Breast Cancer Treatment Response Research Articles

Prospective comparison of early interim 18F-FDG-PET with 18F-FLT-PET for predicting treatment response and survival in metastatic breast cancer

BackgroundTo compare the value of interim 18F-FLT-PET and 18F-FDG-PET for predicting treatment outcomes in patients with metastatic breast cancer after salvage therapy.MethodsPatients with metastatic breast cancer received PET/CT using 18F-FLT and 18F-FDG at baseline, after the 1st and 2nd cycle of systemic chemotherapy. The clinical response was classified according to Response Evaluation Criteria in Solid Tumors 1.1 based on contrast-enhanced CT after 3 months of systemic chemotherapy. The metabolic response on PET was assessed according to European Organization for Research and Treatment of Cancer criteria or PET Response Criteria in Solid Tumors (PERCIST) and was correlated to the clinical response, overall survival (OS), and progression-free survival (PFS).ResultsTwenty-five patients entered final analysis. On 18F-FDG-PET, clinical responders after 2 chemotherapy cycles (post-2c) had a significantly greater reduction of maximal standardized uptake value (SUV) and the peak SUV corrected for lean body mass (SULpeak) of the tumor than non-responders (P = 0.030 and 0.003). Metabolic response determined by PERCIST on post-2c 18F-FDG-PET showed a high area under the receiver operating characteristics curve of 0.801 in predicting clinical response (P = 0.011). Patients who were metabolic responders by PERCIST on post-2c 18F-FDG-PET had a significantly longer PFS (53.8% vs. 16.7%, P = 0.014) and OS (100% vs. 47.6%, P = 0.046) than non-responders. Survival differences between responders and non-responders in the interim 18F-FLT-PET were not significant.Conclusions18F-FLT-PET failed to show an advantage over 18F-FDG-PET in predicting the treatment response and survival in patients with metastatic breast cancer. Assessment of treatment outcome by interim 18F-FDG-PET may aid treatment.Trial registrationThe study was retrospectively registered on 02/06/2020 on Clinicaltrials.gov (identifier NCT04411966).

Ultrasound segmentation-guided edge artifact reduction in diffuse optical tomography using connected component analysis.

Ultrasound (US)-guided diffuse optical tomography (DOT) has demonstrated potential value for breast cancer diagnosis and treatment response assessment. However, in clinical use, the chest wall, poor probe-tissue contact, and tissue heterogeneity can all cause image artifacts. These image artifacts, appearing commonly as hot spots in the non-lesion regions (edge artifacts), can decrease the reconstruction accuracy and cause misinterpretation of lesion images. Here we introduce an iterative, connected component analysis-based image artifact reduction algorithm. A convolutional neural network (CNN) is used to segment co-registered US images to extract the lesion location and size to guide the artifact reduction. We demonstrate its performance using Monte Carlo simulations on VICTRE digital breast phantoms and breast patient images. In simulated tissue mismatch models, this algorithm successfully reduces edge artifacts without significantly changing the reconstructed target absorption coefficients. With clinical data it improves the optical contrast between malignant and benign groups, from 1.55 without artifact reduction to 1.91 with artifact reduction. The proposed algorithm has a broad range of applications in other modality-guided DOT imaging.

PET/CT Imaging for Evaluation of Treatment Response in Breast Cancer

PET/CT Imaging for Evaluation of Treatment Response in Breast Cancer

Abnormal Long Non-Coding RNAs Expression Patterns Have the Potential Ability for Predicting Survival and Treatment Response in Breast Cancer.

Abnormal long non-coding RNAs (lncRNAs) expression has been documented to have oncogene or tumor suppressor functions in the development and progression of cancer, emerging as promising independent biomarkers for molecular cancer stratification and patients’ prognosis. Examining the relationship between lncRNAs and the survival rates in malignancies creates new scenarios for precision medicine and targeted therapy. Breast cancer (BRCA) is a heterogeneous malignancy. Despite advances in its molecular classification, there are still gaps to explain in its multifaceted presentations and a substantial lack of biomarkers that can better predict patients’ prognosis in response to different therapeutic strategies. Here, we performed a re-analysis of gene expression data generated using cDNA microarrays in a previous study of our group, aiming to identify differentially expressed lncRNAs (DELncRNAs) with a potential predictive value for response to treatment with taxanes in breast cancer patients. Results revealed 157 DELncRNAs (90 up- and 67 down-regulated). We validated these new biomarkers as having prognostic and predictive value for breast cancer using in silico analysis in public databases. Data from TCGA showed that compared to normal tissue, MIAT was up-regulated, while KCNQ1OT1, LOC100270804, and FLJ10038 were down-regulated in breast tumor tissues. KCNQ1OT1, LOC100270804, and FLJ10038 median levels were found to be significantly higher in the luminal subtype. The ROC plotter platform results showed that reduced expression of these three DElncRNAs was associated with breast cancer patients who did not respond to taxane treatment. Kaplan–Meier survival analysis revealed that a lower expression of the selected lncRNAs was significantly associated with worse relapse-free survival (RFS) in breast cancer patients. Further validation of the expression of these DELncRNAs might be helpful to better tailor breast cancer prognosis and treatment.

Cancer-Associated Fibroblasts in Breast Cancer Treatment Response and Metastasis.

Simple SummaryBreast cancer is a major public health problem with a large impact on the life of patients and their families. It is a highly curable disease when detected early, and an inevitably mortal disease when discovered too late. Therapy resistance and metastases are the most critical clinical issues faced by breast cancer oncologists nowadays. It has become evident that interactions between carcinoma cells and tumor microenvironment are an essential part of tumor growth and progression. Cells that support the function of epithelial cells, like cancer-associated fibroblasts (CAFs), contribute to therapy resistance and metastasis via the production of several secreted factors and direct interaction with cancer cells. Here we review the role of CAFs in radiotherapy, chemotherapy, endocrine and targeted therapies resistance. We also highlight the role of CAFs and fibroblasts from metastatic sites in metastasis progression. Finally, we discuss advances and potential therapeutic strategies to target CAFs for overcoming resistance and preventing metastases.Breast cancer (BrCa) is the leading cause of death among women worldwide, with about one million new cases diagnosed each year. In spite of the improvements in diagnosis, early detection and treatment, there is still a high incidence of mortality and failure to respond to current therapies. With the use of several well-established biomarkers, such as hormone receptors and human epidermal growth factor receptor-2 (HER2), as well as genetic analysis, BrCa patients can be categorized into multiple subgroups: Luminal A, Luminal B, HER2-enriched, and Basal-like, with specific treatment strategies. Although chemotherapy and targeted therapies have greatly improved the survival of patients with BrCa, there is still a large number of patients who relapse or who fail to respond. The role of the tumor microenvironment in BrCa progression is becoming increasingly understood. Cancer-associated fibroblasts (CAFs) are the principal population of stromal cells in breast tumors. In this review, we discuss the current understanding of CAFs’ role in altering the tumor response to therapeutic agents as well as in fostering metastasis in BrCa. In addition, we also review the available CAFs-directed molecular therapies and their potential implications for BrCa management.

18F-FDG PET/CT for Monitoring of Treatment Response in Breast Cancer

Abstract Background: Breast cancer is the most common cancer and the second leading cause of cancer mortality in women. Accurate diagnosis and staging are essential for the selection of the most appropriate therapeutic strategy and major deter-minants of patient prognosis and survival. Aim of Study: The purpose of our study is to evaluate the potential role of 18F-FDG PET/CT in monitoring treatment of breast cancer and assessment of recurrence after surgical or systemic treatment. Patients and Methods: This study is retrospective study, was conducted on (25) female patients over a period of 6 months between 2018 and 2019. Their ages ranged from 34 to 78 years with mean age of 52 years, all patients have positive history of breast cancer treatment. Those patients were referred to the Radio Diagnosis Department & Nuclear Medicine Department in Ain Shams University. Results: FDG-PET-CT is the investigation of choice for post-treatment follow-up of breast cancer. It has a great role in detection of newly developed lesions and detection of the disease progression. Conclusion: FDG-PET-CT is highly useful for monitoring response to therapeutic interventions. This technique can identify response to therapy earlier than any other imaging method currently available which greatly improves patient management by allowing termination of ineffective and toxic therapies. PET-CT proved to be helpful in the evaluation of anatomic regions that have been previously treated by surgery or radiation in which the discrimination between post-treatment scar and recurrent tumor can be problematic.

PCN190 Budget Impact of the DiviTum®Tka Assay in Postmenopausal Women with Hormone Receptor Positive Metastatic Breast Cancer

DiviTum®TKa, a blood-based biomarker assay developed to monitor and predict treatment response in hormone receptor positive metastatic breast cancer (HR+ mBC), may decrease traditional disease monitoring assessments and avoid prolongation of futile treatments. Our objective was to estimate the diagnostic- and treatment budget impact of the assay on a postmenopausal HR+ mBC population in a one-million-member U.S. health plan. We developed a budget impact model comparing inclusion and exclusion of DiviTum®TKa to standard care under which DiviTum®TKa 1) reduces frequency of traditional mBC monitoring tools, and 2) predicts treatment futility in advance of radiological disease progression. Traditional disease monitoring assessment schedules were based on guidelines and expert opinion. DiviTum®TKA’s impact on therapy utilization was based on published literature and expert opinion. Modeled costs included DiviTum®TKa, NCCN-recommended treatments, imaging, biomarker testing, and adverse events. Unit costs were based on CMS fee schedules and wholesale acquisition costs. Annual rates of incident and recurrent postmenopausal HR+ mBC were estimated from SEER and publicly available data. We calculated total and per-member per-month (PMPM) costs with a 3-year time horizon. Inclusion of DiviTum®TKa resulted in total cost-savings of $439,700, equaling PMPM cost-savings of $0.013. Looking at 3-year diagnostic and treatment impacts separately, addition of DiviTum®TKa (+$166,400) to monitoring was offset by reductions to other tests (-$144,800): CT scans (-203), bone scans (-93), and biomarker tests (-180), with a PMPM of +$0.001. Treatment-related cost-savings were $465,300. Results were most sensitive to DiviTum®TKa cost, population parameters, and treatment costs. Clinical use of DiviTum®TKa is expected to decrease traditional imaging and monitoring and may reduce overall costs of managing mBC if it leads to clinical decisions to avoid futile therapy. Post-coverage, real world monitoring of palliative therapies among postmenopausal mBC populations is needed to better categorize cost savings over time.

UPA-PAI-1 heteromerization promotes breast cancer progression by attracting tumorigenic neutrophils.

High intratumoral levels of urokinase‐type plasminogen activator (uPA)‐plasminogen activator inhibitor‐1 (PAI‐1) heteromers predict impaired survival and treatment response in early breast cancer. The pathogenetic role of this protein complex remains obscure. Here, we demonstrate that heteromerization of uPA and PAI‐1 multiplies the potential of the single proteins to attract pro‐tumorigenic neutrophils. To this end, tumor‐released uPA‐PAI‐1 utilizes very low‐density lipoprotein receptor and mitogen‐activated protein kinases to initiate a pro‐inflammatory program in perivascular macrophages. This enforces neutrophil trafficking to cancerous lesions and skews these immune cells toward a pro‐tumorigenic phenotype, thus supporting tumor growth and metastasis. Blockade of uPA‐PAI‐1 heteromerization by a novel small‐molecule inhibitor interfered with these events and effectively prevented tumor progression. Our findings identify a therapeutically targetable, hitherto unknown interplay between hemostasis and innate immunity that drives breast cancer progression. As a personalized immunotherapeutic strategy, blockade of uPA‐PAI‐1 heteromerization might be particularly beneficial for patients with highly aggressive uPA‐PAI‐1high tumors.

33P Epigenetic biomarkers ID1, HOXB2 and ATOH8 could predict response to chemotherapy and prognosis in early breast cancer

Epigenetic alterations play an important role in the development of breast cancer and could differ between the different subtypes as well act as prognostic and/or predictive factor of response to chemotherapy. The potential reversibility of these alterations justifies the growing interest in their research as possible therapeutic targets in the context of precision medicine. Our aim is to perform a DNA methylation screening to identify potential biomarkers of prognosis and treatment response in breast cancer.

Cohort profile: The Singapore Breast Cancer Cohort (SGBCC), a multi-center breast cancer cohort for evaluation of phenotypic risk factors and genetic markers.

This article aims to provide a detailed description of the Singapore Breast Cancer Cohort (SGBCC), an ongoing multi-ethnic cohort established with the overarching goal to identify genetic markers for breast cancer risk, prognosis and treatment response, as well as to understand the ethnic differences in disease risk and outcome in an Asian setting. The cohort comprises of breast cancer patients aged 21 years and above from six public hospitals which diagnose and treat nearly 76% breast cancer cases in Singapore. Self-reported data on sociodemographic and lifestyle, reproductive risk factors, medical history and family history of breast or ovarian cancer is collected using a structured questionnaire. Clinical data on tumour characteristics, and treatment modalities are obtained through medical record. Bio-specimens (blood or saliva) is collected at recruitment. Follow-up on survival information is done through routine linkage with the Registry of Births and Deaths. As of 31 December 2016, 7,768 subjects have been recruited to the study with 76% subjects contributed bio-specimens. The SGBCC provides a valuable platform which offers a unique, large and rich resource for new research ideas on breast cancer related phenotypic risk factors and genetic markers.

The impact of tumor epithelial and microenvironmental heterogeneity on treatment responses in HER2+ breast cancer.

Despite the availability of multiple human epidermal growth factor receptor 2–targeted (HER2-targeted) treatments, therapeutic resistance in HER2+ breast cancer remains a clinical challenge. Intratumor heterogeneity for HER2 and resistance-conferring mutations in the PIK3CA gene (encoding PI3K catalytic subunit α) have been investigated in response and resistance to HER2-targeting agents, while the role of divergent cellular phenotypes and tumor epithelial-stromal cell interactions is less well understood. Here, we assessed the effect of intratumor cellular genetic heterogeneity for ERBB2 (encoding HER2) copy number and PIK3CA mutation on different types of neoadjuvant HER2-targeting therapies and clinical outcome in HER2+ breast cancer. We found that the frequency of cells lacking HER2 was a better predictor of response to HER2-targeted treatment than intratumor heterogeneity. We also compared the efficacy of different therapies in the same tumor using patient-derived xenograft models of heterogeneous HER2+ breast cancer and single-cell approaches. Stromal determinants were better predictors of response than tumor epithelial cells, and we identified alveolar epithelial and fibroblastic reticular cells as well as lymphatic vessel endothelial hyaluronan receptor 1–positive (Lyve1+) macrophages as putative drivers of therapeutic resistance. Our results demonstrate that both preexisting and acquired resistance to HER2-targeting agents involve multiple mechanisms including the tumor microenvironment. Furthermore, our data suggest that intratumor heterogeneity for HER2 should be incorporated into treatment design.

A Systematic Review of the Use of Circulating Cell-Free DNA Dynamics to Monitor Response to Treatment in Metastatic Breast Cancer Patients.

Simple SummaryCurrently, the most commonly used method to monitor response to treatment in metastatic breast cancer patients is by radiological imaging. However, these imaging techniques are relatively insensitive and give little to no insight into biological tumor characteristics that might be relevant for the choice of treatment. Circulating tumor DNA (ctDNA), released by tumor cells into the blood of cancer patients, can be used to overcome these shortcomings. Besides the fact that specific alterations are known to predict response to treatment and development of resistance, the total amount of ctDNA is believed to reflect the proliferation rate of the tumor, suggesting ctDNA levels can be used as a general tool to evaluate treatment response. Different methods are available to measure ctDNA primarily based on detection of cancer-specific somatic mutations, DNA methylation, and copy number variations. In this review we have critically analyzed recently published studies using blood-derived ctDNA of metastatic breast cancer patients on multiple time points to monitor disease response in respect to analytical validity and clinical utility.Monitoring treatment response in metastatic breast cancer currently consists mainly of radiological and clinical assessments. These methods have high inter-observer variation, suboptimal sensitivity to determine response to treatment and give little insight into the biological characteristics of the tumor. Assessing circulating tumor DNA (ctDNA) over time could be employed to address these limitations. Several ways to quantify and characterize ctDNA exist, based on somatic mutations, copy number variations, methylation, and global circulating cell-free DNA (cfDNA) fragment sizes and concentrations. These methods are being explored and technically validated, but to date none of these methods are applied clinically. We systematically reviewed the literature on the use of quantitative ctDNA measurements over time to monitor response to systemic therapy in patients with metastatic breast cancer. Cochrane, Embase, PubMed and Google Scholar databases were searched to find studies focusing on the use of cfDNA to longitudinally monitor treatment response in advanced breast cancer patients until October 2020. This resulted in a total of 33 studies which met the inclusion criteria. These studies were heterogeneous in (pre-)processing procedures, applied techniques and design. An association between ctDNA and treatment response was found in most of the included studies, independent of the applied assay. To implement ctDNA-based response monitoring into daily clinical practice for metastatic breast cancer patients, sample (pre-) processing procedures need to be standardized and large prospectively collected sample cohorts with well annotated clinical follow-up are required to establish its clinical validity.

RADIOMICS BASED BREAST MALIGNANCY INDEX TO DIFFERENTIATE PATHOLOGICAL CHANGES DUE TO NEOADJUVANT CHEMOTHERAPY

The leading cause of deaths among women in the world is Breast Cancer. Neoadjuvant chemotherapy (NAC) offers effective treatment results, thus reducing tumor aggression and allowing treatment monitoring. The Dynamic Contrast Enhanced (DCE) MRI plays a vital role in assessing the treatment response due to NAC. However, quantifying the treatment response in low-grade tumours is visually challenging. Radiomics is an evolving field of medical imaging that reflects the histopathological variations in breast tissues. Integrating radiomics with breast DCE-MRI provides clinically useful measures in evaluating the NAC response. In this work, we have formulated an index called Radiomics based Breast Malignancy Index (RBMI) using texture and Haar wavelets to differentiate the radiological differences of breast tissue due to NAC. The statistically significant radiomic features extracted from 20 DCE-MR images obtained using TCIA database were used in the calculation of RBMI. Results show that, RBMI could statistically differentiate (p=0.007) the treatment response between visit-1 & 2 due to NAC with mean and standard deviation values of 334706.5949 ± 93952.5123 and 296354.9720 ± 77120.6718 respectively. Hence, RBMI seems to be a clinically adjunct measure in evaluating the treatment response of breast cancer due to NAC.

Metabolic Syndrome and Breast Cancer: Prevalence, Treatment Response, and Prognosis.

Metabolic syndrome is a type of multifactorial metabolic disease with the presence of at least three factors: obesity, diabetes mellitus, low high-density lipoprotein, hypertriglyceridemia, and hypertension. Recent studies have shown that metabolic syndrome and its related components exert a significant impact on the initiation, progression, treatment response, and prognosis of breast cancer. Metabolic abnormalities not only increase the disease risk and aggravate tumor progression but also lead to unfavorable treatment responses and more treatment side effects. Moreover, biochemical reactions caused by the imbalance of these metabolic components affect both the host general state and organ-specific tumor microenvironment, resulting in increased rates of recurrence and mortality. Therefore, this review discusses the recent advances in the association of metabolic syndrome and breast cancer, providing potential novel therapeutic targets and intervention strategies to improve breast cancer outcome.

Automatic Detection of the Circulating Cell-Free Methylated DNA Pattern of GCM2, ITPRIPL1 and CCDC181 for Detection of Early Breast Cancer and Surgical Treatment Response.

Simple SummaryBreast cancer is a multifactorial disease that arises from the cumulative accumulation of acquired genetic as well as epigenetic alterations. Epigenetic alteration constitutes a molecular signature that can serve as a promising biomarker for early detection. In this study, we carry out automatic detection of circulating cell-free methylated DNA, including GCM2, ITPRIPL1 and CCDC181, and find a pattern that can detect early breast cancer more accurately compared with currently used biomarkers. The pattern is also useful for the detection of the surgical responses of breast cancer patients. Circulating methylated CCDC181, GCM2 and ITPRIPL1 analysis could be combined with ultrasound to facilitate the early detection of breast cancer.The early detection of cancer can reduce cancer-related mortality. There is no clinically useful noninvasive biomarker for early detection of breast cancer. The aim of this study was to develop accurate and precise early detection biomarkers and a dynamic monitoring system following treatment. We analyzed a genome-wide methylation array in Taiwanese and The Cancer Genome Atlas (TCGA) breast cancer (BC) patients. Most breast cancer-specific circulating methylated CCDC181, GCM2 and ITPRIPL1 biomarkers were found in the plasma. An automatic analysis process of methylated ccfDNA was established. A combined analysis of CCDC181, GCM2 and ITPRIPL1 (CGIm) was performed in R using Recursive Partitioning and Regression Trees to establish a new prediction model. Combined analysis of CCDC181, GCM2 and ITPRIPL1 (CGIm) was found to have a sensitivity level of 97% and an area under the curve (AUC) of 0.955 in the training set, and a sensitivity level of 100% and an AUC of 0.961 in the test set. The circulating methylated CCDC181, GCM2 and ITPRIPL1 was also significantly decreased after surgery (all p < 0.001). The aberrant methylation patterns of the CCDC181, GCM2 and ITPRIPL1 genes means that they are potential biomarkers for the detection of early BC and can be combined with breast imaging data to achieve higher accuracy, sensitivity and specificity, facilitating breast cancer detection. They may also be applied to monitor the surgical treatment response.

Abstract PS3-27: 18F-FDG-PET/CT and MRI in the assessment of neoadjuvant chemotherapy treatment response in breast cancer. Correlation with pathological response

Abstract Introduction: Residual cancer burden (RCB) after neoadjuvant chemotherapy (NAC) can accurately predict disease recurrence and survival in breast cancer. In this context, end of treatment (EOT) image-guided response assessment could be useful to adapt treatment for individual patients. Our main objective was to assess the effectiveness of 18F-FDG PET/CT and MRI in determining NAC response. Methods: Patients with surgically resectable breast cancer (stages II-III) were prospectively included and evaluated with 18F-FDG-PET/CT and MRI before and after standard-of-care neoadjuvant chemotherapy (NAC). Ultrasound guided breast biopsy was performed before NAC and pathologic examination with residual cancer burden (RCB) scoring was performed after surgery. Standard uptake values (SUVmax and SUVmean) from baseline PET scans were measured. EOT images results were compared with RCB scores to assess the sensitivity and specificity of (EOT) 18F-FDG-PET/CT and MRI images. A multinomial logistic regression was performed to assess predictors of pathological response. A p-value of 0.05 was considered significant. Results: 30 patients were included, with 25% showing complete pathological response. EOT 18F-FDG-PET/CT images had a sensitivity of 55% and specificity of 100% to predict RCB &amp;gt; 0, while EOT MRI had a sensitivity of 65% and specificity of 66,6%. Luminal tumors showed significant lower baseline SUVmean and SUVmax values than triple-negative tumors. Ki67 expression didn´t correlate with treatment outcome. High estrogen receptor expression level was significantly associated with non-complete pathological response and higher false negative rates in both EOT 18F-FDG-PET and MRI images (7/8 in PET and 6/7 in MRI). Conclusions: 18F-FDG-PET / CT could be a useful diagnostic tool to assess neoadjuvant chemotherapy treatment response in breast cancer, showing greater specificity than MRI to predict pathological response. A high expression of estrogen receptors could lead to a high rate of false negative findings, both in PET and MRI. A greater number of cases is required to validate these findings. Citation Format: Marco Guarin, M. Eugenia Azar, Carolina Tinetti, M. Dolores Mansilla F., Mauro Namias, Pilar Carballo, Lucia Santamarina, Jorgelina Cavallero, Romina Moreau, Christian Gonzalez, Valeria Caceres, Eduardo Gonzalez, Gabriel Bruno. 18F-FDG-PET/CT and MRI in the assessment of neoadjuvant chemotherapy treatment response in breast cancer. Correlation with pathological response [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS3-27.

Functional Tumor Volume by Fast Dynamic Contrast-Enhanced MRI for Predicting Neoadjuvant Systemic Therapy Response in Triple-Negative Breast Cancer.

Dynamic contrast-enhanced (DCE) MRI is useful for diagnosis and assessment of treatment response in breast cancer. Fast DCE MRI offers a higher sampling rate of contrast enhancement curves in comparison to conventional DCE MRI, potentially characterizing tumor perfusion kinetics more accurately for measurement of functional tumor volume (FTV) as a predictor of treatment response. To investigate FTV by fast DCE MRI as a predictor of neoadjuvant systemic therapy (NAST) response in triple-negative breast cancer (TNBC). Prospective. Sixty patients with biopsy-confirmed TNBC between December 2016 and September 2020. A 3.0 T/3D fast spoiled gradient echo-based DCE MRI ASSESSMENT: Patients underwent MRI at baseline and after four cycles (C4) of NAST, followed by definitive surgery. DCE subtraction images were analyzed in consensus by two breast radiologists with 5 (A.H.A.) and 2 (H.S.M.) years of experience. Tumor volumes (TV) were measured on early and late subtractions. Tumors were segmented on 1 and 2.5-minute early phases subtractions and FTV was determined using optimized signal enhancement thresholds. Interpolated enhancement curves from segmented voxels were used to determine optimal early phase timing. Tumor volumes were compared between patients who had a pathologic complete response (pCR) and those who did not using the area under the receiver operating curve (AUC) and Mann-Whitney U test. About 26 of 60 patients (43%) had pCR. FTV at 1 minute after injection at C4 provided the best discrimination between pCR and non-pCR, with AUC (95% confidence interval [CI])=0.85 (0.74,0.95) (P < 0.05). The 1-minute timing was optimal for FTV measurements at C4 and for the change between C4 and baseline. TV from the early phase at C4 also yielded a good AUC (95%CI) of 0.82 (0.71,0.93) (P < 0.05). FTV and TV measured at 1 minute after injection can predict response to NAST in TNBC. 1 TECHNICAL EFFICACY: 4.

Abstract PS4-30: Neutrophil-to-lymphocyte ratio or platelet-to-lymphocyte ratio as prognostic biomarkers in patients with metastatic breast cancer treated with CDK4/6 inhibitors

Abstract Background: Immune regulation plays an important role in tumor growth and sustainability. The neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) have been reported as peripheral blood surrogates of tumor inflammation and immune response, and have been studied as prognostic markers of treatment response in breast cancer. Cyclin-dependent kinase (CDK) 4/6 inhibitors have shown to enhance the immune response against tumor cells. We aimed to evaluate the impact of NLR and PLR as prognostic biomarkers in patients with estrogen-receptor positive (ER+), human-epidermal growth factor receptor 2 negative (HER2-) metastatic breast cancer (MBC) treated with first line CDK4/6 inhibitors. Methods: This retrospective single cohort study analyzed patients with ER(+)/HER2(-) MBC treated with first line CDK4/6 inhibitors at Albert Einstein Cancer Center. Demographic, clinicopathological, laboratory and treatment characteristics were collected from electronic medical records. Absolute neutrophil count, absolute lymphocyte count and platelet count, were obtained at baseline (T0) and after three months (T3) of treatment with CDK4/6 inhibitors. Optimal cutoff points to define NLR and PLR high vs. low were identified using time-dependent receiver operator curves. Progression free survival (PFS) was calculated from the time of CDK4/6 inhibitor initiation to disease progression, death, or last clinical encounter. PFS was compared among patients with high vs. low ratios at T0 (NLR0HIGH vs. NLR0LOW and PLR0HIGH vs. PLR0LOW) and at T3 (NLR3HIGH vs. NLR3LOW and PLR3HIGH vs. PLR3LOW) of CDK 4/6 inhibitor treatment, using Cox-proportional regression models. Results: A total of 89 patients were evaluated. The median age was 61 years [interquartile range (IQR): 61-69]. Of these, 60% were Non-Hispanic, 40% were Hispanic, 46% were Black, 19% were Caucasian and 6% were Asian. Premenopausal and postmenopausal status was identified in 21% and 75% of patients, respectively. The median Charlson Comorbidity Index (CCI) was 8 [IQR: 7-9]. Visceral metastases were seen in 67% of patients. Palbociclib, Abemaciclib and Ribociclib were used in 78%, 16% and 7% of patients, respectively; with an endocrine therapy backbone of Letrozole, Fulvestrant and Anastrozole in 64%, 24% and 10% of patients, respectively. The median NLR0 and NLR3 were 2.6 [IQR: 1.8-3.6] and 1.3 [IQR: 0.8-2.3], respectively. The median PLR0 and PLR3 were 158 [IQR: 115-250] and 142 [IQR: 94-290], respectively. The cutoff points for defining ratios as being high vs. low for NLR0, NLR3, PLR0, and PLR3 were 3.7, 2.2, 108, and 309, respectively. The median PFS was 10 vs. 19 months for NLR0HIGH vs. NLR0LOW [Hazard Ratio (HR):1.8, 95% Confidence Interval (CI):0.95-3.49, p=0.07] and 12 vs. 19 months for NLR3HIGH vs. NLR3LOW (HR:1.46, CI:0.71-3.00, p=0.3). In multivariable models adjusted for age, CCI, and visceral metastases, neither NLR0(p=0.1) nor NLR3 (p=0.2) was associated with PFS. The median PFS was 13 months vs. not-reached for PLR0HIGH vs. PLR0LOW (HR: 5.5, CI:1.3-23.0, p=0.018), and 32 vs. 16 months for PLR3HIGH vs. PLR3LOW (HR:0.62, CI:0.23-1.64, p=0.3). In multivariable models adjusted for age, CCI, and visceral metastases, an increased PLR0 was associated with worse PFS (HR 4.67, 95%CI 1.1-20, p=0.04), while PLR3 was not associated (p=0.37). Conclusions: Our study is the first in the United States to evaluate NLR and PLR as prognostic biomarkers in MBC patients receiving CDK4/6 inhibitors. PLR0 is a potential biomarker for prognostic stratification in this setting. NLR0, NLR3, and PLR3 were not independent factors for PFS in this setting when other clinicopathological factors were considered. Further studies with a larger sample size are required to validate our results. Citation Format: Ashley Weiner, Laura S. Munoz-Arcos, Heidi Ko, Jesus Anampa. Neutrophil-to-lymphocyte ratio or platelet-to-lymphocyte ratio as prognostic biomarkers in patients with metastatic breast cancer treated with CDK4/6 inhibitors [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS4-30.

Abstract PS7-12: Impact of race/ethnicity on triple negative breast cancer molecular features, treatment response and clinical outcomes in patients receiving neoadjuvant therapy

Abstract Background: Triple negative breast cancer (TNBC) disproportionally impacts Black and Hispanic women and is suggested to be partly responsible for disparities observed in breast cancer mortality. We sought to evaluate the impact of race/ethnicity on TNBC molecular subtype, immune profile, pathologic complete response (pCR) and recurrence free survival (RFS). Methods: The ARTEMIS trial (NCT02276443) uses imaging response and molecular profiling to personalize neoadjuvant chemotherapy in early stage TNBC. After 4 cycles of AC, patients with chemo-sensitive disease receive standard taxane-based therapy, while those with chemo-resistant disease are offered therapeutic trials based upon molecular profiling. Pathologic response was assessed at surgery. Patients self-reported race/ethnicity was categorized as Asian, Black/African-American, Hispanic/Latino and White (non-Hispanic). Patients were excluded if no race or ethnicity was reported. Clinical and pathologic factors were recorded and compared. Gene expression profiling was performed by RNAseq to determine Vanderbilt signature. PD-L1 and Androgen Receptor (AR) were determined by immunohistochemistry. Frequencies at which various factors were observed by race/ethnicity were calculated and Fisher’s exact test performed to determine statistical significance. Kaplan-Meier analysis was used to estimate survival stratified by pCR status and race/ethnicity. Results: Among 321 women enrolled in ARTEMIS, 26 (8.1%) were classified as Asian, 50 (15.6%) as Black, 59 (18.4%) as Hispanic and 186 (57.9%) as White. Demographic and clinical features were similar, except Black women were more likely to have BMI ≥30 (70.0%, p&amp;lt;0.001). Comparing by race/ethnicity, there was no statistically significant difference in tumor histology, tumor size, nodal status, clinical stage, chemo-resistant disease, type of surgery or receipt of radiation. A trend toward higher proportion of N3 disease was observed in Black women (24.0%) compared to other groups (p=0.054). Tumor profiling results are listed in Table 1. No statistically significant difference was observed by race/ethnicity in Vanderbilt signature, presence of PD-L1 or stromal tumor infiltrating lymphocytes (sTIL) status. More AR-positive tumors were identified in Asian women (64%, p=0.007). pCR and RCB status did not significantly vary by race/ethnicity however, higher proportion of RCB-III disease was identified in Black (14%) and Hispanic women (16.9%) as compared to Asian (3.8%) and White (8.6%) women (p=0.164). At median follow up of 23.8 months (range 3.4-51.1), there was no statistically significant difference in RFS by race/ethnicity. Conclusion: Among this population of patients with TNBC treated with neoadjuvant chemotherapy there was no statistically significant difference observed in TNBC Vanderbilt signature, PD-L1 staining, sTIL, pCR or RFS by race/ethnicity. Asian women were found to have a higher incidence of AR-positive subtype. Numerically higher rates of N3 stage in Black women and RCB-III classification in Black and Hispanic women were identified, however not statistically significant. Larger cohorts of patients are needed to further investigate these findings. Table 1. TNBC profiling compared by race/ethnicity.Total n (%)Asian n (%)Black n (%)Hispanic/Latino n (%)White n (%)p valueVanderbilt signature n (%) Basal like (BL1) Basal like 2 (BL2) Immunomodulatory (IM) Luminal androgen receptor (LAR) Mesenchymal (M) Mesenchymal stem-like (MSL) Unstable (UNS)231 50 (21.6) 25 (10.8) 42 (18.2) 22 (9.5) 48 (20.8) 14 (6.0) 30 (13.0)21 (9.1) 0 (0.0) 4 (19.0) 5 (23.8) 3 (14.3) 5 (23.8) 1 (4.8) 3 (14.3)35 (15.2) 9 (25.7) 5 (14.3) 6 (17.1) 2 (5.7) 7 (20.0) 1 (2.9) 5 (14.3)43 (18.6) 14 (32.5) 3 (7.0) 10 (23.2) 5 (11.6) 6 (14.0) 2 (4.7) 3 (7.0)132 (57.1) 27 (20.5) 13 (9.8) 21 (15.9) 12 (9.1) 30 (22.7) 10 (7.6) 19 (14.4)NSAndrogen Receptor n (%) Positive (&amp;gt;=10%) Negative (&amp;lt;10%)311 109 (35.0) 202 (65.0)25 (8.0) 16 (64.0) 9 (36.0)49 (15.8) 11 (22.4) 38 (77.6)57 (18.3) 19 (33.3) 38 (66.7)180 (57.9) 63 (35.0) 117 (65.0)0.007PD-L1 n (%) None &amp;gt;1298 212 (71.1) 86 (28.9)24 (8.1) 15 (62.5) 9 (37.5)47 (15.8) 33 (70.2) 14 (29.8)57 (19.1) 40 (70.2) 17 (29.8)170 (57.0) 124 (72.9) 46 (27.1)NSStromal tumor infiltrating lymphocytes (sTIL) n (%) High (&amp;gt;=20%) Low (&amp;lt;20%)319 107 (33.5) 212 (66.5)26 (8.1) 12 (46.2) 14 (53.8)50 (15.7) 13 (26.0) 37 (74.0)58 (18.2) 21 (36.2) 37 (63.8)185 (58.0) 61 (33.0) 124 (67.0)NS Citation Format: Mediget Teshome, Ryan Sun, Elizabeth E. Ravenberg, Abenaa Brewster, Mariana Chavez-MacGregor, Jason B. White, Stacy Moulder. Impact of race/ethnicity on triple negative breast cancer molecular features, treatment response and clinical outcomes in patients receiving neoadjuvant therapy [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS7-12.

Abstract PS4-11: Identification and validation of stromal immunotype predict survival and benefit from neoadjuvant chemotherapy in patients of breast cancer

Abstract Background Immune infiltration of breast cancer is associated with clinical outcome. A growing number of research suggests the immune response were composed by variously functionally distinct immune cell. But it’s not clear which kinds of cell play the important role. The aim of this study was to determine whether differences in the cellular composition of the immune infiltrate in breast cancer influence survival and treatment response, and construct a stromal immunotype which could predict the response of neoadjuvant therapy and survival. Patients and Methods A total of 1502 ER negative breast cancers from TCGA and METABRIC cohort were used to infer the proportions of 22 subsets of immune cells, Another 320 ER negative breast cancer patients from Guangdong Provincial People’s Hospital in the validation cohort were also included in the study. Immune cell infiltration was evaluated by immunohistochemical staining or CIBERSORT method, Five immune features were selected out of 22 immune features to construct immunotype based on LASSO Cox regression model. ResultOf the cell subsets investigated, CD8+ T cells (hazard ratio [HR] = 0.064, 95% CI 0.018-0.234; p &amp;lt; 0.001), CD4+ T cells (HR 0.072, 95% CI 0.013-0.382; p = 0.002), B cells (HR 0.04, 95% CI 0.005-0.340; p = 0.003) , M1 macrophages(HR 0.09, 95% CI 0.016-0.502; p = 0.006) were associated with favourable outcome. T regulatory cells(HR 10.791, 95% CI 2.059-58.444; p = 0.005) emerged as the most strongly associated with poor outcome. Using the LASSO model, we classified ER negative breast cancer patients into stromal immunotype A subgroup (CD8+T cellshigh CD4+T cellshigh B cellhigh M1 macrophageshigh Treglow) and stromal immunotype B subgroup (CD8+T cellslow CD4+T cellslow B celllow M1 macrophageslow Treg high). Significant differences were found between immunotype A and immunotype B in the combined cohort with 10-year overall survival (66.2% vs. 49.8%; P&amp;lt;0.001) and 10-year disease-free survival (63.8% vs. 44.4%; P&amp;lt;0.001). Stromal immunotype was revealed to be an independent prognostic indicator in multivariate analysis in all cohorts separately, and also showed to be related to pCR in neoadjuvant chemotherapy. Finally, stromal immunotype A showed higher immune checkpoint molecules (PD-L1, PD-1, CTLA-4) expression and three important cytokines expression profiles (IL-2, INF-γ and TGF-β). Conclusion The stromal immunotypes could predict survival and recurrence of ER negative breast cancer patients effectively. Furthermore, the immunotypes might be a practical predictive tool for immunotherapy and neoadjuvant chemotherapy. Citation Format: Fei Ji, Ciqiu Yang, Liulu Zhang, Mei Yang, Jieqing Li, Hongfei Gao, Teng Zhu, Minyi Cheng, Kun Wang. Identification and validation of stromal immunotype predict survival and benefit from neoadjuvant chemotherapy in patients of breast cancer [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS4-11.