Assessing biosimilarity of Trastuzumab monoclonal antibody therapeutics using RNA sequencing
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ABSTRACT:
PROVIDER: PRJNA667165 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR12768200_1.fastq.gz | Fastqsanger.gz | |||
| SRR12768200_2.fastq.gz | Fastqsanger.gz | |||
| SRR12768201_1.fastq.gz | Fastqsanger.gz | |||
| SRR12768201_2.fastq.gz | Fastqsanger.gz | |||
| SRR12768202_1.fastq.gz | Fastqsanger.gz |
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Project description:Assessing biosimilarity of Trastuzumab monoclonal antibody therapeutics using RNA sequencing of treated SKBR3 cells
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Project description:Patents of some therapeutic monoclonal antibodies (mAb) used for cancer treatment are ending soon, allowing for the entry of similar analogs (biosimilars) onto the market. To have a biosimilar approved by health agencies, the manufacturer must typically demonstrate functional and physicochemical similarity between the biosimilar and the approved reference product. Functional similarity is often validated with cell-based assays, but the information gained is limited. In contrast, RNA-seq methods enable a sensitive transcriptomic analysis, providing detailed information on pathways and cellular responses. Trastuzumab inhibits signaling of the cell-surface receptor HER2, which is overexpressed in approximately 30% of all breast cancer patients. Here, we compare the functional effect of the mAb Trastuzumab and a corresponding biosimilar. The BT-474 breast cancer cell line was treated with the reference product, Trastuzumab (Herceptin®), or a proposed biosimilar (ApoTras), and the cellular transcriptomes were analyzed by RNA-seq. Functional similarity was assessed using two statistical contrasts. One contrast evaluated the mechanism of action by comparing treated samples (Her and ApoTras, n = 19) vs. untreated controls (n = 10), which identified 2623 differentially expressed genes (DEG) at a minimum fold change of 1.25. The other contrast directly compared ApoTras (n = 9) vs. Her (n = 10) to determine differences in expression between treatments and identified 24 DEG using a 1.25 fold- change threshold. This low DEG number reveals a very high similarity of effect of both mAb treatments on the cancer cells. A gene set overrepresentation analysis of DEG for mAb treatments revealed mechanisms of action, which were consistent with known trastuzumab effects. Supporting the small number of changes between both treatments, a post-hoc power analysis for the between-treatment comparison estimated power of 0.88 to detect a gene expression fold-changes of 2.0. To summarize these data, we introduce an overall similarity index (SI) to quantify treatment similarity based on changes in gene expression. Using statistical contrasts with RNA-seq analysis provides a powerful tool for the comparison of biological effects of biosimilar and originator compounds and can be broadly used for functional comparisons of drug treatments.
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Project description:Patents of some therapeutic monoclonal antibodies (mAb) used for cancer treatment are ending soon, allowing for the entry of similar analogs (biosimilars) onto the market. To have a biosimilar approved by health agencies, the manufacturer must typically demonstrate functional and physicochemical similarity between the biosimilar and the approved reference product. Functional similarity is often validated with cell-based assays, but the information gained is limited. In contrast, RNA-seq methods enable a sensitive transcriptomic analysis, providing detailed information on pathways and cellular responses. Trastuzumab inhibits signaling of the cell-surface receptor HER2, which is overexpressed in approximately 30% of all breast cancer patients. Here, we compare the functional effect of the mAb Trastuzumab and a corresponding biosimilar. The SKBR3 breast cancer cell line was treated with the reference product, Trastuzumab (Herceptin®), or a proposed biosimilar (ApoTras), and the cellular transcriptomes were analyzed by RNA-seq. Functional similarity was assessed using two statistical contrasts. One contrast evaluated the mechanism of action by comparing treated samples (Her and ApoTras, n = 16) vs. untreated controls (n = 8). The other contrast directly compared ApoTras (n = 8) vs. Her (n = 8) to determine differences in expression between treatments. A gene set overrepresentation analysis of DEG for mAb treatments revealed mechanisms of action, which were consistent with known trastuzumab effects.
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