Stacie Clark, Molecular Microbiology, Third-Year Student: “Full of Surprises”
For this issue of Humans of Sackler, I had the chance to chat with Stacie Clark from the Microbiology program. As someone who mostly socializes within Neuroscience, it’s a real privilege for me to meet students from other programs and learn about some of the incredible, borderline-science-fiction work that’s going on right under my nose here at Sackler! Equally striking, I’ve found, is the treasure trove of unique passions and fascinating life experiences that lie just below the surface of our fellow students when we really get to talking. I’m grateful to Stacie for sharing a few of hers, and hope that you, dear reader, enjoy our conversation!
AH: When did you realize that you wanted to pursue a career in science?
SC: My parents told me they always knew I’d end up in science. From the moment I could walk, I was outside digging for beetles and worms and building terrariums. I was in the honors science program in high school, and I did a year-long project on hand sanitizer and bacterial survival. I was working in a lab as a high school student, and realized I really liked doing that. I think I was born for science, and my parents were super-supportive. When I was growing up, we went hiking all the time, they took us to the EcoTarium in Worcester, and we were members at the Museum of Science and Aquarium. So I was always exposed to all sorts of science.
AH: What places have you traveled to outside of Massachusetts?
SC: I studied abroad in Puerto Rico. Worcester Polytechnic Institute does this differently: they call it the IQP, Interactive Qualifying Project. The point of this project is to teach you how to work effectively in groups and communicate with people outside the university. I worked in the rainforest in Puerto Rico, and we did a project evaluating stream crossings. We wanted to look at how their bridges were affecting stream flow and water quality, so we got to hike all through the [El Yunque] rainforest and evaluate all these different stream crossings. We got to see parts of the rainforest that no one gets to see!
AH: What did you do between graduating from WPI and starting your Ph.D. at Sackler?
SC: Before I started grad school, I had always wanted to work with exotic animals. So I literally just Googled ‘volunteer experience in Costa Rica’ and this small remote place in Costa Rica popped up. I booked a two-week trip, went by myself back-packing in Costa Rica, and volunteered at an animal rehabilitation center. It was quite an adjustment: I was on a mountainside in southern Costa Rica, and it got pitch-black at 6 o’clock at night. I would go into the rehabilitation center, clean the cages, prep all the food, and then feed and play with the animals. The monkeys were my favorite, and there was also an anteater. His name was Gomer; if you went into his cage and just yelled out ‘Hey Gomer!’ he’d come crawling out, and he loved being held. We’d do enrichment activities for some of them too – so with the anteater, I would walk with him out in the jungle and let him go searching for termites and ants on his own, and then I’d go bring him back to his cage. I think everyone should go on at least one trip by themselves, because you learn a lot about yourself and it’s just a good experience!
AH: What do you like to do when you’re not working in the lab?
SC: I volunteer at the animal shelter in Quincy; I’ve been doing that every Monday for four years. I take the dogs out for walks, play with them, cuddle with them if they want to… They only get to go outside twice a day, that’s the only time they get to really play with people. I understand that work-life balance is really important to your mental health, so volunteering on Mondays is the one thing that I won’t let grad school take away from me. It’s something that I do for me that I enjoy – and I’m also a big dog person.
AH: There are so many disciplines within biology – what got you interested in studying bacteria specifically?
SC: I’ve always been fascinated that an organism so small can have such a large impact on humans – that still blows my mind! They’re incredible organisms that can mimic the proteins we have, which I find pretty amazing. We’re full of bacteria, they do a lot for us – and the microbiota is a huge field now. Everyone is fascinated in studying microbiota and the impact they have on our health in general.
AH: What particular species of bacteria do you study, and what makes it so interesting?
SC: Yersinia pseudotuberculosis is a model pathogen that we use to study community behavior of bacteria within its host. Yersinia can establish a distinct niche within the spleen of a mouse, and once it forms a microcolony, it can replicate to high numbers despite the presence of the immune system. You get a recruitment of innate immune cells to the site of infection, triggering a response in the bacteria to create specialized populations within that distinct cluster; I always thought that was cool, the response between the bacteria and the host cells.
Here at Maine Medical Center Research Institute, we are very happy to be supporting Tufts trainees and working with many Tufts investigators here and in Boston to provide core facility services such as transgenic mouse generation.
Did you know that many of our core facilities were established at Maine Medical Center through a special NIH program, the Institutional Development Award (IDeA) Program? The IDeA program was established by Congressional mandate in 1993 to help develop research infrastructure to support biomedical research in 23 states that historically have had a low level of NIH funding. Maine is one of those states. In fact, there was a time when 50% of NIH funding went to researchers in 5 states (Massachusetts being one of those heavily funded states!), while the 23 IDeA eligible states together only received about 5% of all NIH funds. Over the last 23 years, NIH investment in biomedical research in Maine has contributed to a burgeoning biotech scene (http://www.mainebioscience.org/access_resources/bioscience-map-of-maine/) and a highly collaborative network of research institutes.
One of the components of the IDeA program is the Centers of Biomedical Research Excellence (COBRE). Maine Medical Center has been fortunate to have received two COBRE awards since 2000, one with the theme of Vascular Biology, and one in Stem and Progenitor Cell Biology. These awards have supported the recruitment of new junior investigators to Maine Medical Center (with appointments at Tufts University School of Medicine), and also the establishment and expansion of our core facilities. Please visit our website at mmcri.org, and find “Core Facilities” under “Research Services & Resources” to see if we provide services that could be useful to your research!
In January 2015, President Obama announced the launch of the “Precision Medicine Initiative”, proclaiming it to usher in “a new era of medicine that makes sure new jobs and new industries and new lifesaving treatments for diseases are created right here in the United States.” In addition, he remarked that the promise of this initiative laid in “delivering the right treatments, at the right time, every time to the right person”. This initiative, with bipartisan support in the Congress, provided a total of $215 million investment in 2016 for the NIH, along with the FDA and the Office of the National Coordinator for Health Information Technology (ONC), with a large portion of the money ($70 million) awarded to NCI to “scale up efforts to identify genomic drivers in cancer and apply that knowledge in the development of more effective approaches to cancer treatment”. The initiative doesn’t stop at the genome level, as Dr. Francis Collins, Director of the NIH, pointed out in an interview with PBS News Hour, and is meant to provide information about environmental exposures, lifestyle choices and habits and pretty much everything that can affect one’s health. Given the mass of information that will be generated (the initiative aims to enlist 1 million volunteers for its cohort), it is no surprise that patient privacy issues, as well as database infrastructure, are major concerns in this mammoth undertaking.
In addition to this initiative, the US government also launched its “Cancer Moonshot Program” a year later in January 2016. This program, under the leadership of Vice President Joe Biden, and with the help of an expert panel, the “Cancer Moonshot Task Force”, aims to “make more therapies available to more patients, while also improving our ability to prevent cancer and detect it at an early stage.” Since cancer is widely accepted to be a genetic disease, it seems fitting to serve as the poster child for an initiative that aims to cure and prevent diseases based on tailoring therapy for an individual using personal genetic information.
Tied to these two initiatives is also the latest approach to clinical trials at the NCI, commonly termed as “basket trials”. Based on findings from exceptional case reports where patients treated with drugs not commonly used for that type of cancer, the NCI was encouraged to try out drugs traditionally reserved for particular types of cancer for the ones that they weren’t developed for; thus, the Molecular Analysis for Therapy Choice (MATCH) and the Molecular Profiling-Based Assignment of Cancer Therapy (MPACT) trials were incorporated into the Precision Medicine initiative. The NCI-MATCH trial aims to sequence tumor biopsy specimens from ~6,000 patients to identify mutations that will respond to targeted drugs selected for the trial; these drugs are already approved by the FDA for certain cancer types or are being tested in other clinical trials. On the other hand, the MPACT trial will compare whether patients with solid tumors fare better with targeted therapy vs non-targeted therapy.
Despite the initial fanfare, the recently released NCI-MATCH major interim analysis report does not paint a pretty picture for the trial’s outcome. While the enrollment was higher than expected (795 people registered in first 3 months compared to the projected 50 patients/month) and the labs were able to sequence most of the tumors (87%), it was also found that “most of the actual mutation prevalence rates were much lower than expected based on estimates from The Cancer Genome Atlas and other sources”. In fact, the overall expected mutation match rate was adjusted to 23% for the 24 treatment arms in the study as it continues.
While no endpoint has yet been reached to draw conclusive remarks about this trial, data available from other clinical trials that have taken a similar approach do not seem favorable. In the SHIVA trial, a randomized phase II trial carried out in France where 99 patients were treated based on identified mutation(s) compared to 96 patients treated with drugs of their physicians’ choice, median progression-free survival was 2.3 and 2 months, respectively. Current clinical data on patients with relapsed cancers, a major focus of the MATCH trial, do not seem favorable either. As Dr. Vinay Prasad, a haematologist-oncologist at Knight Cancer Institute, points out, only 30% of such patients respond to drugs based on biological markers and the median progression-free survival is 5.7 months. Based on this response rate, he estimated only 1.5% of patients with relapsed and refractory solid tumors to benefit from the precision medicine approach.
In a review of current clinical trials and past trials that have used the targeted therapy approach, Tannock & Hickman (NEJM, 2016) warn about the limitations of such an approach – heterogeneity and clonal evolution of cancer cells when challenged with targeted therapy, the inconsistency between expected and clinically achievable levels of inhibition of candidate molecules and of course, the efficacy of such therapies compared to currently available, standard but effective therapies such as aromatase inhibitors for breast cancer. While one can argue that heterogeneity in tumors can be countered with combination targeted therapy, the authors point out that “combinations of molecular targeted agents that target different pathways have often resulted in dose reduction because of toxic effects… in a review of 95 doublet combinations in 144 trials, approximately 50% of the combinations could use the full doses that were recommended for use as single agents, whereas other doublets required substantial dose reductions.” Even if it is possible that intratumoral heterogeneity can be countered with combination targeted therapy, a much-overlooked point in this initiative is the cost of such treatment strategy, considering the exorbitant costs of targeted cancer therapy. There already exists a disparity among cancer patients from a socio-economic standpoint and this initiative does little to address how to bridge such a gap. Questions such as how many drugs will a patient have to take, especially in cases of tumors that are highly heterogeneous, such as glioblastoma multiforme and how that would affect the living standard of a patient need to be considered before heralding a victory for the precision oncology approach even if the MATCH trial outcomes are favorable.
In another recent study, Dr. Victor Velculescu and his team from Johns Hopkins showed that sequencing only tumor genetic data can lead to false positives. After analyzing 815 cancer patients’ tumor sequencing data and comparing that data to the one from the patients’ healthy tissue, they found that 65% of genetic changes identified with tumor-only sequencing data were unrelated to the cancer and therefore, “false positives”. The team also found that 33% of mutations, which are targets of currently available drugs, were also false positives when the patient’s germline genome was compared to the tumor genome; this affected 48% of the patients in their cohort.
The paradigm behind the MATCH trial, and in general the Precision Medicine initiative, seems to be blind to an obvious aspect of biology – context matters, and more so, in case of mutations that are deemed to be “carcinogenic”. As outlined in a recent paper by Zhu et al (Cell, 2016) and the famous “bad luck” paper by Tomasetti and Vogelstein, it appears that the stem cells and their differential regenerative properties in different tissue types are responsible for the differential rates of carcinogenesis in various tissue types, a finding that again, buttresses the idea that tissue specificity matters. In fact, Iorio et al (Cell, 2016) was able to show just that in the context of pharmacogenomic interactions of currently available cancer drugs with data available from patient samples in the TCGA and other databases. Using a big data and machine learning approach, the authors developed a logic-based model that would predict the efficacy of any drug that is either approved or undergoing clinical trials against the mutation it is intended for in different cancer types ,which is essentially the basis of the MATCH trial. Surprisingly, it appeared that tissue specificity determined the pharmacological agents’ effects on the intended molecular targets; more specifically, only one drug interaction (out of 265 drugs tested) was found to be significant in multiple cancer types, which may sober up the expectations from the MATCH trial outcome. Therefore, using a blanket approach to target mutations in various tissue types without consideration to their environments can seem futile in the light of such findings.
The evidence from all these basic science and clinical studies raise the question of whether precision medicine is doomed to fail. While the gene-centric view of disease etiology have deepened over the years since the completion of the Human Genome Project, does this evidence point to the necessity of another paradigm in our understanding of cancer and other complex diseases, whose cures have been presumed to lie in genetic aberrations and molecular targets? An even more concerning question, relevant in this era of big data, is whether we actually understand what the data is telling us, as the prominent cancer researcher, Dr. Robert Weinberg, admits that “while data mining, as it’s now called, occassionally flags one or another highly interesting gene or protein, the use of entire data sets to rationalize how and why a cancer cell behaves as it does is still far beyond our reach”. A strong critic of the initiative, Dr. Michael Joyner from Mayo Clinic, opines that while “hundreds of genetic risk variants with small effects have been identified…But for widespread diseases like diabetes, heart disease and most cancers, no clear genetic story has emerged for a vast majority of cases” and that “when higher-risk genetic variants are found, their predictive power is frequently dependent on environment, culture and behavior”.
The success of Precision Medicine Initiative, and in particular, the precision oncology approach, ultimately rests on whether it can stem and curb deaths resulting from cancer and other complex diseases, based on molecular targeted therapy. Unfortunately, it appears that large scale public health initiatives have done more to that end (e.g. – tobacco control has largely cut down rates of lung cancer incidence, diet and exercise can cut down the risk of converting pre-diabetes to diabetes by nearly two-thirds), compared to what targeted therapy have achieved. However, it seems that such public health success was overlooked by the Cancer Moonshot panel as in February 2016, right after the program was announced, public health researchers across the country had to urge the Vice President to make prevention a bigger focus in controlling cancer incidence in the population, rather than just trying to find a cure. This approach should have been incorporated into a billion-dollar initiative by default, one would think, but this didn’t seem to be the case and one must wonder why.
In order for this huge, publicly-funded initiative to achieve more than just lukewarm outcomes and to actually become a breakthrough it is promised to be, the Precision Medicine initiative needs to break free of the gene-centered tunnel vision and incorporate all factors that affect an individual’s health, such as lifestyle choices and environmental exposures, as Dr. Collins boasted it to be. While this initiative is only at its infantile stage, changes based on clinical trial and basic science evidence should be made early enough so that favorable outcomes can be achieved and does not require the government to stage another public bailout as it did for the failing banks and wall street corporations back in 2008 when they were deemed to be “too big to fail”.
You can customize your preferences to make searching PubMed and other NCBI databases easier. Log in to your My NCBI account (see Insight March 2016 for details on creating a My NCBI account) and click the ‘NCBI Site Preferences’ link in the top right corner of the homepage.
Here are a few preferences that you may want to adjust:
Highlighting: Highlights your search terms in a set of results, making scanning for relevant articles more efficient.
Filters & Icons: Personalized filters displayed in the right-hand column on results page. I recommend adding the MEDLINE filter, which limits results to articles that have had MeSH terms applied to them. To do so, click on the ‘Filters & Icons’ link on the Preferences page, and on the page that opens, select the ‘Properties’ radio button. Enter ‘MEDLINE’ in the search with terms box, then check the box next to MEDLINE. You can also add the ‘Find it @Tufts’ button, which enables you to access the full text of an article through Tufts Libraries. Adding this button to your NCBI account would obviate the need to access PubMed through the Hirsh Health Sciences Library website. To add the ‘Find it @Tufts’ button, select the ‘LinkOut’ radio button on the Filters & Icons page. Then, enter ‘Tufts University’ in the search box and check the link icon box next to Tufts University Hirsh Health Sciences and Veterinary Libraries.
Outside Tool: A simpler method of adding the ‘Find it @Tufts’ button to your account preferences. Click the ‘Outside Tool’ link on the Preferences page. On the page that opens, select the radio button next to ‘Tufts’.
Result Display Settings: You can choose the format (summary or abstract) in which results are displayed, how results are sorted (I do not recommend changing this from the default, recently added), and the number of items per page (I prefer 200, so I don’t have to click through multiple pages).
These are just a few of the preferences that you can adjust in your My NCBI account. You can also explore customized settings for other NCBI databases, such as Gene.
TBBC Case Study Group: Mondays – 5-7PM beginning M Feb 6, Jaharis 508
Practice solving cases, gain insight and tips, and learn more about the field of consulting.
TBBC Seminar Series: Liz O’Day, Founder and CEO of Olaris Therapeutics
Tu Dec 6: Liz O’Day, PhD, presented actionable tips and insight into her transition from the academic world to being an entrepreneur. Olaris is a venture-backed drug discovery company that uses a proprietary NMR-metabolite profiling platform to unlock aspects of human metabolism that could never before be analyzed.
TBBC Consulting Seminar Series: Peter Bak, PhD
Tu Dec 13: Peter Bak, PhD, Manager at Back Bay Life Science Advisors, spoke about transitioning from a PhD program to life sciences consulting and career opportunities at BBLSA.
We often get asked about what statistical and data analysis programs are installed on the library’s computers, or available for installation on personal computers. Here is a summary of the computers available at the Hirsh Health Sciences Library, and a chart indicating which statistical and data analysis programs are installed on these computers and available to students:
Public Computers: Desktop computers on the 4th and 5th floors of the Sackler; available for anyone to use.
Computers labs: Desktop computers in Sackler 510 and 514; available for use when not reserved for a class (check schedule on white board behind Tufts Technology Service Desk on 5th floor of Sackler). All computers in both labs were recently replaced.
Laptops: Mac and PC laptops available for checkout at the Library Service Desk on the 4th floor of Sackler; available for students, faculty and staff to checkout for 4 hours.