PTEN in triple-negative breast carcinoma: protein expression and genomic alteration in pretreatment and posttreatment specimens

Background

Recent advances have been made in targeting the phosphoinositide 3-kinase pathway in breast cancer. Phosphatase and tensin homolog (PTEN) is a key component of that pathway.

Objective

To understand the changes in PTEN expression over the course of the disease in patients with triple-negative breast cancer (TNBC) and whether PTEN copy number variation (CNV) by next-generation sequencing (NGS) can serve as an alternative to immunohistochemistry (IHC) to identify PTEN loss.

Methods

We compared PTEN expression by IHC between pretreatment tumors and residual tumors in the breast and lymph nodes after neoadjuvant chemotherapy in 96 patients enrolled in a TNBC clinical trial. A correlative analysis between PTEN protein expression and PTEN CNV by NGS was also performed.

Results

With a stringent cutoff for PTEN IHC scoring, PTEN expression was discordant between pretreatment and posttreatment primary tumors in 5% of patients (n = 96) and between posttreatment primary tumors and lymph node metastases in 9% (n = 33). A less stringent cutoff yielded similar discordance rates. Intratumoral heterogeneity for PTEN loss was observed in 7% of the patients. Among pretreatment tumors, PTEN copy numbers by whole exome sequencing (n = 72) were significantly higher in the PTEN-positive tumors by IHC compared with the IHC PTEN-loss tumors (p < 0.0001). However, PTEN-positive and PTEN-loss tumors by IHC overlapped in copy numbers: 14 of 60 PTEN-positive samples showed decreased copy numbers in the range of those of the PTEN-loss tumors.

Conclusion

Testing various specimens by IHC may generate different PTEN results in a small proportion of patients with TNBC; therefore, the decision of testing one versus multiple specimens in a clinical trial should be defined in the patient inclusion criteria. Although a distinct cutoff by which CNV differentiated PTEN-positive tumors from those with PTEN loss was not identified, higher copy number of PTEN may confer positive PTEN, whereas lower copy number of PTEN would necessitate additional testing by IHC to assess PTEN loss.

Trial registration

NCT02276443.

PD-L1 (22C3) Expression Correlates with Clinical and Molecular Features of Lung Adenocarcinomas in Cytological Samples

INTRODUCTION

PD-L1 expression is the most widely used predictive marker for immune checkpoint inhibitor (ICI) therapy in patients with lung adenocarcinoma. However, the current understanding of the association between PD-L1 expression and treatment response is suboptimal. A significant percentage of patients have only a cytological specimen available for clinical management. Therefore, it is relevant to examine the impact of molecular features on PD-L1 expression in cytological samples and how it might correlate with a therapeutic response.

METHODS

We evaluated patients diagnosed with adenocarcinoma of the lung who had both in-house targeted next-generation sequencing analysis and paired PD-L1 (22C3) immunohistochemical staining performed on the same cell blocks. We explored the association between molecular features and PD-L1 expression. In patients who underwent ICIs therapy, we assessed how a specific gene mutation impacted a therapeutic response.

RESULTS

145 patients with lung adenocarcinoma were included in this study. PD-L1-high expression was found to be more common in pleural fluid than in other sample sites. Regional lymph node samples showed a higher proportion of PD-L1-high expression (29%) compared with lung samples (6%). The predictive value of PD-L1 expression was retained in cytological samples. Mutations in KRAS were also associated with a PD-L1-high expression. However, tumors with TP53 or KRAS mutations showed a lower therapy response rate regardless of the PD-L1 expression.

CONCLUSION

Cytological samples maintain a predictive value for PD-L1 expression in patients with lung adenocarcinoma as regards the benefit of ICI treatment. Specific molecular alterations additionally impact PD-L1 expression and its predictive value.

A Radiomics Model Based on Synthetic MRI Acquisition for Predicting Neoadjuvant Systemic Treatment Response in Triple-Negative Breast Cancer

Purpose To determine if a radiomics model based on quantitative maps acquired with synthetic MRI (SyMRI) is useful for predicting neoadjuvant systemic therapy (NAST) response in triple-negative breast cancer (TNBC). Materials and Methods In this prospective study, 181 women diagnosed with stage I-III TNBC were scanned with a SyMRI sequence at baseline and at midtreatment (after four cycles of NAST), producing T1, T2, and proton density (PD) maps. Histopathologic analysis at surgery was used to determine pathologic complete response (pCR) or non-pCR status. From three-dimensional tumor contours drawn on the three maps, 310 histogram and textural features were extracted, resulting in 930 features per scan. Radiomic features were compared between pCR and non-pCR groups by using Wilcoxon rank sum test. To build a multivariable predictive model, logistic regression with elastic net regularization and cross-validation was performed for texture feature selection using 119 participants (median age, 52 years [range, 26-77 years]). An independent testing cohort of 62 participants (median age, 48 years [range, 23-74 years]) was used to evaluate and compare the models by area under the receiver operating characteristic curve (AUC). Results Univariable analysis identified 15 T1, 10 T2, and 12 PD radiomic features at midtreatment that predicted pCR with an AUC greater than 0.70 in both the training and testing cohorts. Multivariable radiomics models of maps acquired at midtreatment demonstrated superior performance over those acquired at baseline, achieving AUCs as high as 0.78 and 0.72 in the training and testing cohorts, respectively. Conclusion SyMRI-based radiomic features acquired at midtreatment are potentially useful for identifying early NAST responders in TNBC. Keywords: MR Imaging, Breast, Outcomes Analysis ClinicalTrials.gov registration no. NCT02276443 Supplemental material is available for this article. © RSNA, 2023 See also the commentary by Houser and Rapelyea in this issue.

Predictive Roles of Baseline Stromal Tumor-Infiltrating Lymphocytes and Ki-67 in Pathologic Complete Response in an Early-Stage Triple-Negative Breast Cancer Prospective Trial

High stromal tumor-infiltrating lymphocytes (sTILs) are associated with improved pathologic complete response (pCR) in triple-negative breast cancer (TNBC). We hypothesize that integrating high sTILs and additional clinicopathologic features associated with pCR could enhance our ability to predict the group of patients on whom treatment de-escalation strategies could be tested. In this prospective early-stage TNBC neoadjuvant chemotherapy study, pretreatment biopsies from 408 patients were evaluated for their clinical and demographic features, as well as biomarkers including sTILs, Ki-67, PD-L1 and androgen receptor. Multivariate logistic regression models were developed to generate a computed response score to predict pCR. The pCR rate for the entire cohort was 41%. Recursive partitioning analysis identified ≥20% as the optimal cutoff for sTILs to denote 35% (143/408) of patients as having high sTILs, with a pCR rate of 59%, and 65% (265/408) of patients as having low sTILs, with a pCR rate of 31%. High Ki-67 (cutoff > 35%) was identified as the only predictor of pCR in addition to sTILs in the training set. This finding was verified in the testing set, where the highest computed response score encompassing both high sTILa and high Ki-67 predicted a pCR rate of 65%. Integrating Ki67 and sTIL may refine the selection of early stage TNBC patients for neoadjuvant clinical trials evaluating de-escalation strategies.

Mutations in Homologous Recombination Genes and Loss of Heterozygosity Status in Advanced-Stage Breast Carcinoma

Poly (adenosine diphosphate-ribose) polymerase inhibitors (PARPis) have demonstrated antitumor activity in cancers with a homologous recombination deficiency (HRD) and have recently been approved by the FDA for the treatment of germline BRCA1/2-mutation-associated breast cancer. PARPis have also been found to be efficacious in BRCA wild-type (BRCAwt) lesions with high genomic loss of heterozygosity (LOH-high). The goal of this study was to retrospectively investigate the tumor mutations in homologous recombination (HRR) genes and the LOH score in advanced-stage breast carcinomas (BCs). Sixty-three patients were included in our study, 25% of whom had HRR gene mutations in their tumors, including 6% BRCA1/2 and 19% non-BRCA-containing gene mutations. An HRR gene mutation was associated with a triple-negative phenotype. Twenty-eight percent of the patients had an LOH-high score, which, in turn, was associated with a high histological grade, a triple-negative phenotype, and a high tumor mutational burden (TMB). Among the six patients who received PARPi therapy, one had a tumor with a PALB2 mutation other than BRCA and had a clinical partial response. Twenty-two percent of the LOH-low tumors had BRCAwt-HRR gene mutations, compared with 11% of the LOH-high tumors. Comprehensive genomic profiling revealed a subset of breast cancer patients with a BRCAwt-HRR gene mutation that would be missed by an LOH test. The necessity of next-generation sequencing coupled with HRR gene analysis for PARPi therapy requires further investigation in clinical trials.

A phase II study of neoadjuvant atezolizumab and nab-paclitaxel in patients with anthracycline-resistant early-stage triple-negative breast cancer

PURPOSE

Neoadjuvant anti-PD-(L)1 therapy improves the pathological complete response (pCR) rate in unselected triple-negative breast cancer (TNBC). Given the potential for long-term morbidity from immune-related adverse events (irAEs), optimizing the risk-benefit ratio for these agents in the curative neoadjuvant setting is important. Suboptimal clinical response to initial neoadjuvant therapy (NAT) is associated with low rates of pCR (2-5%) and may define a patient selection strategy for neoadjuvant immune checkpoint blockade. We conducted a single-arm phase II study of atezolizumab and nab-paclitaxel as the second phase of NAT in patients with doxorubicin and cyclophosphamide (AC)-resistant TNBC (NCT02530489).

METHODS

Patients with stage I-III, AC-resistant TNBC, defined as disease progression or a < 80% reduction in tumor volume after 4 cycles of AC, were eligible. Patients received atezolizumab (1200 mg IV, Q3weeks × 4) and nab-paclitaxel (100 mg/m² IV,Q1 week × 12) as the second phase of NAT before undergoing surgery followed by adjuvant atezolizumab (1200 mg IV, Q3 weeks, × 4). A two-stage Gehan-type design was employed to detect an improvement in pCR/residual cancer burden class I (RCB-I) rate from 5 to 20%.

RESULTS

From 2/15/2016 through 1/29/2021, 37 patients with AC-resistant TNBC were enrolled. The pCR/RCB-I rate was 46%. No new safety signals were observed. Seven patients (19%) discontinued atezolizumab due to irAEs.

CONCLUSION

This study met its primary endpoint, demonstrating a promising signal of activity in this high-risk population (pCR/RCB-I = 46% vs 5% in historical controls), suggesting that a response-adapted approach to the utilization of neoadjuvant immunotherapy should be considered for further evaluation in a randomized clinical trial.

Abstract 2147: Decoding the natural biology of triple-negative breast cancer and response to chemotherapy by single-cell transcriptomics

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer that lacks the expression of estrogen receptor (ER), progesterone receptor (PR) and HER2 and therefore have limited hormonal treatment options. Neoadjuvant chemotherapy (NAC) is backbone of treatment for TNBC, and about 50% of patients respond well leading to pathological complete response (pCR). However, the remaining patients develop resistance to NAC and progress to metastatic disease and poor survival in 1-2 years after the initial treatment. Previous studies have performed bulk RNA expression profiling of TNBC patients and identified 5-6 subgroups of patients, however these studies could not resolve expression programs at single cell resolution to distinguish between the tumor cells and different components of the tumor microenvironment (TME). Here we performed scRNA-seq of pre-treatment fresh core biopsy tissue samples from TNBC patients in the ARTEMIS clinical trial and compared these data between pCR and non-pCR patients to identify programs associated with response to NAC. We also compared these data to scRNA-seq data from patients with disease-free breast tissue to understand the basic biology of TNBC and identify cell types that are reprogrammed in malignant disease. Using the single cell tumor cell data, we identified 4 archetypes of TNBC which represent patient-level intertumor expression programs: luminal secretory-like (LS), basal/luminal-like (BL), immunoregulatory (IM), and luminal androgen receptor (LAR). Notably, the archetype BL was associated with non-pCR, while IM was associated with pCR. We further identified 13 metatraits, which are unique intratumoral expression programs that are shared across patients. Across the cancer cells, we identified 13 metatraits such as cell cycling, stress, hypoxia, interferon response, HLA, partial epithelial-mesenchymal transition, and endoplasmic reticulum stress, many of which corresponded to NAC response. In the immune compartment, we found 15 myeloid cell states, 14 T/NK cell states, and 6 B cell states, several of which corresponded to pCR/non-pCR. Similarly, in the stromal compartment, there were 4 fibroblast cell states, 4 pericyte cell states, and 7 endothelial cell subtypes, of which several cell states were associated with NAC response. Overall, these data report the natural biology of TNBC patients and malignant cell states that are reprogrammed in malignant disease, as well as their correspondence to NAC response, providing new data to predict which TNBC patients are likely to respond to chemotherapy.

Citation Format: Tapsi Kumar, Yiyun Lin, Yun Yan, Shanshan Bai, Jianzhuo Li, Tuan Tran, Min Hu, Elizabeth Ravenberg, Maia Rauch, Alyson Clayborn, Alastair Thompson, Lei Huo, Stacy Moulder, Clinton Yam, Nicholas Navin. Decoding the natural biology of triple-negative breast cancer and response to chemotherapy by single-cell transcriptomics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2147.

High prevalence of vertebral deformity in tumor-induced osteomalacia associated with impaired bone microstructure

PURPOSE

Patients with tumor-induced osteomalacia (TIO) often suffer from irreversible height loss due to vertebral deformity. However, the prevalence of vertebral deformity in TIO patients varies among limited studies. In addition, the distribution and type of vertebral deformity, as well as its risk factors, remain unknown. This study aimed to identify the prevalence, distribution, type and risk factors for vertebral deformity in a large cohort of TIO patients.

METHODS

A total of 164 TIO patients were enrolled in this retrospective study. Deformity in vertebrae T4-L4 by lateral thoracolumbar spine radiographs was evaluated according to the semiquantitative method of Genant. Bone microstructure was evaluated by trabecular bone score (TBS) and high-resolution peripheral QCT (HR-pQCT).

RESULTS

Ninety-nine (99/164, 60.4%) patients had 517 deformed vertebrae with a bimodal pattern of distribution (T7-9 and T11-L1), and biconcave deformity was the most common type (267/517, 51.6%). Compared with patients without vertebral deformity, those with vertebral deformity had a higher male/female ratio, longer disease duration, more height loss, lower serum phosphate, higher bone turnover markers, lower TBS, lower areal bone mineral density (aBMD), lower peripheral volumetric BMD (vBMD) and worse microstructure. Lower trabecular vBMD and worse trabecular microstructure in the peripheral bone and lower spine TBS were associated with an increased risk of vertebral deformity independently of aBMD. After adjusting for the number of deformed vertebrae, we found little difference in clinical indexes among the patients with different types of vertebral deformity. However, we found significant correlations of clinical indexes with the number of deformed vertebrae and the spinal deformity index.

CONCLUSION

We reported a high prevalence of vertebral deformity in the largest cohort of TIO patients and described the vertebral deformity in detail for the first time. Risk factors for vertebral deformity included male sex, long disease duration, height loss, abnormal biochemical indexes and bone impairment. Clinical manifestation, biochemical indexes and bone impairment were correlated with the number of deformed vertebrae and degree of deformity, but not the type of deformity.

Abstract P6-01-06: Multi-Parametric MRI-Based Radiomics Models from Tumor and Peritumoral Regions as Potential Predictors of Treatment Response to Neoadjuvant Systemic Therapy in Triple Negative Breast Cancer Patients

PURPOSE Triple negative breast cancer (TNBC) is an aggressive and heterogeneous subtype of breast cancer. Pathologic complete response (pCR) to neoadjuvant systemic therapy (NAST) predicts better survival. Early prediction of the treatment response can potentially triage non-responding patients to alternative protocol treatments, spare them of the unneeded toxicity, and improve pCR. We evaluated the ability of radiomic textural analysis of intratumoral and peritumoral regions on the dynamic contrast enhanced (DCE) and diffusion-weighted imaging (DWI) MRI images obtained early during NAST to predict pCR. MATERIALS AND METHODS This IRB-approved prospective study (NCT02276443) included 182 patients with biopsy proven stage I-III TNBC who had multiparametric MRIs at baseline (BL), post 2 cycles (C2), and post 4 cycles (C4) of NAST before surgery. Tumors and peritumoral regions of 5 mm and 10 mm in thickness were segmented on the 2.5 minutes DCE subtraction images and on the b=800 DWI images. Ten histogram-based first order texture features including mean, minimum, maximum, standard deviation, kurtosis, skewness, 1st, 5th, 95th, and 99th percentile, and 300 radiomic Grey Level Co-occurrence matrix (GLCM) features along with their absolute and relative differences between the 3 imaging time points were extracted from the tumors and from the peritumoral regions with an in-house Matlab toolbox. Treatment response at surgery (pCR vs non-pCR) was documented. The samples were divided into training and testing datasets by a 2:1 ratio. Area under the receiver operating characteristics curve (AUC ROC) was calculated for univariate analysis in predicting pCR. Logistic regression with elastic net regularization was performed for texture feature selection. Parameter optimization was performed by using 5-fold cross-validation based on mean cross-validated AUC in the training set. RESULTS Of 182 TNBC patients, 88 (48%) had pCR and 94 (52%) did not achieve pCR. Eight multivariate models combining radiomic features from both DCE and DWI tumoral and peritumoral regions had AUC &gt; 0.8 (0.807-0.831) with p-value &lt; 0.001 in both training and testing sets. The highest AUC=0.831 was obtained from a model consisting of 15 radiomic features: tumor DWI (5 GLCM features) at C2, peritumoral region on DCE (skewness) at C2, tumor DCE (1st, 5th percentile) at C4, tumor DWI (3 GLCM features) at C4, peritumoral region DWI (1 GLCM feature) at C4, and the relative difference between C4/C2 on DCE (5th, 95th percentile and mean). CONCLUSION Multi-parametric MRI-based radiomics models from the tumor and the peritumoral regions showed high accuracy as potential early predictors of NAST response in TNBC patients.

Citation Format: Rania M. Mohamed, Bikash Panthi, Beatriz Adrada, Rosalind Candelaria, Mary S. Guirguis, Wei Yang, Medine Boge, Miral Patel, Nabil Elshafeey, Sanaz Pashapoor, Zijian Zhou, Jong Bum Son, Ken-Pin Hwang, H. T. Carisa Le-Petross, Jessica Leung, Marion E. Scoggins, Gary J. Whitman, Zhan Xu, Deanna L. Lane, Tanya Moseley, Frances Perez, Jason White, Elizabeth Ravenberg, Alyson Clayborn, Mark Pagel, Huiqin Chen, Jia Sun, Peng Wei, Alastair M. Thompson, Stacy Moulder, Anil Korkut, Lei Huo, Kelly K. Hunt, Jennifer K. Litton, Vicente Valero, Debu Tripathy, Clinton Yam, Jingfei Ma, Gaiane Rauch. Multi-Parametric MRI-Based Radiomics Models from Tumor and Peritumoral Regions as Potential Predictors of Treatment Response to Neoadjuvant Systemic Therapy in Triple Negative Breast Cancer Patients [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P6-01-06.

Abstract P6-01-34: Longitudinal DCE-MRI Radiomic Models for Early Prediction of Response to Neoadjuvant Systemic Therapy (NAST) in Triple Negative Breast Cancer (TNBC) Patients

Background and Purpose Early prediction of neoadjuvant systemic therapy (NAST) response in triple negative breast cancer (TNBC) patients could potentially aid in the selection of alternative therapies and avoid unnecessary toxicity in patients unlikely to achieve pathologic complete response (pCR) with NAST. In this study, we investigated the radiomic features of the peritumoral and the tumoral regions from dynamic contrast enhanced (DCE) MRI acquired at different time points of NAST for early treatment response prediction in TNBC. Methods and Materials This study included 182 biopsy-confirmed stage I-III TNBC patients enrolled in an IRB approved prospective clinical trial (NCT02276433). All patients underwent DCE-MRI on a GE 3T MRI scanner at baseline (BL), after two (C2) and four (C4) cycles of doxorubicin/cyclophosphamide based chemotherapy and before surgery. The peritumoral and the tumoral regions were segmented manually by two fellowship-trained radiologists using early phase (2.5 min) DCE-MRI subtraction images. Ten first order radiomic features, 300 grey-level-co-occurrence matrix (GLCM) features along with their absolute and relative differences (C4/BL, C2/BL, C4/C2) between the 3 imaging time points were extracted from the peritumoral and the tumoral regions. Patients were randomly divided into training and testing sets in a 2:1 ratio. For univariate analysis, area under the receiver operating characteristics curve (AUC ROC) was measured to determine the features most predictive of pCR/non-pCR. Wilcoxon Rank Sum test was used to test the statistical significance of predictive performance. In multivariate analysis, radiomic models were established using logistic regression with elastic net regularization followed by 5-fold cross validation for performance assessment. Results Eighty-eight (48%) patients had pCR (59 training, 29 testing) and 94 (52%) patients had non-pCR (63 training, 31 testing). Twenty-five radiomic features (4 from peritumoral C4, 5 from tumoral C4, 4 from peritumoral C4/BL, 6 from tumoral C4/BL, 2 from peritumoral C4/C2 and 4 from tumoral C4/C2) were statistically significant with AUC ≥ 0.75 in both the training and the testing sets at the univariate analysis. The significant features at C4 had AUCs of 0.75-0.79 for the training set and 0.76-0.81 for the testing set. Changes measured between C4 and BL or C2 showed AUC of 0.76-0.84 in the training and 0.75-0.81 in the testing datasets. Eleven multivariate regression models comprised of radiomic features at BL, C2, C4 and their changes (C4/BL, C4/C2 and C2/BL) showed an AUC of 0.80-0.84 for cross validation and an AUC of 0.80-0.82 for independent testing. Conclusions Radiomic models using longitudinal DCE MRI parameters of peritumoral and tumoral regions during NAST have the potential to predict pCR in TNBC patients undergoing NAST.

Citation Format: Bikash Panthi, Rania M. Mohamed, Beatriz Adrada, Rosalind Candelaria, Mary S. Guirguis, Wei Yang, Medine Boge, Miral Patel, Nabil Elshafeey, Sanaz Pashapoor, Zijian Zhou, Jong Bum Son, Ken-Pin Hwang, H. T. Carisa Le-Petross, Jessica Leung, Marion E. Scoggins, Gary J. Whitman, Zhan Xu, Deanna L. Lane, Tanya Moseley, Frances Perez, Jason White, Elizabeth Ravenberg, Alyson Clayborn, Mark Pagel, Huiqin Chen, Jia Sun, Peng Wei, Alastair M. Thompson, Stacy Moulder, Anil Korkut, Lei Huo, Kelly K. Hunt, Jennifer K. Litton, Vicente Valero, Debu Tripathy, Clinton Yam, Jingfei Ma, Gaiane Rauch. Longitudinal DCE-MRI Radiomic Models for Early Prediction of Response to Neoadjuvant Systemic Therapy (NAST) in Triple Negative Breast Cancer (TNBC) Patients [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P6-01-34.

Abstract HER2-01: HER2-01 Clinical and Molecular Characteristics of HER2-low/zero Early Stage Triple-Negative Breast Cancer

Background: In the metastatic setting, low HER2 expression is associated with clinical benefit from trastuzumab deruxtecan, a HER2-targeting antibody drug conjugates. However, little is known about the biological significance of low HER2 expression in patients with early stage triple-negative breast cancer (TNBC) receiving neoadjuvant therapy (NAT). Methods: Out of 595 patients with stage I-III TNBC enrolled on the prospective ARTEMIS trial (NCT02276443) from 2015-2021, we identified 367 patients with available HER2 immunohistochemistry (IHC) results on pre-NAT tumor tissue (HER2-zero: n=218; HER2-low [IHC 1+, 2+]: n=149). All patients were treated with anthracycline-based NAT. In cases where sufficient pre-NAT tumor tissue were available, additional IHC and/or RNAseq were performed. Differential gene expression (DGE) and pathway analysis were performed using DEseq2. Gene set enrichment analysis (GSEA) was performed using the Hallmark gene sets. Deconvolution analyses were performed using CIBERSORT. We controlled for multiple hypothesis using a false discovery rate (FDR) threshold with the Benjamini-Hochberg method, accepting as significant genes with at least a 2-fold change and &lt; 5% FDR. Results: Table 1 summarizes baseline clinicopathological features of the 367 patients. Compared to HER2-zero tumors, HER2-low tumors were less likely of metaplastic histology (p=0.001), associated with lower Ki67 (p=0.017) and were more likely to be androgen receptor (AR)-positive (p=0.01). There were no significant differences in tumor-infiltrating lymphocytes (TILs) infiltration and PD-L1 expression between HER2-zero and HER2-low tumors. Among the 226 patients with sufficient pre-NAT tissue for RNAseq, DGE analyses demonstrated upregulation of genes involved in fatty acid metabolism (ACSM1) and steroid hormone metabolism (DHRS2, UGT2B28) in HER2-low tumors compared with HER2-zero tumors. Deconvolution analyses revealed no significant differences between predicted proportions of immune cell subpopulations between HER2-low and HER2-zero tumors. Although rates of pCR were not significantly different between patients with HER2-zero (46%) and HER2-low tumors (40%) (p=0.34), non-pCR in patients with HER2-low tumors was associated with increased expression of EREG, which encodes an EGFR ligand, while non-pCR in patients with HER2-zero tumors was associated with downregulation in genes involved in immune response pathways. GSEA further identified the Hallmark allograft rejection (FDR q=0.001), interferon gamma response (FDR q=0.002), and interferon alpha response pathways (FDR q=0.007) as the 3 most significantly downregulated pathways in HER2-zero tumors from patients experiencing a non-pCR relative to HER2-zero tumors from patients experiencing a pCR. Conclusion: In early stage TNBC, low HER2 expression is associated with increased AR expression and upregulation of genes associated with fatty acid and steroid hormone metabolism. Gene expression analyses suggest that drivers of resistance to NAT differ between HER2-low and HER2-zero tumors. Biological differences between HER2-zero and HER2-low tumors exist and may influence future personalized treatment for patients with early stage TNBC.

Citation Format: Clinton Yam, Ziyi Li, Anil Korkut, Wencai Ma, Elisabeth Kong, Holly A. Hill, Hussein Abbas, Sausan Abouharb, Beatriz Adrada, Banu K. Arun, Carlos H. Barcenas, Ajit Bisen, Daniel Booser, Aman Buzdar, Rosalind Candelaria, Junjie Chen, Alyson Clayborn, Senthil Damodaran, Qingqing Ding, Haven Garber, Gabriel N. Hortobagyi, Kelly K. Hunt, Nuhad K. Ibrahim, Adaeze Iheme, Meghan S. Karuturi, Kimberly Koenig, Rachel M. Layman, Jangsoon Lee, Jennifer K. Litton, Melissa Mitchell, Giancarlo Moscol, Jason Mouabbi, Rashmi K. Murthy, Oluchi Oke, Paula Pohlmann, David Ramirez, Elizabeth Ravenberg, Sadia Saleem, Mediget Teshome, Vicente Valero, Jason White, Madison Williams, Wendy Woodward, Chasity Yajima, Naoto T. Ueno, Ken Chen, Gaiane Rauch, Lei Huo, Debu Tripathy. HER2-01 Clinical and Molecular Characteristics of HER2-low/zero Early Stage Triple-Negative Breast Cancer [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr HER2-01.

[Preliminary study on the ability of 68Ga-Pentixafor PET/CT to differentiate between adrenal aldosterone-producing adenoma and nonfunctional adenoma]

Objective: To evaluate the ability of ⁶⁸Ga-Pentixafor (nuclide ligand imaging agents for chemokine receptor 4) PET/CT to differentiate between aldosterone-producing adenoma (APA) and adrenal nonfunctional adenoma (NFA), and to assess how well this imaging method correlates with clinical features and postoperative outcomes. Methods: This was a cross-sectional study involving 73 APA and 12 NFA patients who received ⁶⁸Ga-Pentixafor PET/CT imaging at Peking Union Medical College Hospital from August 2018 to October 2021. The receiver operating characteristic (ROC) curve was used to evaluate the differential value of visual analysis and the maximum standard uptake value (SUV_max) of the focus on APA and NFA. The related factors of SUV_max, and its predictive effect on postoperative outcomes were analyzed using Pearson or Spearman analysis and χ² text. Results: ⁶⁸Ga-Pentixafor PET/CT imaging was positive in 64 APA patients (sensitivity=87.7%) and negative in all 12 NFA patients (specificity=100%). The area under the ROC curve with SUV_max differentiating APA and NFA was 0.932 (P<0.001). When the SUV_max cut-off point was 6.23, the sensitivity was 80.8% and the specificity was 100%. The SUV_max correlated positively with lesion size (r=0.598) and aldosterone/renin activity ratio (r=0.313) and correlated negatively with potassium level (r=-0.286), renin activity (r=-0.240) and age of diagnosis (r=-0.273) (all P<0.05). Of the patients who underwent adrenalectomy and received more than 6 months of post-surgical follow-up, the clinical complete remission rate was higher for ⁶⁸Ga-Pentixafor PET/CT imaging-positive patients than imaging-negative patients (24/39 vs. 0/4, P=0.031). Conclusions: ⁶⁸Ga-Pentixafor PET/CT is effective at differentiating between APA and NFA. The SUV_max of ⁶⁸Ga-Pentixafor PET/CT correlates with age at onset, lesion size, and the severity of clinical manifestations, and is able to predict postoperative outcomes.

Abstract P1-05-15: DCE-MRI for early prediction of excellent response versus chemoresistance in triple negative breast cancer

PURPOSE Triple-negative breast cancer (TNBC) is a heterogeneous disease with variable response to neoadjuvant therapy (NAT). Pathologic complete response (pCR) has become a prognostic marker for overall and disease-free survival. The aim of this study was to determine if dynamic contrast-enhanced (DCE)-MRI after 2 and/or 4 cycles of NAT can identify patients with a high likelihood of achieving pCR, triaging them to standard of care (SOC), or, when appropriate, to de-escalation trials. Conversely, we aimed to identify chemoresistant tumors that are unlikely to achieve pCR and may benefit from escalated targeted trials.

METHOD AND MATERIALS 309 patients with stage I-III TNBC underwent DCE-MRI (temporal resolution: 9-12 sec) at baseline (BL), 2 cycles (C2), and 4 cycles (C4) of SOC doxorubicin/cyclophosphamide (AC) NAT as part of a prospective IRB-approved study (NCT02276443). Tumor volumes of the index lesion were calculated using 3 axis measurements during the early phase of the DCE-MRI (60s). Percent tumor volume reduction (TVR) between BL, C2, and C4 was calculated. Patients were randomly assigned to a training or a validation cohort in a 1:1 ratio. pCR was assessed at surgery after completion of SOC NAT. Correlation between pCR and TVR was evaluated using ROC analysis.

RESULTS Of 309 TNBC patients, 136 (44%) achieved pCR. Following 2 cycles of NAT, TVR &gt;80% was predictive of pCR (chemosensitivity), while TVR ≤ 55% was predictive of non-pCR (chemoresistance) with PPV 80%, NPV 89%, AUC 0.811 (0.73~0.893, p&lt; 0.0001) in the training cohort, and PPV 82%, NPV 85%, AUC 0.815 (CI:0.736~0.894, p&lt; 0.0001) in the validation cohort. Following 4 cycles of NAT, TVR &gt;90% was predictive of pCR, while TVR ≤80% was predictive of non-pCR with PPV 80%, NPV 84%, AUC 0.827 (0.756~0.898, p&lt; 0.0001) in the training cohort and with PPV 73%, NPV 82%, AUC 0.785 (CI:0.709~0.862, p&lt; 0.001) in the validation cohort. Using this model, the pCR status was correctly classified in 50% of TNBC patients using C2 DCE-MRI in the training cohort, and 54% in the validation cohort. Only 8% were misclassified in the training cohort, and 10% in the validation cohort. Using C4 DCE-MRI, the pCR status of 61% and 57% of TNBC was correctly classified in the validation and the testing cohorts, respectively. 12% were misclassified in the validation cohort, and 21% in the testing cohort.

CONCLUSION DCE-MRI after 2 and 4 cycles of AC-based NAT correctly predicted the pCR status of 54% and 57% of TNBC patients, respectively, as either excellent responders or nonresponders with high AUC 0.811 and 0.827. This may allow patients to be triaged to SOC NAT with option of de-escalation or early targeted therapies for non-responders.

Breast Cancer With a HER2 FISH Group 2 Result: Should HER2 Tests be Repeated?

BACKGROUND

Breast cancer with fluorescence in situ hybridization (FISH) group 2 pattern (HER2 <4 and HER2/CEP17 ratio ≥2, a subset of monosomy CEP17) was historically considered HER2-positive, but mostly HER2-negative according to updated 2018 American Society of Clinical Oncology (ASCO)/College of American Pathologists (CAP) guidelines unless 3+ by immunohistochemistry (IHC). Therapeutic relevance of this group remained elusive, therefore we assessed if repeat IHC and FISH can assist final HER2 classification.

PATIENT AND METHODS

We retrospectively reviewed HER2 FISH performed at our institution from 2014 to 2018 and identified 23 of 3554 (0.6%) breast cancer cases with at least one-time measurement of HER2 FISH categorized as group 2. Repeat HER2 tests were performed for cases with available alternative tumor samples and compared with initial testing following 2018 ASCO/CAP guidelines.

RESULTS

Only 1 of 23 group 2 cases was HER2-positive, 0/18 in primary and 1/5 in metastatic/recurrent tumors. Of 13 primary tumors with repeat HER2 results; 10 (77%) remained HER2-negative; 3 (23%) changed from HER2-negative (group 2 and IHC 2+) to HER2-positive (group 1 and IHC 2+). Among 8 of these 13 patients receiving neoadjuvant systemic therapy containing anti-HER2 agent, 3 (38%) achieved pathologic complete response (pCR). Two of 3 pCR cases were HER2-positive converters on repeat testing. Three pCR cases were ER-negative or -low positive and Ki67 ≥40%, while 5 partial responders were ER-positive and Ki67 <40% (P < .05).

CONCLUSION

Breast cancer with HER2 FISH group 2 result may represent heterogeneous populations of tumor cells being originated de novo or preferentially selected secondary to therapy. Repeat HER2 tests on alternative samples may be considered to guide anti-HER2 therapy.

SOX17: A Highly Sensitive and Specific Immunomarker for Ovarian and Endometrial Carcinomas

PAX8 is the most commonly used immunomarker to link a carcinoma to the gynecologic tract; however, it lacks specificity. Through mining The Cancer Genome Atlas mRNA expression profile data, we identified SOX17 as a potential specific marker at the mRNA level for gynecologic tumors. To evaluate the utility of this marker in the identification of the gynecologic origin of a given carcinoma, we performed immunochemical staining in a large cohort of ovarian and endometrial cancer cases (n = 416), together with a large cohort of solid tumors from other organs (n = 1544) in tissue microarrays. Similar to PAX8, SOX17 was highly expressed in different subtypes of ovarian carcinoma (97.5% for SOX17 vs 97% for PAX8 in serous carcinoma, 90% vs 90% in endometrioid carcinoma, and 100% vs 100% in clear cell carcinoma), except for mucinous carcinoma (0% vs 27%), and was also highly expressed in different subtypes of endometrial carcinoma (88% vs 84% in endometrioid carcinoma, 100% vs 100% in serous and clear cell carcinoma). SOX17 was not expressed in thyroid and renal cell carcinomas, whereas PAX8 expression was high (86% and 85%, respectively). In addition, SOX17 was expressed at low levels in cervical adenocarcinoma (20%) and had no expression in cervical squamous carcinoma, mesothelioma, and carcinomas from the breast, lung, pancreas, colon, stomach, liver, bladder, and salivary gland. Our data indicate that SOX17 is not only a sensitive but also a specific marker for the origin of ovarian and endometrial carcinomas.

Predictors of success in establishing orthotopic patient-derived xenograft models of triple negative breast cancer

Patient-derived xenograft (PDX) models of breast cancer are an effective discovery platform and tool for preclinical pharmacologic testing and biomarker identification. We established orthotopic PDX models of triple negative breast cancer (TNBC) from the primary breast tumors of patients prior to and following neoadjuvant chemotherapy (NACT) while they were enrolled in the ARTEMIS trial (NCT02276443). Serial biopsies were obtained from patients prior to treatment (pre-NACT), from poorly responsive disease after four cycles of Adriamycin and cyclophosphamide (AC, mid-NACT), and in cases of AC-resistance, after a 3-month course of different experimental therapies and/or additional chemotherapy (post-NACT). Our study cohort includes a total of 269 fine needle aspirates (FNAs) from 217 women, generating a total of 62 PDX models (overall success-rate = 23%). Success of PDX engraftment was generally higher from those cancers that proved to be treatment-resistant, whether poorly responsive to AC as determined by ultrasound measurements mid-NACT (p = 0.063), RCB II/III status after NACT (p = 0.046), or metastatic relapse within 2 years of surgery (p = 0.008). TNBC molecular subtype determined from gene expression microarrays of pre-NACT tumors revealed no significant association with PDX engraftment rate (p = 0.877). Finally, we developed a statistical model predictive of PDX engraftment using percent Ki67 positive cells in the patient's diagnostic biopsy, positive lymph node status at diagnosis, and low volumetric reduction of the patient's tumor following AC treatment. This novel bank of 62 PDX models of TNBC provides a valuable resource for biomarker discovery and preclinical therapeutic trials aimed at improving neoadjuvant response rates for patients with TNBC.

Preoperative differentiation of hepatocellular carcinoma with peripheral rim-like enhancement from intrahepatic mass-forming cholangiocarcinoma on contrast-enhanced MRI

Purpose

The present study aimed to determine the reliable imaging features to distinguish atypical hepatocellular carcinoma (HCC) with peripheral rim-like enhancement from intrahepatic mass-forming cholangiocarcinoma (IMCC) on contrast-enhanced magnetic resonance imaging (MRI).

Methods

A total of 168 patients (130 male, 57.10 ± 10.53 years) pathological confirmed HCC or IMCC who underwent contrast-enhanced MRI between July 2019 and February 2022 were retrospectively included. Univariate and multivariate logistic regression analyses were used to determine independent differential factors for distinguishing HCC from IMCC, and the model was established. Bootstrap resampling 1000 times was used to verify the model, which was visualized by nomograms. The predictive performance of the model was evaluated based on discrimination, calibration, and clinical utility.

Results

Radiological capsule (OR 0.024, 95% CI: 0.006, 0.095, P<0.001), heterogeneous signal intensity (SI) on T1WI (OR 0.009, 95%CI: 0.001,0.056, P<0.001) were independent differential factors for predicting HCC over IMCC. A lobulated contour (OR 11.732, 95%CI: 2.928,47.007, P = 0.001), target sign on DP (OR 14.269, 95%CI: 2.849,82.106, P = 0.007), bile duct dilatation (OR 12.856, 95%CI: 2.013, P = 0.001) were independent differential factors for predicting IMCCs over HCCs. The independent differential factors constituted a model to distinguish atypical HCCs and IMCCs. The area under receiver operating characteristic (ROC) curve, sensitivity, and specificity values of the model were 0.964(0.940,0.987), 0.88, and 0.906, indicating that the model had an excellent differential diagnostic performance. The decision curve analysis (DCA) curve showed that the model obtained a better net clinical benefit.

Conclusion

The present study identified reliable imaging features for distinguishing atypical HCCs with peripheral rim-like enhancement from IMCCs on contrast-enhanced MRI. Our findings may help radiologists provide clinicians with more accurate preoperative imaging diagnoses to select appropriate treatment options.

MRI-Based Digital Models Forecast Patient-Specific Treatment Responses to Neoadjuvant Chemotherapy in Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is persistently refractory to therapy, and methods to improve targeting and evaluation of responses to therapy in this disease are needed. Here, we integrate quantitative MRI data with biologically based mathematical modeling to accurately predict the response of TNBC to neoadjuvant systemic therapy (NAST) on an individual basis. Specifically, 56 patients with TNBC enrolled in the ARTEMIS trial (NCT02276443) underwent standard-of-care doxorubicin/cyclophosphamide (A/C) and then paclitaxel for NAST, where dynamic contrast-enhanced MRI and diffusion-weighted MRI were acquired before treatment and after two and four cycles of A/C. A biologically based model was established to characterize tumor cell movement, proliferation, and treatment-induced cell death. Two evaluation frameworks were investigated using: (i) images acquired before and after two cycles of A/C for calibration and predicting tumor status after A/C, and (ii) images acquired before, after two cycles, and after four cycles of A/C for calibration and predicting response following NAST. For Framework 1, the concordance correlation coefficients between the predicted and measured patient-specific, post-A/C changes in tumor cellularity and volume were 0.95 and 0.94, respectively. For Framework 2, the biologically based model achieved an area under the receiver operator characteristic curve of 0.89 (sensitivity/specificity = 0.72/0.95) for differentiating pathological complete response (pCR) from non-pCR, which is statistically superior (P &amp;lt; 0.05) to the value of 0.78 (sensitivity/specificity = 0.72/0.79) achieved by tumor volume measured after four cycles of A/C. Overall, this model successfully captured patient-specific, spatiotemporal dynamics of TNBC response to NAST, providing highly accurate predictions of NAST response.

SIGNIFICANCE

Integrating MRI data with biologically based mathematical modeling successfully predicts breast cancer response to chemotherapy, suggesting digital twins could facilitate a paradigm shift from simply assessing response to predicting and optimizing therapeutic efficacy.

A preoperative model based on gadobenate-enhanced MRI for predicting microvascular invasion in hepatocellular carcinomas (≤ 5 cm)

Purpose

The present study aimed to develop and validate a preoperative model based on gadobenate-enhanced magnetic resonance imaging (MRI) for predicting microvascular invasion (MVI) in patients with hepatocellular carcinoma (HCC) size of ≤5 cm. In order to provide preoperative guidance for clinicians to optimize treatment options.

Methods

164 patients with pathologically confirmed HCC and preoperative gadobenate-enhanced MRI from July 2016 to December 2020 were retrospectively included. Univariate and multivariate logistic regression (forward LR) analyses were used to determine the predictors of MVI and the model was established. Four-fold cross validation was used to verify the model, which was visualized by nomograms. The predictive performance of the model was evaluated based on discrimination, calibration, and clinical utility.

Results

Elevated alpha-fetoprotein (HR 1.849, 95% CI: 1.193, 2.867, P=0.006), atypical enhancement pattern (HR 3.441, 95% CI: 1.523, 7.772, P=0.003), peritumoral hypointensity on HBP (HR 7.822, 95% CI: 3.317, 18.445, P<0.001), and HBP hypointensity (HR 3.258, 95% CI: 1.381, 7.687, P=0.007) were independent risk factors to MVI and constituted the HBP model. The mean area under the curve (AUC), sensitivity, specificity, and accuracy values for the HBP model were as follows: 0.830 (95% CI: 0.784, 0.876), 0.71, 0.78, 0.81 in training set; 0.826 (95% CI:0.765, 0.887), 0.8, 0.7, 0.79 in test set. The decision curve analysis (DCA) curve showed that the HBP model achieved great clinical benefits.

Conclusion

In conclusion, the HBP imaging features of Gd-BOPTA-enhanced MRI play an important role in predicting MVI for HCC. A preoperative model, mainly based on HBP imaging features of gadobenate-enhanced MRI, was able to excellently predict the MVI for HCC size of ≤5cm. The model may help clinicians preoperatively assess the risk of MVI in HCC patients so as to guide clinicians to optimize treatment options.

Hepatobiliary Phase Features of Preoperative Gadobenate-Enhanced MR can Predict Early Recurrence of Hepatocellular Carcinoma in Patients Who Underwent Anatomical Hepatectomy

Purpose

The purpose of this study was to establish a model for predicting early recurrence (≤2 years) of hepatocellular carcinoma (HCC) after anatomical hepatectomy based on the hepatobiliary phase (HBP) imaging characteristics of gadobenate-enhanced MRI.

Methods

A total of 155 patients who underwent anatomical hepatectomy HCC therapy and gadobenate-enhanced MRI were included retrospectively. The patients were divided into the early recurrence-free group (n = 103) and the early recurrence group (n = 52). Univariate and multivariate Cox regression analysis was used to determine the independent risk factors related to early recurrence, and four models were established. The preoperative model with/without HBP imaging features (HBP-pre/No HBP-pre model) and the postoperative model with/without HBP imaging features (HBP-post/No HBP-post model). Bootstrap resampling 1,000 times was used to verify the model and displayed by nomograms. The performance of nomograms was evaluated by discrimination, calibration, and clinical utility. Net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were used to evaluate the differences between models and to select the optimal model.

Results

Shape, arterial peritumoral enhancement, AFP-L3, and peritumoral hypointensity on HBP were identified as independent risk factors. Prothrombin time (PT) and r-glutamyltransferase (GGT) were selected by multivariate Cox regression. These six factors construct the HBP-pre model. Removing peritumoral hypointensity on HBP was the No HBP-pre model. Adding microvascular invasion (MVI) and microscopic capsule factors were the HBP-post and No HBP-post model. The C-index was 0.766, 0.738, 0.770, and 0.742, respectively. The NRI and IDI of the HBP-pre vs. the No HBP-pre model and the HBP-post vs. the No HBP-post model significantly increased 0.258, 0.092, 0.280, and 0.086, respectively. The calibration curve and decision curve analysis (DCA) had good consistency and clinical utility. However, the NRI and IDI of the No HBP-post vs. the No HBP-pre model and the HBP-post vs. the HBP-pre model did not increase significantly.

Conclusions

Preoperative gadobenate-enhanced MR HBP imaging features significantly improve the model performance while the postoperative pathological factors do not. Therefore, the HBP-pre model is selected as the optimal model. The strong performance of this model may help hepatologists to assess the risk of recurrence in order to guide the selection of treatment options.

Radiomics-Based Preoperative Prediction of Lymph Node Metastasis in Intrahepatic Cholangiocarcinoma Using Contrast-Enhanced Computed Tomography

BACKGROUND

Lymph node (LN) metastasis is significantly associated with worse prognosis for patients with intrahepatic cholangiocarcinoma (ICC). Improvement in preoperative assessment on LN metastasis helps in treatment decision-making. We aimed to investigate the role of radiomics-based method in predicting LN metastasis for patients with ICC.

METHODS

A total of 296 patients with ICC who underwent curative-intent hepatectomy and lymphadenectomy at two centers in China were analyzed. Radiomic features, including histogram- and wavelet-based features, shape and size features, and texture features were extracted from four-phase computerized tomography (CT) images. The clinical and conventional radiological variables which were independently associated with LN metastasis were also identified. A combined nomogram predicting LN metastasis was developed, and its performance was determined by discrimination, calibration, and stratification of long-term prognosis. The results were validated by the internal and external validation cohorts.

RESULTS

Twenty-four radiomic features were selected into the nomogram. The established nomogram demonstrated good discrimination and calibration, with areas under the curve (AUCs) of 0.98 [95% confidence interval (CI) 0.96-0.99], 0.93 (0.88-0.98), and 0.89 (0.81-0.96) in the training and two validation cohorts, respectively. The 5-year overall survival (OS) and recurrence-free survival (RFS) rates of patients with high risk of LN metastasis as grouped by nomogram were poorer than those of patients with low risk in the training cohort (OS 28.8% versus 53.9%, p < 0.001; RFS 26.3% versus 44.2%, p = 0.001). Similar results were observed in the two validation cohorts.

CONCLUSIONS

Radiomics-based method provided accurate prediction of LN metastasis and prognostic assessment for ICC patients, and might aid the preoperative surgical decision.

Molecular Characterization and Prospective Evaluation of Pathologic Response and Outcomes with Neoadjuvant Therapy in Metaplastic Triple-Negative Breast Cancer

PURPOSE

Metaplastic breast cancer (MpBC) is a rare subtype of breast cancer that is commonly triple-negative and poorly responsive to neoadjuvant therapy in retrospective studies.

EXPERIMENTAL DESIGN

To better define clinical outcomes and correlates of response, we analyzed the rate of pathologic complete response (pCR) to neoadjuvant therapy, survival outcomes, and genomic and transcriptomic profiles of the pretreatment tumors in a prospective clinical trial (NCT02276443). A total of 211 patients with triple-negative breast cancer (TNBC), including 39 with MpBC, received doxorubicin-cyclophosphamide-based neoadjuvant therapy.

RESULTS

Although not meeting the threshold for statistical significance, patients with MpBCs were less likely to experience a pCR (23% vs. 40%; P = 0.07), had shorter event-free survival (29.4 vs. 32.2 months, P = 0.15), metastasis-free survival (30.3 vs. 32.4 months, P = 0.22); and overall survival (32.6 vs. 34.3 months, P = 0.21). This heterogeneity is mirrored in the molecular profiling. Mutations in PI3KCA (23% vs. 9%, P = 0.07) and its pathway (41% vs. 18%, P = 0.02) were frequently observed and enriched in MpBCs. The gene expression profiles of each histologically defined subtype were distinguishable and characterized by distinctive gene signatures. Among nonmetaplastic (non-Mp) TNBCs, 10% possessed a metaplastic-like gene expression signature and had pCR rates and survival outcomes similar to MpBC.

CONCLUSIONS

Further investigations will determine if metaplastic-like tumors should be treated more similarly to MpBC in the clinic. The 23% pCR rate in this study suggests that patients with MpBC should be considered for NAT. To improve this rate, a pathway analysis predicted enrichment of histone deacetylase (HDAC) and RTK/MAPK pathways in MpBC, which may serve as new targetable vulnerabilities.