nCounter® Breast Cancer 360™ Panel

 

The nCounter Breast Cancer 360 panel and data analysis service provides a unique 360 degree view of gene expression for the breast tumor microenvironment and immune response. Now researchers can more quickly decode the complexities of breast cancer biology, develop novel breast cancer gene signatures, and categorize disease heterogeneity using 32 biological signatures including signatures based upon the validated PAM50 and Tumor Inflammation Signature* (TIS) assays.

Product Highlights:

  • Breast Cancer 360 Subtype, Signatures, and Biology tableExpertly curated, comprehensive content includes 770 genes across 23 key breast cancer pathways and processes
  • Expanded evaluation of breast cancer subtypes includes: PAM50 Signature, Triple Negative Breast Cancer Signature, and Claudin-Low Signature
  • Streamlined analysis with access to two signatures based upon the validated PAM50 and Tumor Inflammation Signatures and 30 unique signatures with a well-established role in breast cancer and immuno-oncology 
  • Easy to use nCounter system provides publication ready figures in 24 hrs with less than 30 mins hands-on time

Download Gene List:

Learn about our nCounter Analysis System and nSolver™ Analysis Software.

*Ayers, Mark, et al. "IFN-y-related mRNA profile predicts clinical response to PD-1 blockade." The Journal of Clinical Investigation 127.8 (2017).

Breast Cancer Subtyping Breast Cancer Receptor Signaling Tumor Responsiveness Tumor Regulation Inhibitory Tumor Mechanisms Stromal Factors Inhibitory Metabolism Anti-Tumor Immune Activity Inhibitory Immune Signaling Immune Cell Population Abundance
PAM50 Molecular Subtyping ESR1 Gene Expression Antigen Processing Machinery Apoptosis IDO1 Gene Expression Endothelial Cells Hypoxia Tumor Inflammation Signature (TIS) Inflammatory Chemokines Cytotoxic Cell Abundance
Claudin-Low Subtyping PGR Gene Expression HRD Proliferation PD-L1 Gene Expression Stromal Abundance   Cytotoxicity   CD8+ T Cell Abundance
Triple Negative Breast Cancer Subtyping ERBB2 Gene Expression BRCA Differentiation       Interferon Gamma Signaling TIGIT Gene Expression Macrophage Abundance
  Estrogen Receptor Signaling P53 FOXA1 Gene Expression       MHC Class II Antigen Presentation   Mast Cell Abundance
                  Treg Abundance

 

Breast Cancer 360 Biological Signatures Supplement

Research Signatures

Breast Cancer Subtyping
Claudin-Low Subtype Signature5 This molecular subtype is characterized by low levels of luminal differentiation markers, high enrichment for epithelial-to-mesenchymal transition markers, immune response and cancer stem cell-like genes.
Triple Negative Breast Cancer Signature6 This signature identifies four distinct TNBC subtypes: Luminal/AR subtype 1, characterized by AR, ER, prolactin and ErbB4 signaling; Mesenchymal subtype 2, characterized by cell cycle, mismatch repair, and DNA damage networks; Basal-like Immune-Suppressed subtype 3, characterized by downregulation of B, T and NK-cells immune-regulating and cytokine pathways; Basal-like Immune Activated subtype 4, characterized by upregulation of B, T and NK cells immune-regulating pathways, and activation of STAT.

 

Tumor Responsiveness
Breast Cancer p53 Signature7 This signature categorizes p53 status by mutant-like vs wild-type-like and the signature is significantly associated with overall survival in breast cancer, identifying a group with high unmet need.
BRCAness Signature8 This signature captures breast cancer biology representative that is informative as to defects in the DNA damage repair–genes BRCA1 and BRCA2. Similar to our Homologous Recombination Deficiency signature this captures breakdown in BRCA-related DNA damage repair.
HRD Signature9 This signature is used to functionally assess Homologous Recombination Repair status, with potential to predict sensitivity to DNA-damage repair inhibitors such as PARP inhibitors. This signature captures cell cycle regulation, DNA damage, DNA replication, and DNA recombination and repair pathways.
Differentiation Signature This signature assigns a score of differentiation to the sample. Well-differentiated tumors that is phenotypically more similar to normal cells or tissue will grow and spread at a slow rated compared with poorly differentiated tumors, these present with abnormal cells that often grow rapidly.

 

Breast Cancer Receptor Signaling
ER Signaling Estrogen-binding systems associate with various proteins that direct cell cycle signaling, proliferation and survival.  This signature captures ER-mediated signaling pathways to elucidate how ER modulates activity of key transcription factors through stabilizing DNA-protein complexes and recruiting co-activators.  This signature also captures the impact to other signaling pathways induced by the binding of estrogens in the nuclea causing conformational changes in receptors. 
ESR1 This gene encodes an estrogen receptor, a ligand-activated transcription factor composed of several domains important for hormone binding, DNA binding, and activation of transcription.  The associated ER protein is a key pathological marker of breast cancer.
PGR This gene encodes a member of the steroid receptor superfamily. The encoded protein mediates the physiological effects of progesterone, which plays a central role in reproductive events and the associated protein is a key pathological marker of breast cancer.
ERBB2 This gene encodes a member of the EGF receptor family of receptor tyrosine kinases. This protein has no ligand binding domain of its own and therefore cannot bind growth factors. However, it does bind tightly to other ligand-bound EGF receptor family members to form a heterodimer, stabilizing ligand binding and enhancing kinase-mediated activation of downstream signaling pathways.  Amplification and overexpression are well established in breast cancer and the associated protein is a key pathological marker.

 

Novel Immune Signatures
Proliferation Endothelial Angiogenesis Cytotoxicity Stroma Inflammatory Chemokines Apoptosis
Treg Hypoxia INF gamma FOXA1   APM IDO1
MHC2 PDL1 TIGIT CD8 T Cells Cytotoxic Cells Mast Cells Macrophages
Cytotoxic Cells            

Includes expertly curated 770 genes across 23 categories of breast cancer tumor biology to support the evaluation of pathways and process, as well as novel signature development. 

Pathways
Cell Cycle ER Signaling Chromatin Modification Hedgehog MAPK Wnt
Notch STAT PI3K TGFβ RAS  

 

Processes
Tumor Microenvironment Immune
Breast Cancer Subtypes Cancer Progression EMT Immune Cell Marker
Triple Negative Tumor Biology Microenvironment Tissue Marker Immune Infiltration
Tumor Metabolism Cancer Progression Immune Response
Tumor Proliferation Angiogenesis  
Tumor Suppression    

Content included in the Breast Cancer 360 panel allows for a more comprehensive measurement of biological variables crucial to tumor progression and response to a wide-range of treatments. Research signatures are enriched with potentially predictive genes involved in proliferation, endothelial, angiogenesis, cytotoxicity, stroma, inflammatory chemokines, and apoptosis.

  • 32 signatures including two analytically validated signatures- PAM501,2 and Tumor Inflammation Signature3
  • 7 research focused signatures and 17 novel signatures measuring important tumor and immune activities
  • adapted to decode breast cancer biology in concert 

 

Analytically Validated Signatures

PAM50 Signature1,2

Included with the Breast Cancer 360 panel is the PAM50 Signature.  This 50-gene signature measures a gene expression profile that allows for the classification of breast cancer into four biologically distinct subtypes and a prognostic score.

  • PAM50 Subtype
    • Luminal A
    • Luminal B
    • HER2-Enriched
    • Basal-like
  • Prosigna Score / Risk of Recurrence

PAM50 gene expression signature heatmap subtypes

 

Tumor Inflammation Signature3

Included with the Breast Cancer 360 panel is the Tumor Inflammation Signature. This 18-gene signature measures activity known to be associated with response to PD-1/PD-L1 inhibitors pathway blockade3.

  • Includes 4 Areas of immune biology used to determine peripherally suppressed immune response and the identification of “hot” or “cold” tumors
    • Antigen Presenting Cells
    • T Cell/NK presence
    • IFNγ Biology
    • T Cell Exhaustion
  • Tissue-of-origin agnostic (Pan-cancer)
  • Potential surrogate for PD-L1 and mutational load in research setting4

Neuro_TIS.png

 

View publication and video.

 

18-gene Tumor Inflammation Signature
CCL5 CD8A STAT1 PD-L2/PDCD1LG2 HLA-DQA1 HLA-DRB1
CXCL9 CXCR6 TIGIT PD-L1/CD274 HLA-E CMKLR1
CD27 IDO1 LAG3 CD276 PSMB10 NKG7

 

Feature Specifications
Number of Targets 770 (Human), Including internal reference genes
Sample Input – Standard (No amplification required) 50 – 300 ng
Sample Input – Low Input As little as 10 ng with nCounter RNA Low Input Kit and Panel specific primer pools (sold separately)
Breast Cancer 360 Panel Standard Synthetic oligonucleotide pool corresponding to all panel gene targets used for normalization
Sample Type(s) FFPE-derived RNA, total RNA, and cell lysates
Customizable Add up to 30 unique genes with Panel-Plus
Time to Results Approximately 24 hours
Data Analysis nSolver Analysis software, BC 360 Data Analysis Service

 

1.       Walden B, Storhoff J, Nielsen T, et al. Development and verification of the PAM50-based Prosigna breast cancer gene signature assay. BMC Med Genomics. 2015;8:54

2.       Perou CM, Sørlie T, Eisen MB, et al. Molecular portraits of human breast tumours. Nature. 2000;406(6797):747-52.2

3.       Ayers, Mark, et al. “IFN-γ–related mRNA profile predicts clinical response to PD-1 blockade.” The Journal of Clinical Investigation 127.8 (2017)

4.       Haddad R., Abstract 6009, ASCO 2017  

5.       Prat A, Parker JS, Karginova O, et al. Phenotypic and molecular characterization of the claudin-low intrinsic subtype of breast cancer. Breast Cancer Res. 2010;12(5):R68

6.     Burstein MD, Tsimelzon A, Poage GM, et al. Comprehensive genomic analysis identifies novel subtypes and targets of triple-negative breast cancer. Clin Cancer Res. 2015;21(7):1688-98

7.     Troester MA, Herschkowitz JI, Oh DS, et al. Gene expression patterns associated with p53 status in breast cancer. BMC Cancer. 2006;6:276

8.     Severson TM, Wolf DM, Yau C, et al. The BRCA1ness signature is associated significantly with response to PARP inhibitor treatment versus control in the I-SPY 2 randomized neoadjuvant setting. Breast Cancer Res. 2017;19(1):99.

9.     Peng G, Chun-jen lin C, Mo W, et al. Genome-wide transcriptome profiling of homologous recombination DNA repair. Nat Commun. 2014;5:3361

For Research Use Only. Not for use in diagnostic procedures.

More Info

Join thought leader Jeremy Force as he talks immune profiling of BRCA-mutated breast cancers.

jeremy_force.jpg