Abstract
Background
Because a number of years may be required for normal cells to develop into carcinoma, genes involved in tumorigenesis and progression might differ among breast cancers in young women and those in older women. The present study sought to analyze subclonality during breast cancer evolution as well as diversity within each individual in our young patients’ cohort.
Methods
A total of 13 women aged <35 years at diagnosis with early breast cancer were recruited. Serial sections of breast samples consisting of synchronous invasive carcinoma, adjacent ductal carcinoma in situ (DCIS), normal breast tissue, and metastatic lymph nodes were collected and prepared for immunohistochemical analysis of estrogen receptor, progesterone receptor, HER2, and Ki67, and for extraction of genomic DNA. Germline and somatic gene alterations of genomic DNA were examined by targeted sequencing.
Results
Genomic DNA from 13 blood samples and 36 breast tissues consisting of 14 invasive carcinomas, nine adjacent DCIS, 11 normal breast tissues, and two metastatic lymph nodes were successfully sequenced. Germline gene alterations including pathogenic variants and gene alterations that were not yet evaluated for their clinical significance were detected in all patients but one. Somatic gene alterations were identified in eight invasive carcinomas, five DCIS, and one metastatic lymph node. Different somatic gene alterations between invasive carcinoma and DCIS were detected in two patients. Somatic gene mutations were present in non-neoplastic tissues in three patients. No two patients had the same gene alterations.
Conclusion
Our results reveal diversity within each individual during breast cancer progression.
Keywords: Breast cancer, Ductal carcinoma in situ, Invasive carcinoma, Heterogeneity, Targeted sequencing, Young women
Highlights
-
•
Subclonality during breast cancer progression in young patients were analyzed.
-
•
No two patients had the same germline and/or somatic gene alterations.
-
•
Somatic gene mutations were present in normal breast tissue.
1. Introduction
The evolution of cancers involves the gradual accumulation of genetic and epigenetic cancer-promoting changes [1]. The changes accumulate throughout the lifespan, and a number of years may be required for early pre-cancerous lesions to develop into carcinoma in situ and invasive carcinoma. Recent sequencing-based strategies have revealed that mutations could have been acquired prior to the cell becoming a malignant cell, and the amount of exposure to each mutational process could vary from one person to another [2]. Furthermore, each tumor shows individual subclonality in which subclones progress from normal cells to noninvasive and invasive carcinomas, then metastasis [3]. An understanding of cancer evolution might lead to appropriate treatment strategies and improved clinical outcomes [4].
Breast cancer in young women, usually defined as patients aged ≤40 years at diagnosis, is often characterized as aggressive molecular subtypes [[5], [6], [7], [8]], with an increased risk of recurrence and shorter disease-free survival compared to their older counterparts [[8], [9], [10], [11]]. Momozawa and colleagues reported that germline pathogenic variants were found in 15% of women diagnosed at < 40 years, and the proportion of patients with a pathogenic variant significantly decreased with advancing age [12]. In addition to genetic factors, it is suggested that genes and/or pathways involved in tumorigenesis and progression differ between breast cancers in young women and those in older women. Although there are numerous reports of genomic features in early and metastatic breast cancers [2,[13], [14], [15]], few studies have reported subclonal evolution in breast cancer in young women. Understanding the key mechanism of progression in each young patient will lead to appropriate prevention and treatment strategies.
We have performed a targeted amplicon exome sequencing for 160 cancer-related genes using genomic DNA from both tumor tissue and blood at our hospital. The clinical utility of our genomic testing for patients with meningioma [16], thyroid carcinoma [17], sinonasal papilloma [18], pancreatic cancer [19], various cancers such as colorectal, stomach, and lung cancers [20], and breast cancer [21] was shown previously.
Here, we analyzed germline and somatic gene alterations of genomic DNA extracted from blood and breast tissues consisting of synchronous invasive carcinoma, adjacent ductal carcinoma in situ (DCIS), normal breast tissue, and metastatic lymph nodes in 13 women aged <35 years at diagnosis by targeted sequencing. We sought to analyze subclonality during breast cancer evolution as well as diversity within each individual.
2. Methods
2.1. Patients
A total of 13 women aged <35 years with early breast cancer who had undergone breast surgery between May 2012 and August 2016 at Hokkaido University Hospital were recruited to this study (Table 1). This study was approved by the Ethics Committee of the Hokkaido University Graduate School of Medicine (No. 16–033), and conformed to the guidelines of the 1996 Declaration of Helsinki. Written informed consent for the use of blood and tumor tissues was provided by each patient. Patients who were positive for axillary lymph nodes or who had human epidermal growth factor receptor 2 (HER2)-positive breast cancer received adjuvant or neoadjuvant chemotherapy including anthracyclines and/or taxanes with or without anti-HER2 drugs. Tumor samples were obtained during surgery. Patients with estrogen receptor (ER)-positive breast cancer received adjuvant endocrine therapy (tamoxifen ± luteinizing hormone-releasing hormone agonist).
Table 1.
Characteristics of patients and tumors.
| Characteristics | Patients (n = 13) |
|---|---|
| Age, median (range), years | 32 (25–34) |
| Sex | |
| Female | 13 (100%) |
| Male | 0 (0%) |
| Family history of cancer | |
| Breast cancer and/or ovarian cancer | 6 (46%) |
| Other cancer | 6 (46%) |
| No family history of cancer | 4 (31%) |
| Stage | |
| I | 4 (31%) |
| II | 8 (62%) |
| III | 1 (8%) |
| Lymph node status | |
| Negative | 10 (77%) |
| Positive | 3 (23%) |
| ER and HER2 status | |
| ER-positive/HER2-negative | 11 (85%) |
| ER-positive/HER2-positive | 1 (8%) |
| ER-negative/HER2-positive | 0 (0%) |
| ER-negative/HER2-negative | 1 (8%) |
| Histopathology | |
| Invasive ductal carcinoma | 9 (69%) |
| Mucinous carcinoma | 3 (23%) |
| Metaplastic carcinoma | 1 (8%) |
| Neoadjuvant therapy | |
| Chemotherapy | 3 (23%) |
| Chemotherapy and anti-HER2 therapy | 1 (8%) |
| None | 9 (69%) |
| Postoperative adjuvant therapy | |
| Endocrine therapy alone | 7 (54%) |
| Chemotherapy alone | 2 (15%) |
| Endocrine therapy and chemotherapy | 3 (23%) |
| Endocrine therapy and anti-HER2 therapy | 1 (8%) |
| Recurrence (distant metastasis) | |
| No | 10 (77%) |
| Yes | 3 (23%) |
| Follow-up, median (range), months | 53.1 (8.6–82.3) |
2.2. Samples and DNA extraction
Formalin-fixed paraffin-embedded (FFPE) breast samples stained with hematoxylin–eosin (H&E) were reviewed, and adequate tissue blocks consisting of invasive carcinoma, adjacent DCIS, normal breast tissue, and metastatic lymph nodes were selected for each patient (Fig. 1). Macrodissection was performed in order to separate invasive carcinoma from DCIS after pathology review. Serial sections (5 μm) were prepared from the selected blocks for immunohistochemical analysis of ER, progesterone receptor (PgR), HER2, and Ki67, and 5–10 sections were used for extraction of genomic DNA. The Ki67 labeling index was assessed as the percentage of tumor cells showing definite nuclear staining among >5000 invasive tumor cells. Immunohistochemical analysis of PTEN (D4.3, Cell Signaling Technology), p53 (DO-7, Dako), and MDM2 (IF2, Invitrogen) was performed. DNA from peripheral blood cells was also analyzed. Genomic DNA was extracted using QIAamp DNA FFPE Tissue Kit (Qiagen, Hilden, Germany), QIAsymphony DSP DNA Mini Kit (Qiagen), or QIAamp DNA Blood Mini Kit (Qiagen). The concentration of the genomic DNA was measured by Qubit dsDNA BR Assay Kit (Thermo Fisher Scientific, Waltham, USA) and Qubit 3.0 Fluorometer (Thermo Fisher Scientific). After checking the quality of the DNA based on the DNA integrity number (DIN) score calculated using the Agilent 2000 TapeStation (Agilent Technologies, Waldbronn, Germany), the minimum amount of DNA was 50 ng and the minimum quality of DNA had a DIN score over 3.1.
Fig. 1.
Selection of adequate tissue blocks for immunohistochemical staining and genomic DNA extraction consisting of invasive carcinoma, adjacent DCIS, and normal breast tissue. Surgically resected breast samples of a representative case (No. 2) are shown. Micrographs (200 × ) of H&E-stained tissue sections of invasive ductal carcinoma (a, tumor content 70%), DCIS (b, tumor content 60%), and normal breast tissue (c, epithelial cell content 40%) in the lower panels are details from the areas delineated by yellow squares in the upper panels. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
2.3. Targeted amplicon sequencing and data analysis
Using the obtained genomic DNA, we then amplified the target genes by a polymerase chain reaction (PCR) method with Gene Read DNA seq Panel PCR Regent V2 (Qiagen) and Human Comprehensive Cancer Panel (Qiagen). We performed targeted amplicon exome sequencing for 160 cancer-related genes based on the Illumina MiSeq sequencing platform (Illumina, San Diego, USA) with an average depth of coverage of approximately 500 × with at least 80% of bases covered >50 × [[16], [17], [18], [19], [20], [21]]. Sequencing (paired-end, 150 bp) of samples and demultiplexing of libraries was performed by Illumina MiSeq Reporter. The list of 160 genes is shown in Supplementary Table 1 [19,20]. Details of data analysis are described in Supplementary Methods. Germline variants were classified according to the American College of Medical Genetics and Genomics (ACMG) guidelines [22], and retained as pathogenic based on the recommendations of ACMG and ClinVar [23]. Germline secondary findings were disclosed only to those patients who agreed to receive this information.
3. Results
3.1. Patient characteristics
Characteristics of the 13 patients recruited in this study are summarized in Table 1, and detailed information of past and family histories of each patient is shown in Table 2. Case 2 had been diagnosed with Cowden syndrome, and case 5 had been diagnosed with neurofibromatosis 1. Six patients had a family history of breast and/or ovarian cancers, and six patients had a family history of other cancers including gastric cancer and thyroid cancer. Eleven were ER-positive/HER2-negative, and case 1 (Table 4) was triple-negative. Case 10 (Table 6) had ER-positive/HER2-positive breast cancer and was treated with neoadjuvant chemotherapy and anti-HER2 therapy. Three patients (cases 11, 12, and 13) received neoadjuvant chemotherapy. All patients received adequate postoperative adjuvant therapy including endocrine therapy, chemotherapy, and anti-HER2 therapy. Three patients (cases 2, 5, and 13) experienced recurrence. First sites of metastatic disease were bone in cases 2 and 5, and lung and brain in case 13. Biopsy at the recurrent sites was not performed in all three cases. The median follow-up time was 53.1 months (range 8.6–82.3). Genomic DNA from 13 blood samples and 36 breast tissue samples consisting of 14 invasive carcinomas, nine adjacent DCIS, 11 normal breast tissues, and two metastatic lymph nodes were successfully sequenced.
Table 2.
Past and family histories of 13 patients.
| No. | Age | Past history | Family history of cancer |
Other cancer |
|---|---|---|---|---|
| Breast cancer and/or ovarian cancer | ||||
| 1 | 32 | Breast cancer | Breast cancer (great grandmother) | |
| 2 | 33 | Cowden syndrome (breast cancer, endometrial cancer, thyroid adenoma) | Breast cancer (aunt) | Bladder cancer (grandfather) |
| 3 | 32 | Thyroid cancer | Gastric cancer (grandmother), Lung cancer (grandfather), Thyroid cancer (grandmother) | |
| 4 | 33 | Benign ovarian tumor | ||
| 5 | 30 | Neurofibromatosis 1 | Breast cancer (grandmother, grandaunt) | Thyroid cancer (grandmother), Multiple myeloma (uncle) |
| 6 | 33 | Ovarian cancer (grandmother) | ||
| 7 | 31 | Endometriosis | Gastric cancer (mother, cousin) | |
| 8 | 33 | Systemic lupus erythematosus | ||
| 9 | 32 | |||
| 10 | 33 | Infertility | Gastric cancer (grandmother), Pancreatic cancer (grandmother) | |
| 11 | 25 | Mature cystic teratoma | Breast cancer (aunt, cousin) | |
| 12 | 34 | Breast cancer (cousin) | Colon cancer (uncle) | |
| 13 | 32 | Partial anomalous pulmonary venous connection |
Table 4.
Samples for clinical sequencing in nine patients treated with primary surgery.
| No. | Histo-pathology | pT | pN | Grade | Normal breast tissue |
Ductal carcinoma in situ |
Invasive carcinoma |
Metastatic lymph node |
||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| ER | PgR | HER2 | Ki67 | ER | PgR | HER2 | Ki67 | ER | PgR | HER2 | Ki67 | ER | PgR | HER2 | Ki67 | |||||
| 1 | IDC | 16 | 0 | 3 | 95 | 95 | 0 | 20 | 0 | 0 | 1+ | 60 | <1 | 0 | 1+ | 99 | N/A | |||
| 2 | IDC | 57 | 1 | 3 | 10 | 60 | 0 | 10 | 90 | 90 | 1+ | 15 | 90 | 90 | 1+ | 10 | – | – | – | – |
| 3 | IDC | 28 | 7 | 2 | 30 | 30 | 0 | 2 | 80 | 50 | 2+ | 20 | 80 | <1 | 1+ | 40 | 95 | 10 | 0 | 30 |
| 4 | IDC | 25 | 1 | 2 | 10 | 10 | 0 | 5 | 90 | 90 | 0 | 5 | 90 | 90 | 0 | 25 | 95 | 50 | 1+ | 30 |
| 5 | IDC | 28 | 0 | 3 | 20 | 5 | 0 | 10 | 90 | 20 | 1+ | 30 | 70 | 20 | 1+ | 60 | N/A | |||
| 6 | IDC | 13 | 0 | 1 | 40 | 40 | 0 | 10 | 100 | 70 | 1+ | 20 | 100 | 80 | 2+∗ | 18 | N/A | |||
| 7 | IDC | 21 | 0 | 2 | 10 | <5 | 0 | 5 | 90 | 90 | 0 | 5 | 90 | 80 | 1+ | 29 | N/A | |||
| 8 | Mucinous | 26 | 0 | 1 | 40 | 40 | 0 | 10 | 95 | 90 | 0 | 10 | 95 | 90 | 1+ | 5 | N/A | |||
| 9 | Mucinous | 60 | 0 | 1 | 30 | 30 | 0 | 5 | N/A | 95 | 95 | 0 | 10 | N/A | ||||||
pT, pathological tumor size (mm); pN, number of positive lymph nodes; Grade, tumor grade; ER, estrogen receptor (% of positive cells); PgR, progesterone receptor (% of positive cells); HER2, score; Ki67, labeling index (%); IDC, invasive ductal carcinoma; Mucinous, mucinous carcinoma; N/A, not applicable; −, not evaluated; ∗equivocal by HER2 in situ hybridization.
Table 6.
Samples for clinical sequencing in four patients treated with neoadjuvant therapy.
| No. | Tissue samples | Histo-pathology | ypT | ypN | Normal breast tissue |
Ductal carcinoma in situ |
Invasive carcinoma |
|||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| ER | PgR | HER2 | Ki67 | ER | PgR | HER2 | Ki67 | ER | PgR | HER2 | Ki67 | |||||||
| 10 | before NAC | IDC | N/A | 95 | 0 | 3+ | 30 | 100 | 0 | 3+ | 30 | |||||||
| after NAC | 16 | 0 | 20 | 10 | 0 | 5 | – | >90 | 2 | 2+ | 1.5 | |||||||
| 11 | after NAC | IDC | 19 | 0 | 80 | 10 | 0 | 1–2 | – | 100 | 90 | 0 | 10 | |||||
| 12 | after NAC | Mucinous | 34 | 0 | – | – | 90 | 70 | 0 | 15 | ||||||||
| 13 | after NAC | Metaplastic | 47 | 0 | – | – | 10 | 0 | 0 | 70 | ||||||||
NAC, neoadjuvant chemotherapy; ypT, pathological tumor size after NAC (mm); ypN, number of positive lymph nodes after NAC; ER, estrogen receptor (% of positive cells); PgR, progesterone receptor (% of positive cells); HER2, score; Ki67, labeling index (%); IDC, invasive ductal carcinoma; Mucinous, mucinous carcinoma; Metaplastic, metaplastic carcinoma; before NAC, samples from primary tumors before neoadjuvant chemotherapy; after NAC, samples from primary tumors after neoadjuvant chemotherapy; N/A, not applicable; −, not evaluated.
3.2. Germline gene alterations
Detailed information regarding germline gene alterations including pathogenic, uncertain significance (VUS), and benign variants is shown in Table 3. Germline pathogenic variants were identified in two patients: PTEN p.E242∗ in case 2 and BRCA2 p.R2336H in case 3. VUS were detected in three patients: TERT p.R951Q in case 1, RET p.E459K in case 6, and CHEK2 p.H414Y in case 11. A benign BRCA2 p.I1929V variant was identified in case 5. This patient was diagnosed with type 1 neurofibromatosis when she was a teenager. However, NF1 and NF2 gene alterations were not detected. Variants with conflicting interpretations between ACMG values and any non-ACMG value were detected in three patients, and variants without an interpretation of clinical significance were detected in eight patients. Germline gene alterations were detected in all the tissue samples including normal breast tissue, DCIS, invasive carcinoma, and metastatic lymph nodes as well as the blood samples. The median variant allele frequency among breast tissues was 50% (range 19–87%).
Table 3.
Germline gene alterations and variant frequency in 13 patients.
| No. | Germline gene alteration |
Variant allele frequency (%) |
|||||||
|---|---|---|---|---|---|---|---|---|---|
| Pathogenic/likely pathogenic | Uncertain significance (VUS) | Othera | Not evaluatedb | Benign/likely benign | Normal breast tissue | Ductal carcinoma in situ | Invasive carcinoma | Metastatic lymph node | |
| 1 | TERT p.R951Q | 47 | 51 | 50 | N/A | ||||
| CDK12 p.L1383I | 50 | 41 | 58 | N/A | |||||
| 2 | PTEN p.E242∗ | 51 | 53 | 54 | – | ||||
| 3 | BRCA2 p.R2336H | 51 | 67 | 61 | 54 | ||||
| 4 | KMT2D p.P2938L | 61 | 58 | 60 | 63 | ||||
| FLT3 p.T382 M | 50 | 48 | 51 | 50 | |||||
| 5 | BRCA2 p.I1929V | 50 | 34 | 19 | N/A | ||||
| 6 | RET p.E459K | 48 | 52 | 47 | N/A | ||||
| CDH1 p.E880K | 47 | 48 | 51 | N/A | |||||
| 7 | PALB2 p.Q460R | 51 | 50 | 50 | N/A | ||||
| SETD2 p.E639K | 51 | 42 | 40 | N/A | |||||
| 8 | FUBP1 p.T601A | 50 | 55 | 51 | N/A | ||||
| TP53 p.E11Q | 49 | 50 | 51 | N/A | |||||
| FLT3 p.T820 N | 49 | 48 | 47 | N/A | |||||
| 9 | – | – | – | N/A | |||||
| 10 | ASXL1 p.E1033Vc | – | 49c | 47c | N/A | ||||
| ASXL1 p.E1033Vd | 51d | – | 48d | N/A | |||||
| 11 | CHEK2 p.H414Y | 45 | – | 53 | N/A | ||||
| ERBB4 p.G319R | 53 | – | 47 | N/A | |||||
| 12 | BRCA2 p.L1908V | – | – | 50 | N/A | ||||
| ATRX splice site | – | – | 68 | N/A | |||||
| 13 | SLC7A8 p.R181Q | – | – | 49 | N/A | ||||
| EP300 p.M556V | – | – | 45 | N/A | |||||
| SETD2 p.M761I | – | – | 87 | N/A | |||||
Conflicting interpretations between ACMG values and any non-ACMG value.
Submissions without an interpretation of clinical significance.
Samples before neoadjuvant chemotherapy.
Samples after neoadjuvant chemotherapy; N/A, not applicable; −, not evaluated.
3.3. Pathological characteristics and somatic gene alterations in patients treated with primary surgery
Eight synchronous breast samples consisting of invasive carcinoma, adjacent DCIS, and normal breast tissue, and one synchronous breast sample consisting of invasive carcinoma and normal breast tissue were evaluated in nine patients who received primary surgery (Table 4, Table 5). Synchronous metastatic lymph nodes were also examined in two patients (cases 3 and 4). One lymph node with micrometastasis (0.3 mm, case 2) could not be evaluated. Somatic gene alterations were identified in two normal breast tissues (cases 1 and 4), four DCIS (cases 2, 4, 5, and 6), six invasive carcinomas (cases 1, 2, 4, 5, 6, and 7), and one metastatic lymph node (case 4).
Table 5.
Somatic gene alterations in nine patients treated with primary surgery.
| No. | Somatic gene alterations |
|||||||
|---|---|---|---|---|---|---|---|---|
| Normal breast tissue |
Ductal carcinoma in situ |
Invasive carcinoma |
Metastatic lymph node |
|||||
| Gene (VAF) | ECC | Gene (VAF) | TC | Gene (VAF) | TC | Gene (VAF) | TC | |
| 1 |
TP53 p.P72Sc (4%) PPP2R1A p.S256F (16%) |
30% | none | 10% | BRCA2 p.E2198∗a (14%) | 20% | N/A | |
| 2 | none | 40% |
PTEN p.E18∗ (22%) GATA3 splice site (7%) |
60% |
PTEN p.E18∗ (28%) GATA3 splice site (28%) |
70% | – | |
| 3 | none | 20% | none | 50% | none | 70% | none | 50% |
| 4 | ERBB2 p.W169∗ (5%) | 20% | TP53 p.R213Lb (17%) | 50% | TP53 p.R213Lb (31%) | 40% | TP53 p.R213Lb (6%) | 40% |
| 5 | none | 40% | PIK3CA p.E81Kb (19%) | 50% | PTEN p.R130Ga (40%) | 80% | N/A | |
| 6 | none | 40% | MAP2K4 del | 60% | MYC amp, CDK12 amp | 50% | N/A | |
| 7 | none | 30% | none | 30% |
TP53 p.T230S (34%) DNMT3A p.R320Q (4%) |
40% | N/A | |
| 8 | none | 20% | none | 30% | none | 65% | N/A | |
| 9 | none | 20% | N/A | none | 70% | N/A | ||
VAF, variant allele frequency; ECC, epithelial cell content; TC, tumor content; del, deletion; amp, amplification; N/A, not applicable; −, not evaluated.
a pathogenic, b likely pathogenic, c uncertain significance, d conflicting interpretations of pathogenicity.
In case 1 with triple-negative breast cancer, high expression of ER and PgR and mutations of TP53 p.P72S and PPP2R1A p.S256F were detected in normal breast tissue, but not in DCIS or invasive carcinoma. Instead, a somatic BRCA2 p.E2198∗ mutation was identified in invasive carcinoma. In case 2 with ER-positive/PgR-positive/HER2-negative breast cancer who had a germline PTEN p.E242∗ pathogenic variant, somatic PTEN p.E18∗ and GATA3 gene mutations were detected in both DCIS and invasive carcinoma. PTEN protein expression was observed in normal epithelial cells, but not in cancer cells in DCIS or invasive carcinoma (Supplementary Fig. 1). Because this somatic PTEN p.E18∗ mutation most likely represents a second hit, it is possible that the two-hit mechanism of PTEN loss in carcinoma occurred in case 2. In case 4 with ER-positive/PgR-positive/HER2-negative breast cancer, a TP53 p.R213L mutation was identified in DCIS, invasive carcinoma, and metastatic lymph nodes, suggesting that this TP53 mutation was a driver for the progression through DCIS and invasive carcinoma to metastasis. Interestingly, a somatic ERBB2 p.W169∗ mutation was detected in normal breast tissue, but not in DCIS, invasive carcinoma, or metastatic lymph nodes in case 4. In case 5 with ER-positive/PgR-positive/HER2-negative breast cancer, ER-positive cell rates decreased and Ki67-positive cell rates increased during the progression from DCIS to invasive carcinoma. A PIK3CA mutation, but not a PTEN mutation, was identified in DCIS, whereas a PTEN mutation but not a PIK3CA mutation was detected in invasive carcinoma in case 5. Previous studies mentioned the discordance between in situ and invasive areas of the same tumor regarding PIK3CA status, and suggested that PIK3CA gene mutation is more likely to play a role in tumor initiation than in invasive progression [24,25]. Different gene mutations detected in DCIS and invasive carcinoma were also identified in case 6 with ER-positive/PgR-positive/HER2-negative breast cancer: MAP2K4 deletion in DCIS and amplifications of MYC and CDK12 genes in invasive carcinoma. In case 7 with ER-positive/PgR-positive/HER2-negative breast cancer, mutations of TP53 p.T230S and DNMT3A p.R320Q were detected in invasive carcinoma, but no mutations were identified in DCIS. Somatic gene alterations in invasive carcinoma were not detected in cases 3, 8, and 9, although case 3 had a germline pathogenic BRCA2 variant and case 8 had germline gene alterations that were not yet evaluated of clinical significance. In case 9 with ER-positive/PgR-positive/HER2-negative mucinous carcinoma, neither germline nor somatic gene alterations were detected in either normal breast tissue or in invasive carcinoma.
3.4. Pathological characteristics and somatic gene alterations in patients treated with neoadjuvant therapy
Samples taken both before and after neoadjuvant treatment were evaluated in case 10 with ER-positive/HER2-positive breast cancer (Table 6, Table 7). RET p.V906M mutation and amplifications of MDM2, CDK12, ERBB2, SPOP, BRIP1, and CD79B genes were identified in both DCIS and invasive carcinoma before neoadjuvant therapy. However, RET p.V906M mutation and amplifications of SPOP, BRIP1, and CD79B genes were not detected, and APC p.S2766∗ mutation was detected in invasive carcinoma after neoadjuvant treatment. This nonsense mutation of the APC gene might be linked to chemotherapy resistance [26,27]. A somatic BRCA2 p.R1512H mutation was also identified in normal breast tissue after neoadjuvant chemotherapy in case 10, whereas this mutation was not detected in DCIS or in invasive carcinoma after the treatment. Samples before neoadjuvant therapy were not available in cases 11, 12, and 13. PBRM1 mutation and deletions of PIK3R1, CDKN2A, CRLF2, and ZRSR2 genes were detected in invasive carcinoma after neoadjuvant chemotherapy in case 13, a patient with metaplastic breast cancer who died 8 months after operation. Somatic gene alterations were not detected in invasive carcinoma after neoadjuvant chemotherapy in cases 11 and 12. Sequencing analysis was not performed for normal tissue after neoadjuvant therapy in cases 12 and 13 because of low amounts of DNA.
Table 7.
Somatic gene alterations in four patients treated with neoadjuvant therapy.
| No | Tissue samples | Somatic gene alterations |
|||||
|---|---|---|---|---|---|---|---|
| Normal breast tissue |
Ductal carcinoma in situ |
Invasive carcinoma |
|||||
| Gene (VAF) | ECC | Gene (VAF) | TC | Gene (VAF) | TC | ||
| 10 | before NAC | N/A |
RET p.V906Mc (13%) MDM2 amp, CDK12 amp, ERBB2 amp, SPOP amp, BRIP1 amp, CD79B amp |
50% |
RET p.V906Mc (13%) MDM2 amp, CDK12 amp, ERBB2 amp, SPOP amp, BRIP1 amp, CD79B amp |
40% | |
| after NAC | BRCA2 p.R1512Hd (7%) | 30% | – |
APC p.S2766∗ (6%) MDM2 amp, CDK12 amp, ERBB2 amp |
40% | ||
| 11 | after NAC | none | 40% | – | none | 50% | |
| 12 | after NAC | – | – | none | 80% | ||
| 13 | after NAC | – | – |
PBRM1 splice site (8%) PIK3R1 del, CDKN2A del, CRLF2 del, ZRSR2 del |
80% | ||
VAF, variant allele frequency; ECC, ductal epithelial cell content; TC, tumor content; NAC, neoadjuvant chemotherapy; del, deletion; amp, amplification; before NAC, samples from primary tumors before neoadjuvant chemotherapy; after NAC, samples from primary tumors after neoadjuvant chemotherapy; N/A, not applicable; −, not evaluated.
a pathogenic, b likely pathogenic, c uncertain significance, d conflicting interpretations of pathogenicity.
3.5. Gene alterations during breast cancer progression
Overall, somatic gene alterations were detected in at least two regions of normal breast tissue, DCIS, invasive carcinoma, or metastatic lymph nodes in six cases (Fig. 2). Somatic gene mutations of TP53 and PPP2R1A (case 1), ERBB2 (case 4), or BRCA2 (case 10) were present in normal breast tissue. However, neither of these mutations were detected in DCIS nor invasive carcinoma in the same patients. Different somatic gene mutations identified in DCIS and invasive carcinoma were detected in two patients (cases 5 and 6). On the other hand, somatic gene mutations of PTEN and GATA3 (case 2), TP53 (case 4), and RET, SPOP etc. (case 10) present in DCIS were also detected in invasive carcinoma. Immunohistochemical examination of PTEN (case 2), p53 (cases 4 and 7), and MDM2 (case 10) is shown in Supplementary Figures.
Fig. 2.
Gene alterations during breast cancer progression. (A) Changes of gene alterations in five cases in which somatic gene alterations were detected in at least two areas of normal breast tissue, DCIS, invasive carcinoma, or metastatic lymph nodes. (B) Changes of gene alterations in case 10 who was treated with neoadjuvant anti-HER2 therapy and chemotherapy.
4. Discussion
In this study, we demonstrated germline and somatic gene alterations in blood and breast tissues simultaneously obtained from invasive carcinoma, adjacent DCIS, normal breast tissue, and/or metastatic lymph nodes in each patient aged <35 years at diagnosis. Interestingly, somatic gene mutations were also present in non-neoplastic tissue samples in three patients. However, neither of these mutations were detected in DCIS nor invasive carcinoma in the same patients, suggesting that these mutations were not drivers for progression of their breast cancer, and that different subclones carrying other mutated genes might progress to carcinoma. Another possibility is that the mutations present in the non-neoplastic epithelial cells might be present in other subclones of DCIS and/or invasive carcinoma that were not revealed in this study. Danforth indicated that normal breast tissues contain evidence of early breast carcinogenesis including loss of heterozygosity, DNA methylation of tumor suppressor and other genes, and telomere shortening [28]. The presence in normal breast tissues of multiple, genetically distinct abnormal clones that could progress independently and simultaneously, provides a possible explanation for the genetic heterogeneity noted in many breast tumors [28].
Different somatic gene mutations identified in DCIS and invasive carcinoma were detected in two patients. It is suggested that the invasive-specific mutations may have occurred at low frequencies in DCIS prior to invasion or, alternatively, after invasion during the expansion of the invasive tumor mass. Another possibility is that the mutations existing in DCIS might be present in other subclones of invasive carcinoma that were not examined in this study, although this is unlikely because both DCIS and invasive carcinoma were collected from adjacent regions. Synchronous normal breast tissue, DCIS, and invasive carcinomas differ in their repertoire of somatic gene alterations even in the absence of systemic therapy, suggesting the contribution of spatial intratumor genetic heterogeneity [2]. On the other hand, somatic gene mutations present in DCIS were also detected in invasive carcinoma in three cases. Casasent and colleagues used single cell sequencing to demonstrate a multiclonal invasion model, in which one or more clones escape the ducts and migrate into the adjacent tissues to establish invasive carcinomas [29]. Their results showed a direct genomic lineage between the in situ and invasive tumor cell subpopulations, and revealed that most mutations and copy number aberrations evolved within the ducts prior to invasion [29].
Somatic gene alterations of TP53, PIK3CA, GATA3, PTEN, ERBB2, MAP2K4, MDM2, PIK3R1, and CDKN2A that were reported as the significantly mutated genes in primary breast cancer in the study of the Cancer Genome Atlas Network [13] were also identified in cancer tissues analyzed in this study. On the other hand, germline variants including pathogenic variants and gene alterations that were not yet evaluated of clinical significance were also detected in all patients but one in our cohort. Interestingly, all patients except case 9 had past and/or family histories. It is considered that hereditary factors affect tumorigenesis and progression of breast cancer disproportionately in young women compared to tumors occurring in older adults. Recognition of yet unexplained variants as a heritable cause might be important to provide not only a better understanding of the biological characteristics of breast cancer but also optimal care to individual young patients.
The present study has several limitations. First, the size of our cohort was small. However, we do show details of the characteristics, immunohistochemical findings, and gene alterations of each patient. Furthermore, gene alterations in breast tissues simultaneously obtained from normal breast tissue, DCIS, invasive carcinoma, and/or metastatic lymph nodes were examined in each patient. Second, the cancer panel for a targeted amplicon exome sequencing used in this study consists of 160 cancer-related genes, and these 160 genes were selected based on previous reports of general cancers in adults [[16], [17], [18], [19], [20], [21]]. Thus, some genes essential for breast cancer progression especially in young women, both germline, such as BARD1, RAD51C, and RAD51D [30], and somatic alterations, might not be covered. In fact, the number of genes detected as germline and somatic gene alterations in each patient were low, and in one patient none were detected. Whole-exome sequencing is required for more appropriate analysis especially for young patients. Fourth, DNA was extracted from only one region of each DCIS, invasive carcinoma, and/or normal breast tissue. Furthermore, because of lack of appropriate quality and/or quantity of extracted DNA, not all samples were evaluated for sequencing. Examining more than one region of normal breast tissue and carcinomas in each patient is necessary for the detailed analysis for cancer evolution.
5. Conclusions
We report germline and somatic gene alterations in blood and breast tissues obtained from synchronous invasive carcinoma, adjacent DCIS, normal breast tissue, and/or metastatic lymph nodes in patients aged <35 years. Our results show diversity within each individual during breast cancer progression. Heritable causes might be important to provide not only understanding of the biological characteristics of breast cancer but also optimal care to individual young patients.
Declaration of competing interest
None.
Acknowledgements
We thank Miyuki Kasegai, Kozue Mori, Mizuho Kasai for their technical assistance.
Footnotes
Supplementary data to this article can be found online at https://doi.org/10.1016/j.breast.2021.10.011.
Funding
This work was partially supported by Japan Society for the Promotion of Science [KAKENHI grant number 17K10531] from the Ministry of Education, Science, Sports and Culture, Japan.
Appendix A. Supplementary data
The following are the Supplementary data to this article:
Immunohistochemical examination of PTEN in normal breast tissue (a), DCIS (b), and invasive ductal carcinoma (c) in case 2. Positive staining can be observed in normal epithelial cells (a) with a germline PTEN p.E242∗ pathogenic variant, whereas negative staining is observed in cancer cells (b and c) with a somatic PTEN p.E18∗ mutation.
Immunohistochemical examination of p53 in normal breast tissue (a), DCIS (b), invasive ductal carcinoma (c), and a metastatic lymph node (d) in case 4. Nuclear staining can be observed in cancer cells (b, c, and d) with a somatic TP53 p.R213L mutation, whereas negative staining is observed in normal epithelial cells (a).
Immunohistochemical examination of p53 in normal breast tissue (a), DCIS (b), and invasive ductal carcinoma (c) in case 7. Nuclear staining can be observed in cancer cells in invasive ductal carcinoma (c) with a somatic TP53 p.T230S mutation, whereas negative staining is observed in normal epithelial cells (a) and in cancer cells in DCIS (b) without this TP53 gene mutation.
Immunohistochemical examination of MDM2 in DCIS (a) and invasive ductal carcinoma (b) before neoadjuvant chemotherapy, and in normal breast tissue (c) and invasive ductal carcinoma (d) after neoadjuvant chemotherapy in case 10. Nuclear staining can be observed in cancer cells in DCIS (a) and invasive ductal carcinoma (b and d) with MDM2 gene amplification, whereas negative staining is observed in normal epithelial cells (c).
References
- 1.Umar A., Dunn B.K., Greenwald P. Future directions in cancer prevention. Nat Rev Cancer. 2012;12:835–848. doi: 10.1038/nrc3397. [DOI] [PubMed] [Google Scholar]
- 2.Nik-Zainal S., Morganella S. Mutational signatures in breast cancer: the problem at the DNA level. Clin Cancer Res. 2017;23:2617–2629. doi: 10.1158/1078-0432.CCR-16-2810. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Yates L.R., Gerstung M., Knappskog S., Desmedt C., Gundem G., Van Loo P. Subclonal diversification of primary breast cancer revealed by multiregion sequencing. Nat Med. 2015;21:751–759. doi: 10.1038/nm.3886. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Turajlic S., Sottoriva A., Graham T., Swanton C. Resolving genetic heterogeneity in cancer. Nat Rev Genet. 2019;20:404–416. doi: 10.1038/s41576-019-0114-6. [DOI] [PubMed] [Google Scholar]
- 5.Azim H.A., Jr., Partridge A.H. Biology of breast cancer in young women. Breast Cancer Res. 2014;16:427. doi: 10.1186/s13058-014-0427-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Anders C.K., Fan C., Parker J.S., Carey L.A., Blackwell K.L., Klauber-DeMore N. Breast carcinomas arising at a young age: unique biology or a surrogate for aggressive intrinsic subtypes? J Clin Oncol. 2011;29:e18–20. doi: 10.1200/JCO.2010.28.9199. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Collins L.C., Marotti J.D., Gelber S., Cole K., Ruddy K., Kereakoglow S. Pathologic features and molecular phenotype by patient age in a large cohort of young women with breast cancer. Breast Cancer Res Treat. 2012;131:1061–1066. doi: 10.1007/s10549-011-1872-9. [DOI] [PubMed] [Google Scholar]
- 8.Azim H.A., Jr., Michiels S., Bedard P.L., Singhal S.K., Criscitiello C., Ignatiadis M. Elucidating prognosis and biology of breast cancer arising in young women using gene expression profiling. Clin Cancer Res. 2012;18:1341–1351. doi: 10.1158/1078-0432.CCR-11-2599. [DOI] [PubMed] [Google Scholar]
- 9.Gnerlich J.L., Deshpande A.D., Jeffe D.B., Sweet A., White N., Margenthaler J.A. Elevated breast cancer mortality in women younger than age 40 years compared with older women is attributed to poorer survival in early-stage disease. J Am Coll Surg. 2009;208:341–347. doi: 10.1016/j.jamcollsurg.2008.12.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Partridge A.H., Hughes M.E., Warner E.T., Ottesen R.A., Wong Y.N., Edge S.B. Subtype-dependent relationship between young age at diagnosis and breast cancer survival. J Clin Oncol. 2016;34:3308–3314. doi: 10.1200/JCO.2015.65.8013. [DOI] [PubMed] [Google Scholar]
- 11.Chen H.L., Zhou M.Q., Tian W., Meng K.X., He H.F. Effect of age on breast cancer patient prognoses: a population-based study using the SEER 18 database. PLoS One. 2016;11 doi: 10.1371/journal.pone.0165409. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Momozawa Y., Iwasaki Y., Parsons M.T., Kamatani Y., Takahashi A., Tamura C. Germline pathogenic variants of 11 breast cancer genes in 7,051 Japanese patients and 11,241 controls. Nat Commun. 2018;9:4083. doi: 10.1038/s41467-018-06581-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Network C.G.A. Comprehensive molecular portraits of human breast tumours. Nature. 2012;490:61–70. doi: 10.1038/nature11412. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Curtis C., Shah S.P., Chin S.F., Turashvili G., Rueda O.M., Dunning M.J. The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups. Nature. 2012;486:346–352. doi: 10.1038/nature10983. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Bertucci F., Ng C.K.Y., Patsouris A., Droin N., Piscuoglio S., Carbuccia N. Genomic characterization of metastatic breast cancers. Nature. 2019;569:560–564. doi: 10.1038/s41586-019-1056-z. [DOI] [PubMed] [Google Scholar]
- 16.Yuzawa S., Nishihara H., Yamaguchi S., Mohri H., Wang L., Kimura T. Clinical impact of targeted amplicon sequencing for meningioma as a practical clinical-sequencing system. Mod Pathol. 2016;29:708–716. doi: 10.1038/modpathol.2016.81. [DOI] [PubMed] [Google Scholar]
- 17.Bandoh N., Akahane T., Goto T., Kono M., Ichikawa H., Sawada T. Targeted next-generation sequencing of cancer-related genes in thyroid carcinoma: a single institution's experience. Oncol Lett. 2018;16:7278–7286. doi: 10.3892/ol.2018.9538. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Yasukawa S., Kano S., Hatakeyama H., Nakamaru Y., Takagi D., Mizumachi T. Genetic mutation analysis of the malignant transformation of sinonasal inverted papilloma by targeted amplicon sequencing. Int J Clin Oncol. 2018;23:835–843. doi: 10.1007/s10147-018-1296-1. [DOI] [PubMed] [Google Scholar]
- 19.Hayashi H., Tanishima S., Fujii K., Mori R., Okamura Y., Yanagita E. Genomic testing for pancreatic cancer in clinical practice as real-world evidence. Pancreatology. 2018;18:647–654. doi: 10.1016/j.pan.2018.07.006. [DOI] [PubMed] [Google Scholar]
- 20.Hayashi H., Tanishima S., Fujii K., Mori R., Okada C., Yanagita E. Clinical impact of a cancer genomic profiling test using an in-house comprehensive targeted sequencing system. Cancer Sci. 2020 doi: 10.1111/cas.14608. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Hagio K., Amano T., Hayashi H., Takeshita T., Oshino T., Kikuchi J. Impact of clinical targeted sequencing on endocrine responsiveness in estrogen receptor-positive, HER2-negative metastatic breast cancer. Sci Rep. 2021;11:8109. doi: 10.1038/s41598-021-87645-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Kalia S.S., Adelman K., Bale S.J., Chung W.K., Eng C., Evans J.P. Recommendations for reporting of secondary findings in clinical exome and genome sequencing, 2016 update (ACMG SF v2.0): a policy statement of the American College of Medical Genetics and Genomics. Genet Med. 2017;19:249–255. doi: 10.1038/gim.2016.190. [DOI] [PubMed] [Google Scholar]
- 23.Landrum M.J., Lee J.M., Benson M., Brown G., Chao C., Chitipiralla S. ClinVar: public archive of interpretations of clinically relevant variants. Nucleic Acids Res. 2016;44:D862–D868. doi: 10.1093/nar/gkv1222. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Miron A., Varadi M., Carrasco D., Li H., Luongo L., Kim H.J. PIK3CA mutations in in situ and invasive breast carcinomas. Cancer Res. 2010;70:5674–5678. doi: 10.1158/0008-5472.CAN-08-2660. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Hernandez L., Wilkerson P.M., Lambros M.B., Campion-Flora A., Rodrigues D.N., Gauthier A. Genomic and mutational profiling of ductal carcinomas in situ and matched adjacent invasive breast cancers reveals intra-tumour genetic heterogeneity and clonal selection. J Pathol. 2012;227:42–52. doi: 10.1002/path.3990. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.VanKlompenberg M.K., Leyden E., Arnason A.H., Zhang J.T., Stefanski C.D., Prosperi J.R. APC loss in breast cancer leads to doxorubicin resistance via STAT3 activation. Oncotarget. 2017;8:102868–102879. doi: 10.18632/oncotarget.22263. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Stefanski C.D., Keffler K., McClintock S., Milac L., Prosperi J.R. APC loss affects DNA damage repair causing doxorubicin resistance in breast cancer cells. Neoplasia. 2019;21:1143–1150. doi: 10.1016/j.neo.2019.09.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Danforth D.N., Jr. Genomic changes in normal breast tissue in women at normal risk or at high risk for breast cancer. Breast Cancer. 2016;10:109–146. doi: 10.4137/BCBCR.S39384. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Casasent A.K., Schalck A., Gao R., Sei E., Long A., Pangburn W. Multiclonal invasion in breast tumors identified by topographic single cell sequencing. Cell. 2018;172:205–217 e12. doi: 10.1016/j.cell.2017.12.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Wong E.S.Y., Shekar S., Met-Domestici M., Chan C., Sze M., Yap Y.S. Inherited breast cancer predisposition in Asians: multigene panel testing outcomes from Singapore. NPJ Genom Med. 2016;1:15003. doi: 10.1038/npjgenmed.2015.3. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Immunohistochemical examination of PTEN in normal breast tissue (a), DCIS (b), and invasive ductal carcinoma (c) in case 2. Positive staining can be observed in normal epithelial cells (a) with a germline PTEN p.E242∗ pathogenic variant, whereas negative staining is observed in cancer cells (b and c) with a somatic PTEN p.E18∗ mutation.
Immunohistochemical examination of p53 in normal breast tissue (a), DCIS (b), invasive ductal carcinoma (c), and a metastatic lymph node (d) in case 4. Nuclear staining can be observed in cancer cells (b, c, and d) with a somatic TP53 p.R213L mutation, whereas negative staining is observed in normal epithelial cells (a).
Immunohistochemical examination of p53 in normal breast tissue (a), DCIS (b), and invasive ductal carcinoma (c) in case 7. Nuclear staining can be observed in cancer cells in invasive ductal carcinoma (c) with a somatic TP53 p.T230S mutation, whereas negative staining is observed in normal epithelial cells (a) and in cancer cells in DCIS (b) without this TP53 gene mutation.
Immunohistochemical examination of MDM2 in DCIS (a) and invasive ductal carcinoma (b) before neoadjuvant chemotherapy, and in normal breast tissue (c) and invasive ductal carcinoma (d) after neoadjuvant chemotherapy in case 10. Nuclear staining can be observed in cancer cells in DCIS (a) and invasive ductal carcinoma (b and d) with MDM2 gene amplification, whereas negative staining is observed in normal epithelial cells (c).