Managing advanced HR-positive, HER2-negative breast cancer with CDK4/6 inhibitors in post-menopausal patients: is there a best sequence?

The current therapeutic landscape of luminal human epidermal growth factor receptor 2 (HER2)-negative metastatic breast cancer (mBC) is fundamentally evolving, particularly in the advent of molecularly targeted therapies, such as inhibitors of mammalian target of rapamycin and cyclin-dependent kinase 4/6 (CDK4/6). In the context of CDK4/6 inhibitors, landmark clinical trials for palbociclib (PALOMA-1, PALOMA-2, PALOMA-3), ribociclib (MONALEESA-2, MONALEESA-3, MONALEESA-7) and abemaciclib (MONARCH-1, MONARCH-2, MONARCH-3) have provided solid data regarding progression-free survival and overall response rate, justifying the introduction of this class of drugs into our therapeutic armoury. However, several clinical questions remain open. One of the most relevant issues faced in practice is that of the optimum sequencing of CDK4/6 inhibitors, particularly given the wide range of therapeutic options open to clinicians treating luminal mBC. In this brief commentary, we would like to focus on the best sequence for CDK4/6 inhibitors and their place in this growing, complex scenario

The role of abemaciclib in treatment of advanced breast cancer

Until recently, the mainstay of treatment in the majority of hormone receptor (HR)-positive, human epidermal growth factor 2 receptor (HER2)-negative advanced breast cancer (ABC) has consisted of single-agent endocrine therapy (ET). However, as understanding of endocrine resistance has grown, newer targeted agents have come to the fore. Inhibition of cyclin-dependent kinase complexes 4 and 6 (CDK4/6) combined with ET has shown significant activity in HR+ HER2− ABC, with impressive results in terms of progression-free survival (PFS) when compared with ET alone. This review summarizes the seminal findings pertaining to CDK4/6 inhibition in this population, specifically focusing on abemaciclib, contrasted with palbociclib and ribociclib. Potential directions for future studies are discussed, as a way of addressing outstanding issues such as establishing optimal treatment sequencing and agent combinations, appropriate patient selection to derive maximal benefits, predictive biomarkers and the employment of CDK4/6 inhibition beyond the ABC setting

Metabolomics to Assess Response to Immune Checkpoint Inhibitors in Patients with Non-Small-Cell Lung Cancer

In the treatment of advanced non-small cell lung cancer (NSCLC), immune checkpoint inhibitors have shown remarkable results. However, not all patients with NSCLC respond to this drug treatment or receive durable benefits. Thus, patient stratification and selection, as well as the identification of predictive biomarkers, represent pivotal aspects to address. In this framework, metabolomics can be used to support the discrimination between responders and non-responders. Here, metabolomics was used to analyze the sera samples from 50 patients with NSCL treated with immune checkpoint inhibitors. All the samples were collected before the beginning of the treatment and were analyzed by NMR spectroscopy and multivariate statistical analyses. Significantly, we show that the metabolomic fingerprint of serum acts as a predictive “collective” biomarker to immune checkpoint inhibitors response, being able to predict individual therapy outcome with > 80% accuracy. Metabolomics represents a potential strategy for the real-time selection and monitoring of patients treated with immunotherapy. The prospective identification of responders and non-responders could improve NSCLC treatment and patient stratification, thus avoiding ineffective therapeutic strategies

A gene expression signature of Retinoblastoma loss-of-function predicts resistance to neoadjuvant chemotherapy in ER-positive/HER2-positive breast cancer patients

HER2-positive (HER2+) breast cancers show heterogeneous response to chemotherapy, with the ER-positive (ER+) subgroup deriving less benefit. Loss of retinoblastoma tumor suppressor gene (RB1) function has been suggested as a cardinal feature of breast cancers that are more sensitive to chemotherapy and conversely resistant to CDK4/6 inhibitors. We performed a retrospective analysis exploring RBsig, a gene signature of RB loss, as a potential predictive marker of response to neoadjuvant chemotherapy in ER+/HER2+ breast cancer patients.We selected clinical trials of neoadjuvant chemotherapy +/- anti-HER2 therapy in HER2+ breast cancer patients with available information on gene expression data, hormone receptor status, and pathological complete response (pCR) rates. RBsig expression was computed in silico and correlated with pCR.Ten studies fulfilled the inclusion criteria and were included in the analysis (514 patients). Overall, of 211 ER+/HER2+ breast cancer patients, 49 achieved pCR (23%). The pCR rate following chemotherapy +/- anti-HER2 drugs in patients with RBsig low expression was significantly lower compared to patients with RBsig high expression (16% vs. 30%, respectively; Fisher's exact test p = 0.015). The area under the ROC curve (AUC) was 0.62 (p = 0.005). In the 303 ER-negative (ER-)/HER2+ patients treated with chemotherapy +/- anti-HER2 drugs, the pCR rate was 43%. No correlation was found between RBsig expression and pCR rate in this group.Low expression of RBsig identifies a subset of ER+/HER2+ patients with low pCR rates following neoadjuvant chemotherapy +/- anti-HER2 therapy. These patients may potentially be spared chemotherapy in favor of anti-HER2, endocrine therapy, and CDK 4/6 inhibitor combinations

European Society of Breast Cancer Specialists/Advanced Breast Cancer Global Alliance quality indicators for metastatic breast cancer care

Aims: Improvement in the care of patients with metastatic breast cancer (MBC) can only occur if the adequate quality of care is implemented and verified, including access to multidisciplinary, specialised care given in accordance with high-quality guidelines. To this purpose, European Society of Breast Cancer Specialists and the Advanced Breast Cancer Global Alliance joined efforts to develop the first set of quality indicators (QI) specifically for MBC that should be routinely measured and evaluated to ensure that breast cancer centres meet the required standards.Methods: A working group of multidisciplinary European experts in breast cancer met to discuss each identified QI, reporting the definition, the minimum and target standard for breast cancer centres to achieve, and the motivation for selection. The level of evidence was determined according to the short version of the United States Agency for HealthcareResults: QI to measure access to and involvement in multidisciplinary and supportive care, appropriate pathological characterisation of disease, systemic therapies and radiotherapy were developed with the consensus of the working group.Conclusions: This is the first effort of a multistep project that aims to have QI for MBC routinely measured and evaluated to ensure that breast cancer centres achieve mandated standards in the care of patients with metastatic disease. (c) 2023 Elsevier Ltd. All rights reserved

Factors Influencing COVID-19 Vaccine Hesitancy among Patients with Serious Chronic Illnesses during the Initial Australian Vaccine Rollout: A Multi-Centre Qualitative Analysis Using the Health Belief Model.

Background: People with chronic illnesses have increased morbidity and mortality associated with COVID-19 infection. The influence of a person's serious and/or comorbid chronic illness on COVID-19 vaccine uptake is not well understood. Aim: To undertake an in-depth exploration of factors influencing COVID-19 vaccine uptake among those with various serious and/or chronic diseases in the Australian context, using secondary data analysis of a survey study. Methods: Adults with cancer, diabetes and multiple sclerosis (MS) were recruited from 10 Australian health services to undertake a cross-sectional online survey (30 June to 5 October 2021) about COVID-19 vaccine uptake, vaccine hesitancy, confidence and complacency and disease-related decision-making impact. Free-text responses were invited regarding thoughts and feelings about the interaction between the participant's disease, COVID-19, and vaccination. Qualitative thematic analysis was undertaken using an iterative process and representative verbatim quotes were chosen to illustrate the themes. Results: Of 4683 survey responses (cancer 3560, diabetes 842, and MS 281), 1604 (34.3%) included free-text comments for qualitative analysis. Participants who provided these were significantly less likely to have received a COVID-19 vaccination than those who did not comment (72.4% and 86.2%, respectively). People with diabetes were significantly less likely to provide free-text comments than those with cancer or MS (29.0%, 35.1% and 39.9%, respectively). Four key themes were identified from qualitative analysis, which were similar across disease states: (1) having a chronic disease heightened perceived susceptibility to and perceived severity of COVID-19; (2) perceived impact of vaccination on chronic disease management and disease-related safety; (3) uncertain benefits of COVID-19 vaccine; and (4) overwhelming information overload disempowering patients. Conclusions: This qualitative analysis highlights an additional layer of complexity related to COVID-19 vaccination decision making in people with underlying health conditions. Appreciation of higher susceptibility to severe COVID-19 outcomes appears to be weighed against uncertain impacts of the vaccine on the progression and management of the comorbid disease. Interactions by clinicians addressing individual factors may alleviate concerns and maximise vaccine uptake in people with significant underlying health conditions

An RB-1 loss of function gene signature as a tool to predict response to neoadjuvant chemotherapy plus anti-HER2 agents: a substudy of the NeoALTTO trial (BIG 1-06)

Background: Chemotherapy added to anti-HER2 agents (H) is the treatment of choice in patients with HER2+ early breast cancer. However, HER2+ tumours are clinically and biologically heterogeneous, and treatment response varies significantly by hormone receptor (HR) status and molecular subtype. Predictive biomarkers are needed in this context. This study assessed whether an RB-1 loss of function gene signature (RBsig) is predictive of response to neoadjuvant chemotherapy in combination with trastuzumab, lapatinib or both, within the NeoALTTO trial. Methods: We collected RNA-sequencing data from pretreatment biopsies derived from the NeoALTTO trial. RBsig expression was computed retrospectively and correlated with pathological complete response (pCR) using receiver-operating characteristic (ROC) curves. The RBsig was dichotomised as High/Low in correspondence to the 25th percentile. Reported p values resulted from Fisher’s exact test. Results: Of 455 NeoALTTO patients, 244 were eligible for this substudy (HR+ n = 129; HR− n = 115). Overall, pCR rate was significantly higher in patients with RBsig High tumours than those with RBsig Low (35% versus 18% respectively; p = 0.01). The area under the ROC curve (AUC) was 0.60 (95% CI 0.52–0.67). A remarkably low pCR rate of 11% was seen in HR+/RBsig Low patients versus 28% in HR+/RBsig High. Conclusions: These results indicate RBsig may add valuable information to HER2 and HR expression, which may in turn inform treatment choices. HR+/HER2+/RBsig Low breast cancers exhibited the poorest pathological response following chemotherapy plus H. Accordingly, in such patients, endocrine therapy in combination with H and, possibly, a CDK4/6 inhibitor, may potentially prove to be a more effective treatment.SCOPUS: ar.jinfo:eu-repo/semantics/publishe