Dataset Information

Transcriptome Characterization of Matched Primary Breast and Brain Metastatic Tumors to Detect Novel Actionable Targets.

ABSTRACT:

Background

Breast cancer brain metastases (BrMs) are defined by complex adaptations to both adjuvant treatment regimens and the brain microenvironment. Consequences of these alterations remain poorly understood, as does their potential for clinical targeting. We utilized genome-wide molecular profiling to identify therapeutic targets acquired in metastatic disease.

Methods

Gene expression profiling of 21 patient-matched primary breast tumors and their associated brain metastases was performed by TrueSeq RNA-sequencing to determine clinically actionable BrM target genes. Identified targets were functionally validated using small molecule inhibitors in a cohort of resected BrM ex vivo explants (n = 4) and in a patient-derived xenograft (PDX) model of BrM. All statistical tests were two-sided.

Results

Considerable shifts in breast cancer cell-specific gene expression profiles were observed (1314 genes upregulated in BrM; 1702 genes downregulated in BrM; DESeq; fold change > 1.5, Padj < .05). Subsequent bioinformatic analysis for readily druggable targets revealed recurrent gains in RET expression and human epidermal growth factor receptor 2 (HER2) signaling. Small molecule inhibition of RET and HER2 in ex vivo patient BrM models (n = 4) resulted in statistically significantly reduced proliferation (P < .001 in four of four models). Furthermore, RET and HER2 inhibition in a PDX model of BrM led to a statistically significant antitumor response vs control (n = 4, % tumor growth inhibition [mean difference; SD], anti-RET = 86.3% [1176; 258.3], P < .001; anti-HER2 = 91.2% [1114; 257.9], P < .01).

Conclusions

RNA-seq profiling of longitudinally collected specimens uncovered recurrent gene expression acquisitions in metastatic tumors, distinct from matched primary tumors. Critically, we identify aberrations in key oncogenic pathways and provide functional evidence for their suitability as therapeutic targets. Altogether, this study establishes recurrent, acquired vulnerabilities in BrM that warrant immediate clinical investigation and suggests paired specimen expression profiling as a compelling and underutilized strategy to identify targetable dependencies in advanced cancers.

SUBMITTER: Vareslija D

PROVIDER: S-EPMC6449168 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Publications

Transcriptome Characterization of Matched Primary Breast and Brain Metastatic Tumors to Detect Novel Actionable Targets.

Varešlija Damir D Priedigkeit Nolan N Fagan Ailís A Purcell Siobhan S Cosgrove Nicola N O'Halloran Philip J PJ Ward Elspeth E Cocchiglia Sinéad S Hartmaier Ryan R Castro Carlos A CA Zhu Li L Tseng George C GC Lucas Peter C PC Puhalla Shannon L SL Brufsky Adam M AM Hamilton Ronald L RL Mathew Aju A Leone Jose P JP Basudan Ahmed A Hudson Lance L Dwyer Róisín R Das Sudipto S O'Connor Darran P DP Buckley Patrick G PG Farrell Michael M Hill Arnold D K ADK Oesterreich Steffi S Lee Adrian V AV Young Leonie S LS

Journal of the National Cancer Institute 20190401 4

<h4>Background</h4>Breast cancer brain metastases (BrMs) are defined by complex adaptations to both adjuvant treatment regimens and the brain microenvironment. Consequences of these alterations remain poorly understood, as does their potential for clinical targeting. We utilized genome-wide molecular profiling to identify therapeutic targets acquired in metastatic disease.<h4>Methods</h4>Gene expression profiling of 21 patient-matched primary breast tumors and their associated brain metastases w ...[more]

PMID: 29961873

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Project description:BACKGROUND:Next-generation sequencing (NGS) studies of matched pairs of primary and metastatic tumors in renal cell carcinoma (RCC) have been limited to small cohorts. OBJECTIVE:To evaluate the discordance in somatic mutations between matched primary and metastatic RCC tumors. DESIGN, SETTING, AND PARTICIPANTS:Primary tumor (P), metastasis (M), and germline DNA from 60 patients with RCC was subjected to NGS with a targeted exon capture-based assay of 341 cancer-associated genes. Somatic mutations were called using a validated pipeline. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS:Mutations were classified as shared (S) or private (Pr) in relation to each other within individual P-M pairs. The concordance score was calculated as (S-Pr)/(S+Pr). To calculate enrichment of Pr/S mutations for a particular gene, we calculated a two-sided p value from a binomial model for each gene with at least ten somatic mutation events, and also implemented a separate permutation test procedure. We adjusted p values for multiple hypothesis testing using the Benjamini-Hochberg procedure. The mutation discordance was calculated using Mann-Whitney U tests according to gene mutations or metastatic sites. RESULTS AND LIMITATIONS:Twenty-one pairs (35%) showed Pr mutations in both P and M samples. Of the remaining 39 pairs (65%), 14 (23%) had Pr mutations specific to P samples, 12 (20%) had Pr mutations to M samples, and 13 (22%) had identical somatic mutations. No individual gene mutation was preferentially enriched in either P or M samples. P-M pairs with SETD2 mutations demonstrated higher discordance than pairs with wild-type SETD2. We observed that patients who received therapy before sampling of the P or M tissue had higher concordance of mutations for P-M pairs than patients who did not (Mann-Whitney p=0.088). CONCLUSIONS:Our data show mutation discordance within matched P-M RCC tumor pairs. As most contemporary precision medicine trials do not differentiate mutations detected in P and M tumors, the prognostic and predictive value of mutations in P versus M tumors warrants further investigation. PATIENT SUMMARY:In this study we evaluated the concordance of mutations between matched primary and metastatic tumors for 60 kidney cancer patients using a panel of 341 cancer genes. Forty-seven patients carried nonidentical cancer gene mutations within their matched primary-metastatic pair. The mutation profile of the primary tumor alone could compromise precision in selecting effective targeted therapies and result in suboptimal clinical outcomes.

Dataset Information

Transcriptome Characterization of Matched Primary Breast and Brain Metastatic Tumors to Detect Novel Actionable Targets.

Background

Methods

Results

Conclusions

Publications

Transcriptome Characterization of Matched Primary Breast and Brain Metastatic Tumors to Detect Novel Actionable Targets.

Similar Datasets

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