Biology subjects

Sousa, R. S.

Publications and source records attributed to Sousa, R. S..

4 recordsLinked to original sources

bioRxiv2025

Integrating Mathematical and Mouse Models Identifies T regulatory Cell Influx as a Key Determinant of Acquired Resistance to PD-1 Immunotherapy

The immune system can eradicate cancer, but various immunosuppressive mechanisms active within a tumor curb this beneficial response. However, unraveling the effects of multimodal interactions between tumor and immune cells and their contributions to tumor control using an experimental approach alone is time- and resource-intensive. To identify the critical immunological features associated with tumor control and escape, we built a mechanistic mathematical model of the interactions between CD8+ T cells, Tregs, DCs, and tumor cells deeply rooted in current biological concepts. A distinguishing feature of our model is that it captures Treg accrual occurring after checkpoint blockade immunotherapy. After successfully fitting the model to experimental data of a mouse model of immunogenic melanoma, we generated hundreds of parameter sets, each representing a unique virtual mouse, that fit the data equally as well to capture variability across individuals. Our model indicates that the tumor and immune states before therapy are a key limiting factor of the immune response. Increasing the initial number of tumor-killing CD8+ T cells alone doesnt always result in a better outcome; instead, the model implies that there exist optimal initial ratios of immune cells that will result in improved tumor control. The model further predicts that the Treg influx into the tumor is a key determinant of resistance to PD-1 immunotherapy. We validated this predictions experimentally. Overall, this integrated approach of modeling and experimental validation identified crucial determinants of resistance to immunotherapy and can be used to guide the development of more effective therapeutic strategies.

immunology↗

bioRxiv2025

Controlling treatment toxicity in ovarian cancer to prime the patient for tumor extinction therapy

High-grade serous ovarian cancer (HGSOC) remains a major clinical challenge. In particular among those patients with homologous recombination (HR)-proficient tumors (>50%), most eventually succumb to their disease due to high recurrence rates, acquired resistance, and cumulative toxicity. This report summarizes work from the 12th IMO Workshop in which we explored an alternative "extinction therapy" strategy for frontline treatment of HGSOC. Inspired by ecological principles, this multi-strike approach aims to eradicate tumors not through a singular "magic bullet" but through a series of therapies after standard frontline treatment when the tumor is still, and perhaps most, vulnerable. We present a framework leveraging mathematical modeling (MM) to develop personalized multi-strike protocols for HGSOC. Key contributions include: 1) An "IMOme" score using liquid biopsy data to assess patient-specific hematopoietic toxicity risk, guiding the timing and selection of subsequent therapies, 2) MM strategies to design effective lowdose combinations of targeted agents to achieve synthetic lethality while managing toxicity, and 3) A MM framework to analyze the interplay between chemotherapy, gut microbiome toxicity, and immunotherapy, demonstrating how mitigating microbiome damage could enhance immune response. Overall, the computational approaches presented herein aim to support the design of personalized, multi-strike regimens in the frontline setting that proactively target tumor extinction while managing toxicity, ultimately seeking to deliver cures for patients with HGSOC.

cancer biology↗

bioRxiv2023

Interruption of the Intratumor CD8:Treg Crosstalk Improves the Efficacy of PD-1 Immunotherapy

PD-1 blockade unleashes the potent antitumor activity of CD8 cells but can also promote immunosuppressive T regulatory (Treg) cells, which may worsen response to immunotherapy. Tumor Treg inhibition is a promising strategy to overcome therapeutic resistance; however, the mechanisms supporting tumor Tregs during PD-1 immunotherapy are largely unexplored. Here, we report that PD-1 blockade increases tumor Tregs in mouse models of immunogenic tumors, including melanoma, and metastatic melanoma patients. Unexpectedly, Treg accumulation was not caused by Treg-intrinsic inhibition of PD-1 signaling but instead depended on an indirect effect of activated CD8 cells. CD8 cells colocalized with Tregs within tumors and produced IL-2, especially after PD-1 immunotherapy. IL-2 upregulated the anti-apoptotic protein ICOS on tumor Tregs, causing their accumulation. ICOS signaling inhibition before PD-1 immunotherapy resulted in increased control of immunogenic melanoma. Thus, interrupting the intratumor CD8:Treg crosstalk is a novel strategy that may enhance the efficacy of immunotherapy in patients.

immunology↗

bioRxiv2021

Facilitation drives estrogen receptor positive (ER+) breast cancer growth and survival under drug pressure

The interplay of positive and negative interactions between drug sensitive and resistant cells influences the effectiveness of treatment in heterogeneous cancer cell populations. In a study of isogenic estrogen receptor positive (ER+) breast cancer cell lineages sensitive and resistant to ribociclib-induced CDK4/6 inhibition in mono- and co-culture, we find that sensitive cells grow and compete more effectively in the absence of treatment. During treatment with ribociclib, sensitive cells survive and proliferate better when grown together with resistant cells than when grown in monoculture, termed facilitation in ecology. Both liquid chromatography-tandem mass spectrometry (LC-MS/MS) assays and single cell RNA-sequencing (scRNAseq) indicate that resistant cell production of estradiol, a highly active estrogen metabolite, is the mechanism of facilitation. Higher estradiol production by resistant cells drives a shift in sensitive cell phenotype to a resistant cell state in coculture. Adding estradiol in monoculture provides sensitive cells with increased resistance to therapy, and cancels facilitation in coculture. Mathematical modeling quantifies the strength of competition and facilitation and predicts that blocking facilitation has the potential to control both resistant and sensitive cell populations and inhibit the emergence of a refractory population.

systems biology↗