Lapatinib in breast cancer: clinical experiences and future perspectives

Efficacy and Safety of Anti-HER2 Targeted Therapy for Metastatic HR-Positive and HER2-Positive Breast Cancer: A Bayesian Network Meta-Analysis

Despite the development of HER2-targeted drugs, achieving favorable outcomes for patients with HR+/HER2+MBC remains challenging. This study utilized Bayesian Network Meta-analysis to compare the efficacy and safety of anti-HER2 combination regimens. The primary analysis focused on progression-free survival (PFS), while secondary analyses included objective response rate, overall survival (OS) and the incidence rate of grade 3/4 adverse events (AEs). A comprehensive search across seven databases identified 25 randomized controlled trials for inclusion in this meta-analysis. For patients eligible for endocrinotherapy, our findings revealed that dual-target combined endocrine therapy, such as Her2-mAb+Her2-mAb+Endo (HR = 0.38; 95%CrI: 0.16-0.88) and Her2-mAb+Her2-tki+Endo (HR = 0.45; 95%CrI: 0.23-0.89), significantly improved PFS compared to endocrine therapy alone. According to the surface under the cumulative ranking curves (SUCRAs), Her2-mAb+Her2-mAb+Endo and Her2-mAb+Her2-tki+Endo ranked highest in terms of PFS and OS, respectively. For patients unsuitable for endocrine therapy, anti-HER2 dual-target combined chemotherapy, such as Her2-mAb+Her2-mAb+Chem (HR = 0.76; 95%CrI: 0.6-0.96) and Her2-mAb+Her2-tki+Chem (HR = 0.48; 95%CrI: 0.29-0.81), demonstrated significant improvements in PFS compared to Her2-mAb+Chem. The results were the same when compared with Her2-tki+Chem. According to the SUCRAs, Her2-mAb+Her2-tki+Chem and Her2-mAb+Her2-mAb+Chem ranked highest for PFS and OS, respectively. Subgroup analyses consistently supported these overall findings, indicating that dual-target therapy was the optimal approach irrespective of treatment line.

Predicting Lapatinib Dose Regimen Using Machine Learning and Deep Learning Techniques Based on a Real-World Study

Lapatinib is used for the treatment of metastatic HER2(+) breast cancer. We aim to establish a prediction model for lapatinib dose using machine learning and deep learning techniques based on a real-world study. There were 149 breast cancer patients enrolled from July 2016 to June 2017 at Fudan University Shanghai Cancer Center. The sequential forward selection algorithm based on random forest was applied for variable selection. Twelve machine learning and deep learning algorithms were compared in terms of their predictive abilities (logistic regression, SVM, random forest, Adaboost, XGBoost, GBDT, LightGBM, CatBoost, TabNet, ANN, Super TML, and Wide&Deep). As a result, TabNet was chosen to construct the prediction model with the best performance (accuracy = 0.82 and AUC = 0.83). Afterward, four variables that strongly correlated with lapatinib dose were ranked via importance score as follows: treatment protocols, weight, number of chemotherapy treatments, and number of metastases. Finally, the confusion matrix was used to validate the model for a dose regimen of 1,250 mg lapatinib (precision = 81% and recall = 95%), and for a dose regimen of 1,000 mg lapatinib (precision = 87% and recall = 64%). To conclude, we established a deep learning model to predict lapatinib dose based on important influencing variables selected from real-world evidence, to achieve an optimal individualized dose regimen with good predictive performance.

Deciphering the signaling network of breast cancer improves drug sensitivity prediction

One goal of precision medicine is to tailor effective treatments to patients' specific molecular markers of disease. Here, we used mass cytometry to characterize the single-cell signaling landscapes of 62 breast cancer cell lines and five lines from healthy tissue. We quantified 34 markers in each cell line upon stimulation by the growth factor EGF in the presence or absence of five kinase inhibitors. These data-on more than 80 million single cells from 4,000 conditions-were used to fit mechanistic signaling network models that provide insight into how cancer cells process information. Our dynamic single-cell-based models accurately predicted drug sensitivity and identified genomic features associated with drug sensitivity, including a missense mutation in DDIT3 predictive of PI3K-inhibition sensitivity. We observed similar trends in genotype-drug sensitivity associations in patient-derived xenograft mouse models. This work provides proof of principle that patient-specific single-cell measurements and modeling could inform effective precision medicine strategies.

Multi-Omic Data Interpretation to Repurpose Subtype Specific Drug Candidates for Breast Cancer

Triple-negative breast cancer (TNBC), which is largely synonymous with the basal-like molecular subtype, is the 5th leading cause of cancer deaths for women in the United States. The overall prognosis for TNBC patients remains poor given that few treatment options exist; including targeted therapies (not FDA approved), and multi-agent chemotherapy as standard-of-care treatment. TNBC like other complex diseases is governed by the perturbations of the complex interaction networks thereby elucidating the underlying molecular mechanisms of this disease in the context of network principles, which have the potential to identify targets for drug development. Here, we present an integrated "omics" approach based on the use of transcriptome and interactome data to identify dynamic/active protein-protein interaction networks (PPINs) in TNBC patients. We have identified three highly connected modules, EED, DHX9, and AURKA, which are extremely activated in TNBC tumors compared to both normal tissues and other breast cancer subtypes. Based on the functional analyses, we propose that these modules are potential drivers of proliferation and, as such, should be considered candidate molecular targets for drug development or drug repositioning in TNBC. Consistent with this argument, we repurposed steroids, anti-inflammatory agents, anti-infective agents, cardiovascular agents for patients with basal-like breast cancer. Finally, we have performed essential metabolite analysis on personalized genome-scale metabolic models and found that metabolites such as sphingosine-1-phosphate and cholesterol-sulfate have utmost importance in TNBC tumor growth.

Molecular effects of lapatinib in patients with HER2 positive ductal carcinoma in situ

Introduction

Human epidermal growth factor receptor 2 (HER2) amplification is frequent in ductal carcinoma in situ (DCIS) of the breast and is associated with poorly differentiated tumors and adverse prognosis features. This study aimed to determine the molecular effects of the HER2 inhibitor lapatinib in patients with HER2 positive DCIS.

Methods

Patients with HER2 positive DCIS received 1,500 mg daily of lapatinib for four consecutive weeks prior to surgical resection. Magnetic resonance imaging (MRI) was used to determine changes in tumor volume. The molecular effects of lapatinib on HER2 signaling (PI3K/AKT and RAS/MAPK pathways), cell proliferation (Ki67 and p27) and apoptosis (TUNEL) were determined in pre and post-lapatinib treatment samples.

Results

A total of 20 patients were included. Lapatinib was well tolerated with only minor and transient side effects. The agent effectively modulated HER2 signaling decreasing significantly pHER2 and pERK1 expression, together with a decrease in tumor size evaluated by MRI. There was no evidence of changes in Ki67.

Conclusions

Four weeks of neoadjuvant lapatinib in patients with HER2-positive DCIS resulted in inhibition of HER2 and RAS/MAPK signaling pathway.

Trial registration

2008-004492-21 (Registered June 25th 2008).

Electronic supplementary material

The online version of this article (doi:10.1186/bcr3695) contains supplementary material, which is available to authorized users.

Clinical pharmacokinetics of tyrosine kinase inhibitors: implications for therapeutic drug monitoring

The treatment of many malignancies has been improved in recent years by the introduction of molecular targeted therapies. These drugs interact preferentially with specific targets that are mutated and/or overexpressed in malignant cells. A group of such targets are the tyrosine kinases, against which a number of inhibitors (tyrosine kinase inhibitors, TKIs) have been developed. Imatinib, a TKI with targets that include the breakpoint cluster region-Abelson (bcr-abl) fusion protein kinase and mast/stem cell growth factor receptor kinase (c-Kit), was the first clinically successful drug of this type and revolutionized the treatment and prognosis of chronic myeloid leukemia and gastrointestinal stromal tumors. This success paved the way for the development of other TKIs for the treatment of a range of hematological malignancies and solid tumors. To date, 14 TKIs have been approved for clinical use and many more are under investigation. All these agents are given orally and are substrates of a range of drug transporters and metabolizing enzymes. In addition, some TKIs are capable of inhibiting their own transporters and metabolizing enzymes, making their disposition and metabolism at steady-state unpredictable. A given dose can therefore give rise to markedly different plasma concentrations in different patients, favoring the selection of resistant clones in the case of subtherapeutic exposure, and increasing the risk of toxicity if dosage is excessive. The aim of this review was to summarize current knowledge of the clinical pharmacokinetics and known adverse effects of the TKIs that are available for clinical use and to provide practical guidance on the implications of these data in patient management, in particular with respect to therapeutic drug monitoring.

Implications of functional proteomics in breast cancer

Breast cancer is one of the major public health problems of the Western world. Recent advances in genomics and gene expression-profiling approaches have enriched our understanding of this heterogeneous disease. However, progress in functional proteomics in breast cancer research has been relatively slow. Allied with genomics, the functional proteomics approach will be important in improving diagnosis through better classification of breast cancer and in predicting prognosis and response to different therapies, including chemotherapy, hormonal therapy, and targeted therapy. In this review, we will present functional proteomic approaches with a focus on the recent clinical implications of utilizing the reverse-phase protein array platform in breast cancer research.

Iatrogenic neurology

Iatrogenic disease is one of the most frequent causes of hospital admissions and constitutes a growing public health problem. The most common type of iatrogenic neurologic disease is pharmacologic, and the central and peripheral nervous systems are particularly vulnerable. Despite this, iatrogenic disease is generally overlooked as a differential diagnosis among neurologic patients. The clinical picture of pharmacologically mediated iatrogenic neurologic disease can range from mild to fatal. Common and uncommon forms of drug toxicity are comprehensively addressed in this chapter. While the majority of neurologic adverse effects are listed and referenced in the tables, the most relevant issues are further discussed in the text.

Targeting EGF receptor variant III: tumor-specific peptide vaccination for malignant gliomas

Glioblastoma multiforme (GBM) is the most common and deadly of the human brain cancers. The EGF receptor is often amplified in GBM and provides a potential therapeutic target. However, targeting the normal receptor is complicated by its nearly ubiquitous and high level of expression in certain tissues. A naturally occurring deletion mutant of the EGF receptor, EGFRvIII, is a constitutively active variant originally identified in a high percentage of brain cancer cases, and more importantly is rarely found in normal tissue. A peptide vaccine, rindopepimut (CDX-110, Celldex Therapeutics), is directed against the novel exon 1-8 junction produced by the EGFRvIII deletion, and it has shown high efficacy in preclinical models. Recent Phase II clinical trials in patients with newly diagnosed GBM have shown EGFRvIII-specific immune responses and significantly increased time to progression and overall survival in those receiving vaccine therapy, as compared with published results for standard of care. Rindopepimut therefore represents a very promising therapy for patients with GBM.

Cardio-oncology in targeting the HER receptor family: the puzzle of different cardiotoxicities of HER2 inhibitors

The HER family of tyrosine kinase receptors includes several members that are clinically important targets in cancer therapies, in particular HER1 (the EGF receptor) and HER2, other members include HER3 and HER4. Trastuzumab, a humanized monoclonal antibody and lapatinib, a tyrosine kinase inhibitor, are drugs that target HER2, which is highly expressed in 20-30% of breast cancers. Trastuzumab is recommended as an adjuvant therapy for lymph node positive, HER2-positive breast cancers, or node-negative cancer with high-risk of recurrence, as well as in stage IV cancers. One serious side effect of trastuzumab is cardiomyocyte dysfunction, resulting in reduced heart contractile efficiency. The incidence of collateral effects on the heart with trastuzumab therapy increases in people with cardiovascular risk factors, heart disease and when combined with other chemotherapeutics. When cardiotoxicity was observed with trastuzumab, several studies have addressed potential cardiac damage of trastuzumab itself and lapatinib. The differences in cardiovascular effects of these two compounds are somewhat unexpected and suggest distinct mechanisms of action, which have clear implications in clinical application and prevention of cardiotoxicity in cardio-oncological approaches.

Quercetin-3-methyl ether inhibits lapatinib-sensitive and -resistant breast cancer cell growth by inducing G(2)/M arrest and apoptosis

Lapatinib, an oral, small-molecule, reversible inhibitor of both EGFR and HER2, is highly active in HER2 positive breast cancer as a single agent and in combination with other therapeutics. However, resistance against lapatinib is an unresolved problem in clinical oncology. Recently, interest in the use of natural compounds to prevent or treat cancers has gained increasing interest because of presumed low toxicity. Quercetin-3-methyl ether, a naturally occurring compound present in various plants, has potent anticancer activity. Here, we found that quercetin-3-methyl ether caused a significant growth inhibition of lapatinib-sensitive and -resistant breast cancer cells. Western blot data showed that quercetin-3-methyl ether had no effect on Akt or ERKs signaling in resistant cells. However, quercetin-3-methyl ether caused a pronounced G(2)/M block mainly through the Chk1-Cdc25c-cyclin B1/Cdk1 pathway in lapatinib-sensitive and -resistant cells. In contrast, lapatinib produced an accumulation of cells in the G(1) phase mediated through cyclin D1, but only in lapatinib-sensitive cells. Moreover, quercetin-3-methyl ether induced significant apoptosis, accompanied with increased levels of cleaved caspase 3, caspase 7, and poly(ADP-ribose) polymerase (PARP) in both cell lines. Overall, these results suggested that quercetin-3-methyl ether might be a novel and promising therapeutic agent in lapatinib-sensitive or -resistant breast cancer patients.

An ErbB-3 antibody, MP-RM-1, inhibits tumor growth by blocking ligand-dependent and independent activation of ErbB-3/Akt signaling

The ErbB receptors, such as ErbB-1 and ErbB-2, have been intensely pursued as targets for cancer therapeutics. Although initially efficacious in a subset of patients, drugs targeting these receptors led invariably to resistance, which is often associated with reactivation of the ErbB-3-PI3K-Akt signaling. This may be overcome by an ErbB-3 ligand that abrogates receptor-mediated signaling. Toward this end, we have generated a mouse monoclonal antibody, MP-RM-1, against the extracellular domain (ECD) of ErbB-3 receptor. Assessment of human tumor cell lines, as well as early passage tumor cells revealed that MP-RM-1 effectively inhibited both NRG-1β-dependent and -independent ErbB-3 activation. The antagonizing effect of MP-RM-1 was of non-competitive type, as binding of [(125)I]-labeled NRG-1β to ErbB-3 was not influenced by the antibody. MP-RM-1 treatment led, in most instances, to decreased ErbB-3 expression. In addition, MP-RM-1 was able to inhibit the colony formation ability of tumor cells and tumor growth in two human tumor xenograft nude mouse models. Treatment with the antibody was associated with a decreased ErbB-3 and Akt phosphorylation and ErbB-3 expression in the excised tumor tissue. Collectively, these results indicate that MP-RM-1 has the potential to interfere with signaling by ErbB-3 and reinforce the notion that ErbB-3 could be a key target in cancer-drug design.

Modular anti-EGFR and anti-Her2 targeting of SK-BR-3 and BT474 breast cancer cell lines in the presence of ErbB receptor-specific growth factors

Over the last decade, a number of monoclonal antibodies and small molecule inhibitors emerged as potent therapeutic agents in the treatment of Her2/neu overexpressing breast cancer. Numerous patients, however, do not adequately respond to anti-epidermal growth factor receptor (EGFR)/Her2 receptor targeting. Receptor- and, in turn, growth-stimulating effects, which potentially hamper antiproliferative cell treatment, have barely been investigated. BT474 and SK-BR-3 breast cancer cell lines were treated with Trastuzumab, Pertuzumab, and Lapatinib alone using different combinations and concentrations. Moreover, epidermal growth factor (EGF) or heregulin (HRG) was added to reveal potential growth factor-mediated compensatory effects. Receptor and intracellular signaling were analyzed as a function of cell treatment. Read-out parameters were cell proliferation and apoptosis. BT474 cells were efficiently driven into quiescence by Trastuzumab, but not by Pertuzumab treatment. Simultaneous EGF or HRG administration, however, restored the BT474 cell proliferation capacity. In contrast, neither therapeutic antibody treatment caused a profound inhibition of SK-BR-3 cell-cycle progress. Lapatinib turned out to be the most potent cell-cycle inhibitor in both cell lines even though its impact was significantly abrogated in the presence of EGF and HRG. The compensatory effect of EGF on Lapatinib-induced cell-cycle inhibition was reversed by Trastuzumab as well as by Pertuzumab treatment. Most importantly, HRG-caused compensation of Lapatinib-induced cell-cycle exit was reversed by Pertuzumab but not by Trastuzumab. Apparently, multiple anti-EGFR/Her2 targeting by using Trastuzumab, Pertuzumab, and Lapatinib more efficiently affects receptor function (interaction and activation) and consequently enhances their antiproliferative capacity. Growth inhibition by anticancer drugs targeted to Her/ErbB receptors, however, can be significantly undermined in the presence of EGF and in particular by HRG treatment, which suggests that specific therapeutic growth factor sequestration might further enhance anti-EGFR/Her2 targeting.