Tarang Gaur is a postdoctoral researcher at the Albert Einstein College of Medicine. She investigates the molecular mechanisms driving drug synergy and therapeutic resistance in acute myeloid leukemia (AML). In this Postdoc Portrait interview, she shares the importance of her work.
Uncovering Synergy in Blood Cancer Pathways
Q | What drew you to leukemia research?
My journey into leukemia research began not in a laboratory, but in the corridors of Tata Memorial Center, India's largest cancer hospital, where I pursued my PhD. Every day, I walked past wards filled with patients with AML—many of them young adults and children who had run out of treatment options. I watched families travel hundreds of miles, spending their life savings, only to hear that the cancer had relapsed and was no longer responding to therapy. I had privilege to speak to them in person during sample collections.
I realized that the real battle against AML wasn't just in treating it, it was in understanding why it fights back. Why do cancer cells become resistant? What vulnerabilities can we exploit before that happens?
That question drove me from Mumbai to New York City where I got a chance to work under my current mentor who a revolutionary scientist in my field. I feel happy that my PhD and postdoc work has a huge translational relevance.
Q | What scientific problem are you trying to solve?
AML is one of the most fatal blood cancers, with poor survival rates and limited treatment options, especially in patients who develop resistance to therapy. My research focuses on identifying novel therapeutic targets and drug combinations to overcome these challenges.
At Albert Einstein College of Medicine, in collaboration with Janssen, I am investigating the molecular mechanisms behind drug synergy specifically how menin inhibitors and FMS-like tyrosine kinase 3 (FLT3) inhibitors work together against AML. In parallel, I am evaluating a novel apoptosis activator combined with the drug Venetoclax in p53-mutated AML, using both patient-derived primary blast cells and patient-derived xenograft (PDX) models to rigorously assess translational potential in a clinically relevant setting.
Working directly with primary patient samples allows me to validate findings beyond standard cell lines, capturing the true biological complexity of AML. PDX models further bridge the gap between the lab and the clinic by recapitulating human disease in vivo.
My ultimate goal is to translate these discoveries into better, more durable treatment options, giving patients with AML a real fighting chance.
Q | What’s one thing you learned from your research that you didn’t expect?
When I began studying drug combinations in AML, I expected the science to be straightforward as in two drugs hitting two targets should simply be better than one. What I didn't expect was how profoundly unpredictable leukemia cells could be.
Working with primary patient samples completely changed my perspective. Unlike neat, well-behaved cell lines in a dish, patient-derived blast cells humbled me constantly. Two patients with seemingly identical AML mutations could respond completely differently to the same drug combination. The cancer wasn't just a genetic problem, it was an ecosystem, shaped by each patient's unique biology, clonal evolution, and tumor microenvironment.
The most surprising discovery was that sometimes, when you push cancer cells hard enough with one drug, they don't just resist, they adapt in ways that inadvertently create new vulnerabilities you never anticipated. What looked like treatment failure was sometimes, counterintuitively, an opportunity.
This taught me that resistance isn't the enemy of good science, it's actually a window into cancer's deepest secrets. Some of my most exciting research directions today emerged directly from experiments that initially failed. Science, I learned, rewards curiosity over expectation.
Redefining Targeted Therapies and Clonal Evolution
Q | If your research succeeds, what are the long-term implications?
AML is devastatingly cruel. The median age of diagnosis is 68, but it strikes young adults and even children without warning. Despite decades of research, the five-year survival rate remains below 30 percent. It is one of the worst among all blood cancers. For patients with p53 mutations or relapsed disease, survival is often measured in months. Right now, some of the most exciting developments in AML are the emerging clinical trials combining menin inhibitors with FLT3 inhibitors, a strategy that has shown remarkable early promise. However, clinical responses remain inconsistent, resistance emerges rapidly, and we still don't fully understand why the combination works in some patients and fails in others. That mechanistic gap is precisely what my research addresses. If my work succeeds, it could provide the scientific rationale to rationally design better combination therapies, identify biomarkers that predict which patients will respond, and ultimately transform these promising clinical trials into durable, lasting remissions. Beyond AML, understanding resistance mechanisms could reshape how we approach targeted therapy across multiple cancers turning what is currently a death sentence for many patients into a manageable, perhaps even curable, disease.
Q | What question are you most excited to answer next?
Using single-cell technologies combined with our PDX models and patient samples, I want to map the evolutionary trajectory of AML cells as they encounter combination therapies like menin and FLT3 inhibitors. Essentially, I want to predict resistance before it happens. The most exciting possibility? That somewhere within these resistance mechanisms lies a universal vulnerability an Achilles heel that AML cells cannot escape regardless of how they evolve. Finding that vulnerability wouldn't just change AML treatment. It could fundamentally rewrite how we think about cancer drug resistance altogether.
Responses have been edited for length and clarity.
Are you a researcher who would like to be featured in the “Postdoc Portraits” series? Send in your application here.
