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Determining breast cancer histological grade from RNA-sequencing data.

Wang M, Klevebring D, Lindberg J, Czene K, Grönberg H, Rantalainen M - Breast Cancer Res. (2016)

Bottom Line: However, grade 2 is associated with an intermediate risk of recurrence, and carries limited information for clinical decision-making.Differentially expressed genes and isoforms associated with HGs were analysed using linear models.We identified a large number of novel genes and isoforms associated with HG.

View Article: PubMed Central - PubMed

Affiliation: Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels Vag 12A, Stockholm, 171 77, Sweden.

ABSTRACT

Background: The histologic grade (HG) of breast cancer is an established prognostic factor. The grade is usually reported on a scale ranging from 1 to 3, where grade 3 tumours are the most aggressive. However, grade 2 is associated with an intermediate risk of recurrence, and carries limited information for clinical decision-making. Patients classified as grade 2 are at risk of both under- and over-treatment.

Methods: RNA-sequencing analysis was conducted in a cohort of 275 women diagnosed with invasive breast cancer. Multivariate prediction models were developed to classify tumours into high and low transcriptomic grade (TG) based on gene- and isoform-level expression data from RNA-sequencing. HG2 tumours were reclassified according to the prediction model and a recurrence-free survival analysis was performed by the multivariate Cox proportional hazards regression model to assess to what extent the TG model could be used to stratify patients. The prediction model was validated in N=487 breast cancer cases from the The Cancer Genome Atlas (TCGA) data set. Differentially expressed genes and isoforms associated with HGs were analysed using linear models.

Results: The classification of grade 1 and grade 3 tumours based on RNA-sequencing data achieved high accuracy (area under the receiver operating characteristic curve = 0.97). The association between recurrence-free survival rate and HGs was confirmed in the study population (hazard ratio of grade 3 versus 1 was 2.62 with 95 % confidence interval = 1.04-6.61). The TG model enabled us to reclassify grade 2 tumours as high TG and low TG gene or isoform grade. The risk of recurrence in the high TG group of grade 2 tumours was higher than in low TG group (hazard ratio = 2.43, 95 % confidence interval = 1.13-5.20). We found 8200 genes and 13,809 isoforms that were differentially expressed between HG1 and HG3 breast cancer tumours.

Conclusions: Gene- and isoform-level expression data from RNA-sequencing could be utilised to differentiate HG1 and HG3 tumours with high accuracy. We identified a large number of novel genes and isoforms associated with HG. Grade 2 tumours could be reclassified as high and low TG, which has the potential to reduce over- and under-treatment if implemented clinically.

No MeSH data available.


Related in: MedlinePlus

DE analysis. a Venn diagram of DE genes between HGs. b Venn diagram of DE isoforms. c Overlaps of DE genes and isoforms between HG1 and HG3. d Top ten enriched pathways of DE genes. Count is the number of genes found in each pathway. DE differential expression or differentially expressed, FDR false discovery rate, HG histologic grade, p.adjust Benjamini and Hochberg FDR corrected p value of the overrepresentation test.
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Fig3: DE analysis. a Venn diagram of DE genes between HGs. b Venn diagram of DE isoforms. c Overlaps of DE genes and isoforms between HG1 and HG3. d Top ten enriched pathways of DE genes. Count is the number of genes found in each pathway. DE differential expression or differentially expressed, FDR false discovery rate, HG histologic grade, p.adjust Benjamini and Hochberg FDR corrected p value of the overrepresentation test.

Mentions: In the Clinseq data set, 8200 genes and 13,809 isoforms were found to be DE (FDR < 0.05) between HG1 and HG3 tumours, while there were few DE genes detected between HG1 and HG2 patients (Fig. 3a, b). If tumour size and lymph node status were adjusted, there were 7928 genes and 13,059 DE isoforms. In 3919 DE genes, the average expression level in HG3 was higher than that for HG1. In contrast, the average expression level in HG1 was higher than for HG3 in the other 4009 genes.Fig. 3


Determining breast cancer histological grade from RNA-sequencing data.

Wang M, Klevebring D, Lindberg J, Czene K, Grönberg H, Rantalainen M - Breast Cancer Res. (2016)

DE analysis. a Venn diagram of DE genes between HGs. b Venn diagram of DE isoforms. c Overlaps of DE genes and isoforms between HG1 and HG3. d Top ten enriched pathways of DE genes. Count is the number of genes found in each pathway. DE differential expression or differentially expressed, FDR false discovery rate, HG histologic grade, p.adjust Benjamini and Hochberg FDR corrected p value of the overrepresentation test.
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4862203&req=5

Fig3: DE analysis. a Venn diagram of DE genes between HGs. b Venn diagram of DE isoforms. c Overlaps of DE genes and isoforms between HG1 and HG3. d Top ten enriched pathways of DE genes. Count is the number of genes found in each pathway. DE differential expression or differentially expressed, FDR false discovery rate, HG histologic grade, p.adjust Benjamini and Hochberg FDR corrected p value of the overrepresentation test.
Mentions: In the Clinseq data set, 8200 genes and 13,809 isoforms were found to be DE (FDR < 0.05) between HG1 and HG3 tumours, while there were few DE genes detected between HG1 and HG2 patients (Fig. 3a, b). If tumour size and lymph node status were adjusted, there were 7928 genes and 13,059 DE isoforms. In 3919 DE genes, the average expression level in HG3 was higher than that for HG1. In contrast, the average expression level in HG1 was higher than for HG3 in the other 4009 genes.Fig. 3

Bottom Line: However, grade 2 is associated with an intermediate risk of recurrence, and carries limited information for clinical decision-making.Differentially expressed genes and isoforms associated with HGs were analysed using linear models.We identified a large number of novel genes and isoforms associated with HG.

View Article: PubMed Central - PubMed

Affiliation: Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels Vag 12A, Stockholm, 171 77, Sweden.

ABSTRACT

Background: The histologic grade (HG) of breast cancer is an established prognostic factor. The grade is usually reported on a scale ranging from 1 to 3, where grade 3 tumours are the most aggressive. However, grade 2 is associated with an intermediate risk of recurrence, and carries limited information for clinical decision-making. Patients classified as grade 2 are at risk of both under- and over-treatment.

Methods: RNA-sequencing analysis was conducted in a cohort of 275 women diagnosed with invasive breast cancer. Multivariate prediction models were developed to classify tumours into high and low transcriptomic grade (TG) based on gene- and isoform-level expression data from RNA-sequencing. HG2 tumours were reclassified according to the prediction model and a recurrence-free survival analysis was performed by the multivariate Cox proportional hazards regression model to assess to what extent the TG model could be used to stratify patients. The prediction model was validated in N=487 breast cancer cases from the The Cancer Genome Atlas (TCGA) data set. Differentially expressed genes and isoforms associated with HGs were analysed using linear models.

Results: The classification of grade 1 and grade 3 tumours based on RNA-sequencing data achieved high accuracy (area under the receiver operating characteristic curve = 0.97). The association between recurrence-free survival rate and HGs was confirmed in the study population (hazard ratio of grade 3 versus 1 was 2.62 with 95 % confidence interval = 1.04-6.61). The TG model enabled us to reclassify grade 2 tumours as high TG and low TG gene or isoform grade. The risk of recurrence in the high TG group of grade 2 tumours was higher than in low TG group (hazard ratio = 2.43, 95 % confidence interval = 1.13-5.20). We found 8200 genes and 13,809 isoforms that were differentially expressed between HG1 and HG3 breast cancer tumours.

Conclusions: Gene- and isoform-level expression data from RNA-sequencing could be utilised to differentiate HG1 and HG3 tumours with high accuracy. We identified a large number of novel genes and isoforms associated with HG. Grade 2 tumours could be reclassified as high and low TG, which has the potential to reduce over- and under-treatment if implemented clinically.

No MeSH data available.


Related in: MedlinePlus