Molecular Subtypes Of Breast Cancer Research Articles

An analysis of the association between breast density and body mass index with breast cancer molecular subtypes in early breast cancer: data from a Spanish population.

Breast cancer is an important health problem, like obesity and dyslipidemia, with a strong association between body mass index (BMI) and breast cancer incidence and mortality. The risk of breast cancer is also high in women with high mammographic breast density (MBD). The purpose of this study was to analyze the association between BMI and MBD according to breast cancer molecular subtypes. This transversal, descriptive, multicenter study was conducted at three Spanish breast cancer units from November 2019 to October 2020 in women with a recent diagnosis of early breast cancer. Data were collected at the time of diagnosis. The study included 162 women with a recent diagnosis of early breast cancer. The median age was 52years and 49.1% were postmenopausal; 52% had normal weight, 32% overweight, and 16% obesity. There was no association between BMI and molecular subtype but, according to menopausal status, BMI was significantly higher in postmenopausal patients with luminal A (p = 0.011) and HER2-positive (p = 0.027) subtypes. There was no association between MBD and molecular subtype, but there were significant differences between BMI and MBD (p < 0.001), with lower BMI in patients with higher MBD. Patients with higher BMI had lower HDL-cholesterol (p < 0.001) and higher insulin (p < 0.001) levels, but there were no significant differences in total cholesterol or vitamin D. This study showed higher BMI in luminal A and HER2-positive postmenopausal patients, and higher BMI in patients with low MBD regardless of menopausal status.

Overexpressing S100A9 ameliorates NK cell dysfunction in estrogen receptor-positive breast cancer

BackgroundEstrogen receptor (ER) positive human epidermal growth factor receptor 2 (HER2) negative breast cancer (ER+/HER2−BC) and triple-negative breast cancer (TNBC) are two distinct breast cancer molecular subtypes, especially in tumor immune microenvironment (TIME). The TIME of TNBC is considered to be more inflammatory than that of ER+/HER2−BC. Natural killer (NK) cells are innate lymphocytes that play an important role of tumor eradication in TME. However, studies focusing on the different cell states of NK cells in breast cancer subtypes are still inadequate.MethodsIn this study, single-cell mRNA sequencing (scRNA-seq) and bulk mRNA sequencing data from ER+/HER2−BC and TNBC were analyzed. Key regulator of NK cell suppression in ER+/HER2−BC, S100A9, was quantified by qPCR and ELISA in MCF-7, T47D, MDA-MB-468 and MDA-MB-231 cell lines. The prognosis predictability of S100A9 and NK activation markers was evaluated by Kaplan–Meier analyses using TCGA-BRAC data. The phenotype changes of NK cells in ER+/HER2−BC after overexpressing S100A9 in cancer cells were evaluated by the production levels of IFN-gamma, perforin and granzyme B and cytotoxicity assay.ResultsBy analyzing scRNA-seq data, we found that multiple genes involved in cellular stress response were upregulated in ER+/HER2−BC compared with TNBC. Moreover, TLR regulation pathway was significantly enriched using differentially expressed genes (DEGs) from comparing the transcriptome data of ER+/HER2−BC and TNBC cancer cells, and NK cell infiltration high/low groups. Among the DEGs, S100A9 was identified as a key regulator. Patients with higher expression levels of S100A9 and NK cell activation markers had better overall survival. Furthermore, we proved that overexpression of S100A9 in ER+/HER2-cells could improve cocultured NK cell function.ConclusionIn conclusion, the study we presented demonstrated that NK cells in ER+/HER2−BC were hypofunctional, and S100A9 was an important regulator of NK cell function in ER+BC. Our work contributes to elucidate the regulatory networks between cancer cells and NK cells and may provide theoretical basis for novel drug development.

Androgen receptor: Structure, signaling, function and potential drug discovery biomarker in different breast cancer subtypes.

The Androgen Receptor (AR) is emerging as an important factor in the pathogenesis of breast cancer (BC), which is the most common malignancy worldwide. >70 % of AR expression in primary and metastatic breast tumors has been observed which suggests that AR may be a new marker and a potential therapeutic target among AR-positive BC patients. Biological insight into AR-positive breast cancer reveals that AR may cross-talk with several vital signaling pathways, including key molecules and receptors. Downstream signaling of AR might also affect many clinically important pathways that are emerging as clinical targets in BC. AR exhibits different behaviors depending on the breast cancer molecular subtype. Preliminary clinical research using AR-targeted drugs, which have already been FDA-approved for prostate cancer (PC), has given promising results for AR-positive breast cancer patients. However, since AR positivity's prognostic and predictive value remains uncertain, it is difficult to identify and stratify patients who would benefit from AR-targeted therapies alone. Thus, the need of the hour is to target the androgen receptor as a monotherapy or in combination with other conventional therapies which has proven to be an effective clinical strategy for the treatment of prostate cancer patients, and these therapeutic strategies are increasingly being investigated in breast cancer. Therefore, in this manuscript, we review the role of AR in various cellular processes that promote tumorigenesis and aggressiveness, in different subtypes of breast cancer, as well as discuss ongoing efforts to target AR for the more effective treatment and prevention of breast cancer.

The discerning influence of dynamic contrast-enhanced MRI in anticipating molecular subtypes of breast cancer through the artistry of artificial intelligence - a narrative review.

Radio genomics is an exciting new area that uses diagnostic imaging to discover genetic features of diseases. In this review, we carefully examined existing literature to evaluate the role of artificial intelligence (AI) and machine learning (ML) on dynamic contrastenhanced MRI (DCE-MRI) data to distinguish molecular subtypes of breast cancer (BC). Implications to noninvasive assessment of molecular subtype include reduction in procedure risks, tailored treatment approaches, ability to examine entire lesion, follow-up of tumour biology in response to treatment and evaluation of treatment resistance and failure secondary to tumour heterogeneity. Recent studies leverage radiomics and AI on DCE-MRI data for reliable, non-invasive breast cancer subtype classification. This review recognizes the potential of AI to predict the molecular subtypes of breast cancer non-invasively.

Abstract PO4-26-06: Identifying mutation-independent signaling pathway activation in molecular subtypes of triple negative breast cancers

Abstract Introduction Triple negative breast cancer (TNBC) is an aggressive cancer defined by the absence of estrogen receptors (ER), progesterone receptors (PR), and lack of human epidermal growth factor receptor 2 (HER-2). We previously identified molecular subgroups with distinct mutational, epigenetic, and clinicopathologic signatures. Here, we sought to identify signaling pathways using targeted RNA expression-based pathway analysis. Methods We analyzed 44 TNBC cases diagnosed at NYU Langone Health between March 2011 and April 2018. Samples were compared based on histology, immunohistochemistry, and epigenetics. We assessed mRNA expression levels of pathway-specific target genes with RT-qPCR using the OncoSIGNal pathway profiling assay. Signal transduction pathway analyses were used to measure activity of the estrogen receptor (ER), androgen receptor (AR), phosphoinositide-3-kinase (PI3K), mitogen-activated protein kinase (MAPK), Hedgehog (HH), Notch, and transforming growth factor beta (TGF- β) pathways. Results DNA methylation Cluster 1, which is enriched for apocrine histology and PI3K/Akt mutations, showed no increased activity in PI3K pathway by RNA expression, but showed increase of AR and MAPK signaling, with a single case of increased ER signaling in the absence of ESR1 activating mutations. In contrast, both DNA methylation Cluster 2 (no recurrent mutations) and Cluster 3 (DNA instability cluster) showed upregulation in PI3K pathway in 4/7 (57%) and 11/25 (44%) of cases, respectively. PI3K pathway activation was invariably associated with high Ki-67 &amp;gt;15%, however not all high Ki-67 cases showed high PI3K activity. Invasive ductal carcinoma (IDC) morphology was characterized by a nearly even split between MAPK (13/28, 46%) and PI3K (12/28, 44%), with single HH and TGF- β driven cases. In 5/28 (18%) of IDC we did not identify an upregulated pathway. Discussion We show that RNA expression-based pathway activity and mutational and epigenetic analyses provide complimentary information about the molecular landscape of TNBC. PI3K mutations are early drivers and lead to distinct epigenetic signatures, however they are not associated with increased PI3K pathway activity by RNA expression. In contrast, TNBC without PI3K mutations may show activation of the PI3K pathway in the absence of PI3K/Akt mutations. Our observation suggests that distinct biomarkers may be differently suited to predict response to PI3K inhibitors in TNBC. This may include expanding the number of patients for which PI3K/Akt pathway inhibition might be a therapeutic option, as well as explaining the lack of response in PI3K mutated tumors. Citation Format: Chanel Schroff, Lawrence Lin, Dianne van Strijp, Daniel Roses, Sigi Neerken, Freya Schnabel, Farbod Darvishian, Matija Snuderl. Identifying mutation-independent signaling pathway activation in molecular subtypes of triple negative breast cancers [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 PO4-26-06.

Abstract PO1-02-07: HER2 Low Non-Metastatic Breast Cancer in Qatar: A Nationwide Retrospective Cohort Study to Evaluate the Response to Neoadjuvant Chemotherapy: A Real-World Analysis

Abstract Background: Breast Cancer is the most diagnosed cancer type worldwide and the second leading cause of cancer-related death among women. HER2-low breast cancer is a newly defined molecular subtype of breast cancer in which tumors exhibit a minimal overexpression of HER2 or no gene amplification. To illustrate, HER2-low tumors typically have an IHC score of 1+ or a score of 2+ with negative amplification. However, emerging evidence suggests that even a minimal amplification of HER2 may significantly impact the response to therapy and prognosis. Our study aims to unveil the impact of HER2-low expression on the response to anthracycline and taxane-based neoadjuvant chemotherapy (NACT) in comparison to the HER2-negative group in non-metastatic breast cancer. The primary objective was evaluating the response to NACT comparing the favorable response (complete and partial response) in each of the two groups of HER2-low and HER2-negative patients. Methods: This is a retrospective cohort study. All patients’ profiles with non-metastatic, HER2-Low, and HER2-negative breast cancers who received neo-adjuvant chemotherapy and underwent surgery between the 1st of January 2018 and the 30th of August 2022 were included. Patients' response was evaluated using surgical pathology reports to compare the two study groups (HER2-low and HER2-negative). Results: The total number of patients included was 262 patients, the majority were HER2-low 89% (233/262) vs. 11% (29/262) HER2-negative. A favorable response to NACT was shown in 71% (185/262) of all patients. The favorable response rate was similar in both groups, 70% (164/233) in the HER2-low group vs. 72% (21/29) in the HER2-negative group, OR: 1 (95% CI: 0.8-1), p-value 0.8. Similarly, the pathological complete response (pCR) rate was the same in both study groups at 14%, OR: 0.7 (95% CI: 0.2-3), p-value: 0.6. Interestingly, patients with hormone-positive tumors across both study groups had a higher response rate as compared to hormone-negative patients. However, statistical significance was shown in the HER2-low group only. In the HER2-low cohort, 73% of the patients (119/164) with hormone-positive tumors showed a favorable response OR: 0.8 (95% CI: 0.8- 1), p-value: 0.001. Comparatively, in the HER2-negative cohort, 52% of the patients (11/21) with hormone-positive tumors had a favorable response OR: 2 (95% CI: 1– 5), p-value: 0.05. Conclusion: Our results did not show any significant impact of HER2-low expression on neoadjuvant chemotherapy response. Nonetheless, a statistically significant difference in response was observed in the hormone-positive HER2-low breast cancer patients. Further studies are needed to evaluate the influence of hormonal expression on the response rate to NACT in the HER2-low patient population. Citation Format: Ahmed Kardousha, Wafaa Shehada, Ahmed Basha, Sahar Nasser, Mufid el Mistiri, Anas Hamad, Salha Al-Bader, Shereen Elazzazy. HER2 Low Non-Metastatic Breast Cancer in Qatar: A Nationwide Retrospective Cohort Study to Evaluate the Response to Neoadjuvant Chemotherapy: A Real-World Analysis [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 PO1-02-07.

Abstract PO5-13-07: Prediction of recurrence in triple negative breast cancer patients after receiving neoadjuvanttreatment using plasma metabolomics

Abstract Background Early-stage triple-negative breast cancer (TNBC) is usually treated with neoadjuvant chemotherapy (NADC), but prognosis remains poor compared with other BC subtypes. Unfortunately, less than 30% of BC patients achieve pathological complete response (pCR) to NADC and the overall survival of TNBC when cancer spreads is estimated at 10-13 months. Complete response is associated with improved progression-free and overall survival rates, but more accurate prognostic markers are needed. In this study, we assessed the prognostic value of blood circulating metabolites by using targeted-based metabolomics. Methods Patients received standard neoadjuvant chemotherapy with epirubicin plus cyclophosphamide followed by paclitaxel. Blood samples were obtained upon completion of chemotherapy and before surgery. Pathological response to treatment was recorded according to the Miller &amp; Payne system, and categorized as partial (MP 1, 2, &amp; 3) or complete response (MP 4 &amp; 5). Blood samples were collected in EDTA tubes, centrifuged and plasma was stored at -80°C. After QC standard addition and methanol extraction of proteins, four fractions of the resulting extract were analysed: two by reverse-phase/UPLC-MS/MS methods with positive ion mode electrospray ionization (ESI), one by reverse phase/UPLC-MS/MS with negative ion mode ESI, and one by hydrophilic interaction liquid chromatography/UPLC-MS/MS) by Metabolon using a Thermo Scientific Q-Exactive mass spectrometer with a heated electrospray ionization source and an Orbitrap mass analyser. Using Metabolon's hardware and software, raw data were extracted, identified, QC processed and quantified using the area under the curve (AUC). Identified compounds were compared with library entries of purified standards or recurrent unknown entities. The prognostic capacity of each metabolite was assessed using BRB ArrayTools. Selected metabolites were validated using a targeted approach using compound standards as follows. Plasma samples were re-analysed by UPLC/MS using a Vanquish LC coupled to an Orbitrap Exploris 240 MS (Thermo Fisher Scientific) with positive and negative ionization mode ESI under polarity switching. Identification of compounds were performed by comparison of retention times (against in-house authentic standards), accurate mass (with an accepted deviation of 3ppm), and MS/MS spectra. These analyses were carried out by MS-Omics (Denmark). Results Twenty patients treated in the Medical Oncology Unit of the University Hospital of Jaén were recruited. Median age was 50 (31-76). Twelve patients obtained a pathological complete response. Median follow-up after surgery was 25 months. Seven patients eventually had distant metastases (2 in the lungs, 1 in the brain, 1 in the bones and 3 multi-site). Metabolon untargeted analysis identified and quantified 985 metabolites, 789 after xenobiotics exclusion. Survival analysis identified 16 metabolites related with distant relapse (p&amp;lt; 0.05). The ten metabolites with lower p-value were selected for targeted validation. Ms-Omics pipeline allowed absolute quantification of 5 metabolites, 3 of them showing high correlation (R &amp;gt;0.7) between both measurements (targeted and untargeted). Validation of the prognostic value of the candidate metabolites is ongoing in a larger TNBC cohort. Conclusions Metabolomics is a useful tool for the detection of simply assessable and cost-effective prognostic biomarkers in TNBC. Easily monitoring the presence of minimal residual disease is worth to be settled up in the clinical practice for the most aggressive molecular subtype of breast cancer. In this work we have defined a set of metabolites that could predict distant relapse events in TNBC patients treated with neoadjuvant chemotherapy. Further analyses are being carried out to validate the prognostic value of the proposed candidate metabolites. Citation Format: Pedro Sánchez-Rovira, Rocio Urbano-Cubero, Angelo Gamez Pozo, Carmen González-Olmedo, Alicia Cano-Jimenez, Andrea Zapater- Moros, Leticia Díaz-Beltrán, Lucia Trilla-Fuertes, Mariana Díaz-Almirón, Enrique Espinosa, Pilar Zamora, Juan Angel Fresno Vara. Prediction of recurrence in triple negative breast cancer patients after receiving neoadjuvanttreatment using plasma metabolomics [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 PO5-13-07.

Abstract PO1-15-04: Young Black Women With Triple-Negative Breast Cancer Molecular Subtypes: Population-Specific Patterns and Batch Effect Considerations

Abstract Introduction: While triple-negative breast cancer (TNBC) molecular subtypes have been associated with biological differences and clinical outcomes, studies have overwhelmingly been conducted in populations of European or Asian ancestry. Data collected across diverse populations is required to better leverage clinical directions from translational studies in TNBC. Through females recruited through the Black Women: Etiology and Survival of Triple-Negative Breast Cancers (BEST) study, we sought to characterize subtypes and explore associations. Methods: Our study included Black women diagnosed with early-stage (I-III) invasive TNBC at &amp;lt; = age 50 from 2005 to 2016, with recruitment from Florida and Tennessee state cancer registries. Germline DNA, tumor RNA, clinical outcomes, and risk factor data were collected. TNBC status in the BEST study was based on immunohistochemistry from pathology reports, cancer registry data, and self-reported data. Analyses on banked tumor samples, extracted at multiple time points, were conducted through PAM50 (Nanostring) and whole-transcriptome RNA-seq. TNBC subtype was assessed using TNBCtype-4 (Lehmann et al. 2016). Sources of batch effect were evaluated using PCA and corrected via limma. Genetic ancestry based on OncoArray or MEGA genotyping data was inferred using 1000Genomes continental reference samples. Immune cell characterization was performed via CIBERSORT and ESTIMATE. Statistical significance in comparing differences across subtypes was assessed via Chi-square test. Kaplan-Meier estimates and log-rank test were used for survival analysis. Results: RNA-seq from 114 self-reported Black females with TNBC was analyzed. TNBC subtype distribution in the BEST study cohort included 31.6% basal-like 1 (BL1), 28.9% basal-like 2 (BL2), 16.7% luminal androgen receptor (LAR), and 21.9% mesenchymal (M). While results were largely consistent with prior studies in patients of European or East Asian ancestry, a higher percentage of BL2 subtype was observed (28.9% vs. 21.0%, p=0.053). Based on PAM50 subtyping, 100% of tumors with BL1 and M were basal, whereas 68.8% of LAR and 86.7% of BL2 subtypes were basal. Tumors without subtype decreased from 9.8% to 1.1% after batch correcting for location at which RNA was extracted (Moffitt vs. Vanderbilt) and time between RNA banking and sequencing. All TNBC subtypes in this population demonstrated monocyte/activated dendritic cell predominance, with no significant subtype-specific associations with immune cell patterns. A lower relative proportion of M subtype was found in tumors from BRCA1/2 carriers, but this was not statistically significant due to the small number of carriers (8% vs. 18%; p=0.22). With a median follow-up time of 9 years, there was no significant difference in 10-year overall survival by TNBC subtype (p=0.18). However, patients with M subtype appeared to have worse survival relative to other subtypes combined (p=0.036). Conclusion: Our study is among the largest to date that interrogates TNBC subtypes and associated molecular/clinical data in self-reported Black females with invasive breast cancer. Our findings suggest that established TNBC subtyping can be applied in patients of African ancestry. Furthermore, data to correct for lab-based confounders remains critical; in this study, it enabled us to use many samples that could not be subtyped initially. Several population-specific patterns were observed, including no difference in 10-year overall survival across TNBC subtypes (consistent with prior data), but worse initial outcomes in M subtype; a preliminary association between BRCA1/2 carriers and non-M subtypes (in contrast to prior data); and no significant difference in immune cell distributions (in contrast to prior data mainly from patients of European ancestry). Studies of associations between TNBC subtypes, additional clinical data, and treatment data (type and response rates) are ongoing. Citation Format: Padma Rajagopal, Sonya Reid, Run Fan, Lindsay Venton, Anne Weidner, Mya Roberson, Susan Vadaparampil, Xuefeng Wang, Sean Yoder, Marilin Rosa, Jibril Hirbo, Jennifer Whisenant, Jennifer Pietenpol, Fei Ye, Tuya Pal, Brian Lehmann. Young Black Women With Triple-Negative Breast Cancer Molecular Subtypes: Population-Specific Patterns and Batch Effect Considerations [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 PO1-15-04.

Abstract PO1-02-08: Comprehensive Molecular Profiling of Breast Cancer: A real-time PCR assay for identifying ESR1, PGR, ERBB2, MKI67 and a novel proliferative signature in core needle biopsies and resected invasive breast cancer tissues

Abstract Background: Accurate status determination of breast cancer (BC) biomarkers, including estrogen receptor (ER/ESR1), progesterone receptor (PR/PGR), human epidermal growth factor receptor 2 (HER2/ERBB2), and marker of proliferation Ki67 (MKI67), is crucial for guiding therapeutic decisions. However, current “gold standard” methods such as immunohistochemistry (IHC) for assessing these biomarkers in formalin-fixed paraffin-embedded (FFPE) tissues face challenges in standardization and exhibit substantial inter- and intra-laboratory variability, particularly for Ki67. To address these limitations, APIS Breast Cancer Subtyping Kit has been developed, utilizing reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) to evaluate the status of ER, PR, HER2, KI67, and a novel proliferative signature in breast cancer core needle biopsy (CNB) and resected specimens. The APIS Breast Cancer Subtyping Kit offers enhanced accuracy, improved reproducibility, and the ability to provide results in a timely manner. Herein we report the development and validation of the APIS Breast Cancer Subtyping Kit, assessing clinical performance using retrospective and prospective sample collection. Furthermore, reproducibility and reliability across three testing sites were evaluated. By comparing the results of the kit with those obtained through standard IHC, we demonstrate the reliability and utility of the APIS Breast Cancer Subtyping Kit for precise breast cancer subtyping and guiding personalized patient management decisions. Methods: FFPE tissue sections (n=652) taken by CNB or resection underwent histological analysis in accordance with laboratory’s standard of care methods. Samples with a HER2 score of 2+ were referred to fluorescence in situ hybridization (FISH) to determine ERBB2 amplification, with the FISH result replacing the IHC result in determining the HER2 status (positive/negative) of the sample. Tumors with greater than 1% positive stained nuclei for ER/PR were scored positive. A cut-off of 20% Ki67 staining was used for positive/negative status. The performance was assessed as the agreement with IHC/ISH status and reported as OPA (overall percent agreement) with corresponding 95% confidence intervals (95% CI). To assess the precision of the assay, a panel of RNA pools (samples) was repeatedly measured on different days across three independent laboratories. Reproducibility was evaluated using variance components analysis. Results: The APIS Breast Cancer Subtyping Kit showed high concordance (OPA) with IHC: 93.1% (95% CI: 90.9-94.8) for ER, 86.8% (95% CI: 84.0-89.2) for PR, 94.2% (95% CI: 92.2-95.8) for HER2 (IHC/FISH), 78.3% (95% CI: 75.0-81.3) for Ki67, and 80.1% (95% CI: 76.8-83.1) for proliferative signature (assessed against MKI67 IHC status). Inter-site reproducibility demonstrated excellent agreement in quantitative measurements, with a total SD ranging from 0.00 to 0.22. Binary single-marker status (positive/negative) calling achieved 100% reproducibility for ER, PR, and HER2 for all tested samples (negative/low positive/medium positive), as well as for most Ki67 samples (87% agreement for negative samples). Conclusions: APIS Breast Cancer Subtyping Kit demonstrated a high level of concordance with standard of care IHC/FISH in assessing breast cancer biomarker status. These findings suggest that the APIS Breast Cancer Subtyping Kit provides highly precise and reproducible quantitative assessment of BC biomarkers and molecular subtypes. Inclusion and exclusion criteria Citation Format: Anna Gasior, Joanna Gorniak, Sara Rollinson, Leanne Gough, Anne-Sophie Wegscheider, Axel Niendorf. Comprehensive Molecular Profiling of Breast Cancer: A real-time PCR assay for identifying ESR1, PGR, ERBB2, MKI67 and a novel proliferative signature in core needle biopsies and resected invasive breast cancer tissues [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 PO1-02-08.

Abstract PO2-15-05: Mesenchymal-like immune-activated: the 4th robust triple-negative breast cancer molecular subtype

Abstract Triple-negative breast cancer (TNBC) accounts for 15-20% of primary BC. This heterogeneous disease is the most aggressive BC subtype. TNBC is characterized by young age at onset, high-grade tumors, high risk of early recurrence and poor prognosis. Until recently, TNBC patients were considered as one group and all patients were treated with conventional chemotherapy. With the emergence of new therapies targeting distinct biological pathways, personalized medicine is now accessible by defining finer TNBC subtypes, e.g. molecular subtypes, and identifying their specific targetable pathways. Several studies based on transcriptomics have identified three to six TNBC molecular subtypes. Today, there is a clear consensus on three TNBC robust subtypes: luminal androgen receptor (LAR), basal-like immune-activated (BLIA) and basal-like immune-suppressed (BLIS). The debate about the robustness of other subtypes is still open, notably mesenchymal-like (M) and mesenchymal stem-like (MSL or MES). The goal of this study was to establish a robust molecular classification of TNBC that allow to determine the best treatment options. To optimize this process, we harvested as much transcriptomic data as possible. Available clinicopathological data linked to these data were also imported. To our knowledge, this is the largest study aimed at subtyping TNBC; it exploits a total of 1942 TNBC patient data collected from 19 datasets: 1243 samples from microarray technology (14 datasets) and 699 from RNAseq technology (five datasets including a new one from our institution [GSE225002]). We performed independent unsupervised analyses on these two large cohorts with consensus k-means clustering including selection of optimal number of clusters and optimal number of variables. Both consensus clustering analyses separated TNBC microarray and RNAseq TNBC cohorts into four optimal clusters. These clusters were then characterized using clinicopathological features, gene ontology enrichment analyses (GOEA), gene set enrichment analysis (GSEA), 70 gene expression signatures (GES) and expression of 47 immune checkpoint genes. We concluded that TNBC are composed of four robust subtypes: LAR, mesenchymal-like immune-activated (MLIA), BLIA and BLIS. Importantly, we propose that MLIA acronym should replace M or MSL, because it highlights the two main biological characteristics of this subtype, i.e. mesenchymal-like features and a high IR comparable to that of BLIA. Furthermore, we showed that each subtype shares common biological characteristics with another one: LAR and MLIA (androgen receptor pathway activation); MLIA and BLIA (immune activation, notably high levels of immune checkpoints); BLIA and BLIS (basal-like features); BLIS and LAR (immune suppression). As regards microarray cohort, LAR included 19.23% (n = 239) of TNBC, MLIA 17.38% (n = 216), BLIA 32.50% (n = 404) and BLIS 30.89% (n = 384). Concerning RNAseq cohort, LAR included 19.60% (n = 137) of TNBC, MLIA 17.31% (n = 121), BLIA 28.47% (n = 199) and BLIS 34.62% (n = 242). Distributions of patients among the four clusters in the two cohorts were similar (p = 0.3583). Distributions were also similar between studies for microarray cohort (p = 0.2479) and RNAseq cohort (p = 0.1775). Pooled data (n = 1942 patients) gave the following distribution: 19.36% for LAR; 17.35% for MLIA; 31.06% for BLIA; 32.23% for BLIS, confirming that TNBC are largely but not exclusively basal-like (63.29%). In brief, according to the TNBC subtype molecular characterisation, anti-androgen therapy could be prescribed for LAR, immune checkpoint inhibitors for MLIA and BLIA, alone or in combination, and TAM-focused and antineurogenic therapies for BLIS. As an extension of this work, TNBC transcriptomic data associated with their clinicopathological features and TNBC subtype annotations were included in bc-GenExMiner v5.0 web tool (http://bcgenex.ico.unicancer.fr). Citation Format: Mario Campone, Pascal Jézéquel, Fadoua Ben Azzouz, Wilfried Gouraud, Agnes Bassevile, Bertrand Michel, Hamza Lasla, Jean Sebastien FRENEL. Mesenchymal-like immune-activated: the 4th robust triple-negative breast cancer molecular subtype [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 PO2-15-05.

Abstract PO5-01-10: Evaluating a computer-aided platform for predicting recurrence and survival in an Oncotype Dx tested breast cancer cohort

Abstract Background: Oncotype DX Breast Recurrence ScoreÒ (ODXRS) is a widely used predictive measure of breast cancer recurrence risk and chemotherapy benefit for patients with estrogen receptor positive (ER+), human epidermal growth factor receptor-2 negative (HER2-) breast cancers. ODXRS testing incurs additional costs and delays. These drawbacks could be obviated by innovative computer-aided technologies within digital pathology workflows. Such technologies could be developed to perform a wide variety of diagnostic and prognostic tests on digital whole slide images (WSIs) of hematoxylin and eosin (H&amp;E)-stained tissue alone. This would save time, cost, and sample tissue whilst still providing critical prognostic information for patient management. Q-Plasia OncoReader Breast (QPORB) is a computer-aided solution which extracts information from H&amp;E WSIs to provide diagnostic and prognostic information for breast cancer specimens. Aims: The aim of this study was to identify whether the computer aided QPROB platform could successfully predict breast cancer recurrence from H&amp;E WSIs alone in line with recurrence predicted by ODXRS. Methods: H&amp;E slides corresponding to tissue blocks sent for ODXRS testing from primary breast cancer resection/excision specimens from St James’s University Hospital, Leeds, UK (n=137 cases, 1 slide per case) were collected, anonymized, and scanned at x20 magnification on an Aperio AT2 scanner. Relevant pathological and clinical data were collected from electronic pathology reports and patient records. These data included ODXRS and recurrence events. QPORB analyzed each case/slide and generated a digital biomarker profile from the H&amp;E images alone, combining statistical physics and tumor biology to quantify malignant cell cycle deformation. QPORB’s biomarker profile and ODXRS for each case was compared to disease-free survival (DFS) and overall survival (OS). Kaplan-Meier survival analyses were performed. Confounding factors (age, tumor grade, invasive tumor size and Charlson Comorbidity Index) were accounted for. Results: Results of three QPORB-generated indices - two putatively associated with overall cell cycle signature and one with G1 deformation, and their combined overall biomarker profile did not predict DFS in this cohort. However, with regards to OS, all three indices and the combined biomarker profile predicted OS over a median follow-up period of 5 years (P=0.044). 5% of WSIs (7/137) did not meet the criteria to be analyzed by QPORB and 4% (6/137) could not be analyzed by QPORB (attrition). While ODXRS similarly predicted OS but not DFS, the follow-up duration was suboptimal. Conclusion: While QPORB indices evaluated in this work, putatively associated with overall cell cycle signature and G1 deformation, did not predict breast cancer recurrence on a par with ODXRS, it has shown promising results as potential adjunct device to provide an estimate of OS for breast cancer patients eligible for ODXRS testing. Future work will expand on this observational cohort, blindly validate these findings, and extend the work to encompass all breast cancer molecular subtypes. Citation Format: Satabhisa Mukhopadhyay, Elizabeth Walsh, Rebecca Millican-Slater, Andrew Hanby, Joanne Stephenson, Tathagata Dasgupta, Nicolas Orsi. Evaluating a computer-aided platform for predicting recurrence and survival in an Oncotype Dx tested breast cancer cohort [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 PO5-01-10.

The prognostic role of circulating tumor DNA across breast cancer molecular subtypes: a systematic review and meta-analysis

ObjectiveCirculating tumor DNA (ctDNA) is increasingly being used as a potential prognostic biomarker in cancer patients. We aimed to assess the prognostic value of ctDNA in different subtypes of breast cancer patients throughout the whole treatment cycle. Materials and methodsPubMed, Web of Science, Embase, Cochrane Library, Scopus, and clinical trials.gov databases were searched from January 2016 to May 2022. The following search terms were used: ctDNA OR circulating tumor DNA AND breast cancer OR breast carcinoma. Only studies written in English languages were included. The following pre-specified criteria should be met for inclusion: (i) original articles, conference abstracts, etc.; (ii) patients with breast cancer; (iii) ctDNA measurement; and (iv) clinical outcome data such as recurrence-free survival (RFS) and overall survival (OS). Random-effect model was preferred considering the potential heterogeneity across studies. The main outcomes are ctDNA detection rate and postoperative long-term outcomes (RFS, OS). ResultsA total of 24 studies were screened. At every measurement time, the ctDNA detection rate of the HR+ subgroup was similar to that of the HR- subgroup (P=0.075; P=0.458; P=0.744; and P=0.578), and the ctDNA detection rate of the HER2+ subgroup was similar to that of the HER2- subgroup (P=0.805; P=0.271; P=0.807; and P=0.703). In the HR+ subgroup, RFS and OS of ctDNA positive patients were similar to those of ctDNA negative patients (P=0.589 and P=0.110), while RFS and OS of the ctDNA positive group was significantly shorter than those of the ctDNA negative patients in the HR- subgroup (HR=4.03, P<0.001; HR=3.21, P<0.001). According to HER grouping, the results were the same as above. In the triple negative breast cancer (TNBC) subgroup, the RFS and OS of ctDNA-positive patients was significantly shorter than of the ctDNA negative patients before and after surgery. ConclusionsctDNA was more predictive of recurrence-free survival and overall survival in the HR- subgroup than in the HR+ subgroup, and the same result was showed in the HER2- subgroup vs. HER2+ subgroup. The prognosis of the TNBC subtype is closely related to ctDNA before and after surgery.

Towards a More Efficient Breast Cancer Therapy Using Active Human Cell Membrane-Coated Metal–Organic Frameworks

The recent description of well-defined molecular subtypes of breast cancer has led to the clinical development of a number of successful molecular targets. Particularly, triple-negative breast cancer (TNBC) is an aggressive type of breast cancer with historically poor outcomes, mainly due to the lack of effective targeted therapies. Recent progresses in materials science have demonstrated the impressive properties of metal–organic framework nanoparticles (NPs) as antitumoral drug delivery systems. Here, in a way to achieve efficient bio-interfaces with cancer cells and improve their internalization, benchmarked MIL-100(Fe) NPs were coated with cell membranes (CMs) derived from the human TNBC cell line MDA-MB-468. The prepared CMs-coated metal–organic framework (CMs_MIL-100(Fe)) showed enhanced colloidal stability, cellular uptake, and cytotoxicity in MDA-MB-468 cells compared to non-coated NPs, paving the way for these human CMs-coated MIL-100(Fe) NPs as effective targeted therapies against the challenging TNBC.

Radiographic features and molecular subtypes association of breast cancer in women younger than 40 years old

Background: Breast cancer is the most commonly diagnosed cancer and the leading cause of cancer death among females, particularly in women under the age of 40 years. However, early detection of breast cancer in this population remains challenging and it tends to present at a later stage with poorer prognosis.Objective: To review mammographic and ultrasonographic findings, pathological features and molecular subtypes of breast cancer in younger than 40-year-old patients diagnosed in King Chulalongkorn Memorial Hospital and to determine which radiological characteristics are associated with molecular subtypes. Materials and Methods: The study included 278 patients aged under 40 years who were diagnosed with breast cancer and underwent mammographic and ultrasonographic studies between January 2009 and December 2019. A retrospective review of mammographic and ultrasonographic findings, histopathological reports as well as biological markers were made. The association of radiological characteristics and molecular subtypes was analyzed by SPSS. Results: In the 278 patients, the most common clinical presentation was palpable mass (268, 96.4%). The common mammographic findings were irregular shape mass (196, 77.8%) with hyperdensity (114, 45.2%) and an obscured margin (99, 39.3%). Presenting of microcalcification is not frequent (122, 48.4%). We found 27 patients with normal mammograms which were later detected in ultrasounds as 25 masses, 1 intraductal lesion and 1 focal duct change. The predominant ultrasonographic features were irregular shape mass (257, 91.5%), an angular margin (89, 31.7%), hypoechogenicity (198, 70.5%), no posterior feature (210, 74.7%) and internal vascularity (170, 60.5%). These radiological characteristics were classified as BI-RADS 5 in 194 lesions (69%). The most common histopathological type was mixed-type carcinoma (143, 50.9%), followed by invasive ductal carcinoma (114, 40.6%). Luminal B was the mostly found in this study (86, 30.6%). The patients frequently presented with stage IIA (91, 32.7%) while 15 patients were detected with an advanced stage at the first presentation. We found that triple negative, HER 2 overexpression and luminal B subtypes were associated with an obscured mass on mammography (p 0.048). Luminal B and HER 2 overexpression subtypes were also associated with the presence of fine pleomorphic microcalcification (p &lt;0.001).        Conclusion: In this study, we found an association of the mass margin and suspicious calcification morphology on mammography with molecular subtypes. It would be helpful for further clinical management in young patients. The knowledge can be used for planning appropriate treatments according to molecular subtypes which are associated with these characteristics. However, the precision of cancer treatment is still based on the tissue diagnosis.

Salivary Tryptophan as a Metabolic Marker of HER2-Negative Molecular Subtypes of Breast Cancer

Changes in the concentration of tryptophan (Trp) indicate a serious metabolic restructuring, which is both a cause and a consequence of many diseases. This work examines the upward change in salivary Trp concentrations among patients with breast cancer. This study involved volunteers divided into three groups: breast cancer (n = 104), non-malignant breast pathologies (n = 30) and healthy controls (n = 20). In all participants, before treatment, the quantitative content of Trp in saliva was determined by capillary electrophoresis. In 20 patients with breast cancer, Trp was re-tested four weeks after surgical removal of the tumor. An increase in the Trp content in saliva in breast cancer has been shown, which statistically significantly decreases after surgical removal of the tumor. A direct correlation was found between increased Trp levels with the degree of malignancy and aggressive molecular subtypes of breast cancer, namely triple negative and luminal B-like HER2-negative. These conclusions were based on an increase in Ki-67 and an increase in Trp in HER2-negative and progesterone-negative subtypes. Factors under which an increase in Trp concentration in saliva was observed were identified: advanced stage of breast cancer, the presence of regional metastasis, low tumor differentiation, a lack of expression of HER2, estrogen and progesterone receptors and the high proliferative activity of the tumor. Thus, the determination of salivary Trp may be a valuable tool in the study of metabolic changes associated with cancer, particularly breast cancer.

Identification of molecular subtypes based on chromatin regulator-related genes and experimental verification of the role of ASCL1 in conferring chemotherapy resistance to breast cancer.

The aim of this study was to identify the molecular subtypes of breast cancer based on chromatin regulator-related genes. The RNA sequencing data of The Cancer Genome Atlas-Breast Cancer cohort were obtained from the official website, while the single-cell data were downloaded from the Gene Expression Omnibus database (GSE176078). Validation was performed using the Molecular Taxonomy of Breast Cancer International Consortium dataset. Furthermore, the immune characteristics, tumor stemness, heterogeneity, and clinical characteristics of these molecular subtypes were analyzed. The correlation between chromatin regulators and chemotherapy resistance was examined in vitro using the quantitative real-time polymerase chain reaction (qRT-PCR) and Cell Counting Kit-8 (CCK8) assays. This study identified three stable molecular subtypes with different prognostic and pathological features. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and protein-protein interaction analyses revealed that the differentially expressed genes were associated with disease processes, such as mitotic nuclear division, chromosome segregation, condensed chromosome, and specific chromosome region. The T stage and subtypes were correlated with the clinical features. Tumor heterogeneity (mutant-allele tumor heterogeneity, tumor mutational burden, purity, and homologous recombination deficiency) and tumor stemness (RNA expression-based stemness score, epigenetically regulated RNA expression-based stemness score, DNA methylation-based stemness score, and epigenetically regulated DNA methylation-based stemness score) significantly varied between the three subtypes. Furthermore, Western blotting, qRT-PCR, and CCK8 assays demonstrated that the expression of ASCL1 was positively correlated with chemotherapy resistance in breast cancer. This study identified the subtypes of breast cancer based on chromatin regulators and analyzed their clinical features, gene mutation status, immunophenotype, and drug sensitivity. The results of this study provide effective strategies for assessing clinical prognosis and developing personalized treatment strategies.

Overexpression of WT1 in all molecular subtypes of breast cancer and its impact on survival: exploring oncogenic and tumor suppressor roles of distinct WT1 isoforms.

Breast cancer is a highly heterogeneous solid tumor, posing challenges in developing targeted therapies effective for all mammary carcinoma subtypes. WT1 emerges as a promising target for breast cancer therapy due to its potential oncogenic role in various cancer types. Previous works have yielded inconsistent results. Therefore, further studies are needed to clarify the behavior of this complex gene in breast cancer. In this study, we examined WT1 expression in both Formalin Fixed Paraffin Embedded breast tumors (n = 41) and healthy adjacent tissues (n = 41) samples from newly diagnosed cases of ductal invasive breast cancer. The fold change in gene expression between the tumor and healthy tissue was determined by calculating 2-∆∆Ct. Disease-free survival analysis was computed using the Kaplan-Meier method. To identify the expression levels of different WT1 isoforms, we explored the ISOexpresso database. Relative quantification of the WT1 gene revealed an overexpression of WT1 in most cases. The percentage of patients surviving free of disease at 8years of follow-up was lower in the group overexpressing WT1 compared to the group with down-regulated WT1. Interestingly, this overexpression was observed in all molecular subtypes of invasive breast cancer, underscoring the significance of WT1 as a potential target in all these subtypes. The observed WT1 down-expression in a few cases of invasive breast cancer, associated with better survival outcomes, may correspond to the down-regulation of a particular WT1-KTS (-) isoform: the WT1 A isoform (EX5-/KTS-). The co-expression of this WT1 oncogenic isoform with a regulated WT1- tumor suppressor isoform, such as the major WT1 F isoform (EX5-/KTS +), could also explain such survival outcomes. Due to its capacity to adopt dual roles, it becomes imperative to conduct individual molecular expression profiling of the WT1 gene. Such an approach holds great promise in the development of personalized treatment strategies for breast cancer.

Enhancing therapeutic efficacy in luminal androgen receptor triple-negative breast cancer: exploring chidamide and enzalutamide as a promising combination strategy

Extensive exploration of the molecular subtypes of triple-negative breast cancer (TNBC) is critical for advancing precision medicine. Notably, the luminal androgen receptor (LAR) subtype has attracted attention for targeted treatment combining androgen receptor antagonists and CDK4/6 inhibitors. Unfortunately, this strategy has proven to be of limited efficacy, highlighting the need for further optimization. Using our center’s comprehensive multiomics dataset (n = 465), we identified novel therapeutic targets and evaluated their efficacy through multiple models, including in vitro LAR cell lines, in vivo cell-derived allograft models and ex vivo patient-derived organoids. Moreover, we conducted flow cytometry and RNA-seq analysis to unveil potential mechanisms underlying the regulation of tumor progression by these therapeutic strategies. LAR breast cancer cells exhibited sensitivity to chidamide and enzalutamide individually, with a drug combination assay revealing their synergistic effect. Crucially, this synergistic effect was verified through in vivo allograft models and patient-derived organoids. Furthermore, transcriptomic analysis demonstrated that the combination therapeutic strategy could inhibit tumor progression by regulating metabolism and autophagy. This study confirmed that the combination of histone deacetylase (HDAC) inhibitors and androgen receptor (AR) antagonists possessed greater therapeutic efficacy than monotherapy in LAR TNBC. This finding significantly bolsters the theoretical basis for the clinical translation of this combination therapy and provides an innovative strategy for the targeted treatment of LAR TNBC.

Breast edema score at breast MRI: its value in prediction of molecular subtype of breast cancer and its impact on axillary LN metastasis

BackgroundSince many newly diagnosed breast cancer patients have breast MRI, the value of preoperative breast magnetic resonance imaging would improve if molecular subtypes could be consistently identified, and prognostic information provided in addition to diagnostic imaging. Breast edema may improve the ability to predict molecular subtypes and clinical and pathological outcomes in invasive breast cancer patients. The prognosis for breast cancer prognosis based on the findings of breast edema by magnetic resonance imaging will be useful in both pretreatment planning and prognosis. Breast edema on T2-weighted images and STIR was scored on a scale of 1 to 4, as follows: (a) breast edema score (BES) 1, no edema; (b) BES 2, peritumoral edema; (c) BES 3, pre pectoral edema; and (d) BES 4, subcutaneous edema (suspicious for occult inflammatory breast cancer “IBC”). Axillary lymph node status and number were also evaluated in T2 and STIR and after contrast administration. The aim of this work was to assess the role of tumour-related breast edema MRI features in distinguishing molecular subtypes of breast cancer and its effect on pathological axillary lymph nodes in patients with breast cancer.ResultsThere was a highly significant difference between BES with respect to the molecular subtypes of breast cancer, size of the mass, Ki-67 expression, LN status, and LN number (p < 0.0001, 0.045, < 0.0001, < 0.0001, and < 0.0001 respectively). However, there was no significant difference between BES and histopathological grade in studied masses, such as p-value = 0.49.ConclusionsTumour-related breast edema MRI characteristics may be useful in distinguishing molecular subtypes of breast cancer and could be used as a promising feature to improve the predictive performance of pathological axillary lymph nodes in patients with breast cancer, contributing to preoperative treatment planning and prognostic outcome.

Determination of target genes for classified molecular subtypes of triple-negative breast cancer form microarray gene expression profiling: An integrative in silico approach.

Highly heterogeneous triple-negative breast cancer (TNBC) has tough clinical features, which were gradually solving and improving in diagnosis by the molecular subtyping of TNBC. Presently, this study was focused on analyzing the genetic makeup of TNBC subtypes. This study explored the MicroArray expression profiling of differentially expressed genes in molecular subtypes BL1, BL2, IM, luminal androgen receptor, M, and mesenchymal stem-like of TNBC by analyzing the Gene Expression Omnibus dataset GSE167213. Various gene ontologies-based protein-protein interaction (PPI) networks were subtyped TNBC genes. The effect of genetic alteration on TNBC cases was also interpreted. The MicroArray gene expression profiling was done through R programming and subjected to functional annotation through the database for annotation, visualization, and integrated discovery. The PPI networking of functionally associated genes was interpreted by STRING. The survival analysis was done through cBioPortal. The t-test was used through R programming to generate the P values for a test of the significance of expressed genes. A total of 54,613 significant probes were analyzed in the TNBC MicroArray dataset. The functional PPI networks of BL1, BL2, and IM upregulated genes showed significant associations. The survival analysis of differentially expressed genes showed the significant prognostic effect of 32 upregulated genes of different subtypes on TNBC cases with genetic alterations, whereas the remaining genes showed no significant effects. The output of the present study provided significant target gene panels for different TNBC subtypes, which would add an informative genetic value to TNBC diagnosis.