Intrinsic Breast Cancer Subtypes Research Articles

STK3 higher expression association with clinical characteristics in intrinsic subtypes of breast cancer invasive ductal carcinoma patients.

STK3 has a central role in maintaining cell homeostasis, proliferation, growth, and apoptosis. Previously, we investigated the functional link between STK3/MST2, and estrogen receptor in MCF-7 breast cancer cells. To expand the investigation, this study evaluated STK3's higher expression and associated genes in breast cancer intrinsic subtypes using publicly available data. The relationship between clinical pathologic features and STK3 high expression was analyzed using descriptive and multivariate analysis. Increased STK3 expression in breast cancer was significantly associated with higher pathological cancer stages, and a different expression level was observed in the intrinsic subtypes of breast cancer. Kaplan-Meier analysis showed that breast cancer with high STK3 had a lower survival rate in IDC patients than that with low STK3 expression (p < 0.05). The multivariate analysis unveiled a strongcorrelation between STK3 expression and the survival rate among IDC patients, demonstrating hazard ratios for lower expression. In the TCGA dataset, the hazard ratio was 0.56 (95% CI 0.34-0.94, p = 0.029) for patients deceased with tumor, and 0.62 (95% CI 0.42-0.92, p = 0.017) for all deceased patients. Additionally, in the METABRIC dataset, the hazard ratio was 0.76 (95% CI 0.64-0.91, p = 0.003) for those deceased with tumor. From GSEA outcomes 7 gene sets were selected based on statistical significance (FDR < 0.25 and p < 0.05). Weighted Sum model (WSM) derived top 5% genes also have higher expression in basal and lower in luminal A in association with STK3. By introducing a novel bioinformatics approach that combines GSEA and WSM, the study successfully identified the top 5% of genes associated with higher expression of STK3.

Association between stromal tumor-infiltrating lymphocytes (TILs) and pathologic complete response (pCR) in patients with early breast cancer (BC) treated with neoadjuvant chemotherapy and HER2-directed therapies in NSABP B-41.

3017 Background: In the phase 3 NSABP B-41 trial, there was an association between pCR and survival in 519 women with early HER2-positive BC treated with neoadjuvant chemotherapy in combination with trastuzumab (T), lapatinib (L), or both (TL). There is a need to identify prognostic biomarkers to tailor patients’ treatment, and the quantification of stromal TILs represents a promising, accessible, and reproducible option. In this analysis, we studied the association between TILs and pCR. Methods: Eligible patients had a baseline core biopsy sample, known pCR status, and no consent withdrawal for the use of specimens. Slides were scanned using an Aperio GT 450 automated scanner to create whole slide images. TIL analysis was then completed based on the international TIL working group guidelines (RS). Patients were grouped into three TIL score categories based on tumor TIL %: low (1-5%), intermediate (6-30%), and high (31-95%). The dose-response relationship between TIL percentage and pCR was explored via generalized linear models with splines. Results: 257 patients were included. 89 (35%) received T, 92 (36%) L, and 76 (29%) TL. 149 (58%) had ER-positive BC. TIL categories in this cohort: 49% low, 22% intermediate, and 29% high. TIL expression was similar across BC intrinsic subtypes and by ER. There was no association between the TIL group and pCR, irrespective of the treatment group (p=0.98). Among tumors with low TILs, T or TL had similar pCR compared to L alone (51.3 v 49%; p=0.95). Among tumors with high TILs, T or TL had higher pCR than L (61.2 v 40.4%; p=0.04). Among patients with ER-positive BC, high TILs were associated with a numerical increase in pCR rate (56% vs 39.6%; p=0.11). Among patients with ER-negative tumors, high TILs were associated with a numerical decreased rate of pCR (50% v. 66.7%; p=0.15). The p-value of the Breslow test of homogeneity of the odds ratios across ER status was 0.016, suggesting that the association between TILs (0-30 v. &gt;30) and pCR varies across ER status.No interaction between the TIL percentage and age, nodal status, menopausal status, or histologic grade was noted. Conclusions: This analysis revealed that patients with a high TIL percentage treated with T or TL compared to L were more likely to achieve a pCR. These findings can be partially explained by the mechanism of action of the HER2-directed agents. T leads to antibody-dependent cell-mediated cytotoxicity, and a higher percentage of TILs may enhance this mechanism, whereas L has intracellular tyrosine kinase disruption. The association between TILs and pCR varied across ER status. Our next steps include additional studies assessing the interaction between TILs and long-term outcomes, as well as gene expression and TILs to validate this biomarker for future clinical trials in HER2+ early BC. Clinical trial information: NCT00486668 .

Relationship of adaptive subtyping and tumour heterogeneity of treatment response to neoadjuvant therapy in hormone receptor–positive HER2-negative early breast cancer: PENELOPE-B.

566 Background: The concept of intrinsic subtyping has been an important step for understanding of breast cancer (BC) as a heterogenous disease. However, these subtypes are not adapted to therapy-induced molecular plasticity. We have evaluated a high-risk luminal BC clinical trial cohort to identify new additional adaptive BC subtypes based on molecular alterations induced during neoadjuvant chemotherapy (NACT). Methods: A total of 1250 ER+/HER2- BC patients (pts) with residual disease after NACT and increased risk (CPS-EG score of ≥3 or 2 with ypN+) were randomized into the PENELOPE-B (NCT01864746) trial to receive palbociclib or placebo. Biomarker analysis was performed in 1411 pre- or postNACT tumor samples including 540 paired samples using the HTG EdgeSeq Oncology Biomarker Panel targeting 2549 genes (HTG Molecular Diagnostics Inc.), with assessment of the absolute assignment of breast cancer intrinsic molecular subtype (AIMS). For a subcohort of 29 pts, we evaluated triplicate samples before and after NACT as well as at the time of metastatic disease. Results: In paired biopsies, a total of 335 genes were significantly different between the pre- and the postNACT cohort. With hierarchical unsupervised clustering of these 335 genes, we characterized five different tumor subtypes with highly significant iDFS survival differences (p&lt;0.0001, n=539). We identified two large groups of tumors with excellent prognosis (adaptive cluster AC1 and AC2, together n=284, 6 events), as well as two groups with a poor prognosis; AC-3 (n=163, 82 events) and AC-4 (n=78, 29 events). The worst prognosis was observed in a small group of tumors with a pre-NACT Basal/HER2E AIMS subtype (n=14, 11 events). AC1 and AC3 are enriched for tumors with an AIMS subtype change from LumB to LumA during NACT, with improved iDFS for AC1. AC2 and AC4 are enriched for tumors with a constant LumA AIMS subtype before and after NACT, with improved iDFS for AC2. The low-risk adaptive subtypes AC1 and AC2 cover a total of 52.7% of pts with a combined event rate of 2.1%. In contrast, the best pretherapeutic conventional AIMS-subtype, preNACT LumA, covers 51.7% of pts, but still has an event rate of 15.4%. This suggests that adaptive subtypes are superior to classical AIMS subtypes for prediction of survival after NACT in luminal BC. Conclusions: Classical approach of intrinsic subtyping relies on constant gene expression, limiting its scope. Adaptive subtyping can complement the classical approach, focusing on those genes that are changed during therapy. Comparison of paired samples before and after therapy is superior to classical subtyping of baseline samples. This approach identified large subgroups of pts with excellent prognosis after NACT despite clinical high risk. This can be an important step to focus on high-risk pts for new neoadjuvant and post-neoadjuvant therapy concepts.

A gap analysis of UK biobank publications reveals SNPs associated with intrinsic subtypes of breast cancer

Breast cancer is a multifaceted disease and a leading cause of cancer morbidity and mortality in females across the globe. In 2020 alone, 2.3 million women were diagnosed and 685,000 died of breast cancer worldwide. With the number of diagnoses projected to increase to 3 million per year by 2040 it is essential that new methods of detection and disease stratification are sought to decrease this global cancer burden.Although significant improvements have been made in breast cancer diagnosis and treatment, the prognosis of breast cancer remains poor in some patient groups (i.e. triple negative breast cancer), necessitating research into better patient stratification, diagnosis and drug discovery. The UK Biobank, a comprehensive biomedical and epidemiological database with a wide variety of multiomics data (genomics, proteomics, metabolomics) offers huge potential to uncover groundbreaking discoveries in breast cancer research leading to improved patient stratification. Combining genomic, proteomic, and metabolic profiles of breast cancer in combination with histological classification, can aid treatment decisions through accurate diagnosis and prognosis prediction of tumor behaviour.Here, we systematically reviewed PubMed publications reporting the analysis of UK Biobank data in breast cancer research. Our analysis of UK Biobank studies in the past five years identified 125 publications, of which 76 focussed on genomic data analysis. Interestingly, only two studies reported the analysis of metabolomics and proteomics data, with none performing multiomics analysis of breast cancer. A meta-analysis of the 76 publications identified 2870 genetic variants associated with breast cancer across 445 genes. Subtype analysis revealed differential genetic alteration in 13 of the 445 genes and the identification of 59 well-established breast cancer genes. in differential pathways. Pathway interaction analyses illuminated their involvement in general cancer biomolecular pathways (e.g. DNA damage repair, Gene expression). While our meta-analysis only measured genetic differences in breast cancer due to current usage of UK Biobank data, minimal multi-omics analyses have been performed and the potential for harnessing multi-omics strategies within the UK Biobank cohort holds promise for unravelling the biological signatures of distinct breast cancer subtypes further in the future.

Abstract PO5-09-03: Multi-tissue transcriptome-wide association studies identified genes for intrinsic subtypes of breast cancer

Abstract Background: Though several genome-wide association studies (GWAS) of breast cancer (BC) have identified common variants which differ between intrinsic subtypes, the genes through which these variants act through to impact BC risk have not been fully established. Furthermore, transcriptome-wide association studies (TWAS) have thus far been primarily employed to identify genes associated with overall BC risk, while overlooking how the influence of common variation on gene expression may contribute to subtype-specific differences. Methods: In this study, we performed two complementary multi-tissue TWASs for each of the following BC intrinsic subtypes: Luminal A-like, Luminal B-like, Luminal B/HER2-negative-like, HER2-enriched-like, Triple Negative BC. These two approaches included 1) an expression-based approach that collated TWAS signals from expression quantitative trait loci (eQTLs) across multiple tissues using the Aggregated Cauchy Association Test (ACAT) and 2) a splicing-based approach that utilized two applications of ACAT to collate splicing QTLs (sQTLs) for a given gene in a tissue and then across tissues. To perform these two TWASs, we utilized e/sQTL models trained in 11 tissues from the Genotype-Tissue Expression Project including breast, ovary, uterus, vagina, EBV-transformed lymphocytes, whole blood, spleen, liver, subcutaneous adipose, visceral adipose, and cell-cultured fibroblasts. GWAS summary statistics were previously generated from 133,384 BC cases and 113,789 controls who were participants in the Breast Cancer Association Consortium (BCAC). We further performed our TWAS while conditioning e/sQTL effect sizes on nearby GWAS index SNPs. Additionally, we utilized gene-based fine-mapping of eQTLs and sQTL to identify candidate causal genes for each intrinsic subtype. Results: Overall, we identified 164 genes in 69 loci that were associated with Luminal A-like, 19 genes in 9 loci with Luminal B-like, 18 genes in 11 loci with Luminal B/HER2-negative-like, 10 genes in 7 loci with HER2-enriched-like, and 29 genes in 12 loci with TNBC. Among these genes, 17 genes had not been reported in previous TWAS of BC, and 140 genes, 1 gene, 2 genes, 2 genes, and 16 genes were uniquely associated with each of the intrinsic subtypes, respectively. Additionally, we identified one gene associated with Luminal A-like and one gene with Luminal B-like BC that were each in a locus located at least 1.4 Mb from published GWAS hits. Furthermore, we identified 106, 11, 10, 5, and 21 candidate causal genes for each of the intrinsic subtypes, respectively, that had a posterior inclusion probability of 0.9 in at least one e/sQTL. Conclusion: In summary, our multi-tissue TWAS corroborated previous GWAS loci for overall BC risk and intrinsic subtypes, while underscoring how common variation impacts BC etiology by modulating the expression and splicing of genes in multiple tissue types. Citation Format: James Li, Julian McClellan, Haoyu Zhang, Guimin Gao, Dezheng Huo. Multi-tissue transcriptome-wide association studies identified genes for intrinsic subtypes of breast cancer [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 PO5-09-03.

Abstract PO3-16-04: Distribution of intrinsic subtypes in endocrine-resistant and endocrine-sensitive breast cancer

Abstract Background Breast cancer (BC) is a heterogeneous disease that can be divided into intrinsic molecular subtypes. Among the four intrinsic subtypes, Luminal A and Luminal B are the most common and associated with the best outcome, whereas HER2-enriched and basal-like are less frequent. Tumors that are estrogen receptor α (ER)-positive and human epidermal growth factor receptor 2 (HER2)-negative (ER+/HER2-) are mostly found among the luminal subtypes. Despite that patients with ER+/HER2- tumors are offered adjuvant endocrine therapy, around one-third eventually develop endocrine resistance. The aim of this study was to explore the distribution of intrinsic subtypes in endocrine-resistant primary and relapse tumors, comparing these to endocrine-sensitive controls. Materials and methods Verified endocrine-resistant BC patients diagnosed in 2008-2012 were retrospectively collected at the Karolinska University Hospital, Stockholm, Sweden. Cases (N=70) were identified as patients with ER+/HER2- primary tumors and subsequent ER+/HER2- relapse tumors within 5 years and during endocrine therapy. Patients with primary ER+/HER2- tumors without progression or relapse at 10 years of follow-up were defined as controls (N=78), diagnosed in 2005-2006. Extracted RNA from formalin-fixed paraffin-embedded tumor tissue was analyzed by Affymetrix Clariom D Microarray and assessed by Transcriptome Analysis Console and R software. Results Among the controls, the distribution of Luminal A, Luminal B, and HER2-enriched subtypes was 65.4%, 34.6%, and 0%, respectively. In primary tumors, the distribution was in turn 55.4%, 43.1%, and 1.5%, and among relapse tumors 57.6%, 37.9%, and 4.5%, respectively. A total of 19 cases, accounting for 27.1%, switched intrinsic subtypes between the paired primary and relapse tumors. No tumors exhibited the basal-like subtype. Conclusion In this unique cohort, Luminal B and HER2-enriched subtypes were more common in primary and relapse tumors of verified endocrine-resistant patients than in primary tumors of endocrine-sensitive controls. Further, the HER2-enriched subtype, although sparse, was more frequently found in patients’ relapse tumors than in their corresponding primary tumors, and over one-fourth of cases switched subtypes during progression. These findings support the presence of subtype shifting in endocrine-resistant relapses and that endocrine-resistant tumors are more prone to be of Luminal B or HER2-enriched subtypes than endocrine-sensitive tumors. Citation Format: Caroline Schagerholm, Stephanie Robertson, Emelie Karlsson, Emmanouil Sifakis, Johan Hartman. Distribution of intrinsic subtypes in endocrine-resistant and endocrine-sensitive breast cancer [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 PO3-16-04.

Abstract PO5-24-03: Breast cancer intrinsic subtypes predict outcomes in primary and metastatic samples

Abstract Background: The prognostic and predictive value of the PAM50 intrinsic subtypes, namely Luminal A, Luminal B, Her2, and Basal-like subtypes, is well-studied in primary as well as metastatic breast cancer settings. Prosigna has emerged as a rapid PAM50 subtype predictor based on the NanoString nCounter assay. However, assay reproducibility across various RNASeq or qRT-PCR platforms can be challenging, especially when applying the predictor on metastatic breast cancer tumors. Here, we used SpinAdapt to create an intrinsic subtype predictor that works on RNA sequencing data, and validates on multiple tumor-sites. We evaluate real-world outcomes for our intrinsic subtype predictions across various immunohistochemical (IHC) labels and metastatic sites. Methods: We trained the subtype predictor on a cohort of 2,497 breast cancer patients using the PAM50 genes, profiled using Nanostring RNA nCounter assay (GSE148426). Approximately 5,423 de-identified records of breast cancer patients sequenced using whole-exome capture RNA-seq were included in our reference dataset. The reference dataset contained samples collected from various sites including breast (n=2440), liver (n=936), lymph node (n=577), lung (n=540), and bone (n=304). For subtype classification, we first batch-corrected the external dataset to Tempus RNA-seq reference dataset using SpinAdapt, then trained a Support-Vector Classifier (SVC) on the corrected data. A 10-fold CV experiment was performed on the corrected dataset to analytically validate the intrinsic subtype predictions. We retrospectively analyzed 7,021 de-identified breast cancer patients with known hormone receptor (HR) or HER2 status and a matched RNASeq sample. The concordance between HR/HER2 status and PAM50 prediction was analyzed, and these patients were excluded from training. Real-world overall survival (rwOS) was evaluated from the time of first diagnosis. The outcomes across intrinsic subtypes were further assessed according to tumor collection site and HR/HER2 IHC status. Results: The 10-fold CV experiment on the Tempus-adapted GSE148426 dataset achieved F-1 scores of 0.97, 0.86, 0.94, and 0.87 on Basal, HER2-like, Luminal A, and Luminal B PAM50 subtypes, respectively. On the Tempus evaluation dataset, 85.3% of HR+/HER2- patients (n=4,366), 65.4% of HR-/HER2+ patients (n=240), and 75.4% of HR-/HER2- patients (n=1,930) were classified as Luminal, HER2-like, and Basal, respectively. Evaluating outcomes on Tempus patients for each PAM50 group, the rwOS for the basal group was significantly shorter than patients not predicted to be basal (n=5,845, p&amp;lt; 2e-90). The rwOS for the predicted PAM50 basal patients remained significantly shorter than non-basal patients even when stratified by site of metastasis: breast (n=2,405; p&amp;lt; 1e-27), lymph node (n=577, p&amp;lt; 1e-7), liver (n=936; p&amp;lt; 1e-25), lung (n=540, p&amp;lt; 1e-13), and bone (n=304, p&amp;lt; 1e-3). Interestingly, within both HR+/HER2- (n=3,653) and HR-/HER2- (n=1,664) IHC cohorts with available outcomes data, the predicted PAM50 basal subtype could further stratify each of these populations with basal-subtype showing significantly worse prognosis than the non-basal subtype (p&amp;lt; 1e-27 and p&amp;lt; 1e-7, respectively). Conclusions: We retrospectively analyzed Tempus multimodal RWD to validate an in-house breast intrinsic subtype predictor that is agnostic to the site of metastasis. The prognostic value of the basal subtype was significant for breast cancer patients across various sites of metastasis including lymph node, liver, lung, and bones and IHC groups. For patients in each of the HR+/HER2- and triple negative IHC groups, the intrinsic molecular subtypes provided an additional level of prognostic detail with statistical significance. These data emphasize the importance of combining molecular subtypes with IHC-based diagnostics to fully characterize clinically relevant subpopulations and risk. Citation Format: Talal Ahmed, Mark Carty, Kaveri Nadhamuni, Raphael Pelossof. Breast cancer intrinsic subtypes predict outcomes in primary and metastatic samples [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 PO5-24-03.

The relationship of changes in molecular subtypes with metastases and progression-free survival in breast cancer.

Molecular subtyping of breast cancer cells is increasingly being developed as an initial step in selecting therapy and predicting the prognosis of breast cancer patients. During breast cancer, the molecular subtype of cancer cells can change. This study aimed to analyze the relationship between changes in the intrinsic subtype of breast cancer with metastasis and progression-free survival in breast cancer patients. This was a retrospective cohort study of patients diagnosed with breast cancer from 2016 to 2021. The molecular subtypes from the immunohistochemical examination results were recorded twice, and metastasis and progression-free survival (PFS) were recorded. The data were analyzed using the chi-square test and SPSS 26. Of the 44 patients, 19 (43.2%) experienced a change in molecular subtype, and 25 (56.8%) did not. No significant relationship existed between changes in molecular subtype and metastasis (p =0.405). No significant relationship existed between changes in molecular subtype and PFS (p =0.900). A significant relationship was found between changes in the molecular subtype and PFS in the patients with changes in the molecular subtype (p =0.022). Changes in the intrinsic subtype were associated with PFS in breast cancer patients. Patients with an intrinsic subtype that changed to triple-negative showed worse PFS.

Abstract 7660: L-Arginine metabolism is of prognostic relevance in women with breast cancer, but varies considerably between subtypes in vitro - A bedside-to-bench translational approach

Abstract Availability of the semi-essential amino acid L-arginine (L-arg) is limiting for proliferation in highly proliferative tissues. L-Arg is also a substrate for nitric oxide synthases (NOS) and arginases (ARG) 1 and 2. Methylation of L-arg residues within proteins by protein L-arg methyltransferases (PRMTs) leads to asymmetric (ADMA) and symmetric dimethylarginine (SDMA). Protein L-arg methylation is an important post-translational mechanism to regulate gene expression and cell cycle control. We measured L-arg and its metabolites in a prospective cohort of patients with primary breast cancer (BC). We further measured these metabolites and expression of genes involved in L-arg metabolic pathways in cell lines representing intrinsic BC subtypes. Plasma L-arg-related metabolite concentrations from 243 women with primary BC were associated with total mortality and disease recurrence during a median follow-up of 88 (IQR, 82-93) months. MCF-7, BT-474, SK-BR-3, and MDA-MB-468 cells representing ER-positive, HER2-positive, and triple negative BC were cultured in standard conditions and compared to MCF-12A normal breast epithelial cells. The plasma (in vivo) and intracellular concentrations (in vitro) of L-arg, L-ornithine (L-orn), L-citrulline (L-cit), ADMA, and SDMA were measured by UPLC-MS/MS. mRNA expression was quantified by qRT-PCR and protein expression was analyzed by Western Blot. In vivo, the plasma concentrations of all L-arg metabolites differed significantly between BC patients and healthy controls. L-Arg and ADMA were significantly higher in patients with recurrent disease and in those who died during follow up. ADMA was significantly associated with total mortality and recurrent disease in Luminal A patients; low L-orn/L-arg ratio was associated with survival in HER2+ BC patients, and low L-cit was associated with survival in triple negative BC. With the exception of MCF-7 cells, DDAH1 and DDAH2 mRNA concentrations in vitro were significantly higher in BC cells than in MCF-12A cells (DDAH1: 32-44 fold, DDAH2: 1.7-4.2 fold; p&amp;lt;0.05). These differences were mirrored by DDAH1 and DDAH2 protein concentrations. By contrast, MCF-7 cells were characterized by low DDAH1 and DDAH2, but high PRMT4 and PRMT6 mRNA expression and high L-arg content. BT-474 cells showed high ARG2 expression and high L-arg and L-orn concentrations, and MDA-MB-468 cells had the highest L-cit/L-arg ratio. In conclusion, regulation of L-arg metabolic pathways shows a complex and differential pattern between intrinsic BC subtypes, which is mirrored in representative cell lines in vitro. ADMA is a prognostic biomarker in Luminal A breast cancer patients; its metabolizing enzyme, DDAH, is highly overexpressed in BC cells in vitro. Thus, fingerprinting of L-arg metabolism may offer novel personalized treatment options within intrinsic BC subtypes. Citation Format: Juliane Hannemann, Leticia Oliveira Ferrer, Antonia Röglin, Fiona Kleinsang, Volkmar Müller, Isabell Witzel, Rainer Böger. L-Arginine metabolism is of prognostic relevance in women with breast cancer, but varies considerably between subtypes in vitro - A bedside-to-bench translational approach [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7660.

Multi-tissue transcriptome-wide association studies identified 235 genes for intrinsic subtypes of breast cancer.

Although genome-wide association studies (GWAS) of breast cancer (BC) identified common variants which differ between intrinsic subtypes, genes through which these variants act to impact BC risk have not been fully established. Transcriptome-wide association studies (TWAS) have identified genes associated with overall BC risk, but subtype-specific differences are largely unknown. We performed two multi-tissue TWASs for each BC intrinsic subtype including an expression-based approach that collated TWAS signals from expression quantitative trait loci (eQTLs) across multiple tissues and a novel splicing-based approach that collated signals from splicing QTLs (sQTLs) across intron clusters and subsequently across tissues. We utilized summary statistics for five intrinsic subtypes including Luminal A-like, Luminal B-like, Luminal B/HER2-negative-like, HER2-enriched-like, and Triple-negative BC, generated from 106,278 BC cases and 91,477 controls in the Breast Cancer Association Consortium. Overall, we identified 235 genes in 88 loci across were associated with at least one of the five intrinsic subtypes. Most genes were subtype-specific, and many have not been reported in previous TWAS. We discovered common variants that modulate expression of CHEK2 confer increased risk to Luminal-A-like BC, in contrast to the viewpoint that CHEK2 primarily harbors rare, penetrant mutations. Additionally, our splicing-based TWAS provided population-level support for MDM4 splice variants that increased triple-negative BC risk. Our comprehensive, multi-tissue TWAS corroborated previous GWAS loci for overall BC risk and intrinsic subtypes, while underscoring how common variation which impacts expression and splicing of genes in multiple tissue types can be used to further elucidate the etiology of BC.

‘Inner world’ of luminal HER 2-negative metastatic breast cancer: Efficacy of ribociclib in different intrinsic subtypes

The heterogeneity of breast cancer (BC), which determines various clinical scenarios of the disease, is still inaccessible to our understanding. Heterogeneity is based primarily on intrinsic subtypes of breast cancer, determined using genomic tests. Currently, four intrinsic subtypes are generally recognized: luminal A and B, HER-enriched (HER2-E) and basal-like. HER2-E subtype in luminal HER-negative (ER+HER–) breast cancer accounts for 11–22 per cent of cases. The efficacy of a combination of hormone therapy (HT) and the CDK4/6 inhibitor ribociclib in the HER2-E subtype was evaluated in a large exploratory analysis of MONALEESA-2, -3, and -7 trials. The gain in progression-free survival (PFS) and overall survival (OS) from the addition of ribociclib to HT was observed in all intrinsic subtypes, except for basal-like, and reached maximum in HER2-E subtype: Ribociclib increased the median PFS to 16.4 months from 5.5 months on HT (HR = 0.389; p &lt; 0.0001) and median OS to 40.3 months from 29.4 months (HR = 0.600; p = 0.0180). The significant frequency of occurrence of the HER2-E subtype in ER+HER-BC, the low efficiency of monoHT in this subtype is another argument in favor of prescribing combination therapy in early lines. Information about the intrinsic subtype not only brings us closer to understanding tumor heterogeneity, but may also become a significant factor in determining treatment tactics in the future.

Integrative multi-omic sequencing reveals the MMTV-Myc mouse model mimics human breast cancer heterogeneity

BackgroundBreast cancer is a complex and heterogeneous disease with distinct subtypes and molecular profiles corresponding to different clinical outcomes. Mouse models of breast cancer are widely used, but their relevance in capturing the heterogeneity of human disease is unclear. Previous studies have shown the heterogeneity at the gene expression level for the MMTV-Myc model, but have only speculated on the underlying genetics.MethodsTumors from the microacinar, squamous, and EMT histological subtypes of the MMTV-Myc mouse model of breast cancer underwent whole genome sequencing. The genomic data obtained were then integrated with previously obtained matched sample gene expression data and extended to additional samples of each histological subtype, totaling 42 gene expression samples. High correlation was observed between genetic copy number events and resulting gene expression by both Spearman’s rank correlation coefficient and the Kendall rank correlation coefficient. These same genetic events are conserved in humans and are indicative of poor overall survival by Kaplan–Meier analysis. A supervised machine learning algorithm trained on METABRIC gene expression data was used to predict the analogous human breast cancer intrinsic subtype from mouse gene expression data.ResultsHerein, we examine three common histological subtypes of the MMTV-Myc model through whole genome sequencing and have integrated these results with gene expression data. Significantly, key genomic alterations driving cell signaling pathways were well conserved within histological subtypes. Genomic changes included frequent, co-occurring mutations in KIT and RARA in the microacinar histological subtype as well as SCRIB mutations in the EMT subtype. EMT tumors additionally displayed strong KRAS activation signatures downstream of genetic activating events primarily ascribed to KRAS activating mutations, but also FGFR2 amplification. Analogous genetic events in human breast cancer showed stark decreases in overall survival. In further analyzing transcriptional heterogeneity of the MMTV-Myc model, we report a supervised machine learning model that classifies MMTV-Myc histological subtypes and other mouse models as being representative of different human intrinsic breast cancer subtypes.ConclusionsWe conclude the well-established MMTV-Myc mouse model presents further opportunities for investigation of human breast cancer heterogeneity.

Omitting Radiotherapy after Breast-Conserving Surgery in Luminal A Breast Cancer

BackgroundAdjuvant radiotherapy is prescribed after breast-conserving surgery to reduce the risk of local recurrence. However, radiotherapy is inconvenient, costly, and associated with both short-term and long-term side effects. Clinicopathologic factors alone are of limited use in the identification of women at low risk for local recurrence in whom radiotherapy can be omitted. Molecularly defined intrinsic subtypes of breast cancer can provide additional prognostic information.MethodsWe performed a prospective cohort study involving women who were at least 55 years of age, had undergone breast-conserving surgery for T1N0 (tumor size <2 cm and node negative), grade 1 or 2, luminal A–subtype breast cancer (defined as estrogen receptor positivity of ≥1%, progesterone receptor positivity of >20%, negative human epidermal growth factor receptor 2, and Ki67 index of ≤13.25%), and had received adjuvant endocrine therapy. Patients who met the clinical eligibility criteria were registered, and Ki67 immunohistochemical analysis was performed centrally. Patients with a Ki67 index of 13.25% or less were enrolled and did not receive radiotherapy. The primary outcome was local recurrence in the ipsilateral breast. In consultation with radiation oncologists and patients with breast cancer, we determined that if the upper boundary of the two-sided 90% confidence interval for the cumulative incidence at 5 years was less than 5%, this would represent an acceptable risk of local recurrence at 5 years.ResultsOf 740 registered patients, 500 eligible patients were enrolled. At 5 years after enrollment, recurrence was reported in 2.3% of the patients (90% confidence interval [CI], 1.3 to 3.8; 95% CI, 1.2 to 4.1), a result that met the prespecified boundary. Breast cancer occurred in the contralateral breast in 1.9% of the patients (90% CI, 1.1 to 3.2), and recurrence of any type was observed in 2.7% (90% CI, 1.6 to 4.1).ConclusionsAmong women who were at least 55 years of age and had T1N0, grade 1 or 2, luminal A breast cancer that were treated with breast-conserving surgery and endocrine therapy alone, the incidence of local recurrence at 5 years was low with the omission of radiotherapy. (Funded by the Canadian Cancer Society and the Canadian Breast Cancer Foundation; LUMINA ClinicalTrials.gov number, NCT01791829.)

The potential roles of lncRNA TINCR in triple negative breast cancer.

Triple negative breast cancer (TNBC) is the most aggressive intrinsic breast cancer subtype characterized by the lack of estrogen receptor (ER), progesterone receptor (PR), and low levels of human epidermal growth factor receptor 2 (HER2). The complex nature of TNBC has resulted in little therapeutic progress for the past several decades. The standard of care remains the FEC cocktail (5-fluorouracil (5-FU), epirubicin and cyclophosphamide). However, early relapse and metastasis in TNBC patients persists in causing dismal clinical outcomes. Due to complex heterogeneity features of TNBC, identifying the biomarker associated to the chemoresistance remains a challenge. The emergence of the long non-coding RNA (lncRNA) as a potential signature may have proven to be a new deterrent to diagnostic and treatment options. Previous studies unveiled the associations of lncRNA in the development of TNBCs whereby the aggressiveness and response to therapies may be associated by the abrogation of the molecular mechanism lncRNA. Terminal differentiation induced ncRNA (TINCR) is a lncRNA which have been linked with many cancers including TNBC. The expression and behavior of TINCR may exert unfavorable outcome in TNBCs. Nevertheless, the underlying molecular mechanism of TINCR in driving chemoresistance in TNBC is not well understood. This review will highlight the potential molecular mechanisms of TINCR in TNBC chemoresistance and how it can serve as a future potential prognostic and therapeutic target for a better treatment intervention.

Luminal B, Human Epidermal Growth Factor Receptor 2 (HER2/neu), and Triple-Negative Breast Cancers Associated With a Better Chemotherapy Response Than Luminal A Breast Cancers in Postneoadjuvant Settings.

Background Breast cancer is a heterogeneous disease with many histological and molecular/intrinsic breast cancer subtypes. Intrinsic breast cancer subtypes include luminal A, luminal B, human epidermal growth factor receptor 2 (HER2/neu), and triple-negative subtypes. The intrinsic breast cancer typing is based on the expression of estrogen receptor (ER), progesterone receptor (PR), HER2/neu, and Ki67-labeling index. One of these patients' foremost prognostic factors upon surgical resection is a response to neoadjuvant chemotherapy. The presence of a pathologically complete response (pCR) indicates a favorable patient outcome compared with a pathologically partial response (pPR). In this study, we compared the neoadjuvant chemotherapy response in breast cancer in different intrinsic breast cancer subtypes. Methodology It was a retrospective cross-sectional study conducted in the Department of Histopathology, Liaquat National Hospital, from January 2019 to December 2022, over three years. A total of 287 post-neoadjuvant chemotherapy cases of breast cancer were included. Anthracyclines and taxanes, coupled with or without anti-HER2/neu therapy, have been used in the neoadjuvant chemotherapy treatment setting contingent upon the patients' HER2/neu status. The post-chemotherapy response was assessed pathologically and categorized into pCR and pPR. Results The mean age of the patients was 47.90 ± 10.34 years, with a mean tumor size and Ki67 index of 5.36 ± 2.59 cm and 36.30 ± 22.14%, respectively. Invasive breast carcinoma of no special type (IBC-NST) made up 88.2% of cases, while grade 2 carcinomas made up 45.5%. The majority of tumors (42.7%) belonged to tumor (T) stage T2, and nodal metastasis was detected in 59.7% of patients. The intrinsic breast cancer subtypes luminal B (40.6%) and triple negative (33.3%) were the most prevalent, followed by luminal A (15.8%) and HER2/neu (10.3%). In 81 cases (24.5%), pCR was detected. The association of post-neoadjuvant chemotherapy response with intrinsic breast cancer subtypes showed asignificant difference (P< 0.001). The highest frequency of pCR was noted in HER2/neu cancers (58.8%), followed by luminal B (25.4%) and triple negative (23.6%). Regarding age, T-stage, tumor grade, and histological type of carcinoma, there was no discernible difference between pCR and pPR.Conversely, a significant association was noted for the Ki67 index. A Ki67 index higher than 25% showed a significantly higher frequency of pCR. Conclusions In postchemotherapy specimens, the HER2/neu breast cancer subtype substantially displayed higher pCR, followed by luminal B and triple-negative subtypes. After identifying the patients' subtypes, intrinsic subtyping can help determine the prognosis and anticipated response to chemotherapy. Furthermore, prechemotherapy breast specimens with high Ki67 index values have shown a direct association with neoadjuvant chemotherapy response.

PAM50 intrinsic subtypes, risk of recurrence score and breast cancer survival in HIV-positive and HIV-negative patients—a South African cohort study

PurposeTreatment decision making for patients with breast cancer increasingly depends on analysis of markers or systems for estimating risk of breast cancer recurrence. Breast cancer intrinsic subtypes and risk of recurrence (ROR) scores have been found to be valuable in predicting survival and determining optimal treatment for individual patients. We studied the association of breast cancer survival with the PAM50 gene expression assay in HIV-positive and HIV-negative patients.MethodRNA was extracted from formalin-fixed paraffin-embedded specimens of histologically confirmed invasive carcinoma and was purified using the AllPrep® DNA/RNA FFPE kit, Qiagen (Hilden, Germany). The NanoString RUO PAM50 algorithm was used to determine the molecular subtype and the risk of recurrence score of each sample. The overall and disease-free survival were determined with comparison made among HIV-positive and -negative patients. We then generated Kaplan–Meier survival curves, calculated p-values and estimated hazard ratios and their 95% confidence intervals using Cox regression models.ResultsOf the 384 RNA samples analysed, 98.4% met the required RNA quality standard and the specified QC threshold for the test. Luminal B was the most common PAM50 intrinsic subtype and 82.1% of patients were at high risk for disease recurrence based on ROR score. HIV infection, PAM50-based HER2-enriched and basal-like intrinsic subtypes, and high ROR were associated with poor overall and disease-free survival. HIV-positive patients with luminal A & B subtypes had significantly worse survival outcomes than HIV-negative luminal patents.ConclusionAggressive tumour biology was common in our cohort. HIV infection, PAM50 HER2-enriched,basal-like intrinsic subtypes and high ROR score were associated with poor overall and disease-free survival. HIV infection impacted survival in patients with luminal subtypes only.

Deep learning generates custom-made logistic regression models for explaining how breast cancer subtypes are classified.

Differentiating the intrinsic subtypes of breast cancer is crucial for deciding the best treatment strategy. Deep learning can predict the subtypes from genetic information more accurately than conventional statistical methods, but to date, deep learning has not been directly utilized to examine which genes are associated with which subtypes. To clarify the mechanisms embedded in the intrinsic subtypes, we developed an explainable deep learning model called a point-wise linear (PWL) model that generates a custom-made logistic regression for each patient. Logistic regression, which is familiar to both physicians and medical informatics researchers, allows us to analyze the importance of the feature variables, and the PWL model harnesses these practical abilities of logistic regression. In this study, we show that analyzing breast cancer subtypes is clinically beneficial for patients and one of the best ways to validate the capability of the PWL model. First, we trained the PWL model with RNA-seq data to predict PAM50 intrinsic subtypes and applied it to the 41/50 genes of PAM50 through the subtype prediction task. Second, we developed a deep enrichment analysis method to reveal the relationships between the PAM50 subtypes and the copy numbers of breast cancer. Our findings showed that the PWL model utilized genes relevant to the cell cycle-related pathways. These preliminary successes in breast cancer subtype analysis demonstrate the potential of our analysis strategy to clarify the mechanisms underlying breast cancer and improve overall clinical outcomes.

Abstract 3311: Tumor cell total mRNA level predicts disease progression across multi-ethnic patient cohorts with triple-negative breast cancer

Abstract Tumor heterogeneity presents a major challenge in the clinical management of breast cancers by impacting patient’s prognosis, therapeutic response, and clinical outcomes. Triple-negative breast cancer (TNBC) carries the worst prognosis among all the breast cancer intrinsic subtypes and has limited treatment options. Currently, TNBC subtypes are mainly refined into four categories: basal-like (BL1 and BL2), luminal androgen receptor (LAR) and mesenchymal (M). Although each of these tumor-specific subtypes represent different gene expression profiles, response to standard treatments and prognosis, further studies did not confirm a prognostic value for these subtypes. Given the distinct outcomes of TNBC patients, there is an urgent need to stratify their prognosis and identify patients who may benefit from potential targeted therapy. TNBC tumors often harbor cancer cells with different features in both genomic and transcriptomic level. With deconvolution of existing genomic and transcriptomic data, we derived a mathematical definition of breast cancer cell plasticity at a patient level. With a total of 765 TNBC patients from The Cancer Genome Atlas (TCGA), Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), Fudan University Shanghai Cancer Center (FUSCC) and Sweden Cancerome Analysis Network-Breast project (SCAN-B), we measured tumor-cell total mRNA expression scores (TmS) through an integrative deconvolution method with matched DNAseq and RNAseq data. In our previous study (Cao et al. Nature Biotechnology 2022), high TmS value is significantly associated with favorable prognosis in both TCGA (n=108) and METABRIC (n=214). We now validated this finding in both FUSCC from Han Chinese (n=245) and SCAN-B from Swedes (n=198). With TmS as a patient-level phenotypic feature, we performed differential expression analysis and gene set enrichment analysis to understand the biological functions indicated by TmS. In all four TNBC cohorts, patients with lower TmS are associated with epithelial to mesenchymal and TGFβ signaling hallmark pathways, with the latter presenting potential molecular targets for TNBC. Gene ontology enrichment revealed patients with higher TmS overexpress genes that are related with immune activities such as B cell and lymphocyte activation. Our results suggest a unique utility of tumor-specific total mRNA level in identifying high-risk TNBC patients across multi-ethnic cohorts and tailoring treatment on individual basis to maximize clinical benefit. Citation Format: Yaoyi Dai, Shaolong Cao, Bora Lim, Johan Staaf, Gloria V. Echeverria, Wenyi Wang. Tumor cell total mRNA level predicts disease progression across multi-ethnic patient cohorts with triple-negative breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3311.

Abstract P6-14-09: Non-canonical Wnt/Ror2 signaling regulates tumor cell invasion and dissemination in breast cancer through cell-matrix crosstalk

Abstract BACKGROUND: Metastasis is the main cause of mortality for breast cancer patients. The early steps of cancer metastasis require that tumor cells actively invade and disseminate from the primary tumor to distant organs. Cell-extracellular matrix (ECM) interactions represent fundamental interactions during tumor invasion and metastasis, yet how particular signal-transduction factors prompt the conversion of tumor cells into migratory populations capable of systemic dissemination remains elusive. OBJECTIVES: Wnt signaling is a known regulator of cell fate, migration, and polarity during various key biological processes. We previously discovered an inverse correlation between the canonical Wnt signature and a non-canonical Wnt receptor, Ror2, across breast cancers in TCGA. The objective of this study is to investigate how canonical and non-canonical Wnt signaling orchestrate tumor cell behavior during cancer invasion and metastasis. METHODS: We used clinically relevant syngeneic TP53-null Genetically Engineered Mouse Model (GEMM) tumors that molecularly reflect the different breast cancer intrinsic subtypes. In vivo transplantation of GEMM models and in vitro 3D tumor organoids were employed to elucidate the molecular mechanism underlying the migration, invasion, and metastasis of tumor cells upon genetic perturbation of Wnt/Ror2 signaling. RESULTS/DISCUSSION: From 3-dimensional (3D) tumor organoid models, we identified novel transcriptional alterations encompassing cell-cell adhesion, cytoskeletal remodeling, and ECM organization upon Ror2 loss. At protein levels, we discovered a significant increase in collagen fibril organization and integrin-α5 and integrin-β3 expression following Ror2 depletion. In addition, the matrisomal protein fibronectin (FN) was concomitantly upregulated and assembled in Ror2-deficient tumor cells at sites of invasion. Consequently, we observed FAK activation and actin cytoskeleton alterations in Ror2-deficient tumor cells, leading to a promigratory tumor cell behavior. The altered cytoskeleton and cell-ECM interaction enhanced the rigidity of the Ror2-depleted cells. Furthermore, Inhibition of either integrin or FAK activation abrogated the increased invasion driven by Ror2-loss. Unexpectedly, these changes were distinct from processes regulated by Wnt/ß-catenin activation. From both spontaneous metastasis and experimental metastasis models, we discovered a shift from canonical to non-canonical Wnt signaling throughout the progression of lung metastasis, indicating that the balance of Wnt signaling may serve as a switch to dictate cell functions at different stages of metastatic development. Consistently, we found enhanced initial colonization in the lungs when Ror2 is depleted in these breast cancer cells. Together, these studies provide new insight into how canonical and alternative Wnt pathways coordinate cell-cell and cell-ECM exchanges during breast cancer progression and metastasis. Supported by grant NIH-CA016303 Citation Format: Hongjiang Si, Na Zhao, Andrea Pedroza, Chad Creighton, Jeffrey Rosen, Kevin Roarty. Non-canonical Wnt/Ror2 signaling regulates tumor cell invasion and dissemination in breast cancer through cell-matrix crosstalk [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P6-14-09.

Abstract P1-05-30: Concordance of preoperative breast MRI finding with definitive postoperative pathology report, after neoadjuvant systemic treatment in patients with breast cancer

Abstract Neoadjuvant, i.e. preoperative, systemic antineoplastic treatment (NAT), in patients with breast cancer enables in vivo monitoring of tumor response to applied therapy, tailoring treatment in real –time accordingly, sparing surgical procedures, better quality of life for patients and implies better patient survival for particular patient, if a pathological complete response (pCR) to treatment is achieved. Use of MRI in monitoring response to NAT has shown in various studies sensitivity and specificity of at least 70% in the detection of residual disease, with a high positive and negative predictive value. Studies have shown higher accuracy in predicting pCR in HER2 positive tumors, and a higher rate of false negative results in HER2 negative tumors. Here we report findings of our pilot project where we tested the accuracy of the MRI, and the concordance of preoperative MRI findings after NAT, with the definitive pathology report after the surgery was performed, in breast cancer patients with different disease biology, in the real clinical practice. The focused pathological supstrate was the primary tumor in the breast. For the simplicity of this pilot analysis, we did not include here the status of the axilla, which will be included in our larger analysis pending. We performed our analysis on a cohort of 200 breast cancer patients who underwent NAT, in our institution, University Hospital for Tumors, in Zagreb, Croatia. Median age of the analyzed patient cohort was 62 years. The representation of individual breast cancer intrinsic subtype surrogates was as follows: HER2 nonluminal tumor 23.5% (47/200), triple negative breast cancer 21.5% (43/200), luminal HER2 positive 22.5% (45/200) and luminal HER2 negative 32.5% (65/200). According to MRI of the primary tumor in the breast, radiological complete response (rCR) to NAT was achieved in 46.5% (93/200) of patients, and the finding of residual tumor was described in 53.5% (107/200) of patients. Postoperatively, pathology report of the primary breast tumor showed pCR in 29% (58/200) of patients, and residual disease in 71% (142/200) of cases. The overall concordance of MR and pathology reports was 62.4% in the assessment of complete response, and 75.35% in the assessment of residual disease. Analyzed according to subgroups, results are as follows: in the cohort of patients with HER2 nonluminal tumors, concordance of MRI and pathology report in the assessment of complete response was 88%, while for residual disease concordance was 70%; in the cohort with triple-negative breast cancer patients, concordance of MRI and pathology report in the assessment of complete response was 83%, and residual disease 87.8%; in the group with luminal HER2-positive breast cancer concordance of MRI and pathology report in assessing complete response, as well as residual disease, was 97%; while in the group with luminal HER2-negative breast cancer, concordance of MRI and pathology report findings in assessing complete response was only 50.5%, and residual disease 77%. Results of our analysis showed relatively high overall concordance between MRI and pathology findings, which is in line with results of large studies worldwide and confirms MRI as a good method in monitoring response to NAT in breast cancer patients. By subgroup analysis, patients with luminal HER2-negative tumors are distinguished. This group has the lowest prevalence of complete response overall, as well as the lowest concordance of MRI and pathology report findings in the detection of these cases. This confirms the weaker response of this type of tumor to neoadjuvant treatment, but also indicates the need for additional caution when analyzing MRI findings in these patients, as well as for considering additional diagnostic arsenal, complementing the standardly – utilised MRI. Citation Format: Ana Tecic Vuger, Melita Peric Balja, Petra Jaksic, Petra Linaric, Mirjana Pavlovic Mavic, Ljubica Vazdar, Robert Separovic. Concordance of preoperative breast MRI finding with definitive postoperative pathology report, after neoadjuvant systemic treatment in patients with breast cancer [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P1-05-30.