Tag: University of Florida

Categories
Oncology

How AI Is Revealing New Targets for Cancer Drugs

Woman in cancer treatment. // National Cancer Institute at Unsplash.com

Introduction

Targeted drug therapy has proven to be a highly advantageous approach to cancer treatments, presenting high efficiency and low patient drug resistance. 

Yet, there are drawbacks to the use of targeted drug therapy for cancer, including a lack of identified druggable genomic targets that extend across the patient population. Artificial intelligence algorithms can help researchers better understand carcinogenesis and identify new cancer targets. 

Artificial Intelligence (AI) is a field combining computer science and extensive data sets to perceive, understand, and solve problems.

Two major branches of AI applied biologically are machine learning-based and network-based. Machine learning is an application of AI wherein a computer can learn without direct instruction through mathematical models and pattern recognition. Network-based AI sorts and compares data, providing and compensating different perspectives. 

The Food and Drug Administration (FDA) and the international community have presented an increased interest in trustworthy and ethical AI adoption and innovation.

Applications

The development of multiomics technology is a factor that has bolstered the process of identifying novel anti-cancer targets. Multiomics is an approach to biological analysis that consists of forming data sets out of “omics”, which in the case of cancer are epigenetics, genomics, proteomics, and metabolomics. AI can analyze these data sets to investigate for anti-cancer targets. 

BioRender image by You Et al. Artificial intelligence in cancer target identification and drug discovery. https://doi.org/10.1038/s41392-022-00994-0

Epigenetics

Unlike the changes in the nucleotide sequence characteristic of genetic mutation, epigenetics is similar to an “on-and-off” switch for the expression of specific genetic attributes without altering the genome. Cancer can be caused by both a genetic mutation or an epigenetic signal gone awry. 

A major problem facing epigenetics cancer research is finding specific gene patterns that predict which patients will respond to a cancer treatment. The study of the reversal of epigenetic modifications through AI can give insight into how exactly healthy cells become cancerous and which genetic marker within a patient will respond to cancer-treating drugs.

Genomics

The study of genomics involves the mapping of an entire genome including its structure, function, and evolution, through genome-wide assays such as sequencing. A network-based AI is capable of finding similarities in specific genetic sequences and patterns in their phenotypic expression and interactions. Cancerous biomarkers can be identified through genomic data sets, identifying which genes medical professionals should consider oncogenes of interest.

Proteomics

Proteomics refers to proteins and their interactions within the body. Protein-protein interaction (PPI) research classifies a certain type of protein as “indispensable” and associates them as a major site of disease-causing mutations and drug targeting. In a 2017 study, Ravindran et al. found by analyzing the human PPI data from cancer patients that there are 56 indispensable genes in nine cancers, 46 of which were associated with getting cancer for the first time. This protein interaction data can be harnessed through AI to reveal novel cancer-associated interactions and their potential drug targets. 

Metabolomics

Metabolomics is the study of metabolites: the substrates, intermediates, and products of the human metabolic pathway. A hallmark of cancer cells is that they work to alter these metabolites in order to support their rapid growth, providing energy to their biosynthetic pathways and changing their redox balance. Cancer can be detected through biological AI network analysis due to the presence of certain biomarker metabolites within biofluids, cells, and tissues of the body.

Conclusion

All aforementioned “omics” data can be presented for review in the form of multiomics integration analysis. Varied and interconnected data in a network format allows researchers to study carcinogenesis and drug targeting from an overarching perspective in a multifaceted group of patients. 

While treatment of cancer remains a formidable challenge, rapid technological advances in data collection and analysis through the use of artificial intelligence combined with robust information exchange may prove to be increasingly beneficial to the way cancer drugs are created and tested, leading to potential a safer and healthier world.

References
  • Breakthroughs Staff. (2017, December 12). Treating Cancer by Using Epigenetics, the ‘Software’ of Our Genes | Pfizer. Pfizer News. https://www.pfizer.com/news/articles/treating-cancer-using-epigenetics-%E2%80%98software%E2%80%99-our-genes
  • Guenthoer, J., Lilly, M., Starr, T. N., Dadonaite, B., Lovendahl, K. N., Croft, J. T., Stoddard, C. I., Chohan, V., Ding, S., Ruiz, F., Kopp, M. S., Finzi, A., Bloom, J. D., Chu, H. Y., Lee, K. K., & Overbaugh, J. (2023). Identification of broad, potent antibodies to functionally constrained regions of SARS-CoV-2 spike following a breakthrough infection. Proceedings of the National Academy of Sciences, 120(23), e2220948120. https://doi.org/10.1073/pnas.2220948120
  • Huang, S., Wang, Z., & Zhao, L. (2021). The Crucial Roles of Intermediate Metabolites in Cancer. Cancer Management and Research, 13, 6291–6307. https://doi.org/10.2147/CMAR.S321433
  • Ravindran, V., V., S., & Bagler, G. (2017). Identification of critical regulatory genes in cancer signaling network using controllability analysis. Physica A: Statistical Mechanics and Its Applications, 474, 134–143. https://doi.org/10.1016/j.physa.2017.01.059
  • U.S. Food and Drug Administration. (2022). Using Artificial Intelligence & Machine Learning in the Development of Drug & Biological Products. https://www.fda.gov/media/167973/download
  • You, Y., Lai, X., Pan, Y., Zheng, H., Vera, J., Liu, S., Deng, S., & Zhang, L. (2022). Artificial intelligence in cancer target identification and drug discovery. Signal Transduction and Targeted Therapy, 7(1), Article 1. https://doi.org/10.1038/s41392-022-00994-0
Categories
Pharmacology

Clascoterone, First Novel Acne Therapy in 38 Years, Treats Acne By Blocking Facial Androgen Receptors

Topical medication cream. // Marco Verch, CC BY 2.0

In 1982, the FDA approved isotretinoin (Accutane), a Vitamin A derivative, for use in patients with acne. No new methods of acne medication had been approved from 1982 until the approval of topical clascoterone in August 2020, almost 40 years later.

Topical clascoterone is a cream that is applied directly to the skin of areas affected by acne. Clascoterone is an antiandrogen, which is a class of drug that blocks androgen receptors. The drug is the first antiandrogen to be approved by the FDA for acne medication, earning it the title of first-in-class medication. Androgens, which are male sex hormones present in males and lower levels in females, play an important role in the pathogenesis of acne.

During puberty, both males and females have increased levels of androgens like testosterone or dihydrotestosterone (DHT). Higher levels of testosterone can cause increased production of sebum, an oily substance secreted by sebaceous glands under the skin. Excessive amounts of sebum in a skin pore can cause a blockage (known as a comedo, blackhead, or whitehead) that may become infected.

Clascoterone was shown in vitro to have higher affinity for androgen receptors than DHT. This blockage of local androgen receptors by clascoterone was then shown by clinical trials to reduce the acne-causing effects of androgens.

The Investigator’s Global Assessment Scale (IGA) is a scale of acne severity that goes from 0 (clear) up to 4 (severe). Two clinical trials found that at least 18% of patients achieved a drop of at least 2 points on the IGA scale (resulting in a score of 0 or 1) at 12 weeks into treatment with topical clascoterone. One trial showed that patients, on average, saw a 39% decrease in total lesion count after 12 weeks of treatment.

The FDA listed the most common side effects of topical clascoterone as reddening, itching, and scaling or dryness of treated skin. The FDA-approved brand of topical clascoterone is Winlevi.

References
  • Piszczatoski, C. (2021, October 2). Topical Clascoterone: The First Novel Agent for Acne Vulgaris in 40 Years. https://doi.org/10.1016/j.clinthera.2021.08.007
  • U.S. Food and Drug Administration. (2020, September 3). Drug trial snapshot: Winlevi. https://www.fda.gov/drugs/drug-approvals-and-databases/drug-trial-snapshot-winlevi
Categories
COVID-19

Researchers Reveal Portable COVID Testing Method, Gives Results Within One Second

person holding test tubes
Photo by Polina Tankilevitch on Pexels.com

Researchers from the University of Florida, along with collaborators from the National Chiao Tung University, recently created the world’s fastest COVID detection test to date using a new method with antibody-infused test strips and a small circuit board.

Since the beginning of the COVID-19 pandemic, RT-PCR tests, commonly referred to as PCR, have been regarded as the gold standard for COVID-19 testing.

Reverse Transcription Polymerase Chain Reaction (RT-PCR) works by first converting RNA into DNA, followed by copying small segments of this DNA over and over, primarily using temperature to denature and bind DNA, along with “primers” to make new copies. The process takes about two hours and uses expensive machinery. Such amplification of DNA makes it easy for machines to detect the small amounts of viral particles present in infected patient samples, but difficult to apply to large populations during a pandemic.

Denaturation is when double stranded DNA splits in two and occurs at high temperatures. The green and purple segments in the image are “primers” which bind to DNA at lower temperatures and elongate it. / microbenotes.com

One of the defining features of the coronavirus is the spike proteins, which enable the virus to penetrate host cells due to their geometry and location. Rather than having to convert RNA to DNA, copy the DNA, and read a signal as is done with RT-PCR tests, a new study described a system which uses the spike protein-antibody bond and circuitry for detection.

Antibodies are Y-shaped proteins our immune system produces to fight and prevent future infection. They work by creating sites to which infectious particles bind, effectively blocking those particles from infecting cells. These sites can include binding locations for viruses such as SARS-CoV-2, which researchers have found to be quite useful for detection.

COVID-19 surrounded by Y-shaped antibodies / cdc.gov


As our need for fast, cheap, and portable detection grows, researchers have been searching for new methods. The researchers from the University of Florida ingeniously combined knowledge of antibodies and circuitry to detect presence of COVID in one second.

First, they modeled commercially available glucose testing strips commonly used for testing blood sugar levels in diabetic patients. If you were to dissect a glucose test strip, you would find several electrodes, coated and made of different materials.

Most commonly, glucose test strips are coated with an enzyme that reacts with glucose to steal its available electrons. These electrons are then transported to the electrode which can detect and quantify their presence, indicating how much glucose was in the blood sample.

A glucose strip, mainly used for diabetes patients, is dissected to reveal electrode and adhesive layers. / electrochem.org

In the study, researchers worked to transform the electrodes using different biological and chemical materials. One of the electrodes was plated with gold then “biofunctionalized” with coronavirus antibodies.  An electrode in the middle was connected to an electronic component called a metal-oxide-semiconductor field-effect transistor (MOSFET), which is used to control and amplify electrical signals.

When spike proteins from a sample interact with the surface, the antibody-antigen complex will spring up and down, causing an electrical signal to be sent to the gate of the MOSFET. The device’s circuit board can then quickly convert and read the signal. 

The MOSFET is especially important as it can convert electrical activity from the interaction of a very small amount of coronavirus with the antibodies into a very large signal, similar to how RT-PCR tests amplify the small amount of genetic material into a much larger and easier-to-detect sample.

Figure (a) shows a completed rendition of the detection test. The microfluidic channel is where saliva is inserted for COVID-19 detection. Figure (b) reveals the inner electronics, which connect the test strips to a MOSFET. / che.ufl.edu

The accuracy and acute sensitivity of this method are a direct result of combining electrical and biological tools of detection. Not only does this allow for the detection of extremely low quantities of virus particles, but it can be accomplished in merely 1 second. Furthermore, the device is inexpensive and portable, paving the way for fast, economical, and highly sensitive at-home diagnostic kits.

Notably, Minghan Xian, first author of the study, remarked that by simply altering the type of antibody used, this detection kit could be reapplied to a multitude of other infectious diseases. The electronic components can also be reused with new electrodes.

References
Categories
COVID-19 Public Health

Recovered Patients of Severe COVID-19 Infection 233% More Likely To Die Within Year Than Negative Counterparts

a grieving man kneeling on a grave with red flower
Photo by RODNAE Productions on Pexels.com

Research published by University of Florida scientists in Frontiers in Medicine reported that patients (aged 18-65) who recovered from severe COVID-19 infection were 233% more likely to die within 12 months than COVID-19-negative counterparts.

Methodology

The study analyzed 13,638 patients in the University of Florida Health system over a 12-month period, including positive (mild, severe) and negative cases. A severe case was defined as one requiring hospitalization within 30 days of a positive COVID-19 test. The 12-month risk of mortality was adjusted for age, sex, race, and comorbidities–meaning these factors did not affect the data.

Results

Survival curve showing probability of survival over time following mild, severe, and lack of COVID-19 illness. / Mainous 2021

Patients aged 18 to 65 who recovered from an initial episode of severe COVID-19 had a 233% increased incidence of mortality in a 12-month period compared to negative counterparts. Recovered patients aged over 65 also had increased mortality compared to negative counterparts, but to a lesser extent.

The difference in 12-month mortality between COVID-negative and mild COVID patients was not statistically significant.

Only 20% of the deaths in the 12-month period were attributed to cardiovascular or respiratory conditions.

Discussion

These results show that those who recover from severe COVID-19 infections are much more likely to die within 12 months of recovery compared to those with mild or no infection. This reveals that the increased risk of death from COVID-19 is not limited to the initial episode of infection, indicating that the biological and physiological insult from severe infection is significant. This is further demonstrated by the unexpectedly low portion of deaths caused by cardiovascular or respiratory conditions.

Arch G. Mainous III, Ph.D., first author of the study and University of Florida College of Medicine faculty member, said in a statement to the University of Florida Health Newsroom that “patients may feel that if they are hospitalized and recover from COVID-19 then they have beaten COVID-19. Unfortunately, having a substantially increased [risk] of death in the next year after recovery from a severe episode of COVID-19 shows that this is not the case. Preventing severe COVID-19 should be our primary focus.”

The study mentions that nearly all hospitalizations and severe infections are preventable. Pfizer and Moderna’s COVID-19 vaccines prevent severe infection in more than 95% of cases.

Mainous hopes that the data, which he described as devastating, will “make everyone rethink the impact of COVID-19.”

References
Categories
COVID-19 Pharmacology

Combining a Protein Found in Milk with Benadryl Reduces SARS-CoV-2 Replication in Lung Cells by 99%

Benadryl tablets. // Castorly Stock via Pexels

Researchers looking for prevention and treatment strategies for COVID-19 that are not impacted by SARS-CoV-2 mutations published findings in Pathogens that showed that a combination of diphenhydramine (the active ingredient antihistamine in Benadryl) with lactoferrin (an immunologically active protein found in human and cow milk) reduced SARS-CoV-2 replication by 99% in human cells.

Background

The key to the researchers’ findings related to proteins called the sigma receptors. These receptor proteins are located in the endoplasmic reticulum (ER), an organelle responsible for protein folding and transportation. Sigma receptors have multiple functions, including regulation of the ER stress response.

The ER stress response occurs when the ER is overwhelmed with unfolded or misfolded proteins. This triggers the unfolded protein response (UPR), which seeks to return the cell to a normal state by increasing protein folding, autophagy (destruction of damaged proteins), and in the case of prolonged UPR, apoptosis (cell suicide).

ER stress usually occurs when the ER is overwhelmed with unfolded or misfolded proteins. Cells mitigate ER stress by provoking the unfolded protein response (UPR), which includes increased protein folding, autophagy (destruction of damaged proteins) and, in prolonged cases, apoptosis (cell suicide).

When the UPR causes autophagy, it does so by forming sites near the ER called autophagosomes. Coronaviruses (CoV) have been found to bind directly to the sigma-2 receptor to cause ER stress, enabling them to hijack autophagosomes for use as virus replication sites.

Implication

Researchers found that by binding a drug molecule to the sigma-2 receptor, SARS-CoV-2 would no longer be able to bind to it to cause ER stress (and ultimately virus replication). This is made even more effective by also binding to and activating the function of the sigma-1 receptor.

Results

The team identified a ligand called AZ66 as being able to bind to both sigma-1 and sigma-2 receptors. In experiments with human lung cells infected with SARS-CoV-2, AZ66 completely blocked virus production. However, the safety of AZ66 is unknown, as the drug candidate has not been tested in clinical trials.

Molecular docking model of human sigma-2 receptor (orange) bound to AZ66 (yellow).

Searching for common compounds with proven records of safety, the researchers analyzed electronic medical records to identify diphenhydramine (DPH), the active ingredient antihistamine in Benadryl, as being associated with higher survival rates for COVID-19 patients. This is due to DPH having effects on the sigma-1 receptor. DPH was found to reduce replication of SARS-CoV-2 in the infected human lung cells by about 30%.

Lactoferrin is an antimicrobial and immunostimulatory iron-sequestering protein found in human and cow milk that was brought to a researcher’s attention by the Global Virus Network’s COVID-19 task force due to its antiviral effects on SARS-CoV-2. When tested, it was also found to reduce virus replication by about 30%. The milk protein has a proven safety record as a supplement widely used to treat stomach ulcers.

When a diphenhydramine/lactoferrin combination was tested in human and monkey epithelial lung cells, they found that a synergistic effect occurred, reducing virus replication by 99%.

Commentary

The study’s first author, David A. Ostrov, Ph.D. of the University of Florida, hailed diphenhydramine and lactoferrin as “effective, economical,” and unlike AZ66, “[having] a long history of safety.” The combination could be used to prevent infection as well as decrease recovery time from COVID-19.

While the researchers await potential interest from pharmaceutical companies, Ostrov told the University of Florida Health Newsroom that he cautions against self-medicating with diphenhydramine or lactoferrin as a COVID-19 prevention or treatment. He said that any off-label use of medication should follow a consultation with a physician. Further, commercially available lactoferrin used for treatment of stomach ulcers is not exactly the same as the lactoferrin used in the study.

Lactovid™ is a combination of diphenhydramine and lactoferrin

Would you be interested in purchasing Lactovid™ as a non-FDA approved over-the-counter product?(required)

Warning against off-label self-medication

This article does not offer medical advice. University of Florida researcher, David A. Ostrov, Ph.D., said that any off-label use of medication should follow a consultation with a physician. Off-label use is when a medication is used for anything other than its approved purpose.

This article is based on the following sources

– Bennett, D. (2020, December 3). Existing antihistamine drugs show effectiveness against COVID-19 virus in cell testing. University of Florida Health Newsroom. https://ufhealth.org/news/2020/existing-antihistamine-drugs-show-effectiveness-against-covid-19-virus-cell-testing
– Bennett, D. (2021, November 22). Two common compounds show effectiveness against COVID-19 virus in early testing. University of Florida Health Newsroom. https://ufhealth.org/news/2021/two-common-compounds-show-effectiveness-against-covid-19-virus-early-testing
– Ostrov, D. A., Bluhm, A. P., Li, D., Norris, M. H., et al. (2021, November 20). Highly specific sigma receptor ligands exhibit anti-viral properties in SARS-Cov-2 infected cells. Pathogens. https://doi.org/10.3390/pathogens10111514
– Vela, J. M. (2020). Repurposing sigma-1 receptor ligands for COVID-19 therapy? Frontiers in Pharmacology. https://doi.org/10.3389/fphar.2020.582310

Categories
Public Health

Study Shows Reddit’s Potential as an Early Warning System for New Designer Drugs

In a new study, researchers demonstrated the use of data mining of social networks like Reddit to predict increased use of novel psychoactive substances (NPS).

Reddit is a social network and media aggregator divided into subreddits pertaining to certain topics, like college football, art, movies, and world news. Niche subreddits exist for many topics, including specific drugs.

Users on subreddits like r/ResearchChemicals discuss designer drugs (including analogs) and other newly discovered substances. Analogs are two drug compounds that have similar molecular structures and/or effects. Sometimes, an analog of an illegal drug has similar effects and properties to its illegal counterpart but has yet to be made illegal.

Under the Federal Analogue Act, compounds “substantially similar” to controlled substances are meant to be treated as if they were the controlled substances themselves. However, designer drugs are often overlooked or may take years for federal authorities to address.

Reddit post on “research chemicals” subreddit discussing novel psychoactive substances.

Researchers from Florida Atlantic University, the University of Florida, and New York University gathered and analyzed data on mentions of newly discovered NPS on Reddit. They found that users mentioned certain NPS months to years before the substances became prevalent in toxicology reports. Such reports are conducted to identify a culprit substance when a patient has overdosed or is subjected to a toxic exposure.

The study mentioned that NPS mentioned on Reddit before any exposures were recorded include:

  • Carfentanil
  • U-47700
  • Eutylone
  • Flualprazolam
  • N-ethylpentylone
  • Isotonitazene
  • Brorphine

Carfentanil, for example, was first mentioned on Reddit in February 2013–almost 4 years before its first reported exposure in October 2016.

Reddit mentions of N-ethylpentylone peaked 5 months before the number of reported cases. (Barenholtz et al, 2021)

The study found that seven of the eight analyzed NPS were mentioned on Reddit before there were any reported cases of the substances in toxicology reports.

Five of the eight analyzed NPS peaked in Reddit mentions months before the substances peaked in reported exposures.

The researchers posit that these data mining methods could prove to be a useful tool for early detection of NPS trends by public health authorities and legislatures.

This article is based on the following works:

– Barenholtz et al. (2021, August 5). Online surveillance of novel psychoactive substances (NPS): Monitoring Reddit discussions as a predictor of increased NPS-related exposures. https://doi.org/10.1016/j.drugpo.2021.103393

Categories
Pharmacology

How “Docking Software” Helped Discover Compounds That Could Boost Stroke, TBI Recovery

Example of molecular docking of a ligand in the main protease of SARS-CoV-2. Yellow: ligand position determined by computer simulation. Black: ligand position determined by experiment. Source: Joshua Vermaas/ORNL, US Department of Energy.

Using the University of Florida’s HiPerGator supercomputer with the University of California San Francisco’s DOCK software, researchers have identified two dipeptides as small molecule activators of the peptidase neurolysin enzyme.

Render of peptidase neurolysin enzyme.

Peptidase neurolysin is an enzyme that has been found to be “one of the brain’s potent, self-protective mechanisms promoting preservation and recovery of the brain after acute injury” (Karamyan). Karamyan’s research posited that in the case of these injuries, neurolysin is responsible for:

  • reducing fluid buildup around the brain (cerebral edema)
  • reducing neural cell death caused by excess neurotransmitters (excitotoxicity)
  • reducing inflammatory response in the brain (neuroinflammation)

Searching for ways to make neurolysin more effective, lead researcher Vardan Karamyan, PhD (Texas Tech University Health Sciences Center Department of Pharmaceutical Sciences) enlisted the help of David Ostrov, PhD (University of Florida College of Medicine Department of Pathology, Immunology and Laboratory Medicine).

Neurolysin is similar in structure to a molecule called ACE2 (angiotensin converting enzyme-2), the main receptor for the virus that causes COVID. Dr. Ostrov previously identified drugs that bind ACE2, and he used the same strategy to identify drug candidates that bind neurolysin.

Superposition of neurolysin (copper) on ACE2 (teal).

Ostrov used UF’s HiPerGator supercomputer to screen 139,725 compounds from a repository at the National Cancer Institute Developmental Therapeutics Program to identify candidates that could fit a site on neurolysin that would facilitate an increase in the enzyme’s function. This was achieved using the DOCK program package, developed by UCSF.

DOCK’s molecular docking simulations were used to identify if and how a ligand (drug-like small molecule) can bind to the active site of a macromolecule (in this case, neurolysin). This is usually done to find ways to promote or inhibit a macromolecule’s function, making molecular docking software a key component in the ever-expanding world of computational drug discovery.

According to the UFHealth Newsroom, UF’s HiPerGator supercomputer completed the query in 15 hours–only 1.4% of the time it would take a desktop computer to complete the same task.

In the lab, the researchers tested the function of DOCK’s best matches on rat neurolysin. They found that the dipeptides L-histidlyl-L-tyrosine and L-histidlyl-L-histidine enhanced the activity of neurolysin.

According to Ostrov, human clinical trials with the mentioned drug candidates could begin within 2 years if FDA approved drugs are found to enhance neurolysin activity. An approved drug could assist or facilitate recovery in stroke and traumatic brain injury (TBI) patients.

This article is based on the following sources

– Bennett, D. (2021, September 7). UF health researcher, collaborators discover compounds that might boost stroke recovery. University of Florida Health. https://ufhealth.org/news/2021/uf-health-researcher-collaborators-discover-compounds-might-boost-stroke-recovery
– Karamyan, V. T. (2019, October). Peptidase neurolysin is an endogenous cerebroprotective mechanism in acute neurodegenerative disorders. https://doi.org/10.1016/j.mehy.2019.109309
– Statements from David A. Ostrov, PhD (University of Florida College of Medicine, Department of Pathology, Immunology and Laboratory Medicine)