Trial-level prediction of long-term outcome based on pathologic complete response (pCR) after neoadjuvant chemotherapy for early-stage breast cancer (EBC)

Imaging-proteomic analysis for prediction of neoadjuvant chemotherapy responses in patients with breast cancer

BACKGROUND

Optimizing patient selection for neoadjuvant chemotherapy in patients with breast cancer remains an unmet clinical need. Quantitative features from medical imaging were reported to be predictive of treatment responses. However, the biologic meaning of these latent features is poorly understood, preventing the clinical use of such noninvasive imaging markers. The study aimed to develop a deep learning signature (DLS) from pretreatment magnetic resonance imaging (MRI) for predicting responses to neoadjuvant chemotherapy in patients with breast cancer and to further investigate the biologic meaning of the DLS by identifying its underlying pathways using paired MRI and proteomic sequencing data.

METHODS

MRI-based DLS was constructed (radiogenomic training dataset, n = 105) and validated (radiogenomic validation dataset, n = 26) for the prediction of pathologic complete response (pCR) to neoadjuvant chemotherapy. Proteomic sequencing revealed biological functions facilitating pCR (n = 139). Their associations with DLS were uncovered by radiogenomic analysis.

RESULTS

The DLS achieved a prediction accuracy of 0.923 with an AUC of 0.958, higher than the performance of the model trained by transfer learning. Cellular membrane formation, endocytosis, insulin-like growth factor binding, protein localization to membranes, and cytoskeleton-dependent trafficking were differentially regulated in patients showing pCR. Oncogenic signaling pathways, features correlated with human phenotypes, and features correlated with general biological processes were significantly correlated with DLS in both training and validation dataset (p.adj < 0.05).

CONCLUSIONS

Our study offers a biologically interpretable DLS for the prediction of pCR to neoadjuvant chemotherapy in patients with breast cancer, which may guide personalized medication.

Residual Disease Burden After Neoadjuvant Therapy Among US Patients With High-Risk HER2-positive Early-Stage Breast Cancer: A Population Effectiveness Model

BACKGROUND

Approximately half of patients with high-risk HER2-positive early-stage breast cancer (ESBC) do not have pathologic complete response (pCR) after neoadjuvant therapy. The residual burden of disease among this population has not been previously quantified.

MATERIALS AND METHODS

We used decision-modeling techniques to simulate recurrence, progression from locoregional to distant cancer, breast cancer-related mortality, and mortality from other causes over a 10-year period in a hypothetical cohort. We derived progression probabilities primarily from the KATHERINE trial of T-DM1 (ado-trastuzumab emtansine) and mortality outcomes from the published literature. Modeled outcomes included recurrences, breast cancer deaths, deaths from other causes, direct medical costs, and costs due to lost productivity. To estimate the residual disease burden, we compared outcomes from a cohort of patients treated with T-DM1 versus a hypothetical cohort with no disease recurrence.

RESULTS

We estimated that 9,300 people would experience incident high-risk HER2-positive ESBC in the United States in 2021 based on cancer surveillance databases, clinical trial data, and expert opinion. We estimated that, in this group, 2,118 would experience disease recurrence, including 1,576 distant recurrences, and 1,358 would experience breast cancer deaths. This residual disease burden resulted in 6,435 life-years lost versus the recurrence-free cohort, and healthcare-related costs totaling $644 million, primarily associated with treating distant cancers.

CONCLUSION

Patients with HER2-positive ESBC who do not achieve pCR after neoadjuvant therapy are at ongoing risk of recurrence despite the effectiveness of neoadjuvant treatment. There is substantial clinical and economic value in further reducing the residual disease burden in this population.

Tumor Glucose and Fatty Acid Metabolism in the Context of Anthracycline and Taxane-Based (Neo)Adjuvant Chemotherapy in Breast Carcinomas

Breast cancer is characterized by considerable metabolic diversity. A relatively high percentage of patients diagnosed with breast carcinoma do not respond to standard-of-care treatment, and alteration in metabolic pathways nowadays is considered one of the major mechanisms responsible for therapeutic resistance. Consequently, there is an emerging need to understand how metabolism shapes therapy response, therapy resistance and not ultimately to analyze the metabolic changes occurring after different treatment regimens. The most commonly applied neoadjuvant chemotherapy regimens in breast cancer contain an anthracycline (doxorubicin or epirubicin) in combination or sequentially administered with taxanes (paclitaxel or docetaxel). Despite several efforts, drug resistance is still frequent in many types of breast cancer, decreasing patients’ survival. Understanding how tumor cells rapidly rewire their signaling pathways to persist after neoadjuvant cancer treatment have to be analyzed in detail and in a more complex system to enable scientists to design novel treatment strategies that target different aspects of tumor cells and tumor resistance. Tumor heterogeneity, the rapidly changing environmental context, differences in nutrient use among different cell types, the cooperative or competitive relationships between cells pose additional challenges in profound analyzes of metabolic changes in different breast carcinoma subtypes and treatment protocols. Delineating the contribution of metabolic pathways to tumor differentiation, progression, and resistance to different drugs is also the focus of research. The present review discusses the changes in glucose and fatty acid pathways associated with the most frequently applied chemotherapeutic drugs in breast cancer, as well the underlying molecular mechanisms and corresponding novel therapeutic strategies.

Laser Capture Proteomics: spatial tissue molecular profiling from the bench to personalized medicine

INTRODUCTION

Laser Capture Microdissection (LCM) uses a laser to isolate, or capture, specific cells of interest in a complex heterogeneous tissue section, under direct microscopic visualization. Recently, there has been a surge of publications using LCM for tissue spatial molecular profiling relevant to a wide range of research topics.

AREAS COVERED

We summarize the many advances in tissue Laser Capture Proteomics (LCP) using mass spectrometry for discovery, and protein arrays for signal pathway network mapping. This review emphasizes: a) transition of LCM phosphoproteomics from the lab to the clinic for individualized cancer therapy, and b) the emerging frontier of LCM single cell molecular analysis combining proteomics with genomic, and transcriptomic analysis. The search strategy was based on the combination of MeSH terms with expert refinement.

EXPERT OPINION

LCM is complemented by a rich set of instruments, methodology protocols, and analytical A.I. (artificial intelligence) software for basic and translational research. Resolution is advancing to the tissue single cell level. A vision for the future evolution of LCM is presented. Emerging LCM technology is combining digital and AI guided remote imaging with automation, and telepathology, to a achieve multi-omic profiling that was not previously possible.

Neoadjuvant Immunotherapy in Resectable Non-Small Cell Lung Cancer. A Narrative Review

Lung cancer is one of the most common malignant tumors and it is the leading cause of cancer-related mortality worldwide. For early-stage Non-Small Cell Lung Cancer (NSCLC), surgical resection is the treatment of choice, but the 5-year survival is still unsatisfying, ranging from 60% to 36% depending on the disease stage. Multimodality treatment with adjuvant chemotherapy did not lead to clinically relevant results, improving survival rates by only 5%. Recently, immune checkpoint inhibitors (ICIs) are being studied as neoadjuvant treatment for resectable NSCLC too, after the satisfactory results obtained in stage IV disease. Several clinical trials are evaluating the safety and feasibility of neoadjuvant immunotherapy and their early findings suggest that ICIs could be better tolerated than standard neoadjuvant chemotherapy and more effective in reducing cancer local recurrence and metastasis. The aim of this review is to retrace the most relevant results of the completed and the ongoing clinical trials, in terms of efficacy and safety, but also to face the open challenges regarding ICIs in neoadjuvant setting for resectable NSCLC.

Bayesian decision making in confirmatory early-stage breast cancer trial

Preoperative or neoadjuvant systemic chemotherapy, once reserved for patients with locally advanced breast cancer (BC) in whom the goal was to render breast cancer operable, has become increasingly common. In the early-stage BC neoadjuvant studies, clinical benefits such as event-free survival (EFS), disease-free survival (DFS) and overall survival (OS) usually take long time to be observed. Pathological complete response (pCR) rate obtained at surgery as an endpoint after the neoadjuvant treatment has been accepted by FDA as a surrogate predictor for long-term time-to-event endpoints to support accelerated approval. Utilizing this early endpoint helps expedite the development of novel therapies in order to fulfill the unmet medical need for certain high-risk or poor prognosis subsets of early-stage BC patients. By applying the correlation between pCR and time-to-event endpoints, an early and informative Go/NoGo decision-making structure can be built with less cost so that it improves the overall clinical development efficiency. We propose a Bayesian hierarchy model procedure that utilizes Bayesian predictive power of EFS in phase III to guide the Go/NoGo decision based on a clinical plausible threshold for the pCR treatment difference in phase II. The model implements a double bootstrap method to estimate the correlation between pCR and EFS in simulated setting. Besides simulation results, a hypothetical example based on the 2-in-1 adaptive design is provided.

Neoadjuvant Chemotherapy for Breast Cancer: Past, Present, and Future

Neoadjuvant chemotherapy (NAC) had been developed as a systematic approach before definitive surgery for the treatment of locally advanced or inoperable breast cancer such as inflammatory breast cancer in the past. In addition to its impact on surgery, the neoadjuvant setting has a benefit of providing the opportunity to monitor the individual drug response. Currently, the subject of NAC has expanded to include patients with early-stage, operable breast cancer because it is revealed that the achievement of a pathologic complete response (pCR) is associated with excellent long-term outcomes, especially in patients with aggressive phenotype breast cancer. In addition, this approach provides the unique opportunity to escalate adjuvant therapy in those with residual disease after NAC. Neoadjuvant chemotherapy in breast cancer is a rapidly evolving topic with tremendous interest in ongoing clinical trials. Here, we review the improvements and further challenges in the NAC setting in translational breast cancer research.

Inflammatory Blood Markers as Prognostic and Predictive Factors in Early Breast Cancer Patients Receiving Neoadjuvant Chemotherapy

Simple Summary

Predictive and prognostic factors are necessary to evaluate the future of women with early breast cancer. Inflammatory blood markers such as neutrophil to lymphocytes ratio and platelet to lymphocytes ratio have been reported to be a predictive factor for pathological complete response and a prognostic factor in breast cancer, with conflicting results. Here we evaluate these inflammatory blood markers in patients with early breast cancer receiving neo adjuvant chemotherapy since neo adjuvant treatment is more and more developed in early breast cancer.

Abstract

Background: Inflammatory blood markers, such as neutrophil to lymphocyte ratio (NLR) and platelet to lymphocyte ratio (PLR), have been reported as putative prognostic factors for survival and predictive factors for pathological complete response and toxicity in cancers, however with conflicting results. Methods: We retrospectively analyzed data of 280 patients with early breast cancer receiving neo-adjuvant chemotherapy between 2005 and 2013 in our center. Neutrophil count, lymphocyte count and platelet count before treatment were collected as well as data on pathological complete response, toxicity, recurrence and survival. Results: In multivariate analysis, high PLR was an independent prognostic factor for relapse-free survival (hazard ratio [HR] = 1.91; 95%CI = 1.15–3.16; p = 0.012) and for shorter overall survival (HR = 1.83; 95%CI = 1.03–3.24; p = 0.039). NLR was an independent predictive factor for febrile neutropenia (HR = 0.28; 95%CI = 0.13–0.58; p = 0.001). In triple negative breast cancer molecular subtype, low white blood cell count (<6.75 G/L) was predictive for a higher pathological complete response rate (odds ratio [OR] = 0.29; 95%CI = 0.14–0.61; p < 0.01). Conclusion: In the present study, PLR was found as an independent prognostic factor for survival, while NLR was an independent predictive factor for febrile neutropenia.

Neo-adjuvant therapy for triple-negative breast cancer: Insights from a network meta-analysis

BACKGROUND

The best regimen of neo-adjuvant therapy for triple-negative breast cancer (TNBC) is unknown. Recent studies have shown promising data that adding carboplatin or pembrolizumab improves the rate of pathologic complete response (pCR) in TNBC. Therefore, we performed a network meta-analysis to define the overall, most effective, neo-adjuvant systemic therapy for TNBC.

METHODS

We searched for studies comparing different neo-adjuvant regimens in patients with TNBC. We performed a network meta-analysis comparing the regimens using the random-effects model. We focused on anthracycline, bevacizumab, pembrolizumab, and platinum salts (Pl). All study regimens contained a taxane. We analyzed the rate of pCR (ypT0/is, N0), and the incidence of febrile neutropenia, grade 3-grade 4 thrombocytopenia, nausea/vomiting, and diarrhea.

RESULTS

We identified a total of 13 randomized control trials for this analysis. We compared ten different classes of regimens. We found that regimens containing Pl were significantly superior to non-PI-containing regimens for the rate of pCR. Similarly, pembrolizumab-containing regimens were associated with significantly higher pCR rates. Regimens containing bevacizumab significantly increased the rate of pCR as well. However, it was equivocal as to whether the addition of Pl to pembrolizumab-containing regimen increases pCR rates. Adding anthracycline into the regimen did not show an improved rate of pCR. In the safety analysis, regimens containing Pl were associated with a significantly higher incidence of febrile neutropenia and grade 3-grade 4 thrombocytopenia. The regimen containing anthracycline plus bevacizumab plus Pl was associated with a higher risk of gastrointestinal adverse events.

CONCLUSIONS

For TNBC, regimens containing bevacizumab, pembrolizumab, or Pl are most effective in terms of pCR rates, though it is unclear whether combining all these medications has the greatest efficacy. Additionally, the benefit of using anthracycline in the neo-adjuvant therapy regimen for TNBC is not apparent, which may warrant a further head-to-head comparison.

HER2-enriched subtype and pathological complete response in HER2-positive breast cancer: A systematic review and meta-analysis

BACKGROUND

HER2-positive (HER2+) breast cancer (BC) comprises all the four PAM50 molecular subtypes. Among these, the HER2-Enriched (HER2-E) appear to be associated with higher pathological complete response (pCR) rates following anti-HER2-based regimens. Here, we present a meta-analysis to validate the association of the HER2-E subtype with pCR following anti-HER2-based neoadjuvant treatments with or without chemotherapy (CT).

METHODS

A systematic literature search was performed in February 2019. The primary objective was to compare the association between HER2-E subtype (versus others) and pCR. Selected secondary objectives were to compare the association between 1) HER2-E subtype and pCR in CT-free studies, 2) HER2-E subtype within hormone receptor (HR)-negative and HR+ disease and 3) HR-negative disease (versus HR+) and pCR in all patients and within HER2-E subtype. A random-effect model was applied. The Higgins' I² was used to quantify heterogeneity.

RESULTS

Sixteen studies were included, 5 of which tested CT-free regimens. HER2-E subtype was significantly associated with pCR in all patients (odds ratio [OR] = 3.50, p < 0.001, I² = 33%), in HR+ (OR = 3.61, p < 0.001, I² = 1%) and HR-negative tumors (OR = 2.28, p = 0.01, I² = 47%). In CT-free studies, HER2-E subtype was associated with pCR in all patients (OR = 5.52, p < 0.001, I² = 0%) and in HR + disease (OR = 4.08, p = 0.001, I² = 0%). HR-negative status was significantly associated with pCR compared to HR + status in all patients (OR = 2.41, p < 0.001, I² = 30%) and within the HER2-E subtype (OR = 1.76, p < 0.001, I² = 0%).

CONCLUSIONS

The HER2-E biomarker identifies patients with a higher likelihood of achieving a pCR following neoadjuvant anti-HER2-based therapy beyond HR status and CT use. Future trial designs to escalate or de-escalate systemic therapy in HER2+ disease should consider this genomic biomarker.