This perspective article discusses emerging advances at the interface of mechanistic modeling and data-driven machine learning, highlighting opportunities for AI to accelerate discovery, improve predictive modeling, and enhance clinical decision-making. We address critical limitations of current AI approaches and propose a perspective on a future where AI augments mechanistic rigor, clinical relevance, and human creativity under the umbrella of a redefined understanding of Mathematical Oncology.

Targeted therapies induce strong clinical responses but fail to eliminate advanced cancers, as a subset of tumor cells survives within residual disease and eventually develops resistance. While numerous cell-intrinsic and microenvironmental mechanisms have been implicated in this survival, their relative contributions remain poorly defined. Using spatial histological inferences from ALK + NSCLC models, we show that peristromal niches protect tumor cells from elimination, enabling in vivo persistence. This spatially restricted sheltering provides an ecological rescue mechanism that sustains residual populations, enabling their eventual evolutionary escape. Mechanistically, this protective effect reflects an integrated action of multiple juxtacrine and paracrine signals. This complexity limits the utility of targeting individual mechanisms of protection, favoring a shift towards exploiting orthogonal collateral sensitivities of residual disease. We find that adaptive HER2 upregulation, associated with both cell-intrinsic and stroma-mediated persistence, can be exploited by the antibody-drug conjugate T-DXd to dramatically enhance therapeutic responses and suppress tumor relapse.

Acute myeloid leukemia (AML) is a hematologic malignancy originating in the bone marrow and often progressing to extramedullary sites. Despite advances in molecularly targeted therapies and hematopoietic stem cell transplantation, clinical outcomes remain poor. Tyrosine kinase inhibitors (TKIs) provide benefit to a subset of AML patients harboring FLT3-ITD mutations; however, relapse and resistance remain common. These therapeutic failures are driven by both intrinsic properties of leukemic stem cells (LSCs)—a quiescent, self-renewing population—and extrinsic cues from the tumor microenvironment. We previously demonstrated that arteriolar endothelial cells (ECs) produce miR-126, which is transferred to LSCs, promoting quiescence, treatment resistance, and niche retention. During disease progression, TNF-α secreted by expanding blasts suppresses EC miR-126 production. Following TKI administration, blast reduction lowers TNF-ɑ levels, restoring EC miR-126 production, and this miR-126 expression enables LSCs to re-enter quiescence—thereby escaping therapy and facilitating relapse. To explore this dynamic, we developed an agent-based computational model of the AML bone marrow microenvironment, parameterized with in vitro and in vivo data. The model captures vascular niche remodeling and feedback between leukemic populations and endothelial signaling. Simulations reveal that LSC protection mediated by miR-126 can be disrupted by combining TKIs with miRisten, a miR-126 inhibitor. When administered on a defined schedule, this combination dismantles the protective niche and enhances LSC eradication. These findings underscore the therapeutic potential of targeting microenvironmental feedback to overcome resistance and prevent AML relapse.

Resistance of cancers to targeted therapies is traditionally framed as a tumor-intrinsic phenomenon, mediated by tumor cell-intrinsic or microenvironmental mechanisms. Here, we identify a tumor-extrinsic, systemic resistance mechanism resulting from hyperactivation of the hepatic cytochrome P450 enzyme, CYP3A4. This tumor-extrinsic resistance mechanism can function independently of, or in tandem with, tumor-intrinsic resistance. Focusing on experimental mouse models of targetable lung cancer, we find that xenobiotic-mediated induction of CYP3A4 results in accelerated drug metabolism and a drastic reduction in systemic and tumor-drug exposure in vivo . CYP3A4 activation can be triggered by chemically unrelated xenobiotics, leading to resistance to a wide range of targeted therapies, including ALK, EGFR, and KRASG12C inhibitors. Retrospective analysis of clinical cohorts suggests that variability in CYP3A4 activity might be a major contributor to variability in clinical outcomes. While higher CYP3A4 activity leads to sub-therapeutic tumor drug exposure and shorter progression-free survival, reduced drug metabolism is expected to result in supratherapeutic exposure and increased systemic toxicity. To address the consequences of abnormal CYP3A4 activity, we utilized mathematical modeling to demonstrate that drug concentrations can be restored through the optimization of dosing amounts and intervals. Further, we show that tumor sensitivity to targeted therapies can be rescued through pharmacological inhibition of CYP3A4. Our findings establish systemic metabolic variability as a bona fide resistance and toxicity driver, providing a translational framework for personalized dosing to maximize both safety and efficacy.

Darwinian evolution results from an interplay between stochastic diversification of heritable phenotypes, impacting the chance of survival and reproduction, and fitness-based selection. The ability of populations to evolve and adapt to environmental changes depends on rates of mutational diversification and the distribution of fitness effects of random mutations. In turn, the distribution of fitness effects of stochastic mutations can be expected to depend on the adaptive state of a population. To systematically study the impact of the interplay between the adaptive state of a population on the ability of asexual populations to adapt, we used a spatial agent-based model of a neoplastic population adapting to a selection pressure of continuous exposure to targeted therapy. We found favorable mutations were overrepresented at the extinction bottleneck but depleted at the adaptive peak. The model-based predictions were tested using an experimental cancer model of an evolution of resistance to a targeted therapy. Consistent with the model's prediction, we found that enhancement of the mutation rate was highly beneficial under therapy but moderately detrimental under the baseline conditions. Our results highlight the importance of considering population fitness in evaluating the fitness distribution of random mutations and support the potential therapeutic utility of restricting mutational variability.

Despite inducing strong and durable clinical responses, targeted therapies do not eliminate advanced cancers, as a subset of tumor cells survives within residual tumors, eventually developing resistance. The ability of tumor cells to avoid therapeutic elimination can be mediated both by cell-intrinsic and microenvironmental mechanisms. Whilst the specific molecular mediators of cell-intrinsic and microenvironmental resistance are well understood, their relative contribution to in vivo therapeutic responses remains poorly defined. Using spatial histological inferences from experimental models of ALK+ NSCLC, we found that peristromal niches protected tumor cells from therapeutic elimination in vivo, enabling in vivo persistence. Whereas the development of bona fide resistance is associated with the development of the development of cell-intrinsic resistance, relapse of tumor growth reflects a combined effect of both cell-intrinsic and microenvironmental mechanisms. Mechanistically, the protective effect of the peristromal niche is not reducible to a single mechanism, instead reflecting a combined effect of multiple juxtacrine and paracrine mediators. The lack of reducibility to a single molecular mediator presents an obvious challenge to the therapeutic paradigms of targeting individual resistance mechanisms. We found that this challenge could be mitigated by shifting the therapeutic focus to orthogonal collateral sensitivities of residual tumors. Exploiting adaptive upregulation of HER2, associated with both cell-intrinsic and microenvironmental persistence, using the antibody-drug conjugate T-DXd strongly enhanced the effect of targeted therapies and suppressed the development of resistance.

The emergence of resistance to therapy remains a significant obstacle to successful treatment in cancer that is driven by somatic evolution. Adaptive therapies represent a novel approach to manage the emergence of resistance, by leveraging the competition between different cell phenotypes to control tumor burden rather than aiming for complete eradication. However, the emergence of phenotypica l y plastic persister cells, exhibiting transient epigenetic resistance, poses a significant challenge to the efficacy of these approaches, and their specific impact is often overlooked in preclinical and mathematical models. This study investigates the role of persisters within adaptive therapy using a spatial agent-based model simulating sensitive, persistent, and genetically resistant cell populations. Our simulations reveal that persisters critically undermine treatment efficacy, significantly reducing progression-free survival (PFS) by approximately 40% (average 207 vs. 344 days in simulations) as they provide a reservoir for acquiring genetic resistance. Furthermore, tumors with higher levels of epigenetic resistance (more robust persisters) showed accelerated evolution towards resistance dominance phenotypes. The model showed treatment was most effective when sensitive cells initially dominated the tumor microenvironment. These findings highlight that persister dynamics are crucial determinants of adaptive therapy outcomes, suggesting that future strategies must account for epigenetic resistance, potentially informing approaches to assess tumor composition and sensitivity to better tailor treatments and improve patient outcomes. ### Competing Interest Statement The authors have declared no competing interest. National Cancer Institute, U54 CA274507

Background:The CD3/CD19 bispecific T cell engager (TCE) blinatumomab has shown efficacy in relapsed/refractory (R/R) B-cell acute lymphoblastic leukemia (B-ALL), but response rates are often limited by T cell exhaustion. Recent preclinical studies suggest that incorporating treatment-free intervals (TFIs) into dosing schedules may enhance therapeutic outcomes. Methods:To systematically evaluate alternative TFI strategies, we developed an agent-based model (ABM) of tumor-T cell interactions under various blinatumomab dosing regimens. The model was calibrated using published in vitro data and incorporated spatial, stochastic, and mechanistic rules governing T cell activation, cytotoxicity, proliferation, and exhaustion. Results:Our ABM recapitulates experimental observations showing that a 7-day TFI improved T cell function over continuous dosing during the initial 28-day treatment period. However, when simulations were extended to a full 42-day cycle to mimic clinical regimen, this advantage was lost. In contrast, shorter TFIs consistently outperformed both 7-day and continuous schedules, leading to superior tumor control at all timepoints. A translationally oriented Monday-through-Friday (MO_FR) regimen also achieved comparable benefits. Conclusions:Our results indicate that the empirically tested 7-day TFI schedule may not be optimal. TFI with shorter intervals as well as translationally relevant schedules such as MO_FR, may offer greater therapeutic benefit. This work demonstrates the value of ABM in preclinical immunotherapy design and supports model-guided refinement of TCE dosing strategies prior to clinical translation. Future work will focus on validating these predictions in more complex in vivo models and leveraging patient-derived data to guide personalized TCE treatment design.

Acute myeloid leukemia (AML) is a hematologic malignancy originating in the bone marrow, frequently progressing to extramedullary sites. Despite advances in molecularly targeted therapies and hematopoietic stem cell transplantation, clinical outcomes remain suboptimal. Tyrosine kinase inhibitors (TKIs) confer benefit in a subset of AML patients harboring FLT3-ITD mutations, yet relapse and resistance are common. These failures are driven by both intrinsic properties of leukemic stem cells (LSCs)—a quiescent, self-renewing population—and extrinsic cues from the tumor microenvironment. We previously demonstrated that arteriolar endothelial cells (ECs) produce miR-126, which is transferred to LSCs, promoting quiescence, treatment resistance, and niche retention. During disease progression, TNF-α secreted by expanding blasts suppresses EC miR-126 production, enabling LSCs and their progeny to proliferate. Following TKI administration, blast reduction lowers TNF-α levels, restoring EC miR-126 production and enabling LSCs to re-enter quiescence—thereby escaping therapy and facilitating relapse. To investigate this dynamic, we developed an agent-based computational model of the AML bone marrow microenvironment, parameterized with in vitro and in vivo data. The model captures vascular niche remodeling and the feedback between leukemic populations and endothelial signaling. Simulations reveal that LSC protection mediated by miR-126 can be overcome by combining TKIs with miRisten, a miR-126 inhibitor. When administered on a defined schedule, this combination disrupts the protective niche and enhances LSC eradication. These findings underscore the therapeutic potential of targeting microenvironmental feedback to overcome resistance and prevent AML relapse. ### Competing Interest Statement The authors have declared no competing interest.

Abstract Multiple myeloma (MM) is an osteolytic plasma cell malignancy that, despite being responsive to therapies such as proteasome inhibitors, frequently relapses. Understanding the mechanism and the niches where resistant disease evolves remains of major clinical importance. Cancer cell intrinsic mechanisms and bone ecosystem factors are known contributors to the evolution of resistant MM but the exact contribution of each is difficult to define with current in vitro and in vivo models. Using a novel bmathematical model that incorporates key cellular species of the bone ecosystem that control normal bone remodeling and, in MM, yields a protective environment we studied how, under therapy, the bone ecosystem contributes to the evolutionary dynamics of resistant MM under control and proteasome inhibitor treatment. Our results show that Environmentally-Mediated Drug Resistance (EMDR) might not be sufficient to explain resistant disease. But our results highlight the importance of EMDR in facilitating the emergence of resistance, and more importantly facilitating the survival of tolerant cells, allowing the tumor multiple routes for resistant disease. Our results also provide evidence that intervention with therapies targetting the bone ecosystem would significantly improve the ability of treatment to increase the time to progression for patients with multiple myeloma and, potentially, other diseases where EMDR plays a role. Citation Format: David Basanta, Ryan Bishop, Anna Miller, Conor C. Lynch, Matthew Froid, Ariosto S. Silva, Kenneth H. Shain. The bone microenvironment's impact on the heterogeneity of resistance to proteasome inhibitors in multiple myeloma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr B019.

Multiple myeloma (MM) is an osteolytic malignancy that is incurable due to the emergence of treatment resistant disease. Defining how, when and where myeloma cell intrinsic and extrinsic bone microenvironmental mechanisms cause relapse is challenging with current biological approaches. Here, we report a biology-driven spatiotemporal hybrid agent-based model of the MM-bone microenvironment. Results indicate MM intrinsic mechanisms drive the evolution of treatment resistant disease but that the protective effects of bone microenvironment mediated drug resistance (EMDR) significantly enhances the probability and heterogeneity of resistant clones arising under treatment. Further, the model predicts that targeting of EMDR deepens therapy response by eliminating sensitive clones proximal to stroma and bone, a finding supported by in vivo studies. Altogether, our model allows for the study of MM clonal evolution over time in the bone microenvironment and will be beneficial for optimizing treatment efficacy so as to significantly delay disease relapse.

Abstract Pharmacological inhibitors of oncogenic signaling, such as drugs that target ALK kinase (ALKi) in ALK+ lung cancers, can induce strong and durable clinical responses. However, targeted therapies are not curative in advanced cancers and even strong responders eventually develop resistance. While therapy resistance is typically attributed to cell-intrinsic (epi)mutational characteristics of tumor cells, it can also result from interactions of tumor cells with the tumor microenvironment (TME). In contrast to the detailed elucidation of the molecular mediators of therapy resistance, our knowledge of the evolutionary dynamics underlying the resistance emergence, including the impact of TME, remains poorly defined. A key open question in understanding the evolutionary dynamics of therapy resistance is whether relapse results from an expansion of pre-existing therapy-resistant subpopulations or from a bona fide gradual evolutionary process. To elucidate this question, we integrated experimental mouse studies with mathematical modeling, interrogating therapeutic responses of therapy-naïve experimental xenograft ALK+ tumors, spiked-in with differentially labeled resistant cells. We found that ALKi treatment induced a rapid expansion of resistant cells, which drastically reduced the magnitude and duration of remissions. Surprisingly, our in silico analyses pointed to the existence of a strong positive ecological interaction between therapy-resistant and therapy-sensitive competitors. Using a combination of spatial analyses, experimental studies, and mathematical modeling, we found that this interaction was mediated by peristromal niches that protected therapy-sensitive tumor cells. Specifically, by limiting tumor regression, the therapy- induced expansion of resistant cells limited the loss of protective peristromal niches, while the subsequent resumption of tumor growth created new peristromal niches capable of supporting the survival and proliferation of therapy-sensitive cells. While this niche-mediated interaction had only a marginal impact on the transition from remission to relapse, enhanced survival of therapy-sensitive cells potentiated their ability to adapt to ALKi, leading to a higher diversity of resistance phenotypes. In summary, our study has revealed a new type of indirect, niche-mediated ecological interaction between therapy-resistant and therapy-sensitive cells. The rapid expansion of rare pre-existent resistant cells and fast transition to relapse challenge a common assumption of the pre-existence of therapy resistance. Finally, our results highlight the essentiality of TME considerations in understanding the evolutionary dynamic underlying the development of therapy resistance. Citation Format: Mark Robertson-Tessi, Bina Desai, Tatiana Miti, Pragya Kumar, Sagnik Yarlagadda, Rishi Shah, Robert Vander Velde, Daria Miroshnychenko, David Basanta, Alexander Anderson, Andriy Marusyk. Therapy-protective peristromal niches mediate positive ecological interaction between therapy-sensitive and therapy-resistant cells, altering the evolutionary dynamics of acquired targeted therapy resistance in lung cancers [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor-body Interactions: The Roles of Micro- and Macroenvironment in Cancer; 2024 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(22_Suppl):Abstract nr B008.

The ability of tumors to survive therapy reflects both cell-intrinsic and microenvironmental mechanisms. Across many cancers, including triple-negative breast cancer (TNBC), a high stroma/tumor ratio correlates with poor survival. In many contexts, this correlation can be explained by the direct reduction of therapy sensitivity by stroma-produced paracrine factors. We sought to explore whether this direct effect contributes to the link between stroma and poor responses to chemotherapies. Our in vitro studies with panels of TNBC cell line models and stromal isolates failed to detect a direct modulation of chemoresistance. At the same time, consistent with prior studies, we observed treatment-independent enhancement of tumor cell proliferation by fibroblast-produced secreted factors. Using spatial statistics analyses, we found that proximity to stroma is often associated with enhanced tumor cell proliferation in vivo . Based on these observations, we hypothesized an indirect link between stroma and chemoresistance, where stroma-augmented proliferation potentiates the recovery of residual tumors between chemotherapy cycles. To evaluate the feasibility of this hypothesis, we developed a spatial agent-based model of stroma impact on proliferation/death dynamics. The model was quantitatively parameterized using inferences from histological analyses and experimental studies. We found that the observed enhancement of tumor cell proliferation within stroma-proximal niches can enable tumors to avoid elimination over multiple chemotherapy cycles. Therefore, our study supports the existence of a novel, indirect mechanism of environment-mediated chemoresistance that might contribute to the negative correlation between stromal content and poor therapy outcomes.

The response of tumors to anti-cancer therapies is defined not only by cell-intrinsic therapy sensitivities but also by local interactions with the tumor microenvironment. Fibroblasts that make tumor stroma have been shown to produce paracrine factors that can strongly reduce the sensitivity of tumor cells to many types of targeted therapies. Moreover, a high stroma/tumor ratio is generally associated with poor survival and reduced therapy responses. However, in contrast to advanced knowledge of the molecular mechanisms responsible for stroma-mediated resistance, its effect on the ability of tumors to escape therapeutic eradication remains poorly understood. To a large extent, this gap of knowledge reflects the challenge of accounting for the spatial aspects of microenvironmental resistance, especially over longer time frames. To address this problem, we integrated spatial inferences of proliferation-death dynamics from an experimental animal model of targeted therapy responses with spatial mathematical modeling. With this approach, we dissected the impact of tumor/stroma distribution, magnitude and distance of stromal effects. While all of the tested parameters affected the ability of tumor cells to resist elimination, spatial patterns of stroma distribution within tumor tissue had a particularly strong impact.

Targeted therapies directed against oncogenic signaling addictions, such as inhibitors of ALK in ALK+ NSCLC often induce strong and durable clinical responses. However, they are not curative in metastatic cancers, as some tumor cells persist through therapy, eventually developing resistance. Therapy sensitivity can reflect not only cell-intrinsic mechanisms but also inputs from stromal microenvironment. Yet, the contribution of tumor stroma to therapeutic responses in vivo remains poorly defined. To address this gap of knowledge, we assessed the contribution of stroma-mediated resistance to therapeutic responses to the frontline ALK inhibitor alectinib in xenograft models of ALK+ NSCLC. We found that stroma-proximal tumor cells are partially protected against cytostatic effects of alectinib. This effect is observed not only in remission, but also during relapse, indicating the strong contribution of stroma-mediated resistance to both persistence and resistance. This therapy-protective effect of the stromal niche reflects a combined action of multiple mechanisms, including growth factors and extracellular matrix components. Consequently, despite improving alectinib responses, suppression of any individual resistance mechanism was insufficient to fully overcome the protective effect of stroma. Focusing on shared collateral sensitivity of persisters offered a superior therapeutic benefit, especially when using an antibody-drug conjugate with bystander effect to limit therapeutic escape. These findings indicate that stroma-mediated resistance might be the major contributor to both residual and progressing disease and highlight the limitation of focusing on suppressing a single resistance mechanism at a time.

Abstract Despite strong initial responses, advanced cancers inevitably develop resistance to pharmacological inhibitors of mutant tyrosine kinases, including EML4-ALK fusion, which drives neoplastic transformation in a subset of lung cancers. Whereas the main thrust of research and development efforts to tackle the issue of resistance is directed toward identification and targeting specific molecular mechanisms, there is also a growing interest in developing strategies to suppress the ability of neoplastic populations to evolve resistance. The success of these strategies is contingent on the accuracy of the basic assumptions on how resistance arises. One of the key issues is the uncertainty over whether the acquired resistance reflects an expansion of pre-existing fully resistant populations or develops de novo from weakly resistant cells initially capable of only narrowly avoiding elimination. To elucidate this question, we decided to examine the impact of a minor subpopulation of resistant cells on the evolutionary dynamics of therapy responses to ALK inhibitors. To this end, we used an integration of experimental studies in mouse xenograft models of ALK+ lung cancers with agent-based in silico modeling approaches. We found that therapy induces a rapid expansion of pre-existing subpopulations, leading to a quick transition toward relapse. Surprisingly, resistant cells modulated the dynamics of sensitive cells, preserving the survival and expansion of their sensitive competitors, indicating a positive ecological interaction. Spatial histological analyses revealed that this positive interaction was mediated by the preservation and expansion of stromal niches that both boosted the competitive fitness of therapy-sensitive cells and promoted their adaptation, thus facilitating tumor heterogeneity. Whereas this effect inhibited the competitive expansion of resistant cells and tumor relapse, our analyses suggest that pre-existing resistance is incompatible with long remissions observed in a large subset of patients treated with advanced ALK inhibitors. In summary, our results challenge a common assumption of the pre-existence of full resistance prior to therapy and highlight the essentiality of considering ecological factors in understanding the evolutionary dynamics of therapy responses. Citation Format: Bina Desai, Mark Robertson-Tessi, Robert Vander Velde, Tatiana Miti, Sagnik Yarlagadda, Rishi Shah, Daria Miroshnychenko, David Basanta, Alexander Anderson, Andriy Marusyk. Positive ecological interaction between therapy-resistant and sensitive cells, mediated by stromal niche, slows the expansion of resistant subpopulations and promotes tumor heterogeneity [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr A016.

Abstract Resistance to targeted therapies, particularly those inhibiting oncogenic tyrosine kinases (TKIs), presents a significant challenge in the treatment of advanced non-small cell lung cancer (NSCLC). Despite initial robust clinical responses, tumors often relapse due to the emergence of resistant cell populations. The origins of this resistance—whether it is pre-existing in a subset of tumor cells or arises de novo during treatment—remains a critical question in understanding and combating therapeutic failure. To investigate this, we developed in silico mathematical models that integrate both pre-existing and de novo resistance mechanisms within a framework that explicitly integrates the stromal niche. Our study focused on the evolutionary dynamics of NSCLC in response to therapy, using a hybrid agent-based spatial modeling framework (HAL) to simulate tumor behavior under treatment. These models were designed to simulate the complex interactions between resistant and sensitive tumor cells, mediated by the stroma, and to predict the timing of relapse based on these interactions. Our findings suggest that stroma-mediated interactions play a crucial role in the evolutionary dynamics of therapy responses, influencing the fitness and survival of both resistant and sensitive cells. Specifically, our models predict that pre-existing resistance is unlikely to be compatible with the long remission periods observed in a substantial subset of patients treated with advanced anaplastic lymphoma kinase (ALK) inhibitors. This conclusion was supported by the observed relapse times and volumetric tumor growth data from subsequent animal models. Moreover, our analyses highlight the importance of ecological factors within the tumor microenvironment in shaping the response to therapy. The spatial models we developed reveal that the stroma can foster positive interactions between resistant and sensitive cells, thereby accelerating the emergence of resistance. These insights underscore the need to consider the stromal niche when developing new therapeutic strategies and when interpreting the dynamics of drug resistance. In conclusion, our study provides new insights into the role of stroma in mediating resistance to TKIs in NSCLC. By combining mathematical modeling with experimental data, we have elucidated how stroma-mediated interactions between tumor cells can influence the evolution of resistance, challenging the assumption that pre-existing resistance alone drives relapses in TKI-treated patients. Our findings emphasize the need for adaptive therapeutic approaches that anticipate and disrupt these microenvironmental interactions to improve patient outcomes. Citation Format: Rishi M. Shah, Sagnik Yarlagadda, Mark Robertson-Tessi, Bina Desai, Tatiana Miti, Daria Miroshnychenko, David Basanta, Andriy Marusyk, Alexander Anderson. A novel stroma-mediated positive interaction between resistant and sensitive cells in non-small cell lung cancer facilitates drug resistance [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor-body Interactions: The Roles of Micro- and Macroenvironment in Cancer; 2024 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(22_Suppl):Abstract nr A040.

Abstract Despite the ability to induce strong clinical responses, therapies that target mutational drivers of oncogenic signaling are not curative in advanced cancers, as a subset of cancer cells is capable of surviving therapy and evolving resistance. While therapy resistance is commonly viewed as a cell-intrinsic phenomenon, multiple factors produced by tumors can also confer strong therapy resistance. In contrast to the detailed elucidation of molecular mediators of cell-intrinsic and stroma-mediated (SM) resistance, the relative importance of cell-intrinsic and SM resistance to in vivo therapeutic responses remains poorly defined. To address this gap of knowledge, we used a well-characterized experimental model of ALK+ lung cancer H3122 cell line that exemplifies a duality observed across common models of targetable cancers. Under standard stroma-free in vitro cultures, H3122 cells can survive under therapeutically relevant concentrations of ALK inhibitors (ALKi), eventually acquiring cell-intrinsic therapy resistance. At the same time, co-culture with stromal fibroblasts drastically reduces the sensitivity of H3122 cells to ALKi, indicating the relevance of SM resistance. To understand the impact of SM resistance on in vivo responses, we sought to identify the mechanism(s) responsible for the therapy-protective effects of stromal fibroblasts, subsequently interrogating the impact of the disruption of this mechanism on in vivo therapeutic responses. Our in vitro studies with a large panel of primary stromal fibroblast isolates identified the HGF-cMET axis as the major mechanism responsible for ALKi desensitization. Surprisingly, xenograft validation studies demonstrated a weak effect of HGF-cMET modulation. Histological analyses of tumor tissues revealed that this relative weakness is attributable to a strong, spatially limited HGF-independent component of SM resistance. Mechanistic follow-up demonstrated that the HGF-independent component of SM resistance integrates the effect of multiple well-known juxtacrine and paracrine-acting mechanisms. Whereas the multifactorial nature of stroma-mediated resistance prevented a clear assessment of its relative contribution to in vivo therapy responses, our spatial analyses indicate that SM resistance dominates the ability of tumors to avoid therapeutic elimination. Surprisingly, we found that SM resistance was also a substantial contributor to tumor relapse, indicating that in vivo therapy resistance can integrate both cell-intrinsic and cell-extrinsic effects. This duality of therapy resistance and the multifactorial underpinning of both cell-intrinsic and stroma-mediated resistance present a challenge to therapeutic strategies focused on identifying and targeting specific resistance mechanisms. Our studies suggest that this limitation can be overcome by shifting the therapeutic focus towards shared orthogonal therapeutic sensitivities of tumor cells within residual disease. Citation Format: Bina Desai, Tatiana Miti, Sandhya Prabhakaran, Daria Miroshnychenko, Menkara Henry, Viktoriya Marusyk, Chandler Gatenbee, Marilyn Bui, Jacob Scott, Philipp M. Altrock, Eric Haura, Alexander R.A. Anderson, David Basanta, Andriy Marusyk. Spatially limited stroma-mediated resistance potentiates targeted therapy resistance through an integration of multiple juxtacrine and paracrine mechanisms [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor-body Interactions: The Roles of Micro- and Macroenvironment in Cancer; 2024 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(22_Suppl):Abstract nr C035.

Supplementary Table 1, Figures 1-3, Methods from Microenvironmental Independence Associated with Tumor Progression

Abstract The ability of tumors to survive therapy reflects both cell-intrinsic and microenvironmental mechanisms. Across many cancers, including triple-negative breast cancer (TNBC), a high stroma/tumor ratio correlates with poor survival. In many contexts, this correlation can be explained by the direct reduction of therapy sensitivity induced by stroma-produced paracrine factors. We sought to explore whether this direct effect contributes to the link between stroma and poor responses to chemotherapies. In vitro studies with panels of TNBC cell line models and stromal isolates failed to detect a direct modulation of chemoresistance. At the same time, consistent with prior studies, fibroblast-produced secreted factors stimulated treatment-independent enhancement of tumor cell proliferation. Spatial analyses indicated that proximity to stroma is often associated with enhanced tumor cell proliferation in vivo. These observations suggested an indirect link between stroma and chemoresistance, where stroma-augmented proliferation potentiates the recovery of residual tumors between chemotherapy cycles. To evaluate this hypothesis, a spatial agent–based model of stroma impact on proliferation/death dynamics was developed that was quantitatively parameterized using inferences from histologic analyses and experimental studies. The model demonstrated that the observed enhancement of tumor cell proliferation within stroma-proximal niches could enable tumors to avoid elimination over multiple chemotherapy cycles. Therefore, this study supports the existence of an indirect mechanism of environment-mediated chemoresistance that might contribute to the negative correlation between stromal content and poor therapy outcomes. Significance: Integration of experimental research with mathematical modeling reveals an indirect microenvironmental chemoresistance mechanism by which stromal cells stimulate breast cancer cell proliferation and highlights the importance of consideration of proliferation/death dynamics. See related commentary by Wall and Echeverria, p. 3667