Evaluation of Copanlisib in Combination with Eribulin in Triple-negative Breast Cancer Patient-derived Xenograft Models.

The PI3K pathway regulates essential cellular functions and promotes chemotherapy resistance. Activation of PI3K pathway signaling is commonly observed in triple-negative breast cancer (TNBC). However previous studies that combined PI3K pathway inhibitors with taxane regimens have yielded inconsistent results. We therefore set out to examine whether the combination of copanlisib, a clinical grade pan-PI3K inhibitor, and eribulin, an antimitotic chemotherapy approved for taxane-resistant metastatic breast cancer, improves the antitumor effect in TNBC. A panel of eight TNBC patient-derived xenograft (PDX) models was tested for tumor growth response to copanlisib and eribulin, alone or in combination. Treatment-induced signaling changes were examined by reverse phase protein array, immunohistochemistry (IHC) and 18F-fluorodeoxyglucose PET (18F-FDG PET). Compared with each drug alone, the combination of eribulin and copanlisib led to enhanced tumor growth inhibition, which was observed in both eribulin-sensitive and -resistant TNBC PDX models, regardless of PI3K pathway alterations or PTEN status. Copanlisib reduced PI3K signaling and enhanced eribulin-induced mitotic arrest. The combination enhanced induction of apoptosis compared with each drug alone. Interestingly, eribulin upregulated PI3K pathway signaling in PDX tumors, as demonstrated by increased tracer uptake by 18F-FDG PET scan and AKT phosphorylation by IHC. These changes were inhibited by the addition of copanlisib. These data support further clinical development for the combination of copanlisib and eribulin and led to a phase I/II trial of copanlisib and eribulin in patients with metastatic TNBC. SIGNIFICANCE: In this research, we demonstrated that the pan-PI3K inhibitor copanlisib enhanced the cytotoxicity of eribulin in a panel of TNBC PDX models. The improved tumor growth inhibition was irrespective of PI3K pathway alteration and was corroborated by the enhanced mitotic arrest and apoptotic induction observed in PDX tumors after combination therapy compared with each drug alone. These data provide the preclinical rationale for the clinical testing in TNBC.

O-GlcNAcylation of MITF regulates its activity and CDK4/6 inhibitor resistance in breast cancer.

Cyclin-dependent kinases 4 and 6 (CDK4/6) play a pivotal role in cell cycle and cancer development. Targeting CDK4/6 has demonstrated promising effects against breast cancer. However, resistance to CDK4/6 inhibitors (CDK4/6i), such as palbociclib, remains a substantial challenge in clinical settings. Using high-throughput combinatorial drug screening and genomic sequencing, we find that the microphthalmia-associated transcription factor (MITF) is activated via O-GlcNAcylation by O-GlcNAc transferase (OGT) in palbociclib-resistant breast cancer cells and tumors. Mechanistically, O-GlcNAcylation of MITF at Serine 49 enhances its interaction with importin α/ß, thus promoting its translocation to nuclei, where it suppresses palbociclib-induced senescence. Inhibition of MITF or its O-GlcNAcylation re-sensitizes resistant cells to palbociclib. Moreover, clinical studies confirm the activation of MITF in tumors from patients who are palbociclib-resistant or undergoing palbociclib treatment. Collectively, our studies shed light on the mechanism regulating palbociclib resistance and present clinical evidence for developing therapeutic approaches to treat CDK4/6i-resistant breast cancer patients.

A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis.

Patient-derived xenografts (PDX) model human intra- and intertumoral heterogeneity in the context of the intact tissue of immunocompromised mice. Histologic imaging via hematoxylin and eosin (H&E) staining is routinely performed on PDX samples, which could be harnessed for computational analysis. Prior studies of large clinical H&E image repositories have shown that deep learning analysis can identify intercellular and morphologic signals correlated with disease phenotype and therapeutic response. In this study, we developed an extensive, pan-cancer repository of >1,000 PDX and paired parental tumor H&E images. These images, curated from the PDX Development and Trial Centers Research Network Consortium, had a range of associated genomic and transcriptomic data, clinical metadata, pathologic assessments of cell composition, and, in several cases, detailed pathologic annotations of neoplastic, stromal, and necrotic regions. The amenability of these images to deep learning was highlighted through three applications: (i) development of a classifier for neoplastic, stromal, and necrotic regions; (ii) development of a predictor of xenograft-transplant lymphoproliferative disorder; and (iii) application of a published predictor of microsatellite instability. Together, this PDX Development and Trial Centers Research Network image repository provides a valuable resource for controlled digital pathology analysis, both for the evaluation of technical issues and for the development of computational image-based methods that make clinical predictions based on PDX treatment studies. Significance: A pan-cancer repository of >1,000 patient-derived xenograft hematoxylin and eosin-stained images will facilitate cancer biology investigations through histopathologic analysis and contributes important model system data that expand existing human histology repositories.

Transferrin receptor in primary and metastatic breast cancer: Evaluation of expression and experimental modulation to improve molecular targeting.

BACKGROUND: Conjugation of transferrin (Tf) to imaging or nanotherapeutic agents is a promising strategy to target breast cancer. Since the efficacy of these biomaterials often depends on the overexpression of the targeted receptor, we set out to survey expression of transferrin receptor (TfR) in primary and metastatic breast cancer samples, including metastases and relapse, and investigate its modulation in experimental models. METHODS: Gene expression was investigated by datamining in twelve publicly-available datasets. Dedicated Tissue microarrays (TMAs) were generated to evaluate matched primary and bone metastases as well as and pre and post chemotherapy tumors from the same patient. TMA were stained with the FDA-approved MRQ-48 antibody against TfR and graded by staining intensity (H-score). Patient-derived xenografts (PDX) and isogenic metastatic mouse models were used to study in vivo TfR expression and uptake of transferrin. RESULTS: TFRC gene and protein expression were high in breast cancer of all subtypes and stages, and in 60-85% of bone metastases. TfR was detectable after neoadjuvant chemotherapy, albeit with some variability. Fluorophore-conjugated transferrin iron chelator deferoxamine (DFO) enhanced TfR uptake in human breast cancer cells in vitro and proved transferrin localization at metastatic sites and correlation of tumor burden relative to untreated tumor mice. CONCLUSIONS: TfR is expressed in breast cancer, primary, metastatic, and after neoadjuvant chemotherapy. Variability in expression of TfR suggests that evaluation of the expression of TfR in individual patients could identify the best candidates for targeting. Further, systemic iron chelation with DFO may upregulate receptor expression and improve uptake of therapeutics or tracers that use transferrin as a homing ligand.

Combining the Tyrosine Kinase Inhibitor Cabozantinib and the mTORC1/2 Inhibitor Sapanisertib Blocks ERK Pathway Activity and Suppresses Tumor Growth in Renal Cell Carcinoma.

Current treatment approaches for renal cell carcinoma (RCC) face challenges in achieving durable tumor responses due to tumor heterogeneity and drug resistance. Combination therapies that leverage tumor molecular profiles could offer an avenue for enhancing treatment efficacy and addressing the limitations of current therapies. To identify effective strategies for treating RCC, we selected ten drugs guided by tumor biology to test in six RCC patient-derived xenograft (PDX) models. The multitargeted tyrosine kinase inhibitor (TKI) cabozantinib and mTORC1/2 inhibitor sapanisertib emerged as the most effective drugs, particularly when combined. The combination demonstrated favorable tolerability and inhibited tumor growth or induced tumor regression in all models, including two from patients who experienced treatment failure with FDA-approved TKI and immunotherapy combinations. In cabozantinib-treated samples, imaging analysis revealed a significant reduction in vascular density, and single-nucleus RNA sequencing (snRNA-seq) analysis indicated a decreased proportion of endothelial cells in the tumors. SnRNA-seq data further identified a tumor subpopulation enriched with cell-cycle activity that exhibited heightened sensitivity to the cabozantinib and sapanisertib combination. Conversely, activation of the epithelial-mesenchymal transition pathway, detected at the protein level, was associated with drug resistance in residual tumors following combination treatment. The combination effectively restrained ERK phosphorylation and reduced expression of ERK downstream transcription factors and their target genes implicated in cell-cycle control and apoptosis. This study highlights the potential of the cabozantinib plus sapanisertib combination as a promising treatment approach for patients with RCC, particularly those whose tumors progressed on immune checkpoint inhibitors and other TKIs. SIGNIFICANCE: The molecular-guided therapeutic strategy of combining cabozantinib and sapanisertib restrains ERK activity to effectively suppress growth of renal cell carcinomas, including those unresponsive to immune checkpoint inhibitors.