Novel computational biology modeling system can accurately forecast response to neoadjuvant therapy in early breast cancer.

BACKGROUND: Generalizable population-based studies are unable to account for individual tumor heterogeneity that contributes to variability in a patient's response to physician-chosen therapy. Although molecular characterization of tumors has advanced precision medicine, in early-stage and locally advanced breast cancer patients, predicting a patient's response to neoadjuvant therapy (NAT) remains a gap in current clinical practice. Here, we perform a study in an independent cohort of early-stage and locally advanced breast cancer patients to forecast tumor response to NAT and assess the stability of a previously validated biophysical simulation platform. METHODS: A single-blinded study was performed using a retrospective database from a single institution (9/2014-12/2020). Patients included: ≥ 18 years with breast cancer who completed NAT, with pre-treatment dynamic contrast enhanced magnetic resonance imaging. Demographics, chemotherapy, baseline (pre-treatment) MRI and pathologic data were input into the TumorScope Predict (TS) biophysical simulation platform to generate predictions. Primary outcomes included predictions of pathological complete response (pCR) versus residual disease (RD) and final volume for each tumor. For validation, post-NAT predicted pCR and tumor volumes were compared to actual pathological assessment and MRI-assessed volumes. Predicted pCR was pre-defined as residual tumor volume ≤ 0.01 cm3 (≥ 99.9% reduction). RESULTS: The cohort consisted of eighty patients; 36 Caucasian and 40 African American. Most tumors were high-grade (54.4% grade 3) invasive ductal carcinomas (90.0%). Receptor subtypes included hormone receptor positive (HR+)/human epidermal growth factor receptor 2 positive (HER2+, 30%), HR+/HER2- (35%), HR-/HER2+ (12.5%) and triple negative breast cancer (TNBC, 22.5%). Simulated tumor volume was significantly correlated with post-treatment radiographic MRI calculated volumes (r = 0.53, p = 1.3 × 10-7, mean absolute error of 6.57%). TS prediction of pCR compared favorably to pathological assessment (pCR: TS n = 28; Path n = 27; RD: TS n = 52; Path n = 53), for an overall accuracy of 91.2% (95% CI: 82.8% - 96.4%; Clopper-Pearson interval). Five-year risk of recurrence demonstrated similar prognostic performance between TS predictions (Hazard ratio (HR): - 1.99; 95% CI [- 3.96, - 0.02]; p = 0.043) and clinically assessed pCR (HR: - 1.76; 95% CI [- 3.75, 0.23]; p = 0.054). CONCLUSION: We demonstrated TS ability to simulate and model tumor in vivo conditions in silico and forecast volume response to NAT across breast tumor subtypes.

Next generation immuno-oncology tumor profiling using a rapid, non-invasive, computational biophysics biomarker in early-stage breast cancer.

Background: Immuno-oncology (IO) therapies targeting the PD-1/PD-L1 axis, such as immune checkpoint inhibitor (ICI) antibodies, have emerged as promising treatments for early-stage breast cancer (ESBC). Despite immunotherapy's clinical significance, the number of benefiting patients remains small, and the therapy can prompt severe immune-related events. Current pathologic and transcriptomic predictions of IO response are limited in terms of accuracy and rely on single-site biopsies, which cannot fully account for tumor heterogeneity. In addition, transcriptomic analyses are costly and time-consuming. We therefore constructed a computational biomarker coupling biophysical simulations and artificial intelligence-based tissue segmentation of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRIs), enabling IO response prediction across the entire tumor. Methods: By analyzing both single-cell and whole-tissue RNA-seq data from non-IO-treated ESBC patients, we associated gene expression levels of the PD-1/PD-L1 axis with local tumor biology. PD-L1 expression was then linked to biophysical features derived from DCE-MRIs to generate spatially- and temporally-resolved atlases (virtual tumors) of tumor biology, as well as the TumorIO biomarker of IO response. We quantified TumorIO within patient virtual tumors (n = 63) using integrative modeling to train and develop a corresponding TumorIO Score. Results: We validated the TumorIO biomarker and TumorIO Score in a small, independent cohort of IO-treated patients (n = 17) and correctly predicted pathologic complete response (pCR) in 15/17 individuals (88.2% accuracy), comprising 10/12 in triple negative breast cancer (TNBC) and 5/5 in HR+/HER2- tumors. We applied the TumorIO Score in a virtual clinical trial (n = 292) simulating ICI administration in an IO-naïve cohort that underwent standard chemotherapy. Using this approach, we predicted pCR rates of 67.1% for TNBC and 17.9% for HR+/HER2- tumors with addition of IO therapy; comparing favorably to empiric pCR rates derived from published trials utilizing ICI in both cancer subtypes. Conclusion: The TumorIO biomarker and TumorIO Score represent a next generation approach using integrative biophysical analysis to assess cancer responsiveness to immunotherapy. This computational biomarker performs as well as PD-L1 transcript levels in identifying a patient's likelihood of pCR following anti-PD-1 IO therapy. The TumorIO biomarker allows for rapid IO profiling of tumors and may confer high clinical decision impact to further enable personalized oncologic care.

The myeloid cell type I IFN system promotes antitumor immunity over pro-tumoral inflammation in cancer T-cell therapy.

OBJECTIVES: Type I interferons are evolutionally conserved cytokines, with broad antimicrobial and immunoregulatory functions. Despite well-characterised role in spontaneous cancer immunosurveillance, the function of type I IFNs in cancer immunotherapy remains incompletely understood. METHODS: We utilised genetic mouse models to explore the role of the type I IFN system in CD8+ T-cell immunotherapy targeting the melanocytic lineage antigen gp100. RESULTS: The therapeutic efficacy of adoptively transferred T cells was found to depend on a functional type I IFN system in myeloid immune cells. Compromised type I IFN signalling in myeloid immune cells did not prevent expansion, tumor infiltration or effector function of melanoma-specific Pmel-1 CD8+ T cells. However, melanomas growing in globally (Ifnar1-/-) or conditionally (Ifnar1ΔLysM) type I IFN system-deficient mice displayed increased myeloid infiltration, hypoxia and melanoma cell dedifferentiation. Mechanistically, hypoxia was found to induce dedifferentiation and loss of the gp100 target antigen in melanoma cells and type I IFN could directly inhibit the inflammatory activation of myeloid cells. Unexpectedly, the immunotherapy induced significant reduction in tumor blood vessel density and whereas host type I IFN system was not required for the vasculosculpting, it promoted vessel permeability. CONCLUSION: Our results substantiate a complex and plastic phenotypic interconnection between melanoma and myeloid cells in the context of T-cell immunotherapy. Type I IFN signalling in myeloid cells was identified as a key regulator of the balance between antitumor immunity and disease-promoting inflammation, thus supporting the development of novel combinatorial immunotherapies targeting this immune cell compartment.

MAPK Signaling and Inflammation Link Melanoma Phenotype Switching to Induction of CD73 during Immunotherapy.

Evolution of tumor cell phenotypes promotes heterogeneity and therapy resistance. Here we found that induction of CD73, the enzyme that generates immunosuppressive adenosine, is linked to melanoma phenotype switching. Activating MAPK mutations and growth factors drove CD73 expression, which marked both nascent and full activation of a mesenchymal-like melanoma cell state program. Proinflammatory cytokines like TNFα cooperated with MAPK signaling through the c-Jun/AP-1 transcription factor complex to activate CD73 transcription by binding to an intronic enhancer. In a mouse model of T-cell immunotherapy, CD73 was induced in relapse melanomas, which acquired a mesenchymal-like phenotype. We also detected CD73 upregulation in melanoma patients progressing under adoptive T-cell transfer or immune checkpoint blockade, arguing for an adaptive resistance mechanism. Our work substantiates CD73 as a target to combine with current immunotherapies, but its dynamic regulation suggests limited value of CD73 pretreatment expression as a biomarker to stratify melanoma patients. Cancer Res; 77(17); 4697-709. ©2017 AACR.

Immune cell-poor melanomas benefit from PD-1 blockade after targeted type I IFN activation.

UNLABELLED: Infiltration of human melanomas with cytotoxic immune cells correlates with spontaneous type I IFN activation and a favorable prognosis. Therapeutic blockade of immune-inhibitory receptors in patients with preexisting lymphocytic infiltrates prolongs survival, but new complementary strategies are needed to activate cellular antitumor immunity in immune cell-poor melanomas. Here, we show that primary melanomas in Hgf-Cdk4(R24C) mice, which imitate human immune cell-poor melanomas with a poor outcome, escape IFN-induced immune surveillance and editing. Peritumoral injections of immunostimulatory RNA initiated a cytotoxic inflammatory response in the tumor microenvironment and significantly impaired tumor growth. This critically required the coordinated induction of type I IFN responses by dendritic, myeloid, natural killer, and T cells. Importantly, antibody-mediated blockade of the IFN-induced immune-inhibitory interaction between PD-L1 and PD-1 receptors further prolonged the survival. These results highlight important interconnections between type I IFNs and immune-inhibitory receptors in melanoma pathogenesis, which serve as targets for combination immunotherapies. SIGNIFICANCE: Using a genetically engineered mouse melanoma model, we demonstrate that targeted activation of the type I IFN system with immunostimulatory RNA in combination with blockade of immune-inhibitory receptors is a rational strategy to expose immune cell-poor tumors to cellular immune surveillance.

Ultraviolet-radiation-induced inflammation promotes angiotropism and metastasis in melanoma.

Intermittent intense ultraviolet (UV) exposure represents an important aetiological factor in the development of malignant melanoma. The ability of UV radiation to cause tumour-initiating DNA mutations in melanocytes is now firmly established, but how the microenvironmental effects of UV radiation influence melanoma pathogenesis is not fully understood. Here we report that repetitive UV exposure of primary cutaneous melanomas in a genetically engineered mouse model promotes metastatic progression, independent of its tumour-initiating effects. UV irradiation enhanced the expansion of tumour cells along abluminal blood vessel surfaces and increased the number of lung metastases. This effect depended on the recruitment and activation of neutrophils, initiated by the release of high mobility group box 1 (HMGB1) from UV-damaged epidermal keratinocytes and driven by Toll-like receptor 4 (TLR4). The UV-induced neutrophilic inflammatory response stimulated angiogenesis and promoted the ability of melanoma cells to migrate towards endothelial cells and use selective motility cues on their surfaces. Our results not only reveal how UV irradiation of epidermal keratinocytes is sensed by the innate immune system, but also show that the resulting inflammatory response catalyses reciprocal melanoma-endothelial cell interactions leading to perivascular invasion, a phenomenon originally described as angiotropism in human melanomas by histopathologists. Angiotropism represents a hitherto underappreciated mechanism of metastasis that also increases the likelihood of intravasation and haematogenous dissemination. Consistent with our findings, ulcerated primary human melanomas with abundant neutrophils and reactive angiogenesis frequently show angiotropism and a high risk for metastases. Our work indicates that targeting the inflammation-induced phenotypic plasticity of melanoma cells and their association with endothelial cells represent rational strategies to specifically interfere with metastatic progression.

The protective role of the transmembrane thioredoxin-related protein TMX in inflammatory liver injury.

AIMS: Accumulating evidence indicates that oxidative stress is associated with inflammation, and the cellular redox status can determine the sensitivity and the final outcome in response to inflammatory stimuli. To control the redox balance, mammalian cells contain a variety of oxidoreductases belonging to the thioredoxin superfamily. The large number of these enzymes suggests a complex mechanism of redox regulation in mammals, but the precise function of each family member awaits further investigations. RESULTS: We generated mice deficient in transmembrane thioredoxin-related protein (TMX), a transmembrane oxidoreductase in the endoplasmic reticulum (ER). When exposed to lipopolysaccharide (LPS) and d-(+)-galactosamine (GalN) to induce inflammatory liver injury, mutant mice were highly susceptible to the toxicants and developed severe liver damage. LPS-induced production of inflammatory mediators was equivalent in both wild-type and TMX(-/-) mice, whereas neutralization of the proinflammatory cytokine tumor necrosis factor-α suppressed the toxic effects of LPS/GalN in the mutant mice. Liver transcriptional profiles revealed enhanced activation of the p53-signaling pathway in the TMX(-/-) mice after LPS/GalN treatment. Furthermore, TMX deficiency also caused increased sensitivity to thioacetamide, which exerts its hepatotoxicity through the generation of reactive oxygen species. INNOVATION: The present study is the first to address the role of the oxidoreductase TMX in inflammatory liver injury. The phenotype of mice deficient in TMX suggests a functional link between redox regulation in the ER and susceptibility to oxidative tissue damage. CONCLUSION: We conclude that TMX plays a major role in host defense under the type of inflammatory conditions associated with oxidative stress.