1

Clustering analysis of tumor samples (IBC 20, nIBC 20) normals excluded

sample typeER

HER2

A B

Figure. Results of hierarchical clustering analysis.1000 probes having the greatest SD were chosen for unsupervised hierarchical clustering analysis. High relative expression is green, low relative expression is red. Sample type (IBC or nIBC) and ER/HER2 status (based on IHC) of the samples are color-coded as shown.

Hierarchical clustering analysis was performed with 1000 most informative probes.

• Two clusters were formed.cluster A -- many ER + cases (83%, 15 out of 18).cluster B -- many ER - cases (59%, 13 out of 22).

• No cluster enriched in IBC was formed.cluster A -- IBC is 61% (11 out of 18).cluster B -- IBC is 41% (9 out of 22).

A cluster rich in IBC was not formed.

sample type (■: nIBC, ■: IBC)HER2 (□: 0-1, ■: 2 (FISH-), ■: 2(FISH+)-3) 　 ER (□: 0, ■:1, ■:3-5)

2

⇒ 779 genes were selected.

Gene AIBC nIBC

6050

4700

2750

1200

IBC nIBC

6500

3800

2900

1000

Gene B

exclude select

Gene A → 4700 Gene B → 2900

Gene A → false negative 5, false positive 0 → ×Gene B → false negative 1, false positive 1 → ○

Selection of the gene set for assessment of IBC

1) differentially expressed genes

2) lower false-negative/false-positive rates

・ t-test (non-paired)p-value ＜ 0.05・ fold change 2≧

Filtered by the following criteria:

・ Determination of the positive threshold in each gene The value that gives the minimum of the sum of false-

positives and false-negatives.

・ False-positive/negative are detected in two or less samples

(1) ASSESSMENT OF IBC BY mRNA EXPRESSION

24 samples (IBC 12, non-IBC 12) were used as a learning set and the remaining 16 samples were used as validation set

<gene selection criteria>

132 genes were selected as the gene set for assessment of IBC• 100 genes were expressed at higher levels in IBC.• 32 genes were expressed at lower levels in IBC.

3

Clustering analysis of the learning set (IBC 12, nIBC 12)

sample type

ER

HER2

Figure. Results of hierarchical clustering analysis.Unsupervised hierarchical clustering was performed using 132 genes. High relative expression is green, low relative expression is red. Sample type (IBC or nIBC) and ER/HER2 status (based on IHC) of the samples are color-coded as shown.

sample type (■: nIBC, ■: IBC)HER2 (□: 0-1, ■: 2 (FISH-), ■: 2 (FISH+)-3) 　 ER (□: 0, ■:1, ■:3-5)

• Two clusters were formed. -- ER+ enriched cluster was not formed

cluster A -- ER+ ; 75% (9 out of 12)cluster B -- ER+ ; 75% (9 out of 12)• A cluster enriched for IBC was formed.cluster A -- nIBC cluster (nIBC ; 100%, 12 out of 12)cluster B -- IBC cluster (IBC ; 100%, 12 out of 12)

The learning set clustered according to sample type (IBC / nIBC). The selected 132 genes could discriminate IBC from non-IBC.

Hierarchical clustering analysis of the learning set was performed with 132 genes.

A B

IBC>

nIBC

gen

esnI

BC>I

BC g

enes

(1) ASSESSMENT OF IBC BY mRNA EXPRESSION

4

IBC score ：　 Index of IBC-likeness of a sample= The rate of the positive genes in each sample 　

　

・ nIBC ＞ IBC genes→ positive when lower than threshold

1) Positive/Negative was judged for every gene

positive genes / 132 (all genes) x 100

2) The IBC score for each sample was determined by calculating the percentage of positive genes.

・ IBC ＞ nIBC genes→ positive when higher than threshold

The learning set could be divided into IBC and nIBC by the IBC score.

IBCnIBC

IBC diagnostic criteria 43.0

IBC-like

nIBC-like

IBC

scor

e

Evaluation of the IBC assessment with the learning set

Figure. Distribution of the IBC score. The scores of the IBC group were higher and the two groups were completely separated.

※ we defined ‘IBC score’ as an index of IBC-likeness

IBC-likeness was computed in each sample, and the IBC assessment was evaluated.

• IBC diagnostic criteria was set to 43.0

(1) ASSESSMENT OF IBC BY mRNA EXPRESSION