RON signalling promotes therapeutic resistance in ESR1 mutant breast cancer

Identification of modules and key genes associated with breast cancer subtypes through network analysis

Breast cancer is the most common malignancy in women around the world. Intratumor and intertumoral heterogeneity persist in mammary tumors. Therefore, the identification of biomarkers is essential for the treatment of this malignancy. This study analyzed 28,143 genes expressed in 49 breast cancer cell lines using a Weighted Gene Co-expression Network Analysis to determine specific target proteins for Basal A, Basal B, Luminal A, Luminal B, and HER2 ampl breast cancer subtypes. Sixty-five modules were identified, of which five were characterized as having a high correlation with breast cancer subtypes. Genes overexpressed in the tumor were found to participate in the following mechanisms: regulation of the apoptotic process, transcriptional regulation, angiogenesis, signaling, and cellular survival. In particular, we identified the following genes, considered as hubs: IFIT3, an inhibitor of viral and cellular processes; ETS1, a transcription factor involved in cell death and tumorigenesis; ENSG00000259723 lncRNA, expressed in cancers; AL033519.3, a hypothetical gene; and TMEM86A, important for regulating keratinocyte membrane properties, considered as a key in Basal A, Basal B, Luminal A, Luminal B, and HER2 ampl breast cancer subtypes, respectively. The modules and genes identified in this work can be used to identify possible biomarkers or therapeutic targets in different breast cancer subtypes.

Proteomic profiling reveals that ESR1 mutations enhance cyclin-dependent kinase signaling

Three quarters of all breast cancers express the estrogen receptor (ER, ESR1 gene), which promotes tumor growth and constitutes a direct target for endocrine therapies. ESR1 mutations have been implicated in therapy resistance in metastatic breast cancer, in particular to aromatase inhibitors. ESR1 mutations promote constitutive ER activity and affect other signaling pathways, allowing cancer cells to proliferate by employing mechanisms within and without direct regulation by the ER. Although subjected to extensive genetic and transcriptomic analyses, understanding of protein alterations remains poorly investigated. Towards this, we employed an integrated mass spectrometry based proteomic approach to profile the protein and phosphoprotein differences in breast cancer cell lines expressing the frequent Y537N and Y537S ER mutations. Global proteome analysis revealed enrichment of mitotic and immune signaling pathways in ER mutant cells, while phosphoprotein analysis evidenced enriched activity of proliferation associated kinases, in particular CDKs and mTOR. Integration of protein expression and phosphorylation data revealed pathway-dependent discrepancies (motility vs proliferation) that were observed at varying degrees across mutant and wt ER cells. Additionally, protein expression and phosphorylation patterns, while under different regulation, still recapitulated the estrogen-independent phenotype of ER mutant cells. Our study is the first proteome-centric characterization of ESR1 mutant models, out of which we confirm estrogen independence of ER mutants and reveal the enrichment of immune signaling pathways at the proteomic level.

Small-molecule agents for cancer immunotherapy

Cancer immunotherapy, exemplified by the remarkable clinical benefits of the immune checkpoint blockade and chimeric antigen receptor T-cell therapy, is revolutionizing cancer therapy. They induce long-term tumor regression and overall survival benefit in many types of cancer. With the advances in our knowledge about the tumor immune microenvironment, remarkable progress has been made in the development of small-molecule drugs for immunotherapy. Small molecules targeting PRR-associated pathways, immune checkpoints, oncogenic signaling, metabolic pathways, cytokine/chemokine signaling, and immune-related kinases have been extensively investigated. Monotherapy of small-molecule immunotherapeutic drugs and their combinations with other antitumor modalities are under active clinical investigations to overcome immune tolerance and circumvent immune checkpoint inhibitor resistance. Here, we review the latest development of small-molecule agents for cancer immunotherapy by targeting defined pathways and highlighting their progress in recent clinical investigations.

Differences in metabolic transport and resistance mechanisms of Abemaciclib, Palbociclib, and Ribociclib

Cyclin-dependent kinase 4/6 inhibitors (CDK4/6i) play a crucial role in cancer treatment, particularly in breast cancer, and their mechanism of drug resistance is a topic of global interest in research. Hence, it is vital to comprehend the distinctions between various CDK4/6i, including their mechanisms of action and resistance mechanisms. This article aims to summarize the metabolic and transport variations as well as the differences in resistance among the three FDA-approved CDK4/6 inhibitors: Abemaciclib, Palbociclib, and Ribociclib. It also aims to discuss how these differences impact the effectiveness and safety of anticancer drugs. It was conducted in March 2023 to search PubMed, Embase, and Web of Science for literature related to this topic. Despite all being CDK4/6i, differences in their metabolism and transport were found, which are related to their chemical structure. Moreover, there are variations in preclinical pharmacology, pharmacokinetics, and clinical safety and efficacy of the different inhibitors. Genetic mutations, drug tolerance, and other factors may influence CDK4/6 resistance mechanisms. Currently, the resistance mechanisms differences of the three drugs remain largely unknown, and there are differences in the resistance mechanisms among them, necessitating further exploration and research.

FOXA1 Reprogramming Dictates Retinoid X Receptor Response in ESR1-Mutant Breast Cancer

Estrogen receptor alpha (ER/ESR1) mutations occur in 30% to 40% of endocrine resistant ER-positive (ER+) breast cancer. Forkhead box A1 (FOXA1) is a key pioneer factor mediating ER-chromatin interactions and endocrine response in ER+ breast cancer, but its role in ESR1-mutant breast cancer remains unclear. Our previous FOXA1 chromatin immunoprecipitation sequencing (ChIP-seq) identified a large portion of redistributed binding sites in T47D genome-edited Y537S and D538G ESR1-mutant cells. Here, we further integrated FOXA1 genomic binding profile with the isogenic ER cistrome, accessible genome, and transcriptome data of T47D cell model. FOXA1 redistribution was significantly associated with transcriptomic alterations caused by ESR1 mutations. Furthermore, in ESR1-mutant cells, FOXA1-binding sites less frequently overlapped with ER, and differential gene expression was less associated with the canonical FOXA1-ER axis. Motif analysis revealed a unique enrichment of retinoid X receptor (RXR) motifs in FOXA1-binding sites of ESR1-mutant cells. Consistently, ESR1-mutant cells were more sensitive to growth stimulation with the RXR agonist LG268. The mutant-specific response was dependent on two RXR isoforms, RXR-α and RXR-β, with a stronger dependency on the latter. In addition, T3, the agonist of thyroid receptor (TR) also showed a similar growth-promoting effect in ESR1-mutant cells. Importantly, RXR antagonist HX531 blocked growth of ESR1-mutant cells and a patient-derived xenograft (PDX)-derived organoid with an ESR1 D538G mutation. Collectively, our data support the evidence for a stronger RXR response associated with FOXA1 reprograming in ESR1-mutant cells, suggesting development of therapeutic strategies targeting RXR pathways in breast tumors with ESR1 mutation.

IMPLICATIONS

It provides comprehensive characterization of the role of FOXA1 in ESR1-mutant breast cancer and potential therapeutic strategy through blocking RXR activation.

Multiplexed kinase interactome profiling quantifies cellular network activity and plasticity

Dynamic changes in protein-protein interaction (PPI) networks underlie all physiological cellular functions and drive devastating human diseases. Profiling PPI networks can, therefore, provide critical insight into disease mechanisms and identify new drug targets. Kinases are regulatory nodes in many PPI networks; yet, facile methods to systematically study kinase interactome dynamics are lacking. We describe kinobead competition and correlation analysis (kiCCA), a quantitative mass spectrometry-based chemoproteomic method for rapid and highly multiplexed profiling of endogenous kinase interactomes. Using kiCCA, we identified 1,154 PPIs of 238 kinases across 18 diverse cancer lines, quantifying context-dependent kinase interactome changes linked to cancer type, plasticity, and signaling states, thereby assembling an extensive knowledgebase for cell signaling research. We discovered drug target candidates, including an endocytic adapter-associated kinase (AAK1) complex that promotes cancer cell epithelial-mesenchymal plasticity and drug resistance. Our data demonstrate the importance of kinase interactome dynamics for cellular signaling in health and disease.

An Introduction and Overview of RON Receptor Tyrosine Kinase Signaling

RON is a receptor tyrosine kinase (RTK) of the MET receptor family that is canonically involved in mediating growth and inflammatory signaling. RON is expressed at low levels in a variety of tissues, but its overexpression and activation have been associated with malignancies in multiple tissue types and worse patient outcomes. RON and its ligand HGFL demonstrate cross-talk with other growth receptors and, consequentially, positions RON at the intersection of numerous tumorigenic signaling programs. For this reason, RON is an attractive therapeutic target in cancer research. A better understanding of homeostatic and oncogenic RON activity serves to enhance clinical insights in treating RON-expressing cancers.

Assessment of durable chemoimmunotherapy response via circulating tumor DNA in advanced esophageal squamous cell carcinoma

Immune checkpoint inhibitor (ICI)‐based therapies have shown promising advances for the first‐line treatment of advanced or metastatic esophageal cancer (EC). However, few studies concerning the identification of patients who achieve durable response from ICIs have been previously reported. In the present study, pre‐ and on‐treatment plasma circulating tumor DNA (ctDNA) were analyzed in 10 patients with advanced esophageal squamous cell cancer (ESCC) receiving first‐line chemoimmunotherapy. Patients with decreased molecular tumor burden index (mTBI) >7% experienced longer progression‐free survival (PFS) and durable clinical benefit (DCB, PFS ≥ 6 months). In addition, five patients showed stable disease at first scan, all three patients with decreased mTBI > 7% achieved DCB, while two cases with decreased mTBI ≤ 7% experienced non‐DCB. Our results demonstrate that ctDNA monitor might help identify which ESCC patients respond to chemoimmunotherapy.

Identification of (S)-1-(2-(2,4-difluorophenyl)-4-oxothiazolidin-3-yl)-3-(4-((7-(3-(4-ethylpiperazin-1-yl)propoxy)-6-methoxyquinolin-4-yl)oxy)-3,5-difluorophenyl)urea as a potential anti-colorectal cancer agent

In our previous study, 1-(2-(2,6-difluorophenyl)-4-oxothiazolidin-3-yl)-3-(4-((7-(3-(4-ethylpiperazin-1-yl)propoxy)-6-methoxyquinolin-4-yl)oxy)-3,5-difluorophenyl)urea (1) was obtained as a potent tyrosine kinase inhibitor. Further structural optimization was performed in this investigation, and a series of novel quinoline derivates were designed, synthesized and evaluated for their biological activity. Among them, compound 8m possessed nanomolar c-Met and Ron inhibitory activity, with IC₅₀ values of 4.32 nM and 2.39 nM, respectively. Kinase profile study demonstrated that it could also inhibit ABL, PDGFRβ, AXL, RET, and FLT3 with submicromolar potency. It also exhibited moderate to excellent cytotoxic activity against different types of human cancer cell lines, especially against COLO 205 cells (IC₅₀ = 0.035 μM) which was remarkably superior to that of Cabozantinib (IC₅₀ = 6.6 μM) and Fruquintinib (IC₅₀ > 10.0 μM). Compared to ( ± )-8m, isomer (S)-8m and (R)-8m showed similar kinase inhibitory activity against c-Met/RON and in vitro anticancer activity against COLO 205 cells. Differently, compound (S)-8m showed an over 238-fold selectivity toward COLO 205 (IC₅₀ = 0.042 μM) cells to FHC cells (IC₅₀ > 10.0 μM), which indicated its low cytotoxicity against human normal tissue cells. Flow cytometry study demonstrated that compound (S)-8m could significantly induce apoptosis in COLO 205 cells in a dose-dependent manner. Cell cycle arrest assays showed that compound (S)-8m could not arrest the cell-cycle progression due to the massive dead cells.

An immune-humanized patient-derived xenograft model of estrogen-independent, hormone receptor positive metastatic breast cancer

BACKGROUND

Metastatic breast cancer (MBC) is incurable, with a 5-year survival rate of 28%. In the USA, more than 42,000 patients die from MBC every year. The most common type of breast cancer is estrogen receptor-positive (ER+), and more patients die from ER+ breast cancer than from any other subtype. ER+ tumors can be successfully treated with hormone therapy, but many tumors acquire endocrine resistance, at which point treatment options are limited. There is an urgent need for model systems that better represent human ER+ MBC in vivo, where tumors can metastasize. Patient-derived xenografts (PDX) made from MBC spontaneously metastasize, but the immunodeficient host is a caveat, given the known role of the immune system in tumor progression and response to therapy. Thus, we attempted to develop an immune-humanized PDX model of ER+ MBC.

METHODS

NSG-SGM3 mice were immune-humanized with CD34+ hematopoietic stem cells, followed by engraftment of human ER+ endocrine resistant MBC tumor fragments. Strategies for exogenous estrogen supplementation were compared, and immune-humanization in blood, bone marrow, spleen, and tumors was assessed by flow cytometry and tissue immunostaining. Characterization of the new model includes assessment of the human tumor microenvironment performed by immunostaining.

RESULTS

We describe the development of an immune-humanized PDX model of estrogen-independent endocrine resistant ER+ MBC. Importantly, our model harbors a naturally occurring ESR1 mutation, and immune-humanization recapitulates the lymphocyte-excluded and myeloid-rich tumor microenvironment of human ER+ breast tumors.

CONCLUSION

This model sets the stage for development of other clinically relevant models of human breast cancer and should allow future studies on mechanisms of endocrine resistance and tumor-immune interactions in an immune-humanized in vivo setting.

MicroRNA Expression Profiling of Lung Cancer with Differential Expression of the RON Receptor Tyrosine Kinase

Background

The Ron receptor tyrosine kinase (RON) can act as a protooncogene and may play a prominent role in the initiation and development of lung cancer. microRNAs (miRNA) are master regulators of gene expression through direct or indirect regulation, and impact all aspects of cell biology.

Methods

Nonsmall-cell lung cancer (NSCLC) samples and small-cell lung cancer (SCLC) were stratified based on RON expression to identify miRNA profiles associated with RON expression levels, differentially expressed miRNA regulated by RON were screened out, and their biological behavior was analyzed.

Results

miRNA expression was most significantly affected by cancer type, and we found 85 miRNAs that were significantly differentially expressed between NSCLC and SCLC. There were 46 miRNAs differentially expressed between high RON expressing NSCLC compared to low RON expressing NSCLC. Biological processes and pathways found to be significantly influenced by RON expression included epithelial-mesenchymal transition (EMT) and activation of the PI3K-Akt and MAPK signaling pathways.

Conclusions

These data may provide the basis for a novel strategy to characterize lung cancer by RON expression and microRNA genotyping.

Metastasis: complexity thwarts precision targeting

Metastasis is the spread of cancer cells to new areas of the body by way of the lymph system or bloodstream. Mechanism-based therapeutics have transformed its treatment. This issue of British Journal of Cancer will highlight recent advances in our understanding of metastasis, and how to block its spread.

Understanding breast cancer heterogeneity through non-genetic heterogeneity

Intricacy in treatment and diagnosis of breast cancer has been an obstacle due to genotype and phenotype heterogeneity. Understanding of non-genetic heterogeneity mechanisms along with considering role of genetic heterogeneity may fill the gaps in landscape painting of heterogeneity. The main factors contribute to non-genetic heterogeneity including: transcriptional pulsing/bursting or discontinuous transcriptions, stochastic partitioning of components at cell division and various signal transduction from tumor ecosystem. Throughout this review, we desired to provide a conceptual framework focused on non-genetic heterogeneity, which has been intended to offer insight into prediction, diagnosis and treatment of breast cancer.

Laboratory Models for Investigating Breast Cancer Therapy Resistance and Metastasis

While numerous therapies are highly efficacious in early-stage breast cancers and in particular subsets of breast cancers, therapeutic resistance and metastasis unfortunately arise in many patients. In many cases, tumors that are resistant to standard of care therapies, as well as tumors that have metastasized, are treatable but incurable with existing clinical strategies. Both therapy resistance and metastasis are multi-step processes during which tumor cells must overcome diverse environmental and selective hurdles. Mechanisms by which tumor cells achieve this are numerous and include acquisition of invasive and migratory capabilities, cell-intrinsic genetic and/or epigenetic adaptations, clonal selection, immune evasion, interactions with stromal cells, entering a state of dormancy or senescence, and maintaining self-renewal capacity. To overcome therapy resistance and metastasis in breast cancer, the ability to effectively model each of these mechanisms in the laboratory is essential. Herein we review historic and the current state-of-the-art laboratory model systems and experimental approaches used to investigate breast cancer metastasis and resistance to standard of care therapeutics. While each model system has inherent limitations, they have provided invaluable insights, many of which have translated into regimens undergoing clinical evaluation. We will discuss the limitations and advantages of a variety of model systems that have been used to investigate breast cancer metastasis and therapy resistance and outline potential strategies to improve experimental modeling to further our knowledge of these processes, which will be crucial for the continued development of effective breast cancer treatments.