Integrative Modeling Identifies Key Determinants of Inhibitor Sensitivity in Breast Cancer Cell Lines

A Cost-Effective and Robust Cell-Based Bioassay Method for Evaluating the Bioactivity of Trastuzumab-like Antibodies

Background/Objectives: Trastuzumab is an effective therapeutic intervention for treating HER2-positive breast cancers. The cost-effectiveness, global demand, and patent expiration of trastuzumab have led to the inflow of its biosimilars in the global market. With the rise of biosimilars in the biopharmaceutical market, it has become crucial to ensure that the biosimilar is at par with the original monoclonal antibody (mAb)in terms of efficacy, safety, and quality. Bioassay is one of the critical quality attributes (CQAs), hence developing a reliable and robust bioassay is essential for the evaluation of their biological activity and the harmonization of the quality of these biologics, supporting their safe and effective use in clinical practice. Methods: The present study aimed to develop a robust cell-based bioassay to assess the bioactivity of trastuzumab and its biosimilars for quality control testing. For this purpose, molecular characterization of different HER2-positive breast cancer cell lines of SKBR3, BT474, MDA-MD-453, MDA-MB-175, MCF-7, and MDA-MB-231 was performed to select a suitable cell line for the cell-based bioassay. Results: The SKBR3 cell line was found to express the HER2 receptors significantly higher in comparison to the other cell lines, and it was thereby selected for further bioassay optimization. The biological activity of trastuzumab was determined using the inhibition of proliferation (IOP) assay on the SKBR3, which was optimized based on the parameters of cell seeding density, drug dilution range, and incubation time, and it was further validated as per the compendial guidelines and found valid for the parameters of specificity, accuracy (% relative bias = 0.0067%), precision (repeatability: % GCV = 1.21%), linearity (R2 = 0.99), and range (50% to 200%). Additionally, the biological activity of different trastuzumab biosimilars was assessed using the validated IOP assay and compared to the HER2 binding assay performed by flow cytometry. The biological activity of different trastuzumab biosimilars was found to be comparable to the WHO primary reference standard of trastuzumab in terms of its relative potency using the IOP assay and binding assay by flow cytometry. Conclusions: Thus, an economic and robust cell-based bioassay method was successfully developed to assess the bioactivity of trastuzumab and its biosimilars.

eIF4A1 enhances LARP1-mediated translational repression during mTORC1 inhibition

Eukaryotic translation initiation factor (eIF)4A-a DEAD-box RNA-binding protein-plays an essential role in translation initiation. Recent reports have suggested helicase-dependent and helicase-independent functions for eIF4A, but the multifaceted roles of eIF4A have not been fully explored. Here we show that eIF4A1 enhances translational repression during the inhibition of mechanistic target of rapamycin complex 1 (mTORC1), an essential kinase complex controlling cell proliferation. RNA pulldown followed by sequencing revealed that eIF4A1 preferentially binds to mRNAs containing terminal oligopyrimidine (TOP) motifs, whose translation is rapidly repressed upon mTORC1 inhibition. This selective interaction depends on a La-related RNA-binding protein, LARP1. Ribosome profiling revealed that deletion of EIF4A1 attenuated the translational repression of TOP mRNAs upon mTORC1 inactivation. Moreover, eIF4A1 increases the interaction between TOP mRNAs and LARP1 and, thus, ensures stronger translational repression upon mTORC1 inhibition. Our data show the multimodality of eIF4A1 in modulating protein synthesis through an inhibitory binding partner and provide a unique example of the repressive role of a universal translational activator.

Nuclear VANGL2 Inhibits Lactogenic Differentiation

Planar cell polarity (PCP) proteins coordinate tissue morphogenesis by governing cell patterning and polarity. Asymmetrically localized on the plasma membrane of cells, transmembrane PCP proteins are trafficked by endocytosis, suggesting they may have intracellular functions that are dependent or independent of their extracellular role, but whether these functions extend to transcriptional control remains unknown. Here, we show the nuclear localization of transmembrane, PCP protein, VANGL2, in the HCC1569 breast cancer cell line, and in undifferentiated, but not differentiated, HC11 cells that serve as a model for mammary lactogenic differentiation. The loss of Vangl2 function results in upregulation of pathways related to STAT5 signaling. We identify DNA binding sites and a nuclear localization signal in VANGL2, and use CUT&RUN to demonstrate recruitment of VANGL2 to specific DNA binding motifs, including one in the Stat5a promoter. Knockdown (KD) of Vangl2 in HC11 cells and primary mammary organoids results in upregulation of Stat5a, Ccnd1 and Csn2, larger acini and organoids, and precocious differentiation; phenotypes are rescued by overexpression of Vangl2, but not Vangl2ΔNLS. Together, these results advance a paradigm whereby PCP proteins coordinate tissue morphogenesis by keeping transcriptional programs governing differentiation in check.

MYC is a clinically significant driver of mTOR inhibitor resistance in breast cancer

Targeting the PI3K-AKT-mTOR pathway is a promising therapeutic strategy for breast cancer treatment. However, low response rates and development of resistance to PI3K-AKT-mTOR inhibitors remain major clinical challenges. Here, we show that MYC activation drives resistance to mTOR inhibitors (mTORi) in breast cancer. Multiomic profiling of mouse invasive lobular carcinoma (ILC) tumors revealed recurrent Myc amplifications in tumors that acquired resistance to the mTORi AZD8055. MYC activation was associated with biological processes linked to mTORi response and counteracted mTORi-induced translation inhibition by promoting translation of ribosomal proteins. In vitro and in vivo induction of MYC conferred mTORi resistance in mouse and human breast cancer models. Conversely, AZD8055-resistant ILC cells depended on MYC, as demonstrated by the synergistic effects of mTORi and MYCi combination treatment. Notably, MYC status was significantly associated with poor response to everolimus therapy in metastatic breast cancer patients. Thus, MYC is a clinically relevant driver of mTORi resistance that may stratify breast cancer patients for mTOR-targeted therapies.

The PTX3/TLR4 autocrine loop as a novel therapeutic target in triple negative breast cancer

BACKGROUND

The pattern recognition receptor long pentraxin-3 (PTX3) plays conflicting roles in cancer by acting as an oncosuppressor or as a pro-tumor mediator depending on tumor context. Triple negative breast cancer (TNBC) represents the most aggressive histotype of breast cancer, characterized by the lack of efficacious therapeutic targets/approaches and poor prognosis. Thus, the characterization of new molecular pathways and/or alternative druggable targets is of great interest in TNBC.

METHODS

The expression of PTX3 in BC tumor samples and in BC cell lines has been analyzed using the Gene Expression-Based Outcome for Breast Cancer Online (GOBO), qPCR, Western blot and ELISA assay. The contribution of tumor and stromal cells to PTX3 production in TNBC was assessed by analyzing single cell RNA sequencing data and RNAscope performed on TNBC tumor samples. In order to investigate the effects of PTX3 in TNBC, different cell lines were engineered to knock-down (MDA-MB-231 and BT549 cells) or overexpress (MDA-MB-468 and E0771 cells) PTX3. Finally, using these engineered cells, in vitro (including gene expression profiling and gene set enrichment analyses) and in vivo (orthotopic tumor models in immune-compromised and immune competent mice) analyses were performed to assess the role and the molecular mechanism(s) exerted by PTX3 in TNBC.

RESULTS

In silico and experimental data indicate that PTX3 is mainly produced by tumor cells in TNBC and that its expression levels correlate with tumor stage. Accordingly, gene expression and in vitro results demonstrate that PTX3 overexpression confers a high aggressive/proliferative phenotype and fosters stem-like features in TNBC cells. Also, PTX3 expression induces a more tumorigenic potential when TNBC cells are grafted orthotopically in vivo. Conversely, PTX3 downregulation results in a less aggressive behavior of TNBC cells. Mechanistically, our data reveal that PTX3 drives the activation of the pro-tumorigenic Toll-like receptor 4 (TLR4) signaling pathway in TNBC, demonstrating for the first time that the PTX3/TLR4 autocrine stimulation loop contributes to TNBC aggressiveness and that TLR4 inhibition significantly impacts the growth of PTX3-producing TNBC cells.

CONCLUSION

Altogether, these data shed light on the role of tumor-produced PTX3 in TNBC and uncover the importance of the PTX3/TLR4 axis for therapeutic and prognostic exploitation in TNBC.

Molecular determinants of αVβ5 localization in flat clathrin lattices: Role of αVβ5 in cell adhesion and proliferation

The vitronectin receptor integrin αVβ5 can reside in two distinct adhesion structures: focal adhesions (FAs) and flat clathrin lattices (FCLs). Here we investigated the mechanism that regulates the subcellular distribution of β5 in keratinocytes and show that β5 has approximately 7- and 5-fold higher affinity for the clathrin adaptors ARH and Numb, respectively, than for talin; all proteins that bind to the membrane-proximal NPxY motif of the β5 cytoplasmic domain. Using mass spectrometry, we identified β5 interactors including the Rho GEFs p115Rho-GEF and GEF-H1, and the serine protein kinase MARK2; depletion of which diminishes the clustering of β5 in FCLs. Substitution of two serines (S759/762) in the β5 cytoplasmic domain with phospho-mimetic glutamates causes a shift in the localization of β5 from FAs into FCLs without affecting the interactions with MARK2, p115Rho-GEF or GEF-H1. Instead, we demonstrate that changes in the actomyosin-based cellular contractility by ectopic expression of activated Rho or disruption of microtubules regulates β5 localization. Finally, we present evidence that β5 in either FAs or FCLs functions to promote adhesion to vitronectin, cell spreading, and proliferation.

DNA Repair Genes as Drug Candidates for Early Breast Cancer Onset in Latin America: A Systematic Review

The prevalence of breast cancer in young women (YWBC) has increased alarmingly. Significant efforts are being made to elucidate the biological mechanisms concerning the development, prognosis, and pathological response in early-onset breast cancer (BC) patients. Dysfunctional DNA repair proteins are implied in BC predisposition, progression, and therapy response, underscoring the need for further analyses on DNA repair genes. Public databases of large patient datasets such as METABRIC, TCGA, COSMIC, and cancer cell lines allow the identification of variants in DNA repair genes and possible precision drug candidates. This study aimed at identifying variants and drug candidates that may benefit Latin American (LA) YWBC. We analyzed pathogenic variants in 90 genes involved in DNA repair in public BC datasets from METABRIC, TCGA, COSMIC, CCLE, and COSMIC Cell Lines Project. Results showed that reported DNA repair germline variants in the LA dataset are underrepresented in large databases, in contrast to other populations. Additionally, only six gene repair variants in women under 50 years old from the study population were reported in BC cell lines. Therefore, there is a need for new approaches to study DNA repair variants reported in young women from LA.

Personalized logical models to investigate cancer response to BRAF treatments in melanomas and colorectal cancers

The study of response to cancer treatments has benefited greatly from the contribution of different omics data but their interpretation is sometimes difficult. Some mathematical models based on prior biological knowledge of signaling pathways facilitate this interpretation but often require fitting of their parameters using perturbation data. We propose a more qualitative mechanistic approach, based on logical formalism and on the sole mapping and interpretation of omics data, and able to recover differences in sensitivity to gene inhibition without model training. This approach is showcased by the study of BRAF inhibition in patients with melanomas and colorectal cancers who experience significant differences in sensitivity despite similar omics profiles. We first gather information from literature and build a logical model summarizing the regulatory network of the mitogen-activated protein kinase (MAPK) pathway surrounding BRAF, with factors involved in the BRAF inhibition resistance mechanisms. The relevance of this model is verified by automatically assessing that it qualitatively reproduces response or resistance behaviors identified in the literature. Data from over 100 melanoma and colorectal cancer cell lines are then used to validate the model's ability to explain differences in sensitivity. This generic model is transformed into personalized cell line-specific logical models by integrating the omics information of the cell lines as constraints of the model. The use of mutations alone allows personalized models to correlate significantly with experimental sensitivities to BRAF inhibition, both from drug and CRISPR targeting, and even better with the joint use of mutations and RNA, supporting multi-omics mechanistic models. A comparison of these untrained models with learning approaches highlights similarities in interpretation and complementarity depending on the size of the datasets. This parsimonious pipeline, which can easily be extended to other biological questions, makes it possible to explore the mechanistic causes of the response to treatment, on an individualized basis.

Approximating multivariate posterior distribution functions from Monte Carlo samples for sequential Bayesian inference

An important feature of Bayesian statistics is the opportunity to do sequential inference: the posterior distribution obtained after seeing a dataset can be used as prior for a second inference. However, when Monte Carlo sampling methods are used for inference, we only have a set of samples from the posterior distribution. To do sequential inference, we then either have to evaluate the second posterior at only these locations and reweight the samples accordingly, or we can estimate a functional description of the posterior probability distribution from the samples and use that as prior for the second inference. Here, we investigated to what extent we can obtain an accurate joint posterior from two datasets if the inference is done sequentially rather than jointly, under the condition that each inference step is done using Monte Carlo sampling. To test this, we evaluated the accuracy of kernel density estimates, Gaussian mixtures, mixtures of factor analyzers, vine copulas and Gaussian processes in approximating posterior distributions, and then tested whether these approximations can be used in sequential inference. In low dimensionality, Gaussian processes are more accurate, whereas in higher dimensionality Gaussian mixtures, mixtures of factor analyzers or vine copulas perform better. In our test cases of sequential inference, using posterior approximations gives more accurate results than direct sample reweighting, but joint inference is still preferable over sequential inference whenever possible. Since the performance is case-specific, we provide an R package mvdens with a unified interface for the density approximation methods.

Comparative Network Reconstruction using mixed integer programming

Motivation

Signal-transduction networks are often aberrated in cancer cells, and new anti-cancer drugs that specifically target oncogenes involved in signaling show great clinical promise. However, the effectiveness of such targeted treatments is often hampered by innate or acquired resistance due to feedbacks, crosstalks or network adaptations in response to drug treatment. A quantitative understanding of these signaling networks and how they differ between cells with different oncogenic mutations or between sensitive and resistant cells can help in addressing this problem.

Results

Here, we present Comparative Network Reconstruction (CNR), a computational method to reconstruct signaling networks based on possibly incomplete perturbation data, and to identify which edges differ quantitatively between two or more signaling networks. Prior knowledge about network topology is not required but can straightforwardly be incorporated. We extensively tested our approach using simulated data and applied it to perturbation data from a BRAF mutant, PTPN11 KO cell line that developed resistance to BRAF inhibition. Comparing the reconstructed networks of sensitive and resistant cells suggests that the resistance mechanism involves re-establishing wild-type MAPK signaling, possibly through an alternative RAF-isoform.

Availability and implementation

CNR is available as a python module at https://github.com/NKI-CCB/cnr. Additionally, code to reproduce all figures is available at https://github.com/NKI-CCB/CNR-analyses.

Supplementary information

Supplementary data are available at Bioinformatics online.

Absence of integrin α3β1 promotes the progression of HER2-driven breast cancer in vivo

BACKGROUND

HER2-driven breast cancer is correlated with poor prognosis, especially during its later stages. Numerous studies have shown the importance of the integrin α3β1 during the initiation and progression of breast cancer; however, its role in this disease is complex and often opposite during different stages and in different types of tumors. In this study, we aim to elucidate the role of integrin α3β1 in a genetically engineered mouse model of HER2-driven mammary tumorigenesis.

METHODS

To investigate the role of α3β1 in HER2-driven tumorigenesis in vivo, we generated a HER2-driven MMTV-cNeu mouse model of mammary tumorigenesis with targeted deletion of Itga3 (Itga3 KO mice). We have further used several established triple-negative and HER2-overexpressing human mammary carcinoma cell lines and generated ITGA3-knockout cells to investigate the role of α3β1 in vitro. Invasion of cells was assessed using Matrigel- and Matrigel/collagen I-coated Transwell assays under static or interstitial fluid flow conditions. The role of α3β1 in initial adhesion to laminin and collagen was assessed using adhesion assays and immunofluorescence.

RESULTS

Tumor onset in mice was independent of the presence of α3β1. In contrast, the depletion of α3β1 reduced the survival of mice and increased tumor growth and vascularization. Furthermore, Itga3 KO mice were significantly more likely to develop lung metastases and had an increased metastatic burden compared to WT mice. In vitro, the deletion of ITGA3 caused a significant increase in the cellular invasion of HER2-overexpressing SKBR3, AU565, and BT474 cells, but not of triple-negative MDA-MB-231. This invasion suppressing function of α3β1 in HER2-driven cells depended on the composition of the extracellular matrix and the interstitial fluid flow.

CONCLUSION

Downregulation of α3β1 in a HER2-driven mouse model and in HER2-overexpressing human mammary carcinoma cells promotes progression and invasiveness of tumors. The invasion-suppressive role of α3β1 was not observed in triple-negative mammary carcinoma cells, illustrating the tumor type-specific and complex function of α3β1 in breast cancer.