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Tumor RNAseq and nCounter for ERY974 monotherapy and/or combination with chemotherapy

Authors: Sano, Yuji;

Tumor RNAseq and nCounter for ERY974 monotherapy and/or combination with chemotherapy

Abstract

We examined pharmacodynamic (PD) of ERY974, CD3 and GPC3-targeting T cell bispecific antibody (TRAB), in tumors of huminized/NOG mice administered with ERY974 and/or chemotherapy. First, we examined the RNAsea data of ERY974 monothrapy for tumors of PC10, NCI-H446, MKN45, and MKN74 of humanized/NOG mice. We found that gene expression related with immune cells at baseline is correlated with efficacy of ERY974. Then,we examined the PD of ERY974 combined with chemotherapy (paclitaxel, cisplatin and capecitabine). In NCI-H446, a representative of non-inflamed-tumor, we examined the tumor RNA of huminized/NOG mice administered with ERY974 and/or paclitaxel, or cisplatin. In MKN45, a representative of non-inflamed-tumor, we examined the tumor RNA of huminized/NOG mice administered with ERY974 and/or capecitabine. For capecitabine combination, we firstly examined the suitable timing among day 3,7,and 14 when combination effect was cleary observed, and found that day 14 is the most suitable timing. From all the data, we found that combination of chemotherpay increased ERY974-induced gene expression related with T cell marker and T cell activation. To examine if our findings are observed in other TRABs in common, we parepred for the EGFR-TRAB, and examined the RNA analysis of MKN45 tumor of huminized/NOG mice administred with EGFR-TRAB and/or paclitaxel. We confirmed that paclitaxel increased EGFR-TRAB-induced gene expression related with T cell marker and T cell activation. We concluded that combination of TRABs with chemotharpy is suitable strategy to erradicate non-inflamed tumors.

The RNAseq reads were mapped to human (GRCh38) and mouse (GRCm38) transcripts simultaneously using RefSeq (Release 62; http://www.ncbi.nlm.nih.gov/refseq/) using bowtie 1.1.2 (maintained by Johns Hopkins University). Reads mapped to the transcripts of both organisms were excluded, followed by the calculation of fragments per kilobase of transcript per million reads mapped (FPKM) using RSEM v1.2.31(The GNU General Public License) parameters as -n 2 -e 99999999 -l 25 -I 1 -S -X 1000 -a -m 200.

These RNA data is obtained using human samples. If anyone would use our dataset, please be sure to contact to sanoyuj@chugai-pharm.co.jp. 

Keywords

FOS: Medical biotechnology

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
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