Identification of nuclear export inhibitor-based combination therapies in preclinical models of triple-negative breast cancer

Positive Feedback Regulation between KLF5 and XPO1 Promotes Cell Cycle Progression of Basal like Breast Cancer

Basal-like breast cancer (BLBC), overlapping with the subgroup of estrogen receptor (ER), progesterone receptor (PR), and HER2 triple-negative breast cancer, has the worst prognosis and limited therapeutics. The XPO1 gene encodes nuclear export protein 1, a promising anticancer target which mediates nucleus-cytoplasm transport of nuclear export signal containing proteins such as tumor suppressor RB1 and some RNAs. Despite drugs targeting XPO1 are used in clinical, the regulation of XPO1 expression and functional mechanism is poorly understood, especially in BLBC. This study finds that KLF5 is a transcription factor of XPO1, which increases RB1 nuclear export and cell proliferation in BLBC cells. Furthermore, XPO1 interacts with the RNA-binding protein PTBP1 to export FOXO1 mRNA to cytoplasm and thus activates the FOXO1-KLF5 axis as a feedback. This work demonstrates that XPO1 inhibitor KPT-330 in combination with CDK4/6 inhibitor additively suppressed BLBC tumor growth in vivo. These results reveal a novel positive feedback regulation loop between KLF5 and XPO1 and provide a novel treatment strategy for BLBC.

A Multimodal Framework to Uncover Drug-Responsive Subpopulations in Triple-Negative Breast Cancer

Understanding how individual cancer cells adapt to drug treatment is a fundamental challenge limiting precision medicine cancer therapy strategies. While single-cell technologies have advanced our understanding of cellular heterogeneity, efforts to connect the behavior of individual cells to broader tumor drug responses and uncover global trends across diverse systems remain limited. There is a growing availability of single-cell and bulk omics data, but a lack of centralized tools and repositories makes it difficult to study drug response globally, especially at the level of single-cell adaptation. To address this, we present a multimodal framework that integrates bulk and single-cell treated and untreated transcriptomics data to identify drug responsive cell populations in triple-negative breast cancer (TNBC). Our framework leverages population-scale bulk transcriptomics data from TNBC samples to define seven main "identities", each representing unique combinations of biologically relevant genes. These identities are dynamic and trackable, allowing us to map them onto single cells and uncover global patterns of how cell populations respond to drug treatment. Unlike static classifications, this approach captures the evolving nature of cellular states, revealing that a select few identities dominate and drive population-level responses during treatment. Crucially, our ability to decode these trends through the inherent noise of single-cell data provides a clearer picture of how heterogeneous cell populations adapt to therapy. By identifying the dominant identities and their dynamics, we can better predict how entire tumors respond to treatment. This insight is essential for designing precise combination therapies tailored to the unique heterogeneity of patient tumors, addressing the single-cell variations that ultimately determine therapeutic outcomes.

Single-cell transcriptional atlas of human breast cancers and model systems

BACKGROUND

Breast cancer's complex transcriptional landscape requires an improved understanding of cellular diversity to identify effective treatments. The study of genetic variations among breast cancer subtypes at single-cell resolution has potential to deepen our insights into cancer progression.

METHODS

In this study, we amalgamate single-cell RNA sequencing data from patient tumours and matched lymph metastasis, reduction mammoplasties, breast cancer patient-derived xenografts (PDXs), PDX-derived organoids (PDXOs), and cell lines resulting in a diverse dataset of 117 samples with 506 719 total cells. These samples encompass hormone receptor positive (HR+), human epidermal growth factor receptor 2 positive (HER2+), and triple-negative breast cancer (TNBC) subtypes, including isogenic model pairs. Herein, we delineated similarities and distinctions across models and patient samples and explore therapeutic drug efficacy based on subtype proportions.

RESULTS

PDX models more closely resemble patient samples in terms of tumour heterogeneity and cell cycle characteristics when compared with TNBC cell lines. Acquired drug resistance was associated with an increase in basal-like cell proportions within TNBC PDX tumours as defined with SCSubtype and TNBCtype cell typing predictors. All patient samples contained a mixture of subtypes; compared to primary tumours HR+ lymph node metastases had lower proportions of HER2-Enriched cells. PDXOs exhibited differences in metabolic-related transcripts compared to PDX tumours. Correlative analyses of cytotoxic drugs on PDX cells identified therapeutic efficacy was based on subtype proportion.

CONCLUSIONS

We present a substantial multimodel dataset, a dynamic approach to cell-wise sample annotation, and a comprehensive interrogation of models within systems of human breast cancer. This analysis and reference will facilitate informed decision-making in preclinical research and therapeutic development through its elucidation of model limitations, subtype-specific insights and novel targetable pathways.

KEY POINTS

Patient-derived xenografts models more closely resemble patient samples in tumour heterogeneity and cell cycle characteristics when compared with cell lines. 3D organoid models exhibit differences in metabolic profiles compared to their in vivo counterparts. A valuable multimodel reference dataset that can be useful in elucidating model differences and novel targetable pathways.

Novel-and Not So Novel-Inhibitors of the Multifunctional CRM1 Protein

Chromosome Region Maintenance 1 (CRM1), also known as Exportin 1 (XPO1), is a protein that is critical for transport of proteins and RNA to the cytoplasm through the nuclear pore complex. CRM1 inhibition with small molecule inhibitors is currently being studied in many cancers, including leukemias, solid organ malignancies and brain tumors. We review the structure of CRM1, its role in nuclear export, the current availability of CRM1 inhibitors, and the role of CRM1 in a number of distinct cellular processes. A deeper understanding of how CRM1 functions in nuclear export as well as other cellular processes may allow for the development of additional novel CRM1 inhibitors.

The nuclear export protein exportin-1 in solid malignant tumours: From biology to clinical trials

BACKGROUND

Exportin-1 (XPO1), a crucial protein regulating nuclear-cytoplasmic transport, is frequently overexpressed in various cancers, driving tumor progression and drug resistance. This makes XPO1 an attractive therapeutic target. Over the past few decades, the number of available nuclear export-selective inhibitors has been increasing. Only KPT-330 (selinexor) has been successfully used for treating haematological malignancies, and KPT-8602 (eltanexor) has been used for treating haematologic tumours in clinical trials. However, the use of nuclear export-selective inhibitors for the inhibition of XPO1 expression has yet to be thoroughly investigated in clinical studies and therapeutic outcomes for solid tumours.

METHODS

We collected numerous literatures to explain the efficacy of XPO1 Inhibitors in preclinical and clinical studies of a wide range of solid tumours.

RESULTS

In this review, we focus on the nuclear export function of XPO1 and results from clinical trials of its inhibitors in solid malignant tumours. We summarized the mechanism of action and therapeutic potential of XPO1 inhibitors, as well as adverse effects and response biomarkers.

CONCLUSION

XPO1 inhibition has emerged as a promising therapeutic strategy in the fight against cancer, offering a novel approach to targeting tumorigenic processes and overcoming drug resistance. SINE compounds have demonstrated efficacy in a wide range of solid tumours, and ongoing research is focused on optimizing their use, identifying response biomarkers, and developing effective combination therapies.

KEY POINTS

Exportin-1 (XPO1) plays a critical role in mediating nucleocytoplasmic transport and cell cycle. XPO1 dysfunction promotes tumourigenesis and drug resistance within solid tumours. The therapeutic potential and ongoing researches on XPO1 inhibitors in the treatment of solid tumours. Additional researches are essential to address safety concerns and identify biomarkers for predicting patient response to XPO1 inhibitors.

Therapeutic targeting of nuclear export and import receptors in cancer and their potential in combination chemotherapy

Systemic modalities are crucial in the management of disseminated malignancies and liquid tumours. However, patient responses and tolerability to treatment are generally poor and those that enter remission often return with refractory disease. Combination therapies provide a methodology to overcome chemoresistance mechanisms and address dose-limiting toxicities. A deeper understanding of tumorigenic processes at the molecular level has brought a targeted therapy approach to the forefront of cancer research, and novel cancer biomarkers are being identified at a rapid rate, with some showing potential therapeutic benefits. The Karyopherin superfamily of proteins is soluble receptors that mediate nucleocytoplasmic shuttling of proteins and RNAs, and recently, nuclear transport receptors have been recognized as novel anticancer targets. Inhibitors against nuclear export have been approved for clinical use against certain cancer types, whereas inhibitors against nuclear import are in preclinical stages of investigation. Mechanistically, targeting nucleocytoplasmic shuttling has shown to abrogate oncogenic signalling and restore tumour suppressor functions through nuclear sequestration of relevant proteins and mRNAs. Hence, nuclear transport inhibitors display broad spectrum anticancer activity and harbour potential to engage in synergistic interactions with a wide array of cytotoxic agents and other targeted agents. This review is focussed on the most researched nuclear transport receptors in the context of cancer, XPO1 and KPNB1, and highlights how inhibitors targeting these receptors can enhance the therapeutic efficacy of standard of care therapies and novel targeted agents in a combination therapy approach. Furthermore, an updated review on the therapeutic targeting of lesser characterized karyopherin proteins is provided and resistance to clinically approved nuclear export inhibitors is discussed.

Advances in the Management of Early-Stage Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is a subtype of breast cancer with both inter- and intratumor heterogeneity, thought to result in a more aggressive course and worse outcomes. Neoadjuvant therapy (NAT) has become the preferred treatment modality of early-stage TNBC as it allows for the downstaging of tumors in the breast and axilla, monitoring early treatment response, and most importantly, provides important prognostic information that is essential to determining post-surgical therapies to improve outcomes. It focuses on combinations of systemic drugs to optimize pathologic complete response (pCR). Excellent response to NAT has allowed surgical de-escalation in ideal candidates. Further, treatment algorithms guide the systemic management of patients based on their pCR status following surgery. The expanding knowledge of molecular pathways, genomic sequencing, and the immunological profile of TNBC has led to the use of immune checkpoint inhibitors and targeted agents, including PARP inhibitors, further revolutionizing the therapeutic landscape of this clinical entity. However, subgroups most likely to benefit from these novel approaches in TNBC remain elusive and are being extensively studied. In this review, we describe current practices and promising therapeutic options on the horizon for TNBC, surgical advances, and future trends in molecular determinants of response to therapy in early-stage TNBC.

Stratification of Tamoxifen Synergistic Combinations for the Treatment of ER+ Breast Cancer

Breast cancer alone accounts for the majority of cancer deaths among women, with the most commonly diagnosed subtype being estrogen receptor positive (ER+). Survival has greatly improved for patients with ER+ breast cancer, due in part to the development of antiestrogen compounds, such as tamoxifen. While treatment of the primary disease is often successful, as many as 30% of patients will experience recurrence and metastasis, mainly due to developed endocrine therapy resistance. In this study, we discovered two tamoxifen combination therapies, with simeprevir and VX-680, that reduce the tumor burden in animal models of ER+ breast cancer more than either compound or tamoxifen alone. Additionally, these tamoxifen combinations reduced the expression of HER2, a hallmark of tamoxifen treatment, which can facilitate acquisition of a treatment-resistant phenotype. These combinations could provide clinical benefit by potentiating tamoxifen treatment in ER+ breast cancer.

Enhance Mitochondrial Damage by Nuclear Export Inhibition to Suppress Tumor Growth and Metastasis with Increased Antitumor Properties of Macrophages

Mitochondria-targeting damage has become a popular therapeutic option for tumor metastasis; however, its efficacy is limited by the adaptive rescue capacity of nuclei. There is an urgent need for a dual mitochondrial and nuclear targeting strategy that can also increase the antitumor capacity of macrophages. In this study, XPO1 inhibitor KPT-330 nanoparticles were combined with mitochondria-targeting lonidamine (TPP-LND) nanoparticles. The combination of nanoparticles with a 1:4 ratio of KPT and TL demonstrated the best synergistic effect in restraining the proliferation and metastasis of 4T1 breast cancer cells. Investigating the mechanisms both in vitro and in vivo, it was found that KPT nanoparticles not only directly impede tumor growth and metastasis by controlling the expression of associated proteins but also indirectly facilitate mitochondrial damage. The two nanoparticles synergistically decreased the expression of cytoprotective factors, such as Mcl-1 and Survivin, causing mitochondrial dysfunction and thus inducing apoptosis. Additionally, it downregulated metastasis-related proteins like HIF-1α, vascular endothelial growth factor (VEGF), and matrix metalloproteinase 2 (MMP-2) and reduced endothelial-to-mesenchymal transition. Significantly, their combination increased the ratio of M1 tumor-associated macrophages (TAMs)/M2 TAMs both in vitro and in vivo and increased the phagocytosis of tumor cells by macrophages, thus suppressing tumor growth and metastasis. In summary, this research revealed that nuclear export inhibition can synergistically enhance the prevention of mitochondrial damage to tumor cells, heightening the antitumor properties of TAMs, thereby providing a viable and safe therapeutic approach for the treatment of tumor metastasis.

Discovering Synergistic Compounds with BYL-719 in PI3K Overactivated Basal-like PDXs

Basal-like triple-negative breast cancer (TNBC) tumor cells are difficult to eliminate due to resistance mechanisms that promote survival. While this breast cancer subtype has low PIK3CA mutation rates when compared to estrogen receptor-positive (ER+) breast cancers, most basal-like TNBCs have an overactive PI3K pathway due to gene amplification or high gene expression. BYL-719 is a PIK3CA inhibitor that has been found to have low drug-drug interactions, which increases the likelihood that it could be useful for combinatorial therapy. Alpelisib (BYL-719) with fulvestrant was recently approved for treating ER+ breast cancer patients whose cancer had developed resistance to ER-targeting therapy. In these studies, a set of basal-like patient-derived xenograft (PDX) models was transcriptionally defined with bulk and single-cell RNA-sequencing and clinically actionable mutation profiles defined with Oncomine mutational profiling. This information was overlaid onto therapeutic drug screening results. BYL-719-based, synergistic two-drug combinations were identified with 20 different compounds, including everolimus, afatinib, and dronedarone, which were also found to be effective at minimizing tumor growth. These data support the use of these drug combinations towards cancers with activating PIK3CA mutations/gene amplifications or PTEN deficient/PI3K overactive pathways.

Transcriptomic changes underlying EGFR inhibitor resistance in human and mouse models of basal-like breast cancer

The goals of this study were to identify transcriptomic changes that arise in basal-like breast cancer cells during the development of resistance to epidermal growth factor receptor inhibitors (EGFRi) and to identify drugs that are cytotoxic once EGFRi resistance occurs. Human patient-derived xenografts (PDXs) were grown in immunodeficient mice and treated with a set of EGFRi; the EGFRi erlotinib was selected for more expansive in vivo studies. Single-cell RNA sequencing was performed on mammary tumors from the basal-like PDX WHIM2 that was treated with vehicle or erlotinib for 9 weeks. The PDX was then subjected to long-term erlotinib treatment in vivo. Through serial passaging, an erlotinib-resistant subline of WHIM2 was generated. Bulk RNA-sequencing was performed on parental and erlotinib-resistant tumors. In vitro high-throughput drug screening with > 500 clinically used compounds was performed on parental and erlotinib-resistant cells. Previously published bulk gene expression microarray data from MMTV-Wnt1 tumors were contrasted with the WHIM2 PDX data. Erlotinib effectively inhibited WHIM2 tumor growth for approximately 4 weeks. Compared to untreated cells, single-cell RNA sequencing revealed that a greater proportion of erlotinib-treated cells were in the G1 phase of the cell cycle. Comparison of WHIM2 and MMTV-Wnt1 gene expression data revealed a set of 38 overlapping genes that were differentially expressed in the erlotinib-resistant WHIM2 and MMTV-Wnt1 tumors. Comparison of all three data types revealed five genes that were upregulated across all erlotinib-resistant samples: IL19, KLK7, LCN2, SAA1, and SAA2. Of these five genes, LCN2 was most abundantly expressed in triple-negative breast cancers, and its knockdown restored erlotinib sensitivity in vitro. Despite transcriptomic differences, parental and erlotinib-resistant WHIM2 displayed similar responses to the majority of drugs assessed for cytotoxicity in vitro. This study identified transcriptomic changes arising in erlotinib-resistant basal-like breast cancer. These data could be used to identify a biomarker or develop a gene signature predictive of patient response to EGFRi. Future studies should explore the predictive capacity of these gene signatures as well as how LCN2 contributes to the development of EGFRi resistance.

Single-Molecule Sensor for High-Confidence Detection of miRNA

MicroRNAs (miRNAs) play a crucial role in regulating gene expression and have been linked to many diseases. Therefore, sensitive and accurate detection of disease-linked miRNAs is vital to the emerging revolution in early diagnosis of diseases. While the detection of miRNAs is a challenge due to their intrinsic properties such as small size, high sequence similarity among miRNAs and low abundance in biological fluids, the majority of miRNA-detection strategies involve either target/signal amplification or involve complex sensing designs. In this study, we have developed and tested a DNA-based fluorescence resonance energy transfer (FRET) sensor that enables ultrasensitive detection of a miRNA biomarker (miRNA-342-3p) expressed by triple-negative breast cancer (TNBC) cells. The sensor shows a relatively low FRET state in the absence of a target but it undergoes continuous FRET transitions between low- and high-FRET states in the presence of the target. The sensor is highly specific, has a detection limit down to low femtomolar (fM) without having to amplify the target, and has a large dynamic range (3 orders of magnitude) extending to 300 000 fM. Using this strategy, we demonstrated that the sensor allows detection of miRNA-342-3p in the miRNA-extracts from cancer cell lines and TNBC patient-derived xenografts. Given the simple-to-design hybridization-based detection, the sensing platform developed here can be used to detect a wide range of miRNAs enabling early diagnosis and screening of other genetic disorders.