the first time here is unique to Prof Tanuma states, “Our research group has been trying to identify compounds, preferably based on existing drugs, that block the binding of irritants to cellular receptors. We want to find novel drugs to treat inflammation-based conditions.”

Mechanism-Based Target Identification and Drug Discovery in Cancer Research
The promise of new molecularly based medicines founded on a genetic understanding of cancer is in the process of being realized, and the clinical results will point to new research directions. Some of the most exciting results are obtained with agents directed against tyrosine kinases, either as therapeutic antibodies or as small-molecule kinase inhibitors. However, the problem of tumor instability that might lead to resistance is a looming issue, and it still remains to be seen whether these new drugs will offer lasting survival advantages to the patients.

It is also apparent that not all of the approaches are performing as well as anticipated. There is clearly a learning curve with respect to the best ways to use these new agents, just as has been the case in the development of traditional cytotoxic drugs. For example, many of the new agents are being tested in combination with therapies currently used to treat specific cancers.

A number of toxicities are also encountered, some of which are mechanism-based (EGF receptor inhibitors, FTIs, MMPIs) and some of which are caused by the chemical structure of drug unrelated to its mechanism of action (phosphorothioate antisense oligonucleotides). Nevertheless, these newer agents are affording novel ways to mechanistically attack cancer, even if one cannot realize efficacy without toxicity. Increased use of tumor genotyping to guide the choice of cancer therapy can also be anticipated, as is already being done in breast cancer to determine estrogen receptor and HER-2 status. The ultimate goal is still to obtain the best agents that will achieve complete and durable responses.

Targeting the most appropriate patients may be a way of using newer medicines in the most effective manner and achieve a therapeutic index (a ratio between the dose that achieves an antitumor effect versus the dose that gives toxicity) that is greater than currently obtainable in the clinic with cytotoxic agents.

This promise is being realized in current clinical trials with the Bcr-abl protein kinase inhibitor. One can also envision highly safe drugs that can prevent cancer, as is being anticipated with newer SERMs for breast cancer, 5a-reductase inhibitors for prostate cancer, and inhibitors of cyclo-oxygenase 2 for colon polyps and potentially colon cancer. Each step in this slow and sometimes stochastic process, however, should benefit from rigorous target validation and novel mechanistic approaches to enhance the cancer drug development process.

Cancer Target Identification and Pharmaceutical Tractability

Nothing provides more compelling validation for a target than knowledge of the human genetics of a specific disease. In cancer research, the choice of target is often highlighted by the mutated gene underlying cancer. Overexpression of specific gene products, such as HER-2, epidermal growth factor (EGF) and insulin-like growth factor receptors, and cyclins, has also been correlated as a causative factor in some cancers.

Alternatively, a normal gene product may be closely correlated with cancer progression. For example, elevated telomerase activity is observed in essentially all human cancers and increased serum vascular endothelial growth factor (VEGF) has been reported to be a prognostic clinical factor correlated with decreased survival in breast, ovarian, lung, gastric, and colon cancer patients