Signatures In Breast Cancer Research Articles

Transcriptional Signatures Derived from Murine Tumor-Associated Macrophages Predict Outcome in Breast Cancer Patients

Tumor-associated macrophages (TAMs) are frequently the most abundant immune cells in murine and human cancers and are associated with poor survival. Here we generated TAM molecular signatures from K14cre;Cdh1flox/flox;Trp53flox/flox (KEP) and MMTV-NeuT (NeuT) transgenic mice which resemble human invasive lobular carcinoma (ILC) and HER2+ tumors, respectively. Determination of TAM-specific signatures in breast cancer required relationship analysis with healthy mammary tissue macrophages, since comparison with other macrophage populations overestimated TAM-specific gene expression. TAMs from the two models featured a distinct transcriptomic profile and KEP-derived signatures reliably predicted outcome in ILC patients, indicating that translation of murine TAM signatures to patients warrants consideration of the cancer subtype. Collectively, we show that a transgenic mouse tumor model can be utilized to derive a TAM signature for human breast cancer outcome prediction and we provide a generalizable strategy for determining and applying immune cell signatures provided the murine model reflects the human disease.

Characterization of molecular scores and gene expression signatures in primary breast cancer, local recurrences and brain metastases

BackgroundBreast cancer is a leading cause of cancer-related death in women worldwide. Despite extensive studies in all areas of basic, clinical and applied research, accurate prognosis remains elusive, thus leading to overtreatment of many patients. Diagnosis could be improved by introducing multigene molecular scores in standard clinical practice. Several tests that work with formalin-fixed tissue have become routine. Molecular scores usually include several genes representing processes, response to oestrogens, progestogens and human epidermal growth factor receptor 2 (Her2), respectively, which are combined additively in single values. These multi-gene scores have the advantage of being more robust and reproducible than single-gene scores. Their utility may be further enhanced by combining them with classical diagnostic parameters. Here, we present an exploratory study comparing the RISK and research versions of Oncotype DX recurrence score (RS), Prosigna Risk of Recurrence (ROR) and EndoPredict (EP) with respect to their prognostic potential for ipsilateral recurrence and/or distant relapse in brain, and we compared the scores to the intrinsic subtypes based on PAM50.MethodsRNA was extracted from formalin-fixed, paraffin-embedded (FFPE) tissue cores of primary tumours, local recurrences and brain metastases. Gene expression was measured on a NanoString nCounter Analysis System. Intrinsic subtypes and molecular scores were computed according to published literature and RISK, RS, ROR and EP were compared against each other and to the intrinsic subtypes Luminal A (lumA), Luminal B (lumB), Her2-enriched (Her2↑), Basal-like (basal), and Normal-like (normal) of PAM50. Local recurrences and brain metastases were compared to their corresponding primary tumours.ResultsAll four molecular scores were highly correlated. Highest correlations were observed among genes related to proliferation while lower correlations were found among oestrogen-related genes. The scores were significantly higher in primary tumours progressing to brain metastases as compared to recurrence-free primary tumours and primary tumours that relapsed as local recurrences.ConclusionsRISK and ROR-P are prognostic for primary tumours metastasizing to the brain. All four scores, RISK, RS, EP and ROR-P failed to discriminate between primary tumours that remained recurrence-free and primary tumours relapsing as local recurrences.

Investigating the utility of breast cancer (BC) molecular signatures and immune signature profiling (ISP) as predictors of pathological complete response (pCR) to neoadjuvant chemotherapy + trastuzumab (NAC+T) in HER2+ BC.

e12109 Background: Trastuzumab targets HER2 directly as well as contributes to activation of the immune system against the tumor. We investigated the utility of BC molecular signatures and ISP as predictors of pCR to NAC+T in HER2+ BC pts. Methods: The analysis included 73 consecutive HER2+ BC pts with pathological samples at diagnosis, who received NAC+T. RNA was extracted from 73/22 biopsy/surgical specimens (FFPE). RNA was analyzed using NanoString PanCancer Immunoncology 360 (IO360) panel with PAM50 spike-in. Raw gene counts were log2-transformed and normalized (using housekeeping genes). The analysis assessed 47 gene signatures including immune related and PAM50 signatures. Signatures were computed after removing samples with low expression of the housekeeping genes and normalization. Signature scores range from ~0 to 10 and have an average value of 5 in tumor samples from The Cancer Genome Atlas. Results: Overall, 46% of the pts achieved pCR; of 13 pts who were IHC 2+ and FISH positive, one achieved pCR. Significant associations were found between response to NAC+T (pCR, no response) and molecular signatures/ISP from the initial biopsy (Table). For pts who did not experience pCR and who underwent surgery, paired sample analysis was performed assessing molecular signatures/ISP in the initial biopsy sample vs the surgical sample. This analysis demonstrated a significant increase post-treatment (compared to the initial biopsy sample) in Risk of Recurrence (ROR) score (p=.036), interferon (IFN) downstream signature (p=.038), and antigen‐processing machinery (APM) loss (p=.002). Conclusions: Combining molecular BC signatures and ISP on biopsy samples may have a predictive value in HER2+BC pts for whom NAC+T is considered. Luminal A pts and IHC 2+ (FISH positive) are unlikely to achieve pCR with NAC+T. [Table: see text]

Alternative polyadenylation of single cells delineates cell types and serves as a prognostic marker in early stage breast cancer.

Alternative polyadenylation (APA) in 3’ untranslated regions (3’ UTR) plays an important role in regulating transcript abundance, localization, and interaction with microRNAs. Length-variation of 3’UTRs by APA contributes to efficient proliferation of cancer cells. In this study, we investigated APA in single cancer cells and tumor microenvironment cells to understand the physiological implication of APA in different cell types. We analyzed APA patterns and the expression level of genes from the 515 single-cell RNA sequencing (scRNA-seq) dataset from 11 breast cancer patients. Although the overall 3’UTR length of individual genes was distributed equally in tumor and non-tumor cells, we found a differential pattern of polyadenylation in gene sets between tumor and non-tumor cells. In addition, we found a differential pattern of APA across tumor types using scRNA-seq data from 3 glioblastoma patients and 1 renal cell carcinoma patients. In detail, 1,176 gene sets and 53 genes showed the distinct pattern of 3’UTR shortening and over-expression as signatures for five cell types including B lymphocytes, T lymphocytes, myeloid cells, stromal cells, and breast cancer cells. Functional categories of gene sets for cellular proliferation demonstrated concordant regulation of APA and gene expression specific to cell types. The expression of APA genes in breast cancer was significantly correlated with the clinical outcome of earlier stage breast cancer patients. We identified cell type-specific APA in single cells, which allows the identification of cell types based on 3’UTR length variation in combination with gene expression. Specifically, an immune-specific APA signature in breast cancer could be utilized as a prognostic marker of early stage breast cancer.

64P - Identification of serum proteome signatures of male breast cancer

64P - Identification of serum proteome signatures of male breast cancer

Evaluating cooperative roles for STAT3 and Aiolos in lymphocyte mimicry associated with metastatic disease

Abstract Inappropriate expression and function of cytokine and chemokine receptors by both hematopoietic and non-hematopoietic cell populations have been linked to human disease. One example of this is the expression of lymphocytic genes by metastatic cancers, termed lymphocyte mimicry. Specifically, the aberrant expression of chemokine receptors by cancer cells allows for inappropriate responses to immune signals, migration, and increased ability to survive in circulation. The mechanisms that regulate lymphocyte mimicry are currently incompletely understood. Our laboratory recently identified a novel transcriptional complex composed of the Ikaros Zinc Finger transcription factor Aiolos and STAT3 that regulates gene expression in CD4+ T cells, including that of chemokine receptors. Interestingly, Aiolos and STAT3 have been independently implicated in multiple cancers, including metastatic breast cancer. We hypothesized that Aiolos and STAT3 may cooperate to induce chemokine receptor expression in metastatic breast cancer cells. Our study observed increased Aiolos expression and STAT3 activation in metastatic breast cancer cells as compared to non-tumorgenic and non-metastatic controls. This correlated with increased expression of the chemokine receptor CXCR4, which has been previously linked to metastatic cancer. Importantly, shRNA knockdown of Aiolos in metastatic cells resulted in decreased expression of CXCR4. Collectively, these data support a role for Aiolos, possibly in collaboration with STAT3, in the induction of a metastatic gene signature in human breast cancer.

Association of BRCA1- and BRCA2-deficiency with mutation burden, expression of PD-L1/PD-1, immune infiltrates, and T cell-inflamed signature in breast cancer.

Immune checkpoint inhibitors have demonstrated effective anti-tumour response in cancer types with high mutation burden (e.g. melanoma) and in subset of cancers with features of genomic instability (e.g. mismatch-repair deficiency). One possible explanation for this effect is the increased expression of immune checkpoint molecules and pre-existing adaptive immune response in these cancers. Given that BRCA1 and BRCA2 are integral in maintaining genomic integrity, we hypothesise that the inactivation of these genes may give rise to breast cancers with such immunogenic phenotype. Therefore, using two large series of publicly available breast cancer datasets, namely that from The Cancer Genome Atlas and Wellcome Trust Institute, we sought to investigate the association between BRCA1- and BRCA2-deficiency with features of genomic instability, expression of PD-L1 and PD-1, landscape of inferred tumour-infiltrating immune cells, and T-cell inflamed signature in breast cancers. Here, we report that BRCA1 and BRCA2-deficient breast cancers were associated with features of genomic instability including increased mutation burden. Interestingly, BRCA1-, but not BRCA2-, deficient breast cancers were associated with increased expression of PD-L1 and PD-1, higher abundance of tumour-infiltrating immune cells, and enrichment of T cell-inflamed signature. The differences in immunophenotype between BRCA1- and BRCA2-deficient breast cancers can be attributed, in part, to PTEN gene mutation. Therefore, features of genomic instability such as that mediated by BRCA1- and BRCA2- deficiency in breast cancer were necessary, but not always sufficient, for yielding T cell-inflamed tumour microenvironment, and by extension, predicting clinical benefit from immunotherapy.

Genomic mutation signatures in primary breast cancer and their axillary metastatic lymph nodes

Abstract Breast cancer is one of the most common malignant tumors in women all over the world. Metastasis represents a major adverse progression of breast cancer, resulting in poor survival duration. Axillary lymph node metastasis is often the first step of systemic metastasis process of breast cancer. However, the mechanism of lymph node metastasis and the genomic signatures of primary breast tumors and lymph node metastasis are still under exploration. Whole exome sequencing was applied to primary breast cancer, axillary metastatic lymph nodes, and white blood cells from 10 Chinese women patients in our study. Single nucleotide variants (SNVs) and copy-number variants (CNVs) were compared between primary tumors and lymph nodes for individual patients. There are somatic SNVs (average 5.58 ± 2.56 per megabase) in primary breast cancers and somatic SNVs (average 5.46 ± 2.66 per megabase) in axillary metastatic lymph nodes were identified, which is corresponding to a semblable mutation burden in two malignant sites (P = 0.81). No difference was found in CNVs (P = 0.33). In primary breast cancer, somatic SNVs (48.12 ± 13.80%) and CNVs (61.72 ± 35.00%) were overlapping with somatic SNVs (49.43 ± 12.30%) and CNVs (72.01 ± 24.31%) in axillary metastatic lymph nodes. Nine genes were screened for significant specific mutations in primary tumors, and 15 genes were significantly mutated in metastatic lymph nodes. Using MutSigCV screening, it was found that HRNR and AHNAK2 are lymph node metastasis-specific genes. In our study, primary breast tumors are directly related to axillary lymph node metastases together and there are most SNVs and CNVs which were overlapping in primary and metastatic sites. These variants which are overlapping is closely related to the metastatic process of tumor invasion with early genetic variability. This is the first time to prove the concept of polyclonal metastatic model and in this model more than one clone migrates establish the metastases to axillary lymph nodes. This study was approved by the institutional review board (IRB) of the Cancer Hospital, Chinese Academy of Medical Sciences, and Peking Union Medical College, China (approval No. NCC2016G-030) on March 3, 2016.

Construction of prognostic microRNA signature for human invasive breast cancer by integrated analysis.

BackgroundDespite the advances in early detection and treatment methods, breast cancer still has a high mortality rate, even in those patients predicted to have a good prognosis. The purpose of this study is to identify a microRNA signature that could better predict prognosis in breast cancer and add new insights to the current classification criteria.Materials and methodsWe downloaded microRNA sequencing data along with corresponding clinicopathological data from The Cancer Genome Atlas (TCGA). Of 1,098 breast cancer patients identified, 253 patients with fully characterized microRNA profiles were selected for analysis. A three-microRNA signature was generated in the training set. Subsequently, the performance of the signature was confirmed in a validation set. After construction of the signature, we conducted additional experiments, including flow cytometry and the Cell Counting Kit-8 assay, to illustrate the correlation of this microRNA signature with breast cancer cell cycle, apoptosis, and proliferation.ResultsThree microRNAs (hsa-mir-31, hsa-mir-16-2, and hsa-mir-484) were identified to be significantly and independently correlated with patient prognosis, and performed with good stability. Our results suggest that higher expression of hsa-mir-484 indicated worse prognosis, while higher expression of hsa-mir-31 and hsa-mir-16-2 indicated better prognosis. Moreover, additional experiments confirmed that this microRNA signature was related to breast cancer cell cycle and proliferation.ConclusionOur results indicate a three-microRNA signature that can accurately predict the prognosis of breast cancer, especially in basal-like and hormone receptor-positive breast cancer subtypes. We recommend more aggressive therapy and more frequent follow-up for high-risk groups.

Abstract P1-09-01: CD8+ T-cell gene expression and signatures in breast cancer and adjacent normal breast tissue: Association with body mass index, alcohol intake, and age at diagnosis

Abstract Background: Our understanding of mediators of immune infiltration in breast cancer and normal breast tissue remains limited. We hypothesize that patient factors known to be associated with inflammation and immune subsets, including body mass index, alcohol intake, and age and diagnosis, may play an important role in the tumor-immune microenvironment. Analyses of immune gene expression and signatures facilitate interrogation of the immune microenvironment in large patient cohorts. Methods: Participants from the Nurses' Health Study cohorts I and II diagnosed with invasive breast cancer were included. Total RNA extracted and microarray performed for 882 tumor and 695 tumor-adjacent samples, of which 623 tumors have matched tumor-adjacent data. CD8+ T-cell expression metrics were assessed: CD8A single gene expression (CD8Agene), a CD8 T-cell signature (CD8sig), and a tumor infiltrating lymphocyte signature derived from the GeparSixto clinical trial (GSAct). Standard clinicopathologic features were evaluated, as well as body mass index (BMI) one year prior to diagnosis, cumulative average alcohol intake, and age at diagnosis. Results: Overall, tumor and adjacent normal tissue demonstrated positive correlation of CD8Agene, CD8sig, and GSAct (n=623 pairs, Pearson's r = 0.46, 0.36, 0.31, respectively; all p<0.001). Similar correlations were present in TCGA breast cancer, an independent cohort (n=112 pairs, Pearson's r = 0.34, 0.17, 0.45, respectively; all p<0.001). We evaluated paired tumor and adjacent normal samples within individual immunohistochemical (IHC) subtype or PAM50 subtype by Wilcoxon signed-rank test. There was not a consistent trend for CD8Agene, CD8sig, nor GSAct to be greater in tumor or normal within subtypes. We then evaluated patient features/exposures and tumor immune expression metrics. For tumor-adjacent normal, there was no significant association of alcohol intake, BMI, or age at diagnosis with CD8 gene/expression metrics. For tumor tissue, a multivariate model demonstrated that BMI one year before diagnosis was significantly associated with CD8Agene expression. There was no significant association of alcohol intake or age at diagnosis with CD8 gene/expression metrics. We are currently evaluating the association of these CD8 T-cell gene expression signatures with CD8 T-cell immunohistochemistry in a subset of patients, which will be reported at the time of abstract presentation. Conclusion: In this cohort of over 600 tumor:normal pairs and a separate validation cohort, multiple distinct CD8+ T-cell expression metrics are correlated between breast cancer and tumor-adjacent normal breast tissue. This suggests that the adjacent normal breast may reflect an altered immune microenvironment in the context of breast cancer. While age at diagnosis and alcohol intake are not significantly associated with tumor CD8 expression metrics, BMI was significantly associated with tumor CD8Agene expression in a multivariate model. Citation Format: Damicis A, Heng YJ, Kensler K, Asad S, Adams E, Singh J, Zhang Y, Nock W, Wesolowski R, Williams N, Reinbolt R, Sardesai S, VanDeusen J, Noonan A, Lustberg MB, Ramaswamy B, Eliassen AH, Hankinson SE, Tamimi R, Stover DG. CD8+ T-cell gene expression and signatures in breast cancer and adjacent normal breast tissue: Association with body mass index, alcohol intake, and age at diagnosis [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P1-09-01.

Abstract P2-08-17: Tumor inflammation signature (TIS), intrinsic subtypes and chemo-endocrine score (CES) in metastatic triple-negative breast cancer (mTNBC): A SOLTI biomarker program study

Abstract Background: The TIS is a clinical research gene expression-based assay that enriches for response to anti-PD1 monotherapy in multiple cancer-types (Ayers et al. JCI 2017). However, the expression of the TIS in mTNBC and its relationship with other biological classifications and overall survival (OS) is currently unknown. Methods: A comprehensive RNA-based characterization of 45 patients with mTNBC treated at 2 SOLTI sites was performed. RNA from metastatic biopsies was analyzed on the nCounter system using the Breast Cancer 360TM panel, which includes 752 breast cancer-related genes, including the TIS and the PAM50 and TNBCtype subtype classifications. The 1ary objective was to estimate the proportion of TIS-high tumors (defined as a score above its median expression in the PanCancer TCGA dataset) within PAM50 Basal-like disease. 2ary objectives were 1) to explore TIS distribution across the other molecular subtypes, 2) to evaluate the distribution of the PAM50 and TNBCtype subtype classifications in mTNBC, 3) to explore the association between OS and TIS, subtypes and 38 additional signatures tracking multiple tumor biological processes. OS was defined as the time from the date of metastatic diagnosis to death or last follow-up. Descriptive statistics, log-rank tests and univariate cox models were performed using R code. Results: Most tumor samples (77.3%) were obtained at first recurrence or diagnosis of metastatic disease. Metastatic biopsies were obtained from 10 different sites, being skin (31.3%), breast (22.2%) and lung (8.9%) the most frequent. PAM50 subtype distribution was as follows: Basal-like (73.3%), Luminal A (13.3%), HER2-enriched (11.1%) and Luminal B (2.2%). Similarly, all the TNBCtype subtypes were identified: Mesenchymal (MSL, 48.8%), Basal-like Immune-activated (31.2%), Luminal Androgen Receptor (LAR, 15.6%) and Basal-like Immune-Suppressed (4.4%). The vast majority of non-Basal-like tumors were identified as LAR or MSL (81.8%). The proportion of TIS-high within Basal-like disease was 73% (95% confidence interval [CI] 59-84%) and similar to the proportion of TIS-high within TNBC from TCGA (70%, CI 61-78%). The proportion of TIS-high was similar across the PAM50 and TNBCtype molecular subtypes. The median OS was 25.3 months (CI 19.2-36.8). TIS, PAM50 and TNBCtype subtypes were not found associated with OS. Among the 41 biological classifications, expression of 6 signatures were found significantly associated with OS: CES (hazard ratio [HR] 0.44; p=0.015), Basal-like score (HR=5.52; p=0.011), FOXA1 (HR=0.83; p=0.014), mast cells (HR=0.77; p=0.017), differentiation score (HR=0.63; p=0.039) and Luminal A score (HR=0.27; p=0.039). Compared to tumors with a CES-low score, tumors with a CES-high score were found enriched for luminal-related genes, including AR. Conclusions:˜50% of mTNBC tumors are PAM50 Basal-like and are enriched for the TIS. Future studies should determine the ability of this biomarker to predict response to anti-PD1 monotherapy or in combination with chemotherapy. In addition, mTNBC with a high luminal-profile or CES might help identify patients who might benefit from anti-androgen therapies alone or in combination with immunotherapy. Citation Format: Pascual T, Pernaut C, Tolosa P, Galvan P, Bárcena C, Vidal M, Manso L, Adamo B, Dueñas M, Muñoz M, Chic N, Gonzalez-Farre B, Villagrasa P, Ciruelos E, Prat A. Tumor inflammation signature (TIS), intrinsic subtypes and chemo-endocrine score (CES) in metastatic triple-negative breast cancer (mTNBC): A SOLTI biomarker program study [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P2-08-17.

Abstract P2-08-12: Development and validation of prognostic gene signatures for basal-like breast cancer and high grade serous ovarian cancer

Abstract Background: Basal-like breast cancer (BLBC) have poor prognosis. Molecular similarities have been reported between BLBC and high grade serous ovarian cancer (HGSOC). To date, there have been no prognostic biomarkers specifically developed for BLBC or HGSOC that can provide risk stratification and inform treatment selections. In this study, we utilized RNA-seq data available from The Cancer Genome Atlas (TCGA) project to develop molecular signatures for risk stratification in BLBC, and further validated these signatures in HGSOC RNA-seq data from TCGA. Methods: Raw count of RNA-seq data were downloaded from TCGA for 190 BLBC and 374 HGSOC patients. The datasets were annotated with 56963 Ensembl gene IDs. Excluding 31375 gene IDs with no greater than 10 counts in at least 90% of the samples, totally 25228 unique Ensembl gene IDs were used. Progression-free interval (PFI) is the primary study endpoint. Analyses of differentially expressed genes were performed using 3 bioconductor packages: DESEq2, edgeR and voom/limma. Signatures based on commonly identified genes among the 3 analytic methods were established using weighted linear combination of gene expression levels. Their performance was evaluated in the BLBC and HGSOC datasets using Kaplan-Meier survival analysis with log-rank tests and Cox proportional hazard regressions. Results: Among 190 TNBC patients, 18 had recurrences within 2 years and 40 showed no recurrences for at least 5 years. These patients were used as recurrent vs. non-recurrent cases for differential expression analysis. 307 and 343 genes were differentially expressed based on adjusted p value threshold 0.05 and 0.01 in DESeq2 and edgeR analysis, respectively. voom/limma identified no genes differentially expressed based on adjusted p values, but 228 genes had unadjusted p values < 0.01 and were used in the following analysis. Taken together, 63, 58 and 21 genes were commonly identified by DESeq2/edgeR, DESeq2/limma and edgeR/limma analysis, respectively. All 3 signatures were able to significantly stratify the TNBC full dataset (n=190) using either 20-, 50- or 80-percentile as the cut-points. When evaluated in HGSOC patients using 80-percentile cut-point, both 63- and 58-gene signatures were able to significantly stratify patients into different risk groups (HR 2.16, 95% CI: 1.4-3.34, p < 0.001; HR 2.06, 95% CI: 1.36-3.11, p < 0.001). Multivariate Cox regression adjusting for age, grade and stage showed 63- and 58-gene signatures remained to be statistically significant in stratifying HGSOC patients (p = 0.0005 and 0.001, respectively). Conclusion: Gene signatures were specifically identified to prognosticate BLBC patients based on RNA-seq data from TCGA project. Which were able to classify HGSOC patients into differential risk groups. With further validations, these signatures may provide additional prognostic tools for clinicians to better manage triple-negative breast cancer that mostly overlap with BLBC, and HGSOC patients who are difficult-to-treat currently. Disclaimer The views expressed in this article are those of the authors and do not reflect the official policy of the department of Army/Navy/Air Force, Department of Defense, or U.S. government. Citation Format: Hu H, Zhang Y, Liu J, Raj-Kumar P-K, Yang H, Lee M, Kovatich AJ, Shriver CD. Development and validation of prognostic gene signatures for basal-like breast cancer and high grade serous ovarian cancer [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P2-08-12.

Abstract P6-19-01: Evaluation of multiple transcriptomic gene risk signatures in male breast cancer

Abstract Introduction: Male breast cancer (MBC) is a rare disease accounting for less than 1% of all breast cancers (BC) and 1% of all cancers in males. The clinical management is largely extrapolated from female BC. Several multigene assays are increasingly used to guide clinical treatment decisions in female BC, however there is little data on the utility of these tests in MBC. Methods: Here we present the gene expression results of 380 M0, ER+ve, HER2-ve MBCs enrolled in the Part 1 (retrospective joint analysis) International Male Breast Cancer Program of 1483 patients diagnosed between 1990-2010 (Cardoso et al. Annals of Oncology, 2018). Using a custom Nanostring™ panel comprised of the genes from the commercial risk tests Prosigna®, OncotypeDx® and Mammaprint®, risk scores and intrinsic subtyping data were generated to recapitulate the commercial tests as described by Bayani and Yao et al (npjBreast Cancer, 2017). Survival outcomes by risk classification were analyzed using Cox models with time-dependent covariates when the proportional hazard assumption was not met and adjusted for clinical and treatment variables. Results: Prosigna-like risk scores identified 99 (26.1%) as low-risk, 159 (41.8%) as intermediate-risk, and 122 (32.1%) as high-risk. Using the TAILORx cut-off (25) for OncotypeDx-like risk of recurrence scoring, 158 (41.6%) were identified as low-risk, while 222 (58.4%) were identified as high-risk. MammaPrint-like results identified 175 (46.1%) as low-risk and 205 (53.9%) as high-risk. Overall, patients classified as high-risk had higher grade, more nodal involvement, larger tumors, and more frequently treated with chemotherapy than low-risk patients. Survival analyses demonstrated clear clinical utility for each test, showing patients at high-risk with poor relapse-free survival (RFS) as compared to patients classified as low-risk: Prosigna-like RFS at 3-years (HR=2.20, 95% CI, 1.28-3.80); Oncotype-like RFS at 3-years (HR=1.92, 95% CI, 1.17-3.17); MammaPrint-like RFS (HR=1.51, 95% CI, 1.00-2.27); with similar findings for distant relapse-free survival (DRFS) and overall survival (OS). Across outcomes and all gene signatures, patients with concordant Low/Low risk classification had better prognosis than those with concordant High/High risk classification. PAM50 intrinsic subtyping identified 147 (38.7%) as Luminal A, 57 (15.0%) as Luminal B, 80 (21.1%) as Her2-enriched and 96 (25.3%) as Basal-like; showing overall 34.5% concordance to clinic-pathological subtyping by central pathology (95% CI, 29.7%-39.5%). Comparison between the tests in the MBC cohort and a comparable cohort of female BC from the Tamoxifen Exemestane Adjuvant Multinational (TEAM) trial processed in the same way will be presented. Conclusion: Common transcriptomic assays designed to assess residual risk, validated in female BC, provide similar information in male BC patients. Not surprisingly, disagreement between test results at the individual patient level was observed. To our knowledge, this is the largest study of MBC assayed to generate risk scores of the current commercial BC tests to demonstrate their clinical utility and their differences and similarity to female BC. This work has been funded by the Breast Cancer Research Foundation (BCRF). Citation Format: Bayani J, Poncet C, Yao CQ, Crozier C, Anouk N, Piper T, Cunningham C, Sobol M, Aebi S, Benstead K, Bogler O, Dal Lago L, Fraser J, Hilbers FH, Hedenfalk I, Korde L, Linderholm B, Martens J, Middleton L, Murray M, Kelly C, Nilsson C, Nowaczyk M, Peeters S, Peric A, Porter P, Schröder C, Rubio IT, Ruddy KJ, van Asperen C, Van Den Weyngaert D, van Deurzen C, van Leeuwen-Stok E, Vermeij J, Winer E, Boutros PC, Giordano SH, Cardoso F, Bartlett JM. Evaluation of multiple transcriptomic gene risk signatures in male breast cancer [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P6-19-01.

Prognostic significance of high metabolic activity in breast cancer: PET signature in breast cancer

High metabolic activity, reflected in increased glucose uptake, is one of the hallmarks of many cancers including breast cancer. However, not all cancers avidly take up glucose, suggesting heterogeneity in their metabolic demand. Thus, we aim to generate a genomic signature of glucose hypermetabolism in breast cancer and examine its clinical relevance. To identify genes significantly associated with glucose uptake, gene expression data were analyzed together with the standardized uptake values (SUVmax) of 18F-fluorodeoxy-glucose on positron emission tomography (PET) for 11 breast cancers. The resulting PET signature was evaluated for prognostic significance in four large independent patient cohorts (n = 5417). Potential upstream regulators accountable for the high glucose uptake were identified by gene network analysis. A PET signature of 242 genes was significantly correlated with SUVmax in breast cancer. In all four cohorts, high PET signature was significantly associated with poorer prognosis. The prognostic value of this PET signature was further supported by Cox regression analyses (hazard ratio 1.7, confidential interval 1.48–2.02; P < 0.001). The PET signature was also strongly correlated with previously established prognostic genomic signatures such as PAM50, Oncotype DX, and NKI. Gene network analyses suggested that MYC and TBX2 were the most significant upstream transcription factors in the breast cancers with high glucose uptake. A PET signature reflecting high glucose uptake is a novel independent prognostic factor in breast cancer. MYC and TBX2 are potential regulators of glucose uptake.

Abstract P2-08-33: A novel seven-gene signature predicts prognosis in early-stage triple-negative breast cancer

Abstract Purpose: Chemotherapy remains the only systemic treatment option for patients with triple-negative breast cancer (TNBC). However, due to the heterogeneity of TNBC, not all patients benefit from chemotherapy, especially those with early-stage disease. In order to improve prognostic assessment and reduce unnecessary adjuvant systemic therapy in these patients, we have developed a novel seven-gene signature. Experimental Design: With the ComBat method, we integrated the results from 150 transcriptome microarrays samples and 246 RNA-seq samples of early-stage TNBC patients, and identified mRNAs associated with recurrence-free survival (RFS) using Lasso-Cox model, We further analyzed these TNBC samples and compared them with 60 paired normal breast tissues (40 samples from RNA-seq and 20 samples from microarrays) to identify tumor-specific mRNAs. Twenty-one overlapped mRNAs of the RFS-associated mRNAs and the tumor-specific mRNAs are selected as candidate mRNAs. An additional 371 samples of frozen primary tumors were then collected from early-stage TNBC patients (mean follow-up of 45 months) and randomly divided into two sets: a training set (n = 186) and a validation (n = 185) set. Expression level of candidate mRNAs in these samples were measured using RT-qPCR assays, and a seven-gene signature was built through all subset regression in the training set. The prognostic and predictive accuracy of our signature was tested in the validation set and other public databases (GSE5327, GSE2034 and METABRIC). Results: Twenty-one candidate mRNAs were identified in early-stage TNBC patients, from which we developed a novel seven-gene signature (recurrence risk score [mRNA signature] = 1.108*TMEM101 - 0.213*KRT5 - 0.315*ACAN - 0.464*LCA5 + 0.446*RPP40 - 0.373*LAGE3 - 0.257*CDKL2). Patients in the training set were classified into high- or low-risk group based on our seven-gene signature and an optimum cut-off score derived from x-tile. The patients in high-risk group were more likely to suffer from recurrence (HR, 2.718; 95% confidence interval [CI], 1.928–3.726, P= 0.001), and a time-dependent receiver operating curve showed that the seven-gene mRNA signature had a better prognostic value than the clinicopathologic risk factors in both training set and validation set. The prognostic and predictive accuracy of the signature was also validated in the METABRIC and two other public GEO databases (GSE5327 and GSE2034). The time-dependent receiver operating curve showed that this signature had an area under the curve (AUC) of 0.742 (95% CI, 0.705-0.773) in METABRIC, 0.716 (95% CI, 0.682-0.739) and 0.723 (95% CI, 0.683-0.756) in GSE5327 and GSE2034 respectively. Conclusion: In this study, we developed a novel seven-gene signature which can provide additional prognostic information and may guidance in identifying early-stage TNBC patients eligible for adjuvant therapy or reduction of chemotherapy. To our knowledge, this is the first study investigating the prognostic potential of mRNA signature in early-stage triple-negative breast cancer. Our novel signature may provide an opportunity for de-escalating treatment in early-stage TNBC patients in the future. Citation Format: Ren Y, Jiang Y, Zuo W, Xu X, Jin X, Ma D, Shao Z. A novel seven-gene signature predicts prognosis in early-stage triple-negative breast cancer [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P2-08-33.

Abstract P1-20-05: Raman imaging as a tool for the chemical and spatial characterization of breast microcalcifications to improve lesion assessment

Abstract Background: microcalcifications (MC) are common findings on screening mammography and are among the earliest signs of breast cancer. At the same time, from the use of well-known radiographic risk score systems, which include MC assessment, such as Breast Imaging-Reporting and Data System (BI-RADS), only 20% of screened patients are further associated with malignancy. This leads to repeated biopsies and to unnecessary surgeries with discomfort for patients and increased costs for the healthcare system. Furthermore, the definitive diagnosis by histological and immunohistological evaluations is still laborious and time-consuming. Raman Spectroscopy (RS) is a photonic approach capable to provide detailed chemical information of analysed samples without complex tissue preparation or staining. RS has a proven ability to distinguish different crystal structures, including those commonly present in MC. In this context some studies based on RS suggested a correlation between MC chemical features and pathology. On the other hand, previous Raman-based studies mainly investigated the overall MC chemical composition (by single-point scans) while an extensive MC characterization by Raman imaging approaches (mapping) for diagnostic purposes is still lacking. The aim of this study is to assess the usefulness of Raman imaging as a quick and accurate tool for a complete spatial characterization of MC detected on screening mammography and sampled by breast biopsy in order to better distinguish malignant vs. benign lesions. Method: 30 patients with breast calcifications detected on mammography with radiological classification BI-RAD 3-5 where selected and evaluated by core biopsy. 10 μm formalin-fixed paraffin-embedded (FFPE) histological sections obtained from biopsies were dewaxed with a specifically developed protocol that allows the removal of paraffin in less than 15 minutes. All MC present in each tissue section (usually from 2 to &amp;gt;10 per section) were then characterized by a Raman microscope thus obtaining Raman maps with lateral resolution between 5 and 10 μm. After pre-processing steps the Raman maps were analysed by both clustering and multivariate analysis approaches used to produce false-colour images and to perform automated features identification. Results: Our results confirm that hydroxyapatite is the prevalent form of calcium phosphate in MC and that MC composition correlates with lesion malignancy. In addition, thanks to the Raman imaging approach used here, we report for the first time that hydroxyapatite is more homogeneously distributed in malignant lesions and that, on the contrary, benign lesions show a heterogeneous distribution of hydroxyapatite, whitlockite and calcium-carbonate, inside the lesion and in the surrounding tissue. Conclusion: These evidences suggest that the characterization of MC by Raman imaging is a potential tool for the definition of new diagnostic signatures of breast cancer, especially if we consider that these evaluations can be performed by the simple and relative fast scanning of dewaxed slices, without altering the clinical workflow and without the need of staining or antibodies. Further studies with a larger cohort will be done to validate these results. Citation Format: Vanna R, Morasso C, Piccotti F, Sorrentino L, Villani L, Torti E, Bonizzi A, Leporati F, Corsi F. Raman imaging as a tool for the chemical and spatial characterization of breast microcalcifications to improve lesion assessment [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P1-20-05.

Abstract PD7-10: Neoadjuvant trial with letrozole identifies PRR11 in 17q21-23 amplicon as a resistance mechanism to endocrine therapy in ER-positive breast cancer

Abstract Approximately 20% of patients with early ER+ breast cancer (BC) treated with adjuvant antiestrogen therapy relapse with metastatic disease. Previously, we identified 3 amplicons (11q11.3, 8p11.23, and 17q21-23) associated with endocrine-resistance (Giltnane et al. Sci Transl Med 2017). The 17q21-23 amplicon has been associated with highly proliferative luminal B tumors and cancers with high genomic instability. A causal role of this region in endocrine resistance is unclear. We performed whole transcriptome analysis on RNA extracted from 58 ER+ breast cancers of patients treated with letrozole for 5.4-9.2 months (median 7.2 months). PRR11 (Proline rich 11), located in 17q21-23, was significantly upregulated in non-responding tumors as defined by cancer relapse after a median follow up of 5 years and/or a preoperative endocrine prognostic index (PEPI) ≥4. Differential gene expression analysis between tumors expressing low vs high PRR11 mRNA showed that BC signatures associated with proliferation, cell cycle, IGF-1 and PI3K signaling were enriched in tumors with high PRR11 expression. In the Metastatic Breast Cancer Project and TCGA, PRR11 amplification was higher in metastatic vs. primary BCs (16.5% and 8.5%, respectively; Fisher's p=0.0088). Gene Set Enrichment Analysis of mRNA expression in METABRIC and TCGA revealed significant enrichment of hallmark gene sets associated with proliferation in PRR11 amplified ER+ BCs. Genome-scale RNAi screening in Project Achilles showed that among all genes in the 17q21-23 amplicon, PRR11 knockdown results in the 4th strongest anti-proliferative effect in MCF7 cells. PRR11 knockdown with siRNA inhibited proliferation, cell cycle progression, and RB phosphorylation in HCC1428 LTED (long-term estrogen deprived), MCF7 LTED, and fulvestrant-resistant MCF7 cells. Using a PCR array with 84-cell cycle genes, we identified SKP2, CDKN1A, CCNB2, CCNA2, CKS2 and CCNB1 as genes downregulated by PRR11 knockdown. Except for CDKN1A, expression of all those genes was elevated ER+ BCs with PRR11 gain or amplification in TCGA. PRR11 associates with the p85 regulatory subunit of PI3K via its SH3 domain. We speculated this association would suppress p85 homodimers, thus permitting binding of PI3Kα (p110α)-p85 dimers to IRS1 and, hence, activating PI3K/AKT. To test this, we co-transfected HEK293T cells with HA-p85 and FLAG-p85. Transfection of PRR11 into these HEK293T cells reduced HA-p85 and FLAG-p85 homodimers as shown by HA and FLAG pulldowns followed by FLAG and HA immunoblots, respectively. Finally, PRR11 knockdown resulted in a reduction of p110a and S473 P-AKT levels and inhibition of IGF-1/2 stimulated P-AKT. Not inconsistent with these data, PRR11 amplification and PIK3CA mutations in METABRIC and TCGA are exclusive of each other, suggesting these alterations are functionally linked with the same signaling pathway. These data support a role of PRR11 in PI3K/AKT activation that may be causal to resistance to estrogen deprivation. We propose PRR11, located in the 17q21-23 amplicon, is a potential mediator of resistance to antiestrogen therapy by amplifying PI3K/AKT signaling, suggesting PI3K may be a therapeutic target in ER+ BCs harboring PRR11 amplification. Citation Format: Lee K-M, Guerrero-Zotano A, Formisano L, Jansen V, Gonzalez Ericsson P, Arteaga C. Neoadjuvant trial with letrozole identifies PRR11 in 17q21-23 amplicon as a resistance mechanism to endocrine therapy in ER-positive breast cancer [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr PD7-10.

Cellular acidosis triggers human MondoA transcriptional activity by driving mitochondrial ATP production.

Human MondoA requires glucose as well as other modulatory signals to function in transcription. One such signal is acidosis, which increases MondoA activity and also drives a protective gene signature in breast cancer. How low pH controls MondoA transcriptional activity is unknown. We found that low pH medium increases mitochondrial ATP (mtATP), which is subsequently exported from the mitochondrial matrix. Mitochondria-bound hexokinase transfers a phosphate from mtATP to cytoplasmic glucose to generate glucose-6-phosphate (G6P), which is an established MondoA activator. The outer mitochondrial membrane localization of MondoA suggests that it is positioned to coordinate the adaptive transcriptional response to a cell's most abundant energy sources, cytoplasmic glucose and mtATP. In response to acidosis, MondoA shows preferential binding to just two targets, TXNIP and its paralog ARRDC4. Because these transcriptional targets are suppressors of glucose uptake, we propose that MondoA is critical for restoring metabolic homeostasis in response to high energy charge.

Four lncRNAs associated with breast cancer prognosis identified by coexpression network analysis.

Previous studies on long noncoding RNA (lncRNA) have made breakthroughs in the treatment of several tumors, and these findings have brought attention to the lncRNA signature of breast cancer. Increased understanding of genomic architecture and achievement of innovative therapeutic strategies has prompted creation of a novel oncological model for the treatment of solid cancers. In this study, we systematically analyzed the transcriptome of breast cancer tissues to gain more in-depth knowledge of tumor biology. Gene coexpression relationships were studied in 206 samples from The Cancer Genome Atlas database, and nine coexpression modules were identified. After screening and analysis, we identified four important prognosis-related lncRNAs (HOTAIR, SNHG16, HCP5, and TINCR), and constructed a prognostic model, one (HCP5) of which has not previously been identified in the context of breast cancer. Importantly, an understanding of prognosis facilitates precise disease risk assessment and advances the selection of strategies for risk-adaptive management. These findings broaden the landscape of carcinogenic lncRNAs in breast cancer, providing insights into the biological significance and clinical application of lncRNAs in breast cancer.

Serum Proteomic Signatures of Male Breast Cancer.

To date, the elucidation of serum protein alterations in male breast cancer (MBC) has not been extensively studied, due to the rarity of the disease. In the present work, two-dimensional gel electrophoresis (2-DE) and matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) were employed to detect differences in serum protein expression between patients with MBC and healthy controls. A panel of differentially expressed serum proteins was identified, including proteins involved in the regulation of the cell cycle [e.g. cell division cycle 7-related protein kinase (CDC7)], in mitochondrial function [e.g. mitochondrial aldehyde dehydrogenase (ALDH2) and dimethyladenosine transferase 1 (TFB1M)], in lipid metabolism and transport [e.g. apolipoprotein A-I (APOA1) and E (APOE)], in apoptosis and immune response [e.g. CD5 antigen-like (CD5L), clusterin (CLUS) and C-C motif chemokine 14 (CCL14)], in transcription (e.g. protein SSX3 and signal transducer and activator of transcription 3 (STAT3)], in invasion and metastasis (e.g. alpha-2-HS-glycoprotein (FETUA)], in estrogen synthesis [aromatase (CYP19A1)] and other diverse biological roles [e.g. actin-related protein 2/3 complex subunit 4 (ARPC4), dual specificity mitogen-activated protein kinase kinase 4 (MP2K4), ectoderm-neural cortex protein 1 (ENC1), and matrix metalloproteinase-27 (MMP27)]. These findings provide valuable insight into the distinct clinicopathological features of MBC and indicate that select serum proteomic markers may help improve MBC management.