Prognostic Significance Of Breast Cancer Subtypes Among Chinese Women
Chinese women with the triple-negative subtype were younger in age at diagnosis compared with women who had other subtypes of breast cancer, which is similar to findings reported in Western populations . The triple-negative subtype was associated with larger tumor size, higher histologic grade, later TNM stage, and higher prevalence in IDC than in ILC. These clinicopathologic characteristics have been consistently observed in both Western and Chinese populations , suggesting that the triple-negative subtype is an aggressive subtype of breast cancer across all ethnicities. Multivariate analysis confirmed that the triple-negative subtype is an independent prognostic factor for the progression and survival of breast cancer. Most triple-negative cancers defined by IHC present a basal-like subtype profile defined by cDNA microarray, but they do not completely correlate in about 25% of cases . Other molecular subsets may be included in triple-negative cancers. Further epidemiological and biomarker studies for this important subtype in Chinese women is necessary.
Analysis Of Tumor Mutation Burden
Tumor mutation burden was defined as the total amount of somatic gene coding errors, base substitutions, insertions or deletions detected per million bases. TMB data were downloaded from the TCGA database through the GDC tool. We classified the samples of each subtype into low-and high-TMB groups according to the median data. Then, we merged the TMB data with corresponding survival information via the ID number of the samples. KaplanMeier analysis was conducted to compare the survival difference between the low-and high-TMB groups of each subtype, and the p value of the log-rank test was calculated.
The Intrinsic Subtypes Within Cher2+ Disease
The four BC molecular subtypes, also called intrinsic subtypes, have shown different outcome patterns and response to therapy . Clinically HER2+ BC has been considered a single tumor entity for a long time however, in 2012, The Cancer Genome Atlas project demonstrated that not all cHER2+ BC had the same genomic profile. More precisely, only 50 % of cHER2+ tumors were HER2-E, while the other half were Luminal A or B, with high expression of typical luminal genes such as ESR1, GATA3 and BCL2, among others . More recent studies have revealed the presence of cHER2+ Basal-like tumors, especially in HR-negative disease . Among the different subtypes within cHER2+ disease, the HER2-E is characterized by the highest levels of ERBB2 mRNA, phosphorylated HER2, total HER2 protein, pEGFR and EGFR protein, suggesting that this group has the highest activation of the HER2 signaling pathway .
In summary, cHER2+ tumors comprises all of the 4 BCE intrinsic subtypes, with the HER2-E being the most frequent , followed by Luminal B , Luminal A and Basal-like . Yet, the distribution seems to be heavily influenced by HR status, with HER2-E subtype representing 30 % of molecular subtypes within HR+/cHER2+ BC and 75 % in HR-negative/cHER2+ tumors . Although related, the concordance rate between the pathology-based subtypes and the intrinsic subtypes is moderate .
Maurizio Previati, … Stefano Volinia, in, 2013
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Screening And Identification Of Key Common And Specific Genes And Their Prognostic Roles In Different Molecular Subtypes Of Breast Cancer
- 1Department of Breast and Thyroid Surgery, Southwest Hospital, Army Medical University, Chongqing, China
- 2Institute of Pathology and Southwest Cancer Center, Key Laboratory of the Ministry of Education, Southwest Hospital, Army Medical University, Chongqing, China
- 3Institute of Toxicology, College of Preventive Medicine, Army Medical University, Chongqing, China
Identification Of Driver Genes In Breast Cancer Subtypes
To further understand the molecular features of different subtypes, we used the DriverDBv3 online database to predict the driver genes of breast cancer samples in the TCGA database. To increase the accuracy of our results, we used more than seven algorithms to simultaneously predict driver genes and obtained 11 driver genes, namely ERBB2, AKT1, PIK3CA, PIK3R1, PTEN, TP53, CDH1, GATA3, MAP2K4, CTCF, and FOXA1. We analyzed the effect of driver gene expression in the different subtypes and found that the expression of PIK3CA, PIK3R1, and PTEN was significantly lower in tumor samples than in normal samples . ERBB2, GATA3, PIK3CA, MAP2K4, and other driver genes are either overexpressed considerably or expressed at low levels in specific subtypes, which indicates that these genes have essential significance in the formation and progression of tumors in these subtypes and may be used as subtype-determining markers and breast cancer treatment targets.
Figure 4. Analysis of the driver genes in different breast cancer subtypes. The expression levels of eleven driver genes in each subtype. The waterfall chart shows the frequency mutations of the driver genes in each subtype. KaplanMeier survival curve of the driver genes with gene mutations. Red indicates the gene alteration group, and blue indicates the non-alteration group.
Distribution Of Molecular Subtypes Of Breast Cancer In Chinese Women
The prevalence of breast cancer subtypes appears to differ among different races or ethnicities. It has been well documented that the triple-negative subtype is most common among young African-American patients, while luminal A is most common among postmenopausal white women . The increased risk for the triple-negative subtype in African-American women may due to parity and younger age at first full-term pregnancy, multiple live births without breastfeeding, use of medications to suppress lactation , and intrinsic genetic variables, such as higher p53 expression and particularly high prevalence of founder mutations in BRCA1 or BRCA2 gene in young African-American women . In our study population, women with triple-negative breast cancer more frequently reported a family history of breast cancer than did women with other subtypes. This suggests that genetic factors may play a more important role in this molecular subtype of breast cancer. Since BRCA mutations in Chinese women are uncommon other genetic contributors to the triple-negative subtype in Chinese women need to be investigated.
Table 4 Distribution of breast cancer subtypes in different ethnicities and in different geographical areas of China, %
Screening And Validation Of The Key Common And Specific Genes From The Degs
To analyze the crucial common and specific genes in the subtypes, we first validated the potential DEGs using the METABRIC database and bc-GenExMiner v4.5. The DEGs with consistent results in the different databases were retained. After verification, four key common DEGs among the subtypes were identified: NEIL3, CDC25C, NEK2 and HCN2, and their expression were significantly upregulated in all five subtypes. The specific DEGs were 61 genes for Basal-like subtype, 34 genes for Her2 subtype, two genes for LumA subtype, 36 genes for LumB subtype, and two genes for Normal-like subtype . To facilitate further analysis, we further selected the key specific DEGs for each subtype. As just a few validated DEGs were found in the LumA and Normal-like subtypes, these specific DEGs were considered to be the key genes by default. There were many specific DEGs in the Basal-like, Her2 and LumB subtypes, and the top 10 were selected as the key specific DEG for each subtype by combining the specific GO and KEGG enrichment results and the priority of the changed expression. The selected key specific genes were MISP and SMIM22 for LumA subtype, IDH1–AS1 and TMEM233 for Normal-like subtype, MCM10, HPDL, SOX11, PLK1, BUB1, DYNLRB2, OGN, COL4A6, AGTR1, and ADRB2 for Basal-like subtype, SPOCD1, IL21R, JPH3, SAMD11, IFI30, ATRNL1, TNNI3K, PI15, FAM189A2, and MYZAP for Her2 subtype, and CNTD2, NEURL1, SYCE3, STAC2, PPP1R1A, HRCT1, AKR1C2, IL6, FREM1, and HOXA4 for LumB subtype.
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Molecular Subgrouping Valid In Clinical Use
Most of molecular subgrouping studies were performed on non-specific types of ductal carcinoma and is well known, this histological group contains non-specific tumor types. Therefore, efforts aiming to separate this group of heterogeneous group into subgroups seem to be meaningful. Molecular subgrouping can be provided by using a few immunohistochemical markers. A panel including ER, PR, HER2, Ki-67, epidermal growth factor receptor and basal cytokeratins can be used to distinguish between luminal, HER2 and triple negative tumors. In fact, there is no consensus on the determinants defining basal tumors, nevertheless it is considered that the use of EGFR and CK5 / 6 can aid in identification of this subgroup and predict prognosis .
Major molecular subtypes According to gene expression profiles in breast cancer are summarized in Table 2 .
Stage Iii: Generating A Consensus Approach To Personalized Breast Cancer Treatment
As discussed in the previous sections, one important challenge for the development of personalized drug repurposing approaches to anticancer therapy lies in the fact that there is a large molecular and phenotypic heterogeneity between cancer patientsand even molecular heterogeneity among the different cell populations of a single patient tumor. This high variability imposes constrains both at the purely technical and the logistical dimensions of therapeutic designs. The use of large-scale databases spanning all over different breast tumors, such as the ones in large research consortia such as The Cancer Genome Atlasnow Genomic Data Commons and METABRIC , by means of integrated computational analyses has made possible to discern the commonalities and differences in the expression traits, the phenotypes, and survival for thousands of cancer patients. This knowledge is making possible in turn to develop dynamic maps of tumor features and vulnerabilities by classes.
23 PAK1-mediated pathways were identified, which can be useful since a number of PAK1 inhibitors are susceptible of being repurposed and their actual mechanisms of actione.g., inducing PUMA-mediated cell death and p21-mediated cell cycle arrestare currently starting to be understood .
Lars J. Grimm, Maciej A. Mazurowski, in, 2020
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How Your Molecular Subtype Helps Determine Your Treatment Plan
Breast cancer treatment depends on a variety of factors, including the type of breast cancer, the tumors size, its spread, any pre-existing conditions and your treatment preferences. Molecular subtype is taken into account as well, because a cancer fueled by specific hormones or other proteins may have better outcomes when treated with targeted options, which may include hormone therapy, which is also referred to as endocrine therapy.
Some patients, particularly those at high risk for infiltrating breast cancer, may undergo adjuvant chemotherapy after the initial treatment, which is often surgery. Adjuvant means its given in addition to the primary treatment.
Below are some of the most common ways of treating each molecular type of breast cancer.
Luminal A Breast Cancer
Luminal A tumors, the most common molecular type, tend to grow at a slower rate than other cancer types. These are called HR-positive because theyre defined by their hormone receptors, specifically as estrogen receptor -positive and/or progesterone receptor -positive. A cancer that is ER- and/or PR-positive grows from estrogen and/or progesterone. Drugs that lower the amount of these hormones tend to be useful in treating this type of breast cancer.
Luminal A cancers are also described as HER2-negative. HER2 stands for human epidermal growth factor receptor-2, which is a protein normally produced by the body. From a gene perspective, HER2 plays an important role in cell growth and repair in healthy breast cells. A breast cancer patient with a normal amount of the HER2 protein has HER2-negative cancer.
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Test Of The Robustness Of Subtypes To Alternative Method Of Derivation
The six methods employed in the derivation of the BCCS subtypes produced subtypes that potentially varied in the number of subtypes and may have disagreed in classifications . The consensus subtyping method aims to cluster a pair of samples only when multiple systems using different methods clustered them together, and in this sense generates clusters that are less dependent on subtyping method than a single system. To test the degree of robustness of the BCCS subtypes, we repeated the derivation for the ER+ subtypes, the most complex case, using an alternative set of subtyping systems . The alternative six methods produced systems with 6, 3, 4, 5, 4, and 6 subtypes. However, application of the consensus subtyping method resulted in four subtypes that reproduced PCS14 in METABRIC ER+ with accuracy=0.92 and kappa=0.90, providing evidence that the BCCS classifications are robust to changes in the clustering method.
Go Analysis Of The Degs
The functions of the DEGs in all breast cancers and each subtype breast cancer were predicted using GO analysis. Figure 3 shows the top 10 enriched GO entries of all breast cancers and each subtype breast cancer, and the detailed results of all enriched GO entries are shown in Supplementary Tables S2S7. Comparative analysis of the subtypes GO entries showed that a total of 123 GO entries were enriched for the DEGs in the basal-like subtype, and 61 of these GO entries were specifically enriched which were mainly concentrated in mitotic,cell cycle, and oxidoreductase activity. A total of 39 GO entries were enriched for the DEGs in the Her2 subtype, and 10 of these GO entries were specifically enriched which were mainly concentrated in nucleosome,cell differentiation and RAGE receptor binding. A total of six GO entries were enriched for the DEGs in the LumA subtype, whereas there was no specifically enriched GO entry. A total of 50 GO entries were enriched for the DEGs in the LumB subtype, and 13 of these 50 GO entries were specifically enriched that were mainly concentrated in kidney development and chloride channel complex. A total of 86 GO entries were enriched for the DEGs in the normal-like subtype, and 41 of these GO entries were specifically enriched that were mainly concentrated in mitotic DNA damage checkpoint, and DNA damage response.
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Ethics Approval And Consent To Participate
The study was approved by the ethics committee of the University of Heidelberg and in accordance with the Declaration of Helsinki. Because the study was deemed as without risk, including only anonymized analysis of routinely collected data, the ethics committee of the University of Heidelberg did not request approval for consent.
Differences In Immune Cell Infiltration Of Different Subtypes
A high number of mutations in breast cancer samples indicates inferior genome stability, and many mutations in tumor tissues can induce the production of new antigens. Simultaneously, patients with specific gene mutations are suitable candidates for immunotherapy, such as patients with BRCA1/2 gene mutations . Consequently, to study the difference in immune cell infiltration among breast cancer subtypes and identify personalized immunotherapy for patients. Here, we used CIBERSORT to analyze the differences in the infiltration of 22 immune cell types in each subtype of tumor tissues. In the more malignant tumor tissues of the basal-like and HER2 subtypes, the infiltration level of M1 macrophages, activated memory CD4 T cells, and CD8 T cells was significantly higher. In contrast, the infiltration levels of M2 macrophages, naive B cells, and resting memory CD4 T cells were substantially lower . Then, we used an MCP counter to analyze the fibroblast infiltration levels in each subtype , among which the infiltration levels of fibroblasts in the lumB and basal-like subtypes were low. Correlation analysis between immune cells and fibroblasts showed that T cells and fibroblast levels were negatively correlated .
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Relationships Between Bccs Subtypes And Her2 Status
The intrinsic subtype system defined the Her2-enriched subtype to represent all HER2+ tumors. In contrast, HER2+ tumors were found in multiple BCCS subtypes in METABRIC and BRCA . In METABRIC ER+ the distribution of tumors with HER2 gain was: PCS1 , PCS2 , PCS3 , PCS4 . Previously, the enrichment levels in biological pathways between the BCCS subtypes were analyzed with GSEA. To test the possible dependence of these features on HER2 status we repeated GSEA analysis separately for HER2+ and HER2 tumors in METABRIC for those subtypes with a sufficient number of tumors of each type, specifically, PCS13. Results showed that for most gene sets, the degree of enrichment between subtypes was the same in HER2+ and HER2 tumors. For example, HER2+ tumors in PCS3 were enriched in IFN- response compared to HER2+ tumors in PCS2, and HER2+ PCS2 tumors were enriched in estrogen response compared to HER2+ PCS3 tumors. The same relationships held for HER2 PCS2 and PCS3 tumors. Thus, the BCCS subtypes articulated heterogeneity in HER2+ tumors and HER2 tumors alike.
While relationships between BCCS subtypes did not significantly vary by HER2 status, features of samples within a subtype did vary by HER2 status. Application of GSEA showed that within each of PCS1, PCS2 and PCS3, HER2+ tumors were enriched for, e.g., MYC targets, and mTOR signaling in comparison to HER2 tumors, providing further evidence that HER2 status and BCCS provide independent information on tumor biology.
Description Of The Population
In all, 909 cases were included. Mean age at diagnosis was 72.5 years . Only 12.5 % were < 60 years and 58.9 % were 6079 years. Most tumours were 25 cm in diameter , but for 29.5 %, tumour size was unknown or uncertain. At the end of the observation period, 359 had died of breast cancer, 390 of other causes and 160 were still alive. Median follow-up was 6.4 years . See Table 2 for patient and tumour data.
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Gene Mutations Among The Breast Cancer Subtypes
To assess the alteration of genes among different subtypes in breast cancer, we analyzed the mutations in each subtype, including gene mutation and CNV. In summary, these mutations were classified according to different categories, in which missense mutations accounted for the largest fraction . The lumA subtype had the most missense mutations, and the lumB subtype had the lowest . The CNV analysis across the five subtypes revealed that the highest levels of amplification and deletion were detected in the basal-like and lumB subtypes . Comparison across the five subtypes revealed that they all had increased C > T transversions . The C > G transversions were markedly higher in the HER2 subtype than in other subtypes. The basal-like subtype had more T > C transversions than the other subtypes. We further performed mutation analysis on the subtype-specific genes in which mRNA expression was significantly different in each subtype. The results showed that the mutation of these genes, namely ZNF695, RBPMS1-AS1, OIP5, and PYY, correlated with their RNA expression levels .