Transcriptional expression of 8 genes predicts pathological response to first-line docetaxel + trastuzumab-based neoadjuvant chemotherapy

BACKGROUND

Overexpression of HER2 is observed in 20 to 30% of breast carcinomas. The use of trastuzumab has improved the treatment of these patients, especially when it is associated with docetaxel. To optimize the use of this treatment, it seems important to select putative complete responders before treatment administration.

METHODS

In this study, we analyzed by quantitative PCR the expression of 28 genes in HER2-overexpressing tumors treated with trastuzumab + docetaxel-based chemotherapy. We then correlated their expression profile with those of trastuzumab-sensitive and resistant cell lines to classify tumors as having a sensitive (pCR) or resistant (non-pCR) profile. Finally, we used public datasets from the GEO website to validate the reduced gene-expression profile obtained.

RESULTS

We identified an 8-gene-expression combination that predicted the response to treatment with an accuracy of 76%. Based on public microarray data, we showed that the expression profile was specific to first-line trastuzumab + docetaxel-based treatment with an accuracy of 85%.

CONCLUSIONS

Our results showed that by profiling the expression of 8 genes it was possible to predict the response to first-line trastuzumab + docetaxel-based chemotherapy. The use of cancer cell lines as the reference allowed a proper fit with the specificity of different tissues, such as lung or gastric cancers, which could also be eligible to concomitant HER2 inhibition by treatment with trastuzumab or tyrosine kinase inhibitors and docetaxel.

Only missense mutations affecting the DNA binding domain of p53 influence outcomes in patients with breast carcinoma

The presence of a TP53 gene mutation can influence tumour response to some treatments, especially in breast cancer. In this study, we analysed p53 mRNA expression, LOH at 17p13 and TP53 mutations from exons 2 to 11 in 206 patients with breast carcinoma and correlated the results with disease-free and overall survival. The observed mutations were classified according to their type and location in the three protein domains (transactivation domain, DNA binding domain, oligomerization domain) and correlated with disease-free and overall survival. In our population, neither p53 mRNA expression nor LOH correlated with outcome. Concerning TP53 mutations, 27% of tumours were mutated (53/197) and the presence of a mutation in the TP53 gene was associated with worse overall survival (p = 0.0026) but not with disease-free survival (p = 0.0697), with median survival of 80 months and 78 months, respectively. When alterations were segregated into mutation categories and locations, and related to survival, tumours harbouring mutations other than missense mutations in the DNA binding domain of P53 had the same survival profiles as wild-type tumours. Concerning missense mutations in the DNA binding domain, median disease-free and overall survival was 23 months and 35 months, respectively (p = 0.0021 and p<0.0001, respectively), compared with 78 and 80 months in mutated tumours overall. This work shows that disease-free and overall survival in patients with a frameshift mutation of TP53 or missense mutation in the oligomerization domain are the same as those in wild-type TP53 patients.

Apoptosis gene signature of Survivin and its splice variant expression in breast carcinoma

Survivin, an anti-apoptotic protein, was described as strongly expressed in human cancers including breast cancer. However, little is known about the association between Survivin variants (Survivin-2B, Survivin-ΔEx3, Survivin-3B, and Survivin-2α) and the other apoptotic-related genes. In this study, we analyzed the apoptosis gene signature of Survivin and its variant expression in breast cancer. Human Apoptosis Gene Arrays were used to screen genes that could be associated with Survivin variants. Expression of the five transcripts was measured by RT-PCR in 135 breast carcinomas and Cox survival analysis was analyzed according to the patient outcome. Significant associations between Survivin transcripts and apoptotic genes were found. Interestingly, Survivin-3B variant showed major inverse correlations with pro-apoptotic genes. In addition, in vitro results indicated that overexpression of Survivin-3B strongly inhibits 5-fluorouracil/epirubicin/cyclophosphamide-induced apoptosis in breast tumor cell lines. In breast carcinomas, uni- and multivariate analysis showed patients with high level of Survivin-3B expression had a shorter overall (P=0.030 and P=0.042 respectively), and disease-free (P=0.024 and P=0.009) survival. Our data suggest that Survivin-3B contributes to cell survival through the anti-apoptotic pathway and that its expression level could be an important factor in determining therapeutic strategies for breast carcinoma.