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Differential neoadjuvant chemotherapy response in urothelial carcinoma molecular subtypes

ABSTRACT: Differential neoadjuvant chemotherapy response in urothelial carcinoma molecular subtypes

PROVIDER: PRJNA716648 | ENA |

REPOSITORIES: ENA

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Differential neoadjuvant chemotherapy response in urothelial carcinoma molecular subtypes

Project description:For patients with muscle-invasive bladder cancer, there are no biomarkers in clinical use that can identify patients that are sensitive or resistant to neoadjuvant chemotherapy. This study investigates how molecular subtypes impact pathological response and survival in 149 patients receiving preoperative cis-platin based chemotherapy by tumor classification using transcriptomic profiling and a 13-marker immunostaining panel. Furthermore, we explored to what extent gene expression signatures can predict chemotherapy response beyond molecular subtypes. We observed improved pathological response rates and survival outcomes for patients presenting with genomically unstable (GU) and urothelial-like (Uro) subtypes compared to the basal-squamous (BASQ) subtype following neoadjuvant chemotherapy and radical cystectomy. Also, SPP1, coding for osteopontin, displayed a clear subtype-dependent effect on chemotherapy response, confirmed at the protein level. Based on our findings, we hypothesize that urothelial cancer of the luminal-like GU- and Uro-subtypes are more responsive to cisplatin-based chemotherapy which may influence patient selection pending further research.

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Patterns of metastasis and recurrence in urothelial cancer molecular subtypes

Project description:This series contains the gene expression data from urothelial bladder cancer samples from Swedish patients that were used to analyze metastatic sites. Included patients have a recurrence or distant metastasis before or after treatment with chemotherapy. Patients with only lymph-node metastases are not included. A previous series (GSE169455) contains data from all patients that recieved two or more cycles of neoadjuvant chemotherapy with curative intent. Patients in that series that developed distant recurrence are re-analyzed here. A few samples from a previous cystectomy series (GSE83586) are also included as re-analysis. In addition, the current series contains data from patients treated with palliative first-line chemotherapy, curative adjuvant chemotherapy, or < 2 cycles of neoadjuvant chemotherapy. Raw data should be adjusted in data processing for batch variables: Labeling batch and Labeling kit.

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Project description:Four different molecular classifications of muscle-invasive bladder cancer (MIBC) based on gene expression have been proposed. With the ultimate goal of utilizing these molecular subtypes for personalized treatment, we investigated their significance in the context of neoadjuvant cisplatin-based chemotherapy (NAC).

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Radiation induced gene signature predicts pathologic complete response to neoadjuvant chemotherapy in breast cancer patients

Project description:Purpose:The identification of biomarkers predictive of neoadjuvant chemotherapy response in breast cancer patients would be an important advancement in personalized cancer therapy. We hypothesized that due to similarities between radiation and chemotherapy induced cellular response mechanisms, radiation responsive genes may be useful in predicting response to neoadjuvant chemotherapy. Materials and Methods: Murine p53 null breast cancer cell lines representative of the luminal, basal-like and claudin-low human breast cancer subtypes were irradiated to identify radiation responsive genes. These murine radiation induced genes were then converted to their human orthologs. These genes were then used to develop a predictor of pathologic complete response (pCR) that was validated on two independent published neoadjuvant chemotherapy data sets of genomic data with response. Results: A radiation induced gene signature consisting of 30 genes was identified on a training set of 337 human primary breast cancer tumor samples that was prognostic for survival. Mean expression of this signature was calculated for individual samples in two independent published datasets and was found to be significantly predictive of pathologic complete response. Multivariate logistic regression analysis in both independent datasets showed that this 30 gene signature added significant predictive information independent of that provided by standard clinical predictors and other gene expression based predictors of pathologic complete response. Conclusion: This study provides new biologic information regarding response to neoadjuvant chemotherapy and a means of possibly improving the prediction of pathologic complete response. reference x sample

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Triple negative breast cancer subtypes and pathologic complete response rate to neoadjuvant chemotherapy

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