The mRNA expression of SCD5 in breast cancer
To explore the roles of SCD5 in human cancers, we used the data samples from Oncomine, GEO and UALCAN to investigate altered SCD5 expression in normal tissue relative to cancer tissue. The analysis of multiple datasets showed that the SCD5 expression in human cancers was significantly down-regulated compared with their normal counterparts (Table S1, Figure 1A-B). In addition, we also analyzed the expression of SCD5 in breast cancer patients with different molecular and clinicopathological characteristics. The results revealed that SCD5 expression was reduced in high histological grade and late stage breast cancer (Figure 1C-E). According to the expression status of ER, PR and HER2, the primary breast tumor was divided into different subtypes with different outcomes and response to treatment20. Two microarray datasets (GSE22226 and GSE20271) were downloaded from GEO to explore the distribution of SCD5 expression between TNBC and other breast cancer subtypes. Compared to other breast cancer subtypes, elevated SCD5 expression was observed in TNBC (log2[Fold change]>0.5, p<0.05, Figure 2A-C). Due to the high intratumoral heterogeneity of breast cancer, only detecting the expression of ER, PR and HER2 is difficult to overcome the differences between patients and achieve precision medicine. Therefore, Parker et al. derived a minimal gene set (PAM50) to classify intrinsic subtypes of breast cancer in 200921. According to differences in gene expression, breast cancer can be divided into five molecular subtypes (luminal A, luminal B, HER2 enriched, basal-like and normal-like). We further investigated the varied mRNA expression of SCD5 among five molecular subtypes in two GEO cohorts (GSE25065 and GSE22358). Basal-like breast cancer had the highest SCD5 expression compared to patients with other breast cancer subtypes, however, the SCD5 expression in HER2 enriched breast cancer was the lowest among five molecular subtypes (p<0.05, Figure 2D-E). Taken together, these findings indicated that reduced SCD5 expression was related to more aggressive breast cancer phenotypes, such as high histological grade, late stage and HER2 overexpressed breast cancer.
Correlation analysis between mRNA expression of SCD5 and prognostic value
We further explored the correlation between the gene expression and survival in breast cancer to better understand the clinical significance of SCD5. The Kaplan-Meier plotter, GOBO and Oncomine dataset (Loi3 breast dataset) were performed to carry out the survival analysis of breast cancer patients. As shown in Figure 3A, high expression of SCD5 was related to decreased risk of relapse (HR=0.68 95%CI=0.61 to 0.76, p=5.5e-12). Among patients with TNBC, high SCD5 expression cohort had a significantly 43% decreased risk of relapse compared with low SCD5 expression cohort (Figure 3C, HR=0.57 95%CI=0.44 to 0.74, p=1.3e-05). We also observed that SCD5 expression was higher in non-recurrence group than that in recurrence group (Figure 3E, p=0.01). Besides, varied SCD5 expression was correlated to DMFS in TNBC (Figure 3C, HR=0.52 95%CI=0.31 to 0.89, p=0.015), which was not observed in either total breast tumors or other breast cancer subtypes (Figure 3B and Figure A1, p>0.05). The multivariate analysis showed that in patients with PAM50_basal-like breast tumors, lower SCD5 expression was related to higher risk of relapse (Figure 3F, p<0.05). SCD5 expression was positively correlated to survival, especially in TNBC breast cancer patients.
Relationship between mRNA expression of SCD5 and pathological response to neoadjuvant chemotherapy
HER2/ERBB2 (erb-b2 receptor tyrosine kinase 2), a member of the epidermal growth factor receptor family, is amplified/overexpressed in 15 to 20% of breast cancers and associated with a poor prognosis.22 Some correlative studies of breast cancer indicated that the overexpression/amplification of HER2/ERBB2 was associated with a significant benefit from paclitaxel/doxorubicin.23-26 Thus, patients with HER2-negative might benefit relatively less from NACT. Besides, there is still no clinically useful test for prediction of response or survival following chemotherapy for breast cancer. Thus, finding new biomarkers to predict the response of NACT is imperative. Previous study showed that the expression of SCD5 varied between pCR cohort and non-pCR cohort14. In this article, we have already found that the SCD5 expression in triple-negative breast cancer was higher than that in other breast cancer subtypes using public datasets. Then, we further explored the relationship between SCD5 expression and HER2/ERBB2 expression in Oncomine (Gluck breast cancer) and GEO (GSE20194) datasets. As shown in Figure A3, SCD5 expression was negatively correlated HER2/ERBB2 expression (p < 0.05). Thus, we speculated that high SCD5 expression characteristic was associated with unfavorable response to chemotherapy in breast cancer. Therefore, we performed microarray datasets downloaded from GEO (GSE20194, GSE20271 and GSE25055) and Oncomine (Garnett cell line) to further define the value of SCD5 in curative effect assessment of anthracycline/taxane-based NACT for breast cancer. Analysis results showed that SCD5 was differentially expressed between responders and non-responders. The SCD5 exhibited a significant low expression in responders in comparison to non-responders (Figure 4A-B,p<0.05). We also used TNBC samples from GSE20271 datasets to analyze the pathological response-related differentially expressed genes. The volcano plot and heat map showed that SCD5 expression was significantly up-regulated in non-pCR group compared with pCR group (Figure A2). Besides, we found that the fold change of differential SCD5 expression in TNBC was higher than that in total tumors. Furthermore, receiver operating characteristic curve (ROC curve) analysis indicated that SCD5 could be a good predictor of pCR in patients with breast cancer, especially in TNBC (Figure 4C-D, Table 1, p<0.05). In GEO dataset (GSE25055), patients were divided to chemosensitive and chemo-resistant groups according to different pathological responses to taxane-anthracycline based NACT. The SCD5 expression was significantly reduced in chemosensitive group compared with chemo-resistant group (p=0.001, log2 [Fold change] =-0.57). Figure 4F showed that in different cancer cell lines, SCD5 exhibited a high expression in paclitaxel resistant group compared to paclitaxel sensitive group (p=0.05).
Table 1
ROC analysis of SCD5 in pretreatment tumor biopsy samples for predicting pCR
GEO datasets
|
No. of patients
|
AUC
|
P value
|
95% CI
|
Total
|
No. of pCR
|
No. of non-pCR
|
|
|
GSE20194(Total tumors)
|
278
|
56
|
222
|
0.6123
|
0.0094
|
0.5317 to 0.6929
|
GSE20194(TNBC tumors)
|
71
|
25
|
46
|
0.6817
|
0.0119
|
0.5496 to 0.8139
|
GSE20271(Total tumors)
|
178
|
54
|
124
|
0.6441
|
0.0023
|
0.5612 to 0.7271
|
GSE20271(TNBC tumors)
|
59
|
27
|
32
|
0.8368
|
<0.0001
|
0.7329 to 0.9407
|
Potential pathways influenced by SCD5
In the previous section, we mentioned that the SCD5 expression was down-regulated in breast cancer compared to normal breast tissue and was negatively correlated to ERBB2/HER2 expression (p<0.05). Besides, we also found that the compared with wild type, SCD5 expression was down-regulated in several oncogene/tumor suppression genes mutation type (Figure A4) such as KRAS (Kirsten Rat Sarcoma Viral Oncogene Homolog), BRAF (B-Raf proto-oncogene, serine/threonine kinase and CDKN2A (cyclin dependent kinase inhibitor 2A). Therefore, we speculated that SCD5 might play a role in inhibiting the development and progression of tumor cells. KEGG pathway database and Metascape database were used to further explore the potential SCD5 regulatory mechanisms. Analysis of KEGG pathway showed that besides fatty acid metabolic pathway, SCD5 was also involved in peroxisome proliferator-activated receptor (PPAR) and AMP-activated protein kinase (AMPK) signaling pathways (Table 2), which were related to lipid metabolism as well as the inhibition of the multiplication of tumor cell.27-30 In addition, AMPK was also closely involved in cancer drug resistance.31
Table 2
Pathway
|
Description
|
p value
|
hsa01040
|
Biosynthesis of unsaturated fatty acids
|
0.003
|
hsa01212
|
Fatty acid metabolism
|
0.007
|
hsa03320
|
PPAR signaling pathway
|
0.009
|
hsa04152
|
AMPK signaling pathway
|
0.01
|
To further study the possible molecular functions and biological networks of SCD5, two GEO cohorts samples (GSE25055 and GSE25065) were divided into two groups according to high SCD5 expression (top 20%) and low SCD5 expression (bottom 20%). A total of 1923 genes (1315 down-regulated and 608 up-regulated) that had a ∣log2(fold change) ∣≥ 1 and a p-value < 0.05 were considered significantly differentially expressed. Biological annotations and functional enrichment of overlapped DEGs were performed by using Metascape database. The results of GO analysis (Figure 5) showed that the 608 SCD5-related DEGs (up-regulated in breast cancer with high SCD5 expression) were involved in negative regulation of cell cycle (the most significant biological process). In addition, these DEGs were also involved in cell division, DNA repair and so on. SCD5, by and large, might act as a tumor suppression gene and negatively regulate cancer cell growth and proliferation in breast cancer.
In order to further understand the role of SCD5 in cell cycle, we explored correlations between SCD5 expression and several cell cycle regulators using dataset from Oncomine (Hatzis Breast). Most of the known cyclin-dependent kinases (CDKs) could regulate cell cycle progression. There are at least nine isoforms of CDKs in animal cells, among which four isoforms (CDK1-4) are directly involved in the regulation of cell cycle. In mammalian cells, CDK1 interacts with cyclin to drive cell cycle progression. Another isoform, CDK7, is indirectly involved in the activation of cyclin dependent kinase activated kinase.32 Analyses revealed that SCD5 expression was negatively correlated with multiple cell cycle regulators (Table S2).