The Role of Human Epidermal Growth Factor Receptor 2 (HER2)-Targeted Therapies in Early-Stage Breast Cancer: Current Practices, Treatment De-escalation, and Future Prospects.

Human epidermal growth factor receptor 2 (HER2)-targeted therapy has transformed the treatment paradigm for early-stage HER2-positive breast cancer, providing personalized and effective interventions. This comprehensive review delves into the current state of HER2-targeted therapies, emphasizing pivotal clinical trials that have demonstrated their substantial impact on long-term outcomes. Combination therapies that integrate HER2-targeted agents with chemotherapy exhibit enhanced tumor responses, particularly in neoadjuvant settings. Neoadjuvant chemotherapy (NACT) is explored for its role in tumor downsizing, facilitating breast-conserving surgery (BCS), and incorporating oncoplastic solutions to address both oncologic efficacy and aesthetic outcomes. Innovative axillary management post-NACT, such as targeted axillary dissection (TAD), is discussed for minimizing morbidity. The review further explores the delicate balance between maximal therapy and de-escalation, reflecting recent trends in treatment approaches. The therapeutic landscape of HER2-low breast cancer is examined, highlighting considerations in HER2-positive breast cancer with BReast CAncer gene (BRCA) mutations. Emerging immunotherapeutic strategies, encompassing immune checkpoint inhibitors and chimeric antigen receptor (CAR) T-cell therapy, are discussed in the context of their potential integration into treatment paradigms. In conclusion, the evolving landscape of HER2-positive early-stage breast cancer treatment, characterized by targeted therapies and multidisciplinary approaches, underscores the need for ongoing research and collaborative efforts. The aim is to refine treatment strategies and enhance patient outcomes in this dynamic and rapidly evolving field.

A UK prospective multicentre decision impact, decision conflict and economic evaluation of the 21-gene assay in women with node+ve, hormone receptor+ve, HER2-ve breast cancer.

BACKGROUND: For a tumour profiling test to be of value, it needs to demonstrate that it is changing clinical decisions, improving clinical confidence, and of economic benefit. This trial evaluated the use of the Oncotype DX Breast Recurrence Score® assay against these criteria in 680 women with hormone receptor-positive (HR+), HER2-negative early breast cancer with 1-3 lymph nodes positive (LN+) in the UK National Health Service (NHS). METHODS: Prior to receipt of the Recurrence Score (RS) result, both the physician and the patient were asked to state their preference for or against chemotherapy and their level of confidence on a scale of 1-5. Following receipt of the RS result, the physician and patient were asked to make a final decision regarding chemotherapy and record their post-test level of confidence. RESULTS: Receipt of the RS result led to a 51.5% (95% CI, 47.2-55.8%) reduction in chemotherapy, significantly increased the relative and absolute confidence for both physicians and patients and led to an estimated saving to the NHS of £787 per patient. CONCLUSION: The use of the Oncotype DX assay fulfils the criteria of changing clinical decisions, improving confidence and saving money.

Elucidating the chemical and structural composition of breast cancer using Raman micro-spectroscopy.

The current gold standard for breast cancer (BC) diagnosis is the histopathological assessment of biopsy samples. However, this approach limits the understanding of the disease in terms of biochemical changes. Raman spectroscopy has demonstrated its potential to provide diagnostic information and facilitate the prediction of the biochemical progression for different diseases in a rapid non-destructive manner. Raman micro-spectroscopy was used to characterize and differentiate breast cancer and normal breast samples. In this study, tissue microarrays of breast cancer biopsy samples (n=499) and normal breast (n=79) were analyzed using Raman micro-spectroscopy, and principal component analysis (PCA) was used for feature extraction. Linear discriminant analysis (LDA) was used for feature validation. Normal breast and breast cancer were successfully differentiated with a sensitivity of 90 % and specificity of 78 %. Dominance of lipids, specifically fatty acids, was identified in the normal tissue whereas proteins dominated the malignant spectra. Higher intensities of carotenoids, ß-carotenoids, and cholesterol were identified in the normal breast while ceramide related peaks were mostly visible in the BC spectra. The biochemical characterization achieved with Raman micro-spectroscopy showed that this technique is a powerful and reliable tool for the monitoring and diagnosis of BC, regardless of the cohort heterogeneity. Raman spectroscopy also provided a powerful insight into the biochemical changes associated with the BC progression and evolution.

Role of artificial intelligence and vibrational spectroscopy in cancer diagnostics.

INTRODUCTION: Raman and Infrared spectroscopic techniques are being used for the analysis of different types of cancers and other biological molecules. It is possible to identify cancers from normal tissues both in fresh and fixed tissues. These techniques can be used not only for the early diagnosis of cancer but also for monitoring the progression of the disease. Furthermore, chemical pathways to the progression of the disease process can be understood and followed. AREAS COVERED: More recently, Artificial Intelligence (AI), Neural Network (NN), and Machine Learning are being combined with spectroscopy, which is making it easier to understand the chemical structural details of cancers and biological molecules more precisely and accurately. In this report, these aspects are being outlined by using breast cancer as a specific example. EXPERT OPINION: A pathway showing to combine vibrational spectroscopy with AI and ML has immense potential in predicting various stages of different disease processes, in particular, in cancer diagnosis, staging, and designing treatment. This will result in improved patient care pathways.

Advancing cancer diagnostics with artificial intelligence and spectroscopy: identifying chemical changes associated with breast cancer.

Background: Artificial intelligence (AI) and machine learning (ML) approaches in combination with Raman spectroscopy (RS) to obtain accurate medical diagnosis and decision-making is a way forward for understanding not only the chemical pathway to the progression of disease, but also for tailor-made personalized medicine. These processes remove unwanted affects in the spectra such as noise, fluorescence and normalization, and help in the optimization of spectral data by employing chemometrics. Methods: In this study, breast cancer tissues have been analyzed by RS in conjunction with principal component (PCA) and linear discriminate (LDA) analyses. Tissue microarray (TMA) breast biopsies were investigated using RS and chemometric methods and classified breast biopsies into luminal A, luminal B, HER2, and triple negative subtypes. Results: Supervised and unsupervised algorithms were applied on biopsy data to explore intra and inter data set biochemical changes associated with lipids, collagen, and nucleic acid content. LDA predicted specificity accuracy of luminal A, luminal B, HER2, and triple negative subtypes were 70%, 100%, 90%, and 96.7%, respectively. Conclusion: It is envisaged that a combination of RS with AI and ML may create a precise and accurate real-time methodology for cancer diagnosis and monitoring.

Adjuvant Endocrine Therapy for Hormone-positive Breast Cancer, Focusing on Ovarian Suppression and Extended Treatment: An Update.

The benefits of five years of adjuvant endocrine therapy for oestrogen receptor (ER)-positive early breast cancer are well established. However, recent evidence suggests that extended endocrine treatment and ovarian suppression in selected groups of patients have significant advantages. In this article, we review the current evidence for adjuvant endocrine therapy in breast cancer with focus on extended adjuvant endocrine therapy and ovarian suppression, and also highlight the advantages and disadvantages of these therapeutic strategies. A literature search was performed through PubMed, Medline, and Cochrane using the following search terms: Endocrine therapy, Tamoxifen, Anastrazole, Ovarian Suppression, Exemestane, Letrozole and STS Inhibitors. All available evidence for adjuvant endocrine therapy was reviewed and summarised to assess the current guidance and the progress of the management of patients with ER-positive breast cancer. Extended endocrine therapy should be tailored according to patient needs dictated by their individual risk factors, molecular type of breast cancer, menopausal status, comorbidities, life style and risk of recurrence. Clinicians ought to discuss with patients the pros and cons of different adjuvant endocrine therapy approaches and highlight the potential side effects and toxicity.

Erlotinib in non-small cell lung cancer: a review.

Erlotinib (Tarceva, OSI-774; Pfizer, Inc.) is an orally-active, targeted inhibitor of the epidermal growth factor receptor (EGFR/HER1), which is part of a key regulatory pathway in cancer. Patients with advanced, incurable non-small cell lung cancer (NSCLC) may derive a clinical benefit from first- and second-line chemotherapy, but third-line treatment with available cytotoxic agents is not effective. Remarkably, EGFR/HER1 antagonists have demonstrated activity as second- and even third-line treatment for this disease. Erlotinib is the first of this novel class of drug to demonstrate a statistically significant and clinically relevant difference in overall survival, progression free survival and time to disease related symptoms (cough, pain, shortness of breath) compared with treatment with best supportive care in patients who have failed standard first- or second-line chemotherapy. This paper reviews the pharmacology, preclinical and clinical data to support the use of erlotinib in NSCLC.

Molecular imaging of antiangiogenic agents.

Many novel antiangiogenic agents are currently in various phases of clinical testing. These agents tend to be cytostatic, and therefore few responses are observed with conventional imaging by computerized tomography. Furthermore, toxicity with these agents is seen when the maximum-tolerated dose is combined with chemotherapy. Hence, there is a need to develop imaging strategies that can determine the minimum and optimum biologically active doses. There is increasing awareness of the need to obtain evidence of drug activity through the use of surrogate markers of the biologic mechanism of action during early clinical trials, in addition to determining the pharmacokinetics, toxicity profile, and maximum-tolerated dose. One of the major impediments to the rapid development of antiangiogenic agents in the past has been the lack of validated assays capable of measuring an antiangiogenic effect directly in patients. Recently, dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has emerged as a useful technique for noninvasive imaging of tumor vasculature in preclinical and clinical models. The problem of tumor heterogeneity remains to be addressed. The major challenge is the standardization of the technique worldwide for the purpose of early clinical studies that are likely to be multicenter. Convincing data on correlations between changes observed through molecular imaging and changes in tumor angiogenesis, and hence tumor biology, are still lacking. Whether this would translate into a survival advantage remains to be seen. The ultimate test of the surrogate biological end points determined by molecular imaging will occur in randomized phase III trials. Results of the first randomized trial that showed a survival advantage in favor of antiangiogenic agents were released at the American Society of Clinical Oncology meeting in 2003. There it was reported that the combination of 5-fluorouracil, leucovorin, and irinotecan (Camptosar; Pfizer Pharmaceuticals; New York, NY) with anti-vascular endothelial growth factor antibody (bevacizumab-Avastin; Genentech, Inc.; South San Francisco, CA) was superior to the chemotherapy regimen alone when used to treat patients with metastatic colorectal cancer. However, until further phase III clinical trials confirm these results, surrogate end points of clinical efficacy of the newer agents are urgently needed so that development of ineffective drugs can be halted early. This review briefly discusses the role of molecular imaging in general, and DCE-MRI in particular, in relation to treatment with antiangiogenic agents and highlights some of the difficulties encountered in this area.