scholarly journals RNA m6A Methylation Regulators Subclassify Luminal Subtype in Breast Cancer

2021 ◽  
Vol 10 ◽  
Author(s):  
Lin Yang ◽  
Shuangling Wu ◽  
Chunhui Ma ◽  
Shuhui Song ◽  
Feng Jin ◽  
...  

RNA N6-methyladenosine (m6A) methylation is the most prevalent epitranscriptomic modification in mammals, with a complex and fine-tuning regulatory system. Recent studies have illuminated the potential of m6A regulators in clinical applications including diagnosis, therapeutics, and prognosis. Based on six datasets of breast cancer in The Cancer Genome Atlas (TCGA) database and two additional proteomic datasets, we provide a comprehensive view of all the known m6A regulators in their gene expression, copy number variations (CNVs), DNA methylation status, and protein levels in breast tumors and their association with prognosis. Among four breast cancer subtypes, basal-like subtype exhibits distinct expression and genomic alteration in m6A regulators from other subtypes. Accordingly, four representative regulators (IGF2BP2, IGF2BP3, YTHDC2, and RBM15) are identified as basal-like subtype-featured genes. Notably, luminal A/B samples are subclassified into two clusters based on the methylation status of those four genes. In line with its similarity to basal-like subtype, cluster1 shows upregulation in immune-related genes and cell adhesion molecules, as well as an increased number of tumor-infiltrating lymphocytes. Besides, cluster1 has worse disease-free and progression-free survival, especially among patients diagnosed with stage II and luminal B subtype. Together, this study highlights the potential functions of m6A regulators in the occurrence and malignancy progression of breast cancer. Given the heterogeneity within luminal subtype and high risk of recurrence and metastasis in a portion of patients, the prognostic stratification of luminal A/B subtypes utilizing basal-featured m6A regulators may help to improve the accuracy of diagnosis and therapeutics of breast cancer.

2012 ◽  
Vol 30 (15_suppl) ◽  
pp. 1022-1022
Author(s):  
Giuseppe Viale ◽  
Leen Slaets ◽  
Femke De Snoo ◽  
Laura J. van 't Veer ◽  
Emiel J. Rutgers ◽  
...  

1022 Background: Biology has become the main driver of breast cancer therapy. Intrinsic biological subtypes by gene expression profiling have been identified. Pathology can be used to define surrogates of these subtypes but these are not always concordant, which may lead to different treatment plans. We investigated the concordance between BluePrint (BP) + MammaPrint (MP) (micro array based) breast cancer subtypes and pathological surrogates (based on ER, PR, HER2, and Ki67). Contrary to the Perou gene set (evolved into PAM50), BluePrint was trained using pathological data. Methods: Using available data (centrally assessed pathology and genomic) from the MINDACT pilot phase (Rutgers et al 2011) 621 tumors were analyzed. Two pathology classifications were used: one with 4 categories and one with 5 categories (Goldhirsch et al 2011). Based on BP 3 subtypes are formed: Luminal, HER2 and Basal. The Luminal subtype is further split into Luminal A (MP low risk) and Luminal B (MP high risk). Results: See table. Conclusions: All pathological Basal cases are BP Basal, apart from 1 BP HER2 case. Of the BP Basal cases, 15 are not pathological Basal: 1 is Luminal A, 11 are Luminal B (of which 8 are IHC ER/PR borderline (≥1% and < 10%)) and 3 are HER2. All pathological Luminal (A & B) that are BP HER2 are HER2- by TargetPrint. 25 of the 26 pathological HER2+ that are BP Luminal A are ER+. Most discordant cases are seen within the Luminal subtype, indicating that Ki67 discriminates Luminal A vs. B differently than MammaPrint does. The observed subtype discrepancies reveal potential important impact for treatment-decision making. MINDACT will provide important information. [Table: see text]


2012 ◽  
Vol 30 (27_suppl) ◽  
pp. 32-32 ◽  
Author(s):  
Giuseppe Viale ◽  
Leen Slaets ◽  
Femke De Snoo ◽  
Laura J. van 't Veer ◽  
Emiel J. Rutgers ◽  
...  

32 Background: Biology has become the main driver of breast cancer therapy. Intrinsic biological subtypes by gene expression profiling have been identified. Pathology can be used to define surrogates of these subtypes but these are not always concordant, which may lead to different treatment plans. We investigated the concordance between BluePrint (BP) + MammaPrint (MP) (micro array based) breast cancer subtypes and pathological surrogates (based on ER, PR, HER2 and Ki67). Contrary to the Perou gene set (evolved into PAM50), BluePrint was trained using pathological data. Methods: Using available data (centrally assessed pathology and genomic) from the MINDACT pilot phase (Rutgers et al 2011) 621 tumors were analyzed. Two pathology classifications were used: one with 4 categories and one with 5 categories (Goldhirsch et al 2011). Based on BP 3 subtypes are formed: Luminal, HER2 and Basal. The Luminal subtype is further split into Luminal A (MP low risk) and Luminal B (MP high risk). Results: See table. Conclusions: All pathological Basal cases are BP Basal, apart from 1 BP HER2 case. Of the BP Basal cases, 15 are not pathological Basal: 1 is Luminal A, 11 are Luminal B (of which 8 are IHC ER/PR borderline (≥1% and < 10%)) and 3 are HER2. All pathological Luminal (A & B) that are BP HER2 are HER2- by TargetPrint. 25 of the 26 pathological HER2+ that are BP Luminal A are ER+. Most discordant cases are seen within the Luminal subtype, indicating that Ki67 discriminates Luminal A vs. B differently than MammaPrint does. The observed subtype discrepancies reveal potential important impact for treatment-decision making. MINDACT will provide important information. [Table: see text]


2021 ◽  
Vol 28 ◽  
pp. 107327482098851
Author(s):  
Zeng-Hong Wu ◽  
Yun Tang ◽  
Yan Zhou

Background: Epigenetic changes are tightly linked to tumorigenesis development and malignant transformation’ However, DNA methylation occurs earlier and is constant during tumorigenesis. It plays an important role in controlling gene expression in cancer cells. Methods: In this study, we determining the prognostic value of molecular subtypes based on DNA methylation status in breast cancer samples obtained from The Cancer Genome Atlas database (TCGA). Results: Seven clusters and 204 corresponding promoter genes were identified based on consensus clustering using 166 CpG sites that significantly influenced survival outcomes. The overall survival (OS) analysis showed a significant prognostic difference among the 7 groups (p<0.05). Finally, a prognostic model was used to estimate the results of patients on the testing set based on the classification findings of a training dataset DNA methylation subgroups. Conclusions: The model was found to be important in the identification of novel biomarkers and could be of help to patients with different breast cancer subtypes when predicting prognosis, clinical diagnosis and management.


BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Marie S. Sandvei ◽  
Signe Opdahl ◽  
Marit Valla ◽  
Pagona Lagiou ◽  
Ellen Veronika Vesterfjell ◽  
...  

Abstract Background Because birth size appears to be positively associated with breast cancer risk, we have studied whether this risk may differ according to molecular breast cancer subtypes. Methods A cohort of 22,931 women born 1920–1966 were followed up for breast cancer occurrence from 1961 to 2012, and 870 were diagnosed during follow-up. Archival diagnostic material from 537 patients was available to determine molecular breast cancer subtype, specified as Luminal A, Luminal B (human epidermal growth factor receptor 2 (HER2)-), Luminal B (HER2+), HER2 type, and Triple negative (TN) breast cancer. Information on the women’s birth weight, birth length and head circumference at birth was used to estimate hazard ratios (HR) with 95% confidence intervals (CI) for each molecular subtype, applying Cox regression, and stratified by maternal height. Results Birth length (per 2 cm increments) was positively associated with Luminal A (HR = 1.2, 95% CI, 1.0–1.3), Luminal B (HER2+) (HR = 1.3, 95% CI, 1.0–1.7), and TN breast cancer (HR = 1.4, 95% CI, 1.0–1.9). No clear association was found for birth weight and head circumference. The positive associations of birth length were restricted to women whose mothers were relatively tall (above population median). Conclusion We found a positive association of birth length with risk of Luminal A, Luminal B (HER2+) and TN breast cancer that appears to be restricted to women whose mothers were relatively tall. This may support the hypothesis that breast cancer risk is influenced by determinants of longitudinal growth and that this finding deserves further scrutiny.


2006 ◽  
Vol 2 ◽  
pp. 117693510600200 ◽  
Author(s):  
G. Alexe ◽  
G.S. Dalgin ◽  
R. Ramaswamy ◽  
C. Delisi ◽  
G. Bhanot

Molecular stratification of disease based on expression levels of sets of genes can help guide therapeutic decisions if such classifications can be shown to be stable against variations in sample source and data perturbation. Classifications inferred from one set of samples in one lab should be able to consistently stratify a different set of samples in another lab. We present a method for assessing such stability and apply it to the breast cancer (BCA) datasets of Sorlie et al. 2003 and Ma et al. 2003. We find that within the now commonly accepted BCA categories identified by Sorlie et al. Luminal A and Basal are robust, but Luminal B and ERBB2+ are not. In particular, 36% of the samples identified as Luminal B and 55% identified as ERBB2+ cannot be assigned an accurate category because the classification is sensitive to data perturbation. We identify a “core cluster” of samples for each category, and from these we determine “patterns” of gene expression that distinguish the core clusters from each other. We find that the best markers for Luminal A and Basal are (ESR1, LIV1, GATA-3) and (CCNE1, LAD1, KRT5), respectively. Pathways enriched in the patterns regulate apoptosis, tissue remodeling and the immune response. We use a different dataset (Ma et al. 2003) to test the accuracy with which samples can be allocated to the four disease subtypes. We find, as expected, that the classification of samples identified as Luminal A and Basal is robust but classification into the other two subtypes is not.


2019 ◽  
Vol 178 (2) ◽  
pp. 451-458 ◽  
Author(s):  
Giuseppe Viale ◽  
Amy E. Hanlon Newell ◽  
Espen Walker ◽  
Greg Harlow ◽  
Isaac Bai ◽  
...  

2009 ◽  
Vol 27 (15_suppl) ◽  
pp. e11516-e11516
Author(s):  
A. Guerrero-Zotano ◽  
J. Gavila ◽  
M. A. Climent ◽  
M. J. Juan ◽  
V. Guillem ◽  
...  

e11516 Background: Gene expression profiling identifies several breast cancer subtypes with different chemosensitivity and outcome. We used immunohistochemistry surrogate markers to classify tumors according to known breast cancer subtypes and examined the relationship between neoadjuvant chemotherapy (NAC) response and long-term end points, including distant disease-free survival (DDFS) and overall survival (OS). Methods: Review of clinical and pathological data from 271 breast cancer patients treated in our institution with NAC between 1991–2008. Breast cancer subtypes were defined as follows: Luminal A: Estrogen receptor positive (ER+) and/or progesterone peceptor positive (PR+), human epidermal growth factor receptor 2-positive (Her-2+); Luminal B: ER+ and/or PR+,Her-2+; Basal: ER-,PR-,Her-2-;HER2: ER-,PR-,Her-2 +. ER and PR positive scored as positive if tumor cell nuclear staining was at least 2+. Her-2 scored as positive if test DAKO scored 3+ or FISH ratio Her-2/CEP-17>2.2. Results: 121 (45.8%) patients were classifed as Luminal A; 22 (8.1%) as Luminal B; 75 (27.7%) as Basal, and 50 (18.5%) as HER2. Most patients (63%) received NAC based on anthracyclines and taxanes. 36% Her-2+ patients were treated with NAC based on trastuzumab, and 43% received trastuzumab as adjuvant treatment. Response and outcome results are shown below (Table). Independently from subtype, only four patients out of 58 with pCR relapsed. Among patients who didn´t achieved pathologic complete response (pCR), basal and HER2 subtypes have the worst outcome (4 years SG 80% and 72% respectevely) compared with Luminal A (4 years SG: 94.7%), (log-rank p=0.009). Conclusions: Basal and HER2 tumor despite high chemosensitivity have worst long term outcome, particularly if pCR is not achieved after NAC. [Table: see text] No significant financial relationships to disclose.


2012 ◽  
Vol 30 (15_suppl) ◽  
pp. 1041-1041
Author(s):  
Joaquina Martínez-Galan ◽  
Sandra Rios ◽  
Juan Ramon Delgado ◽  
Blanca Torres-Torres ◽  
Jesus Lopez-Peñalver ◽  
...  

1041 Background: Identification of gene expression-based breast cancer subtypes is considered a critical means of prognostication. Genetic mutations along with epigenetic alterations contribute to gene-expression changes occurring in breast cancer. However, the reproducibility of differential DNA methylation discoveries for cancer and the relationship between DNA methylation and aberrant gene expression have not been systematically analysed. The present study was undertaken to dissect the breast cancer methylome and to deliver specific epigenotypes associated with particular breast cancer subtypes. Methods: By using Real Time QMSPCR SYBR green we analyzed DNA methylation in regulatory regions of 107 pts with breast cancer and analyzed association with prognostics factor in triple negative breast cancer and methylation promoter ESR1, APC, E-Cadherin, Rar B and 14-3-3 sigma. Results: We identified novel subtype-specific epigenotypes that clearly demonstrate the differences in the methylation profiles of basal-like and human epidermal growth factor 2 (HER2)-overexpressing tumors. Of the cases, 37pts (40%) were Luminal A (LA), 32pts (33%) Luminal B (LB), 14pts (15%) Triple-negative (TN), and 9pts (10%) HER2+. DNA hypermethylation was highly inversely correlated with the down-regulation of gene expression. Methylation of this panel of promoter was found more frequently in triple negative and HER2 phenotype. ESR1 was preferably associated with TN(80%) and HER2+(60%) subtype. With a median follow up of 6 years, we found worse overall survival (OS) with more frequent ESR1 methylation gene(p>0.05), Luminal A;ESR1 Methylation OS at 5 years 81% vs 93% when was ESR1 Unmethylation. Luminal B;ESR1 Methylation 86% SG at 5 years vs 92% in Unmethylation ESR1. Triple negative;ESR1 Methylation SG at 5 years 75% vs 80% in unmethylation ESR1. HER2;ESR1 Methylation SG at 5 years was 66.7% vs 75% in unmethylation ESR1. Conclusions: Our results provide evidence that well-defined DNA methylation profiles enable breast cancer subtype prediction and support the utilization of this biomarker for prognostication and therapeutic stratification of patients with breast cancer.


2013 ◽  
Vol 31 (15_suppl) ◽  
pp. e22117-e22117
Author(s):  
Pat W. Whitworth ◽  
Mark Gittleman ◽  
Stephanie Akbari ◽  
Lisette Stork ◽  
Femke De Snoo ◽  
...  

e22117 Background: Classification into molecular subtypes may be important for the selection of therapy for patients with early breast cancer. Previous analyses had shown that breast cancer subtypes have distinct clinical outcome (Sorlie, PNAS 2001; Esserman, BCRT 2011). The aim of the prospective NBRST study is to measure chemosensitivity as defined by pathological Complete Response (pCR), or endocrine sensitivity as defined by partial response (PR) and metastasis-free survival in molecular subgroups. Methods: The study includes women aged 18–90 with histologically proven breast cancer, who are scheduled to start neo-adjuvant chemotherapy (CT) or neo-adjuvant endocrine therapy (ET), and who provide written informed consent. Additional inclusion criteria include no excision biopsy or axillary dissection, no confirmed distant metastatic disease, and no prior therapy for breast cancer. Treatment is at the discretion of the physician adhering to NCCN approved regimens. 500 Patients will be enrolled. Results: 128 Patients (median age 52, range 22-79), T1-4 N0-3, had definitive surgery and the overall pCR rate was 22%.14 (11%) patients are classified as Luminal A-type (BluePrint Luminal/MammaPrint Low Risk) of whom 11 received neo-adjuvant CT; none of these patients had a pCR. While 3 patients received neo-adjuvant ET and all 3 had a PR. 47 (37%) Patients are classified as Luminal B-type (BluePrint Luminal/MammaPrint High Risk). All but 1 patient received neo-adjuvant CT and 4 (9%) had a pCR. 20 (16%) Patients are classified as BluePrint HER2-type and received neo-adjuvant CT plus Trastuzumab; 8 (40%) had a pCR. 47 (37%) Patients are classified as BluePrint Basal-type and received neo-adjuvant CT; 15 (32%) had a pCR. Of the patients with IHC/FISH HER2+ cancer 13/39 (33%) had a pCR and 6/21 (29%) of the patients with IHC/FISH triple negative breast cancer. Conclusions: We observed differences in pCR to neo-adjuvant treatment in groups stratified by BluePrint and MammaPrint. Patients with Luminal A-type breast cancer have a high response to neo-adjuvant endocrine therapy (100% PR) and no pCR to neo-adjuvant CT. While patients with BluePrint HER2-type and Basal-type breast cancer have a high pCR rate to neo-adjuvant CT. Clinical trial information: NCT01479101.


2014 ◽  
Vol 32 (26_suppl) ◽  
pp. 29-29
Author(s):  
Pat W. Whitworth ◽  
Mark Gittleman ◽  
Stephanie Akbari ◽  
Lisette Stork ◽  
Femke De Snoo ◽  
...  

29 Background: Classification into molecular subtypes is important for the selection of therapy for patients with breast cancer. Previous analyses demonstrated that breast cancer subtypes have distinct clinical outcome (Gluck, BCRT 2013). The aim of the prospective NBRST study is to measure chemosensitivity as defined by pathologic complete response (pCR), or endocrine sensitivity as defined by partial response (PR) and metastasis-free survival in molecular subgroups. Methods: The study includes women aged 18 to 90 with histologically proven breast cancer, who are scheduled to start neoadjuvant chemotherapy (NCT) or neoadjuvant endocrine therapy (NET), and who provide written informed consent. Additional inclusion criteria include no excision biopsy or axillary dissection, no confirmed distant metastatic disease, and no prior therapy for breast cancer. Treatment is at the discretion of the physician adhering to NCCN approved regimens. Results: Of 336 patients, T1-4 N0-3, had definitive surgery and the overall pCR rate was 24%. 32/167 (19%) IHC/FISH ERPR+/Her2- patients were reclassified by BluePrint (31 Basal). 43/95 (45%) IHC/FISH Her2+ patients were reclassified by BluePrint (25 Luminal and 18 Basal). 3/74 (3%) IHC/FISH triple-negative patients were not Basal by BluePrint. Of 45 (13%) patients classified as Luminal A 32 received NCT; one patient (3%) had a pCR; 13 patients received NET and 9 (70%) had a PR. Of 116 (35%) patients classified as Luminal B, 111 received NCT and seven (6%) had a pCR. The pCR rate (17/149 (11%)) in IHC/FISH ERPR+/HER2- patients was higher. Fifty-five (16%) are BluePrint HER2 and received NCT (51 plus trastuzumab); 27 (49%) had a pCR compared to 35/95 (37%) in IHC/FISH HER2+ patients. One-hundred twenty (36%) are BluePrint Basal and received NCT; 46 (38%) had a pCR, similar to the pCR percentage seen in the 74 patients designated triple-negative by IHC/FISH. Conclusions: Molecular subtyping using MammaPrint and BluePrint leads to a reclassification of 23% (78/336) of tumors. BluePrint reclassification resulted in better grouping of patients into expected response groups compared to local surrogate subtyping with immunostains.


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