An Interview with Dr. Moutih Rafei | Associate Professor, Department of Pharmacology and Physiology | Université de Montréal

Progress in cell and gene therapy is made by people who work across disciplines and build across constraints. RoosterBio’s AMA (Ask Me Anything) series brings to the page those exceptional scientists and engineers whose work sits at the frontier of advanced therapies, bioprocessing, and mechanistic biology. Our aim is simple: let their thinking speak for itself, and let it inform yours.

In this inaugural edition of RoosterBio’s AMA series, we welcome Professor Moutih Rafei. Below, he shares how translational rigor and scalable engineering converge in next-generation immunotherapy.

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Across your study of MSCs, what were some findings you were most eager to share with the world?

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One message I have been most eager to share is that MSCs are not “fixed-function” cells. They are best understood as context-responsive biologics whose immune behavior can be deliberately reprogrammed, sometimes into a phenotype that resembles a professional antigen-presenting cell (APC). In our immunoproteasome-engineered MSC platform (MSC-IPr), for example, forcing immunoproteasome expression yielded an APC-like profile (increased MHC-I with CD80, de novo IL-12, chemokine remodeling) and a cross-presented epitope repertoire that differed markedly from dendritic cells, translating into strong antitumor activity in multiple murine models and synergy with checkpoint blockade.

“…MSCs are not “fixed-function” cells. They are best understood as context-responsive biologics whose immune behavior can be deliberately reprogrammed…”

Complementing genetic engineering, we also showed that pharmacologic perturbations can create “conditional APC” behavior. For instance, UM171a drove mitochondrial ROS that induced Psmb8 and enabled cross-presentation, producing therapeutic benefit in vivo without requiring IFN-γ licensing.  Most recently, second-generation reprogramming approaches (e.g., AccuTOX®/ARM-X) highlight that antigen uptake, endosomal escape, and stress-pathway activation (UPR) can be rationally tuned to improve potency at lower antigen doses.

Fusokines can be a novel way to generate potent biological activity from an engineered molecule. Are there any fusokines that might uniquely affect MSCs?

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Direct, MSC-specific “fusokines” are not yet a clearly established category in the same way that immune-cell–targeted cytokine fusions are, so I would be explicit that the literature base is thinner than for MSC biology. What is established is that engineered cytokine fusions can generate emergent signaling. For example, the GM-CSF/IL-15 fusokine (GIFT15) drove aberrant IL-15R signaling and yielded IL-10-producing regulatory B cells with disease-modifying activity in experimental autoimmunity, illustrating that fusion format can fundamentally change biology rather than simply add two activities.  Separately, GM-CSF–CCL2 (MCP-1) fusion constructs were shown to rewire CCR2 signaling and induce CCR2-dependent apoptosis or inflammatory suppression in preclinical models, underscoring that chemokine–cytokine fusions can “mis-program” GPCR outcomes.  For MSCs specifically, the most plausible fusokine directions are:

1. i) licensing-control designs that tightly deliver inflammatory cues known to toggle MSC immunophenotype (e.g., IFN-γ–linked constructs), and,
2. ii) trafficking and niche designs that couple chemokine axes (CCR2/CCL2-like circuits MSCs participate in) to programmable inflammatory payloads while recognizing the key safety risk that overly durable or systemic inflammatory signaling could negate therapeutic intent, amplify immunogenicity, or destabilize product consistency.

Dendritic cells have already been in the clinic to prime the immune system against cancer. How would you compare the application of dendritic cells vs. MSCs for use in these therapeutics?

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Mechanistically, dendritic cells are purpose-built to capture antigen, migrate to lymphoid organs, and prime naïve T cells. So, DC vaccines are conceptually “on-target” for anticancer vaccination. Sipuleucel-T remains the landmark example of an autologous cellular immunotherapy with a demonstrated survival benefit in metastatic castration-resistant prostate cancer.  At the same time, large, randomized efforts show the translational fragility of DC vaccination. In the VIABLE phase 3 trial (n≈1182), adding an autologous DC-based immunotherapy (DCVAC/PCa) to docetaxel/prednisone did not improve overall survival versus placebo, highlighting that immunogenicity does not automatically translate into clinical benefit.

In contrast, MSCs entered the clinic mainly as immunomodulatory/regenerative products whose effects are largely paracrine and microenvironmental (cytokines, growth factors, extracellular vesicles, and immune-cell crosstalk), with known challenges around variability and potency definition. The strategic opportunity (reflected in our own work) is that MSCs can be engineered or pharmacologically reprogrammed to adopt antigen-presentation functions (MSC-IPr, UM171a-treated MSCs, ARM-X), potentially combining “manufacturing tractability” and platform engineering with vaccination-like mechanism. However, this also creates a new responsibility for managing immunogenicity, clearance, and mechanism-linked potency assays as rigorously as in any cell-based vaccine program.

What kinds of scientific breakthroughs in academia portend scaling to the clinic, in addition to enriching human knowledge?

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In my experience, the academic breakthroughs most predictive of clinical scalability share one feature: they produce a mechanism that can be operationalized into controllable quality attributes. For cell therapies, the “breakthrough” is not only a new pathway, but a pathway that can be tied to release criteria such as potency assays, stability, identity, and comparability. So that the product can survive real-world manufacturing constraints and regulatory scrutiny.  The recent U.S. approval of remestemcel-L-rknd (Ryoncil) for pediatric steroid-refractory acute GVHD is illustrative. It represents a regulatory milestone for MSCs, but also implicitly validates years of process control, clinical framing, and consistency requirements needed for a living product.

In oncology, DC vaccine programs offered us several lessons to work on:

1. Biological rationale and safety are necessary but insufficient,
2. Scalable success requires overcoming tumor microenvironment suppression,
3. Achieving effective trafficking/migration, and
4. Standardizing manufacturing across sites.

Therefore, I watch most closely for “academia-to-clinic” work that couples mechanistic novelty with manufacturable control knobs (metabolic rewiring, stress-pathway gating, targeted cytokine delivery, or platform antigen loading) and provides clear translational hypotheses about patient selection, combination partners, and measurable pharmacodynamic readouts.

How do you envision the next decade unfolding for opportunities to launch life science startups out of universities and tech transfer offices?

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I expect the next decade to be shaped by:

1. Life science and “deep tech” commercialization to remain capital-intensive with long lead times and substantial uncertainty, and
2. Universities and funders to increasingly build infrastructures (incubators, translational cores, proof-of-concept funding, founder support) needed to make those timelines survivable.

Quantitatively, tech transfer remains resilient: the AUTM FY2024 licensing survey reports research funding >$109B, a 5% increase in startups, and an 8% rise in new products reaching the market (with revenue mix shifting toward equity cash-outs and other non-royalty income), which is consistent with a more venture-creation–oriented model of academic commercialization.  Internationally, funding signals for spinouts have also strengthened in some ecosystems (e.g., UK spinouts raising £2.6B in 2024), reinforcing that well-structured university spinout pathways can attract large pools of capital even when broader growth equity is softer.  In parallel, policy trends from the OECD emphasize innovation zones and cluster-based strategies in sectors like life sciences, suggesting that geography and ecosystem design will matter as much as IP quality.

Overall, I expect “platformizable” biology (cell engineering, programmable immunology, synthetic delivery) to dominate university-originated life science formation. On the other hand, the key bottleneck will remain the same: risk-tolerant early capital and experienced translational operators who can bridge academic discovery to CMC and clinical development discipline.

What advice have you received or given that has had the largest impact on your career/your trainees’ careers?

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The advice that has mattered most is to treat translational biology as a discipline of constraints. You have to start with a crisp mechanism, then ask what would break it in the clinic then design experiments that answer those “failure questions” early. That mindset pushes trainees to value negative data (it tells you what won’t scale), to build quantitative assays that reflect the intended mechanism of action, and to document process variables as though they were part of the scientific hypothesis rather than “just methods.”

“The best projects in my group are the ones where mechanistic creativity is paired with reproducible engineering (clear controls, orthogonal validation, and early thinking about comparability)…”

A second, equally practical principle is to pursue ambition without abandoning rigor. The best projects in my group are the ones where mechanistic creativity is paired with reproducible engineering (clear controls, orthogonal validation, and early thinking about comparability), because those are the projects that can attract collaborators, withstand review, and eventually become investable. Finally, for trainees considering entrepreneurship, I emphasize learning the vocabulary of translation: CMC, regulatory strategy, clinical endpoints, and reimbursement. These topics must be grasped early enough that the science can be shaped into a product narrative without distorting the underlying biology.