Invasive Ductal Carcinomas Of No Special Type Research Articles

Abstract GS03-04: Novel Mechanisms of CDH1 Inactivation in Breast Invasive Lobular Carcinoma Unveiled by the Integration of Artificial Intelligence and Genomics

Abstract Background: Invasive lobular carcinoma (ILC) of the breast is the second most common histologic subtype of breast cancer (BC), following invasive ductal carcinoma of no special type (IDC-NST). The hallmark histologic feature of ILC is cellular discohesiveness, the result of bi-allelic inactivation of CDH1, and represents an important genotypic-phenotypic correlation in BC. Although most ILCs harbor CDH1 loss-of function mutations associated to loss-of-heterozygosity (LOH) of the wild type-allele, a subset of ILCs lack these alterations despite displaying a typical lobular phenotype. Here, we sought to identify alternative molecular mechanisms converging on CDH1 inactivation by employing an integrative artificial intelligence (AI) and genomics approach. Materials and Methods: A genomics-driven AI-based algorithm using hematoxylin and eosin (H&E) whole slide images (WSIs) as input, previously developed to detect bi-allelic CDH1 mutations (inactivating mutation associated to LOH) in BC was employed. WSIs of 1,057 BCs including ILCs (n=187) and non-lobular BCs (n=870) previously subjected to FDA-cleared tumor/normal targeted sequencing were subjected to analysis with the AI-based algorithm. Cases predicted to harbor CDH1 bi-allelic mutations by the AI-model but lacking CDH1 bi-allelic mutations by targeted sequencing were assessed through targeted sequencing data re-analysis, CDH1 gene promoter methylation evaluation and/or whole genome sequencing analysis. Results: AI-based analysis WSIs corresponding to 1,057 BCs resulted in the identification of 34 cases found to lack CDH1 bi-allelic mutations by targeted sequencing but predicted to harbor these genetic alterations by the AI-based model. CDH1 gene promoter methylation assessment revealed CDH1 promoter methylation in 18 cases. Targeted sequencing data reanalysis revealed other genetic mechanisms of CDH1 inactivation including CDH1 homozygous deletions (n=3), intragenic deletion with LOH (n=1), and likely pathogenic non-coding CDH1 alterations associated with LOH (n=2). WGS analysis of an ILC revealed a novel deleterious CDH1 fusion stemming from translocation t(13;16), resulting in loss of the 5’UTR, transcription start site and exons 1 and 2 of CDH1, associated with complete loss of E-cadherin protein expression. Taken together, we identified alternative/novel mechanisms of bi-allelic CDH1inactivation in 74% (25/34) cases analyzed. Conclusions: By applying an AI-based algorithm trained to detect a genetic alteration (i.e., CDH1 bi-allelic mutations), we were able to identify alternative epigenetic and genetic molecular mechanisms of CDH1 inactivation in ILCs, including novel non-coding CDH1 genetic alterations and a new inactivating CDH1 fusion gene. These findings indicate that molecular mechanisms affecting a single gene or process converging on the same phenotype can be unveiled by the integration of AI and genomics, highlighting the robustness of this approach for the discovery of novel biology. Citation Format: Fresia Pareja, Higinio Dopeso, Yikan Wang, Andrea Gazzo, David Brown, Pier Selenica, Jan Bernhard, Fatemeh Derakhshan, Edaise M. da Silva, Lorraine Colon-Cartagena, Thais Basili, Antonio Marra, Jillian Sue, Qiqi Ye, Arnaud Da Cruz Paula, Selma Yeni, Xin Pei, Hunter Green, Kaitlyn Gill, Yingjie Zhu, Matthew Lee, Ran Godrich, Adam Casson, Britta Weigelt, Nadeem Riaz, Hanna Y Wen, Edi Brogi, Matthew Hanna, Diana Mandelker, Jeremy Kunz, Brandon Rothrock, Sarat Chandarlapaty, Christopher Kanan, Gerard Oakley III, David Klimstra, Thomas Fuchs, Jorge Reis-Filho. Novel Mechanisms of CDH1 Inactivation in Breast Invasive Lobular Carcinoma Unveiled by the Integration of Artificial Intelligence and Genomics [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr GS03-04.

Prediction of human epidermal growth factor receptor 2 (HER2) status in breast cancer by mammographic radiomics features and clinical characteristics: a multicenter study.

To preoperatively evaluate the human epidermal growth factor 2 (HER2) status in breast cancer using mammographic radiomics features and clinical characteristics on a multi-vendor and multi-center basis. This multi-center study included a cohort of 1512 Chinese female with invasive ductal carcinoma of no special type (IDC-NST) from two different hospitals and five devices (1332 from Institution A, used for training and testing the models, and 180 women from Institution B, as the external validation cohort). The Gradient Boosting Machine (GBM) was employed to establish radiomics and multiomics models. Model efficacy was evaluated by the area under the curve (AUC). The number of HER2-positive patients in the training, testing, and external validation cohort were 245(26.3%), 105 (26.3.8%), and 51(28.3%), respectively, with no statistical differences among the three cohorts (p = 0.842, chi-square test). The radiomics model, based solely on the radiomics features, achieved an AUC of 0.814 (95% CI, 0.784-0.844) in the training cohort, 0.776 (95% CI, 0.727-0.825) in the testing cohort, and 0.702 (95% CI, 0.614-0.790) in the external validation cohort. The multiomics model, incorporated radiomics features with clinical characteristics, consistently outperformed the radiomics model with AUC values of 0.838 (95% CI, 0.810-0.866) in the training cohort, 0.788 (95% CI, 0.741-0.835) in the testing cohort, and 0.722 (95% CI, 0.637-0.811) in the external validation cohort. Our study demonstrates that a model based on radiomics features and clinical characteristics has the potential to accurately predict HER2 status of breast cancer patients across multiple devices and centers. By predicting the HER2 status of breast cancer reliably, the presented model built upon radiomics features and clinical characteristics on a multi-vendor and multi-center basis can help in bolstering the model's applicability and generalizability in real-world clinical scenarios. • The mammographic presentation of breast cancer is closely associated with the status of human epidermal growth factor receptor 2 (HER2). • The radiomics model, based solely on radiomics features, exhibits sub-optimal performance in the external validation cohort. • By combining radiomics features and clinical characteristics, the multiomics model can improve the prediction ability in external data.

Clinicopathologic and genetic analysis of invasive breast carcinomas in women with germline CHEK2 variants

PurposeGermline pathogenic variants in checkpoint kinase 2 (CHEK2) are associated with a moderately increased risk of breast cancer (BC). The spectrum of clinicopathologic features and genetics of these tumors has not been fully established.MethodsWe characterized the histopathologic and clinicopathologic features of 44 CHEK2-associated BCs from 35 women, and assessed responses to neoadjuvant chemotherapy. A subset of cases (n = 23) was additionally analyzed using targeted next-generation DNA sequencing (NGS).ResultsMost (94%, 33/35) patients were heterozygous carriers for germline CHEK2 variants, and 40% had the c.1100delC allele. Two patients were homozygous, and five had additional germline pathogenic variants in ATM (2), PALB2 (1), RAD50 (1), or MUTYH (1). CHEK2-associated BCs occurred in younger women (median age 45 years, range 25–75) and were often multifocal (20%) or bilateral (11%). Most (86%, 38/44) were invasive ductal carcinomas of no special type (IDC-NST). Almost all (95%, 41/43) BCs were ER + (79% ER + HER2-, 16% ER + HER2 + , 5% ER-HER2 +), and most (69%) were luminal B. Nottingham grade, proliferation index, and results of multiparametric molecular testing were heterogeneous. Biallelic CHEK2 alteration with loss of heterozygosity was identified in most BCs (57%, 13/23) by NGS. Additional recurrent alterations included GATA3 (26%), PIK3CA (226%), CCND1 (22%), FGFR1 (22%), ERBB2 (17%), ZNF703 (17%), TP53 (9%), and PPM1D (9%), among others. Responses to neoadjuvant chemotherapy were variable, but few patients (21%, 3/14) achieved pathologic complete response. Most patients (85%) were without evidence of disease at time of study (n = 34). Five patients (15%) developed distant metastasis, and one (3%) died (mean follow-up 50 months).ConclusionAlmost all CHEK2-associated BCs were ER + IDC-NST, with most classified as luminal B with or without HER2 overexpression. NGS supported the luminal-like phenotype and confirmed CHEK2 as an oncogenic driver in the majority of cases. Responses to neoadjuvant chemotherapy were variable but mostly incomplete.

Nonlobular Invasive Breast Carcinomas with Biallelic Pathogenic CDH1 Somatic Alterations: A Histologic, Immunophenotypic, and Genomic Characterization

CDH1 encodes for E-cadherin, and its loss of function is the hallmark of invasive lobular carcinoma (ILC). Albeit vanishingly rare, biallelic CDH1 alterations may be found in nonlobular breast carcinomas (NL-BCs). We sought to determine the clinicopathologic characteristics and repertoire of genetic alterations of NL-BCs harboring CDH1 biallelic genetic alterations. Analysis of 5842 breast cancers (BCs) subjected to clinical tumor-normal sequencing with an FDA-cleared multigene panel was conducted to identify BCs with biallelic CDH1 pathogenic/likely pathogenic somatic mutations lacking lobular features. The genomic profiles of NL-BCs with CDH1 biallelic genetic alterations were compared with those of ILCs and invasive ductal carcinomas (IDCs), matched by clinicopathologic characteristics. Of the 896 CDH1-altered BCs, 889 samples were excluded based on the diagnosis of invasive mixed ductal/lobular carcinoma or ILC or the detection of monoallelic CDH1 alterations. Only 7 of the 5842 (0.11%) BCs harbored biallelic CDH1 alterations and lacked lobular features. Of these, 4/7 (57%) cases were ER-positive/HER2-negative, 1/7 (14%) was ER-positive/HER2-positive, and 2/7 (29%) were ER-negative/HER2-negative. In total, 5/7 (71%) were of Nottingham grade 2, and 2/7 (29%) were of grade 3. The NL-BCs with CDH1 biallelic genetic alterations included a mucinous carcinoma (n = 1), IDCs with focal nested growth (n = 2), IDC with solid papillary (n = 1) or apocrine (n = 2) features, and an IDC of no special type (NST; n = 1). E-cadherin expression, as detected by immunohistochemistry, was absent (3/5) or aberrant (discontinuous membranous/cytoplasmic/granular; 2/5). However, NL-BCs with CDH1 biallelic genetic alterations displayed recurrent genetic alterations, including TP53, PIK3CA (57%, 4/7; each), FGFR1, and NCOR1 (28%, 2/7, each) alterations. Compared with CDH1 wild-type IDC-NSTs, NL-BCs less frequently harbored GATA3 mutations (0% vs 47%, P = .03), but no significant differences were detected when compared with matched ILCs. Therefore, NL-BCs with CDH1 biallelic genetic alterations are vanishingly rare, predominantly comprise IDCs with special histologic features, and have genomic features akin to luminal B ER-positive BCs.

Canonical Kaiso target genes define a functional signature that associates with breast cancer survival and the invasive lobular carcinoma histological type.

Invasive lobular carcinoma (ILC) is a low- to intermediate-grade histological breast cancer type caused by mutational inactivation of E-cadherin function, resulting in the acquisition of anchorage independence (anoikis resistance). Most ILC cases express estrogen receptors, but options are limited in relapsed endocrine-refractory disease as ILC tends to be less responsive to standard chemotherapy. Moreover, ILC can relapse after >15 years, an event that currently cannot be predicted. E-cadherin inactivation leads to p120-catenin-dependent relief of the transcriptional repressor Kaiso (ZBTB33) and activation of canonical Kaiso target genes. Here, we examined whether an anchorage-independent and ILC-specific transcriptional program correlated with clinical parameters in breast cancer. Based on the presence of a canonical Kaiso-binding consensus sequence (cKBS) in the promoters of genes that are upregulated under anchorage-independent conditions, we defined an ILC-specific anoikis resistance transcriptome (ART). Converting the ART genes into human orthologs and adding published Kaiso target genes resulted in the Kaiso-specific ART (KART) 33-gene signature, used subsequently to study correlations with histological and clinical variables in primary breast cancer. Using publicly available data for ERPOS Her2NEG breast cancer, we found that expression of KART was positively associated with the histological ILC breast cancer type (p < 2.7E-07). KART expression associated with younger patients in all invasive breast cancers and smaller tumors in invasive ductal carcinoma of no special type (IDC-NST) (<2 cm, p < 6.3E-10). We observed associations with favorable long-term prognosis in both ILC (hazard ratio [HR] = 0.51, 95% CI = 0.29-0.91, p < 3.4E-02) and IDC-NST (HR = 0.79, 95% CI = 0.66-0.93, p < 1.2E-04). Our analysis thus defines a new mRNA expression signature for human breast cancer based on canonical Kaiso target genes that are upregulated in E-cadherin deficient ILC. The KART signature may enable a deeper understanding of ILC biology and etiology. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

The mixed subtype has a worse prognosis than other histological subtypes: a retrospective analysis of 217 patients with metaplastic breast cancer

ObjectiveMetaplastic breast cancer (MpBC) is an aggressive subtype of all breast cancer. We aimed to investigate the clinicopathological features, treatments and prognoses of MpBC patients.MethodsWe collected the data from MpBC patients diagnosed at Tianjin Medical University Cancer Hospital from 2010 to 2017. Kaplan Meier curves and Cox regression model were used to evaluating clinical outcomes and prognostic factors. After removing baseline differences by propensity score matching (PSM), we analyzed the prognosis between MpBC patients and invasive ductal carcinomas of no special type (IDC-NST) patients.ResultsA total of 217 MpBC patients were subsumed. Of all histological subtypes, 45.1% were mixed subtypes, followed by with mesenchymal differentiation (27.2%), pure squamous (15.2%) and pure spindle (12.4%) subtypes. 69.6% of MpBC were triple-negative, 25.3% and 6.5% were HR-positive and HER2-positive. MpBC patients had worse survival compared to IDC-NST patients, with 5-year RFS of 73.8 and 83.6% (HR = 1.177 95%CI (1.171–2.676) P = 0.0068), and 5-year BCSS of 79.0% and 89.7% (HR = 2.187 95%CI (1.357–3.523) P = 0.0013). In the multivariate COX model, AJCC stage, mixed subtype and chemotherapy were independent prognostic factors. Mixed MpBC is more aggressive than pure and with heterologous mesenchymal differentiation subtypes. And whether squamous or spindle MpBC, mixed forms have shorter outcomes than pure forms.ConclusionsMpBCs are associated with poorer prognoses than IDC-NSTs. They are heterogeneous with different clinicopathological features and clinical outcomes between histological subtypes. Pure and with heterologous mesenchymal differentiation subtypes have more survival benefits than the mixed subtype.

Genetic and immunohistochemical profiling of small cell and large cell neuroendocrine carcinomas of the breast

AbstractNeuroendocrine carcinomas (NEC) of the breast are exceedingly rare tumors, which are classified in the WHO system as small cell (SCNEC) and large cell (LCNEC) carcinoma based on indistinguishable features from their lung counterparts. In contrast to lung and enteropancreatic NEC, the genomics of breast NEC have not been well-characterized. In this study, we examined the clinicopathologic, immunohistochemical, and genetic features of 13 breast NEC (7 SCNEC, 4 LCNEC, 2 NEC with ambiguous small versus large cell morphology [ANEC]). Co-alterations of TP53 and RB1 were identified in 86% (6/7) SCNEC, 100% (2/2) ANEC, and 50% (2/4) LCNEC. The one SCNEC without TP53/RB1 alteration had other p53 pathway aberrations (MDM2 and MDM4 amplification) and was immunohistochemically RB negative. PIK3CA/PTEN pathway alterations and ZNF703 amplifications were each identified in 46% (6/13) NEC. Two tumors (1 SCNEC, 1 LCNEC) were CDH1 mutated. By immunohistochemistry, 100% SCNEC (6/6) and ANEC (2/2) and 50% (2/4) LCNEC (83% NEC) showed RB loss, compared to 0% (0/8) grade 3 neuroendocrine tumors (NET) (p < 0.001) and 38% (36/95) grade 3 invasive ductal carcinomas of no special type (IDC-NST) (p = 0.004). NEC were also more often p53 aberrant (60% vs 0%, p = 0.013), ER negative (69% vs 0%, p = 0.005), and GATA3 negative (67% vs 0%, p = 0.013) than grade 3 NET. Two mixed NEC had IDC-NST components, and 69% (9/13) of tumors were associated with carcinoma in situ (6 neuroendocrine DCIS, 2 non-neuroendocrine DCIS, 1 non-neuroendocrine LCIS). NEC and IDC-NST components of mixed tumors were clonally related and immunophenotypically distinct, lacking ER and GATA3 expression in NEC relative to IDC-NST, with RB loss only in NEC of one ANEC. The findings provide insight into the pathogenesis of breast NEC, underscore their classification as a distinct tumor type, and highlight genetic similarities to extramammary NEC, including highly prevalent p53/RB pathway aberrations in SCNEC.

A comparative clinicopathological and survival analysis of synchronous bilateral breast cancers.

The present study aimed to explore the clinicopathological characteristics, potential heterogeneity and prognostic factors in synchronous bilateral breast cancer (SBBC). We performed a retrospective review and paired comparison of the clinicopathological characteristics of 114 patients with SBBC in the Peking Union Medical College Hospital from January 2008 to September 2019. The prognostic significance of triple negativity status and coexistence ductal carcinoma in situ (DCIS) with bilateral invasive ductal carcinomas of no special type (IDC-NST) was analyzed in SBBC. Most bilateral lesions on both sides were of IDC-NST, grade 2, luminal subtype, and stage I. Although most lesions were concordant between the left and right side, discordances were observed in histological type (25 cases, 21.9%), histological grade (31 cases, 27.2%), pTNM (61 cases, 53.5%), molecular subtypes (20 cases, 17.5%), and immunohistochemical staining of ER (18 cases, 15.8%), PR (26 cases, 22.8%), and HER2 (12 cases, 10.5%). Moreover, there was no significant difference in disease-free survival (DFS) and overall survival (OS) between IDC-NST with coexisting DCIS on both sides and IDC-NST with coexisting DCIS on one side or pure IDC-NST. SBBC with triple negativity on both sides exhibited a significantly shorter DFS and OS when compared with triple negativity on one side or non-triple negativity on both sides (p<0.001), and remained an independent prognostic factor by multivariate analysis. A considerable proportion of discordance in clinicopathological characteristics is observed in SBBC, supporting the necessity of comprehensive pathological examination including immunohistochemical testing on both sides in clinical practice. Moreover, SBBC with triple negativity on both sides is a prognostic for poor survival.

The role of mineralocorticoids and glucocorticoids under the impact of 11β-hydroxysteroid dehydrogenase in human breast lesions

We attempted to explore the possible involvement of the in situ availability of mineralocorticoids and mineralocorticoid receptor (MR) in the pathogenesis of mammary ductal carcinoma. We also explored their individual profiles among different subtypes of invasive ductal carcinomas of no special type (IDC-NST) by evaluating the status of MR, Glucocorticoid receptor (GR), and 11β hydroxysteroid dehydrogenase (HSD) 1/2 at each stage of the putative cascade of the mammary ductal proliferative disorders. In this study, IDC-NST, ductal carcinoma in situ (DCIS), atypical ductal hyperplasia (ADH), and non-pathological breast tissues were all evaluated by immunohistochemistry. MR was significantly lower in ADH than in DCIS or IDC-NST. 11βHSD2 was significantly lower in ADH than normal breast tissue and 11βHSD1 was significantly higher in DCIS than normal, ADH, or IDC-NST. MR in progesterone receptor (PR)-positive IDC-NST cases tended to be associated with the Ki-67 labeling index. Results of the present study demonstrated that the status of MR and GR in conjunction with the 11βHSDs was correlated with the development of low-grade proliferative disorders in mammary glands. In addition, the potential crosstalk between MR and PR could also influence cell proliferation of breast carcinoma cells but further investigations are required for clarification.

Diffusion-weighted imaging of breast invasive lobular carcinoma: comparison with invasive carcinoma of no special type using a histogram analysis.

To investigate the imaging findings and visibility of breast invasive lobular carcinoma (ILC) on diffusion-weighted imaging (DWI) and compare quantitative apparent diffusion coefficient (ADC) metrics of ILC and invasive carcinoma of no special type (NST) using a histogram analysis. We performed an observational retrospective study of 629 consecutive women with pathologically proven ILC and invasive ductal carcinoma of NST, who underwent 3-T MRI including DWI, between January 2017 and August 2020. After propensity score matching, 71 women were allocated to each group. On DWI, 9 (12.7%) lesions of ILC and 4 (5.6%) invasive carcinomas of the NST were not visualized. For the tumor visibility on DWI, tumor size, tumor ADC value, and background diffusion grade were significantly associated with the visibility score in both groups (all P<0.05), whereas the mean background ADC value was not significant (P>0.05). The mean ADC (1.226×10-3 vs. 1.052×10-3 mm2/s, P<0.001), median ADC (1.222×10-3 vs. 1.051×10-3 mm2/s, P=0.002), maximum ADC (1.758×10-3 vs. 1.504×10-3 mm2/s, P<0.001), minimum ADC (0.717×10-3 vs. 0.649×10-3 mm2/s, P=0.003), 90th percentile ADC (1.506×10-3 vs. 1.292×10-3 mm2/s, P<0.001) and 10th percentile ADC (0.956×10-3 vs. 0.818×10-3 mm2/s, P=0.008) were higher in ILC than in invasive carcinoma of NST. Additionally, the ADC difference value of the ILC was higher than that of invasive carcinoma of NST (1.04×10-3 vs. 0.855×10-3 mm2/s, P=0.027). On DWI, the visibility of ILC was lower compared to invasive carcinoma of NST. ILC showed higher quantitative ADC values and higher ADC difference values.

Next-generation sequencing revealed recurrent ZFPM1 mutations in encapsulated papillary carcinoma of the breast

Encapsulated papillary carcinoma (EPC) of the breast is a rare subtype of tumor. To date, the genetic abnormalities underlying EPC remain elusive. The purpose of this study was to gain further insight into EPC mutation profile. Forty-one EPCs diagnosed from 2015 to 2018 were included. Twenty-six EPCs were submitted to whole-exome sequencing (WES), and a 185 gene-targeted sequencing panel was designed to validate the results of the 26 EPCs that underwent WES and 15 additional cases. Recurrently mutated genes were further confirmed by Sanger sequencing. Our study revealed multiple recurrently mutated genes including PI3K-AKT-mTOR pathway genes (PIK3CA, AKT1, ULK1, MAP3K1, MAP2K4, RHOA, and PTEN) (27/41, 65.8%) and chromatin modification genes (ZFPM1, GATA3, CTCF, and KMT2C) (21/41, 51.2%) in EPC. Importantly, somatic ZFPM1 mutations existed in 9/41 (21.9%) of the EPCs. The frequency of ZFPM1 mutations in the EPCs was significantly higher than that of other tumor types. Of the nine ZFPM1 mutations, seven were frameshift mutations, and the remaining two were nonsense mutations. Moreover, a significant concurrence of ZFPM1 and PI3K-AKT-mTOR mutations were revealed in the EPCs. Of note, no TP53 mutations were detected in our EPCs, whereas it was detected in a considerable proportion of the luminal A invasive ductal carcinomas of no special type (IDC-NSTs) from TCGA. We reveal that recurrent somatic ZFPM1 mutation is characteristic of EPC and concurred with mutations in the PI3K-AKT-mTOR pathway. The distinctive genetic features of EPC might underlie its special histological structures and indolent behavior.

Validation of prognostic significance of the proposed uniform classification framework in neuroendocrine neoplasms of the breast.

A uniform classification framework for neuroendocrine neoplasms (NENs) in all the organ systems has been recently proposed by an International Agency for Research on Cancer (IARC) and World Health Organization (WHO) expert panel. Based on the new classification system, the NENs of the breast are divided into well-differentiated neuroendocrine tumors (NETs) and poorly differentiated neuroendocrine carcinomas (NECs). This study is aimed to analysis the prognostic differences between NENs and invasive ductal carcinomas of no special type (IDCs-NST). The surveillance, epidemiology, and end results (SEER) database released on November 2018 was used for this study. Between 2003 and 2016, 361 NENs (NET = 239, NEC = 122) of the breast and 491,908 of IDCs-NST were identified. Survival analysis was performed for disease-specific survival (DSS) and overall survival (OS). The 5-year DSS of NET, NEC, and IDC-NST was 63.39%, 46.00%, and 89.17%, respectively. And the 5-year OS of NET, NEC, and IDC-NST was 55.66%, 38.87%, and 83.17%, respectively. Within the same clinical stage or grade, NETs and NECs of the breast had worse DSS and OS than corresponding stage or grade IDCs-NST (all P < 0.050). In univariate and multivariate survival analysis, NENs of the breast had significantly worse DSS and OS than IDCs-NST (P < 0.001). The universal classification framework for NEN allowed us to further refine the breast carcinoma with neuroendocrine differentiation as a unique pathologic and clinical entity, which has worse clinical outcome compared to IDC-NST.

Whole-exome sequencing analysis of juvenile papillomatosis and coexisting breast carcinoma.

Juvenile papillomatosis (JP) of the breast is a rare benign mass‐forming lesion occurring in young women, which is histologically characterized by a constellation of proliferative changes and large cysts, giving it the gross appearance of Swiss cheese. A subset of patients with JP report a family history of breast carcinoma and/or coexisting or subsequent breast carcinoma. We performed whole‐exome sequencing of the hyperplastic epithelial component of three JPs, including one with coexisting ductal carcinoma in situ (DCIS) and invasive ductal carcinoma of no special type (IDC‐NST). JPs harbored clonal somatic PIK3CA hotspot mutations in two cases. In the JP with coexisting DCIS and IDC‐NST, these lesions were clonally related to the associated JP, sharing a clonal PIK3CA E542K somatic hotspot mutation. JP showed a paucity of copy number alterations, whereas the associated DCIS and IDC‐NST showed concurrent 1q gains/16q losses, hallmarks of estrogen receptor (ER)‐positive breast cancers. We observed JP to harbor a dominant aging‐related mutational signature, whereas coexisting DCIS and IDC‐NST showed greater exposure to an APOBEC signature. Taken together, our findings suggest that, at least in a subset of cases, JP might constitute the substrate from which DCIS and invasive breast carcinomas develop.

Tumor-infiltrating lymphocytes are associated with poor prognosis in invasive lobular breast carcinoma

The prognostic impact of tumor-infiltrating lymphocytes (TILs) within invasive lobular carcinoma (ILC) remains to be better characterized. In estrogen receptor (ER)-negative invasive ductal carcinomas of no special type (IDC-NST), TILs are associated with good prognosis. The aim of this study was to examine TILs in ILC, with particular focus on prognostic and clinicopathologic features. A cohort comprising 459 consecutive ILCs diagnosed in a single institution from 2005 to 2008 met the eligibility criteria for this study. The percentage of tumor area occupied by TILs was quantified by two breast pathologists and categorized into three groups: no TILs, ≤5%, >5%. Clinicopathologic features were tested by Fisher's exact tests or Chi2 tests. Overall survival (OS) and invasive disease-free survival (iDFS) were estimated by Kaplan–Meier and Cox proportional hazard statistics. There were 239 TIL-negative cases, 185 cases with ≤5% TILs, and 35 cases with >5% TILs. TILs were associated with younger age, larger tumors, lymph node involvement, poor Nottingham prognostic index, HER2 amplification, multinucleation, and prominent nucleoli (p < 0.05). Poor OS was significantly associated with increasing TILs in the univariate Cox proportional hazards model (p < 0.001) and Kaplan–Meier estimator (p < 0.05, log-rank test). Similar results were observed for iDFS (p = 0.004 for Cox univariate and p = 0.005 for log-rank test). Notably, TILs can identify a subset of ILC patients with poor OS independently of molecular subtype and lymph node metastases (multivariate Cox, p < 0.001, OS hazard ratio (HR) = 4.38 and HR = 6.15, for ≤5% and >5% TILs, respectively, vs. absence of TILs). Prominent nucleoli was the only nuclear feature associated with poor OS (p = 0.05) and iDFS (p = 0.05) in univariate Cox survival analysis. TILs represent a promising new morphologic biomarker associated with poor outcome of ILC, in contrast with that observed in ER-negative IDC-NST.

The genomic landscape of metastatic histologic special types of invasive breast cancer

Histologic special types of breast cancer (BC) account for ~20% of BCs. Large sequencing studies of metastatic BC have focused on invasive ductal carcinomas of no special type (IDC-NSTs). We sought to define the repertoire of somatic genetic alterations of metastatic histologic special types of BC. We reanalyzed targeted capture sequencing data of 309 special types of BC, including metastatic and primary invasive lobular carcinomas (ILCs; n = 132 and n = 127, respectively), mixed mucinous (n = 5 metastatic and n = 14 primary), micropapillary (n = 12 metastatic and n = 8 primary), and metaplastic BCs (n = 6 metastatic and n = 5 primary), and compared metastatic histologic special types of BC to metastatic IDC-NSTs matched according to clinicopathologic characteristics and to primary special type BCs. The genomic profiles of metastatic and primary special types of BC were similar. Important differences, however, were noted: metastatic ILCs harbored a higher frequency of genetic alterations in TP53, ESR1, FAT1, RFWD2, and NF1 than primary ILCs, and in CDH1, PIK3CA, ERBB2, TBX3, NCOR1, and RFWD2 than metastatic IDC-NSTs. Metastatic ILCs displayed a higher mutational burden, and more frequently dominant APOBEC mutational signatures than primary ILCs and matched metastatic IDC-NSTs. ESR1 and NCOR mutations were frequently detected in metastatic mixed mucinous BCs, whereas PIK3CA and TP53 were the most frequently altered genes in metastatic micropapillary and metaplastic BCs, respectively. Taken together, primary and metastatic BCs histologic special types have remarkably similar repertoires of somatic genetic alterations. Metastatic ILCs more frequently harbor APOBEC mutational signatures than primary ILCs and metastatic IDC-NSTs.

Immune parameters associated with survival in metaplastic breast cancer

BackgroundMetaplastic breast carcinoma (MBC) is a rare histological type of breast cancer, which commonly shows resistance to standard therapies and is associated with poor prognosis. The immune microenvironment in MBC and its significance has not been well established due to its low incurrence rate and complex components. We aimed to investigate the diversity of immune parameters including subsets of TILs and PDL1/PD1 expression in MBC, as well as its correlation with prognosis.MethodsA total of 60 patients diagnosed with MBC from January 2006 to December 2017 were included in our study. The percentage (%) and quantification (per mm2) of TILs and presence of tertiary lymphoid structures (TLS) were evaluated by hematoxylin and eosin staining (HE). The quantification of CD4+, CD8+ TILs (per mm2), and PD-1/PDL1 expression were evaluated through immunohistochemistry and analyzed in relation to clinicopathological characteristics. A ≥ 1% membranous or cytoplasmatic expression of PD1 and PDL1 was considered a positive expression.ResultsWe found squamous cell carcinoma MBC (33/60, 55%) exhibiting most TILs of all the MBC subtypes (p = 0.043). Thirty-three of 60 (50%) of the patients had coexisting invasive ductal carcinoma of no special type (IDC-NST), and the average percentage of TILs in MBC components was lower compared with NST components (p < 0.001). Thirty (50%) patients exhibited positive (≥ 1%) PDL1 expression in their tumor cells, while 36 (60%) had positive (≥ 1%) PDL1 expression in their TILs. Twenty-seven (45%) of all the patients had positive (≥ 1%) PD1 expression in their tumor cells and 33 (55%) had PD1-positive (≥ 1%) stromal TILs. More CD8+ TILs were associated with positive PDL1 expression of tumor cells as well as positive PD1 expression in stromal cells. Greater number of stromal TILS (> 300/mm2, 20%), CD4+ TILs (> 250/mm2), and CD8+ TILs (> 70/mm2) in MBC were found associated with longer disease-free survival. Positive expression of PDL1 in tumor cells (≥ 1%) and PD1 in stromal cells (≥ 1%) were also associated with longer survival.ConclusionsThe immune characteristics differ in various subtypes as well as components of MBC. Immune parameters are key predictive factors of MBC and provide the clinical significance of applying immune checkpoint therapies in patients with MBC.

Radiomics Signatures Based on Multiparametric MRI for the Preoperative Prediction of the HER2 Status of Patients with Breast Cancer

The aim of our study was to preoperatively predict the human epidermal growth factor receptor 2 (HER2) status of patients with breast cancer using radiomics signatures based on single-parametric and multiparametric magnetic resonance imaging (MRI). Three hundred six patients with invasive ductal carcinoma of no special type (IDC-NST) were retrospectively enrolled. Quantitative imaging features were extracted from fat-suppressed T2-weighted and dynamic contrast-enhanced T1 weighted (DCE-T1) preoperative MRI. Then, three radiomics signatures based on fat-suppressed T2-weighted images, DCE-T1 images and their combination were developed using a support vector machine (SVM) to predict the HER2-positive vs HER2-negative status of patients with breast cancer. The area under the curve (AUC), accuracy, sensitivity, and specificity were calculated to assess the predictive performances of the signatures. Twenty-eight quantitative radiomics features, namely, 14 texture features, 4 first-order features, 9 wavelet features, and 1 shape feature, were used to construct radiomics signatures. The performance of the radiomics signatures for distinguishing HER2-positive from HER2-negative breast cancer based on fat-suppressed T2-weighted images, DCE-T1 images, and their combination had an AUC of 0.74 (95% confidence interval [CI], 0.700 to 0.770), 0.71 (0.673 to 0.738), and 0.86 (0.832 to 0.882) in the primary cohort and 0.70 (0.666 to 0.744), 0.68 (0.650 to 0.726), and 0.81 (0.776 to 0.837) in the validation cohort, respectively. Radiomics signatures based on multiparametric MRI represent a potential and efficient alternative tool to evaluate the HER2 status in patients with breast cancer.

Abstract PD8-06: The genomic landscape of metastatic special histologic types of breast cancer

Abstract Introduction: Breast cancer (BC) is heterogeneous and comprises diverse entities with distinctive phenotypes, biology and clinical presentations. There are 21 special histologic types, accounting for approximately 20% of invasive BCs. Large-scale sequencing studies have focused preferentially on common histologic forms, and data on the genomic landscape of special histologic types, particularly in the metastatic setting, are scarce. Here, we sought to define the repertoire of somatic genetic alterations of metastatic special histologic types of BC. Materials and methods: We conducted a reanalysis of MSK-IMPACT targeted sequencing data of 346 special histologic types of BC from Razavi et al (Cancer Cell 2018), including invasive lobular (ILC; primary, n=129; metastasis, n=150), mucinous (primary n=11, metastasis n=5), micropapillary (primary n=8, metastasis n=13) and metaplastic carcinomas (primary, n=6; metastasis, n=11). Somatic single nucleotide variants (SNVs) and copy number alterations (CNAs) were inferred using a validated bioinformatics pipeline, and mutational signatures were assessed with SigMA. Genetic alterations of metastatic special histologic type BCs were compared to those of primary tumors and metastatic invasive ductal carcinomas of no special type (IDC-NSTs) matched by age, menopausal status and estrogen receptor (ER)/HER2 status at a 1:2 ratio for ILCs and at a 1:3 ratio for the remaining BCs. Results: The most frequently mutated genes in metastatic ILCs were CDH1 (71%), PIK3CA (49%), ESR1 (20%) and KMT2C (19%). ESR1 mutations were more frequent in metastatic than in primary ILCs (20% vs 3%; P&amp;lt;0.01). Metastatic ILCs, as compared to matched metastatic IDC-NSTs, had a higher frequency of mutations in CDH1 (71% vs 2%; P&amp;lt;0.001), KMT2C (19% vs 10%; P&amp;lt;0.05), TBX3 (16% vs 5%; P&amp;lt;0.001), ERBB2 (12% vs 3%; P&amp;lt;0.01) and FOXA1 (10% vs 2%; P&amp;lt;0.05), and a lower frequency of mutations in TP53 (16% vs 36%; P&amp;lt;0.001) and GATA3 (6% vs 16%; P&amp;lt;0.01). GATA3, NCOR1 and ESR1 (each, 40%) were the most frequently mutated genes in metastatic mucinous BCs. ESR1 and NCOR were numerically more frequent in metastatic than in primary mucinous BCs (40% vs 0%; P&amp;gt;0.05). Metastatic mucinous BCs had a numerically higher frequency of mutations in ESR1 (40% vs 6%; P&amp;gt;0.05) and GATA3 (40% vs 0%; P&amp;gt;0.05), and lower frequency of TP53 mutations (20% vs 53%; P&amp;gt;0.05) than matched metastatic IDC-NSTs. PIK3CA and TP53 were the most recurrently mutated genes in metastatic micropapillary BCs and were numerically more frequent in metastatic than in primary tumors (PIK3CA, 61% vs 25%; TP53, 46% vs 25%; P&amp;gt;0.05). PIK3CA was more frequently mutated in metastatic micropapillary BCs than IDC-NSTs (61% vs 23%; P&amp;lt;0.05). Metastatic metaplastic BCs most frequently harbored mutations in TP53 (72%) and PIK3CA (45%), with comparable frequencies in primary metaplastic BCs. ATM (27% vs 3%; P&amp;lt;0.05), MAP3K13 and YAP1 (27% vs 0%; P&amp;lt;0.05) were more frequently mutated in metastatic metaplastic BCs than in matched IDC-NSTs. No differences in the frequency of CNAs were seen between metastatic BCs of special histologic type and matched primary tumors or metastatic IDC-NSTs. Akin to metastatic IDC-NSTs, aging or APOBEC were the predominant mutational SNV signatures in metastatic ILCs, micropapillary and metaplastic BCs. Conclusions: The repertoire of somatic genetic alterations of primary and metastatic special histologic type BCs markedly overlaps. Nonetheless, there is an enrichment of mutations in ESR1 in metastatic BCs of typically ER-positive special histologic type. Metastatic BCs of special histologic type show an enrichment of similar genetic alterations as primary tumors, such as a higher frequency of mutations in CDH1, FOXA1 and TBX3 in ILCs, a lower frequency of PIK3CA and TP53 mutations in mucinous BCs and a higher frequency of PIK3CA and TP53 mutations in micropapillary and metaplastic BCs. Citation Format: Fresia Pareja, Simon SK Lee, Francisco Beca, Lorenzo Ferrando, Pier Selenica, David N Brown, Hannah Y Wen, Hong Zhang, Edi Brogi, Pedram Razavi, Sarat Chandarlapaty, Britta Weigelt, Jorge S Reis-Filho. The genomic landscape of metastatic special histologic types of breast cancer [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr PD8-06.

Abstract P4-05-11: Methylation profiling of mucinous breast cancer

Abstract Introduction: Mucinous carcinoma of the breast (MCB) is a rare histologic form of estrogen receptor (ER)-positive/HER2-negative breast cancer characterized by tumor cells floating in lakes of mucin. As compared to invasive ductal carcinoma of no special type (IDC-NST), we have recently shown that MCBs harbor a lower frequency of PIK3CA mutations and lack concurrent 1q gains and 16q losses, hallmark genetic alterations of ER-positive breast cancer. Despite their distinctive phenotype and previous efforts to characterize their genomic landscape by whole-genome, whole-exome and RNA-sequencing, no pathognomonic somatic mutation or fusion gene underpinning MCBs or the mucinous phenotype have been identified. In this study we sought to determine whether MCBs would be defined by specific epigenetic changes. Materials and methods: Thirty-six MCBs were subjected to DNA methylation profiling using Infinium MethylationEPIC arrays. Following quantile normalization, low quality probe filtering, and data background and dye bias correction using the ‘noob’ algorithm, methylation profiling data of MCBs were compared to those of ER-positive/HER2-negative IDC-NSTs from The Cancer Genome Atlas (TCGA) lacking concurrent 1q gains/16q losses or PIK3CA hotspot mutations and matched according to age and menopausal status at a 1:2 ratio (n=72). An enrichment analysis of the differentially methylated targets in gene promoters and enhancers was conducted using Minfi and MethylGSEA R packages. A subset of 12 MCBs of this cohort was subjected to RNA-sequencing and compared to age, menopausal status and molecular features-matched ER-positive/HER2-negative IDC-NSTs from TCGA (1:2 ratio; n=24) using gene set enrichment analysis (GSEA). Results: Enrichment analysis of differentially methylated probes revealed a significant enrichment of targets in promoters and enhancers of mucin-encoding genes and in genes of the mTOR signaling pathway between MCBs and matched IDC-NSTs from TCGA (P&amp;lt;0.01). Compared to matched IDC-NSTs, MCBs displayed promoter/enhancer hypomethylation of mucin-encoding genes, such as MUC1, MUC2 and MUCL1. We also observed promoter/enhancer hypomethylation of mTOR signaling pathway genes including MTOR, which encodes for the catalytic subunit of the mTORC complex, RPTOR, which codes for an mTOR binding protein that positively regulates the downstream effector S6 Kinase 1, EIF4E and EIF4B, key downstream effectors of the mTOR signaling pathway, and the oncogenes PIK3R2 and PIK3R3, which encode for regulatory isoforms of PI3K, in MCBs. Our gene expression analysis revealed that the mucin-encoding genes MUC1, MUC2 and MUCL1, and the mTOR signaling genes MTOR, RPTOR, EIF4E, EPIF4B, PIK3R1 and PIK3R2, found to be hypomethylated in MCBs, displayed a significantly higher gene expression in MCBs (P&amp;lt;0.001, each) compared to clinically and molecularly matched IDC-NSTs. Conclusions: Taken together, our data suggest that MCBs display a high expression of mucin-encoding genes, due to hypomethylation of promoters and enhancers and could provide the basis for their distinctive phenotype. Moreover, our findings suggest that despite the lack of genetic alterations affecting genes of the PI3K/mTOR signaling pathway in MCBs, mTOR signaling might be constitutively active in these tumors via epigenetic mechanisms, supporting the notion that, in the absence of pathognomonic genetic alterations, a disruption of the epigenetic landscape is a critical driver in the development of this rare breast cancer type. Citation Format: Fresia Pareja, Lorenzo Ferrando, Edaise M da Silva, Arnaud Da Cruz Paula, Anthe Stylianou, David N Brown, Pier Selenica, Jonathan Serrano, Hannah Y Wen, Hong Zhang, Edi Brogi, Larry Norton, Matjia Snuderl, Jorge S Reis-Filho, Britta Weigelt. Methylation profiling of mucinous breast cancer [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P4-05-11.

Evaluating the HER-2 status of breast cancer using mammography radiomics features

PurposeThe aim of our study was to evaluate the HER-2 status in breast cancer patients using mammography (MG) radiomics features. MethodsA total of 306 Chinese female patients with invasive ductal carcinoma of no special type (IDC-NST) enrolled from January 2013 to July 2018 were divided into a training set (n = 244) and a testing set (n = 62). One hundred and eighty-six radiomics features were extracted from digital MG images based on the training set. The least absolute shrinkage and selection operator (LASSO) method was used to select the optimal predictive features for HER-2 status from the training set. Both support vector machine (SVM) and logistic regression models were employed based on the selected features. The area under the receiver operating characteristic (ROC) curves (AUCs) of the training set and testing set were used to evaluate the predictive performance of the models. ResultsCompared with the SVM model, the performance of the logistic regression model using a combination of cranial caudal (CC) and mediolateral oblique (MLO) MG views was optimal. In the training set, the sensitivity, specificity, accuracy and area under the curve (AUC) values of the logistic regression model for evaluating HER-2 status based on quantitative radiomics features were 87.29%, 58.73%, 80.00% and 0.846 (95% confidence interval (CI), 0.800-0.887), respectively, and in the testing set, the values were 73.91%, 68.75%, 77.00% and 0.787 (95% CI, 0.673-0.885), respectively. ConclusionsRadiomics features could be an efficient tool for the preoperative evaluation of HER-2 status in patients with breast cancer.