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Ocean Genomics Announces Biomarker Development Collaboration Abstract at ASCO 2021

Ocean Genomics, pioneers in AI-driven transcriptome analysis and biomarker discovery, announces the following abstract performed in collaboration with Aichi Medical Center, Nagoya, the National Cancer Center Hospital East, Kashiwa, and other leading centers in Japan.

“Discovery of a potential predictive marker for eribulin treatment and novel target genes in BRAF V600E mutant metastatic colorectal cancer using an AI-driven RNA-seq analysis platform: Translational research of the BRAVERY study (EPOC1701)”

Ocean Genomics leveraged its AI-driven transcriptome analysis and biomarker discovery platform, txome.ai, to perform the analysis of a metastatic colorectal cancer cohort using RNA sequencing FASTQ files and matched clinical data supplied by the centers in Japan from the BRAVERY trial.

The abstract concluded, “The gene expression analyses suggest that BM2 subtype could be a predictive marker for the efficacy of eribulin and some genes could be novel targets with the goal to improve prognosis of pts with BRAF V600E mt mCRC. This is the first finding for a potential biomarker in this subgroup using RNA-seq analysis tools. These findings will require additional validation.”

The abstract can be found here: https://meetinglibrary.asco.org/record/198553/abstract.

Dr. Takayuki Yoshino, one of the principal investigators, noted, “This was the first and an important collaboration step to address the emerging field of biomarker discovery using RNA-seq when combined with A.I.-driven tools such as those from Ocean Genomics. We will aggressively move forward to a further verification using additional cohorts in the near future, together with Ocean Genomics”.

Dr. Takayuki Yoshino, M.D., PhD., currently works at the National Cancer Center Hospital East (NCCHE) in Chiba, Japan, where he is the Director for the Department of Gastroenterology and Gastrointestinal Oncology and the Head of the Clinical Research Coordinating Division.

“The results of this study are encouraging and highlight the opportunity to improve treatment selection using RNA-seq in biomarker development,” said Carl Kingsford, CEO of Ocean Genomics, Inc. “We look forward to validation and continued collaboration with Dr. Yoshino and the outstanding teams at NCCHE, Aichi Medical Center and affiliated centers of excellence.”

For further information on Ocean Genomics and our txome.ai platform:

Please visit our website: https://oceangenomics.com
Or email us: contact@oceangenomics.com

Abstract Accepted to ASCO 2021: Discovering Responder Predictive Markers in mCRC

https://meetinglibrary.asco.org/record/198553/abstract

Authors:

Toshiki Masuishi, Hiroya Taniguchi, Daisuke Kotani, Hideaki Bando, Taroh Satoh, Taito Esaki, Yoshito Komatsu, Yu Sunakawa, Tomohiro Nishina, Eiji Shinozaki, Naohiro Nishida, Masato Komoda, Satoshi Yuki, Naoki Izawa, Gaurav Sharma, Stan Skrzypczak, Eric Schultz, Carl Kingsford, Akihiro Sato, Takayuki Yoshino

Abstract Disclosures

Research Funding:

Aichi Cancer Center Hospital

Background:
Patients (pts) with BRAF V600E mutant (mt) metastatic colorectal cancer (mCRC) still have a poor prognosis even when treated with encorafenib plus cetuximab. We reported that eribulin that inhibits G2-M cell cycle had limited activity for these pts in the phase II BRAVERY study (Masuishi T, et al. WCGC 2020). Barras D, et al. (2017) reported that BRAF V600E mt mCRCs were classified into BM1 and BM2 characterized by KRAS/AKT pathway activation and deregulation of the cell cycle with G2-M phase activation, respectively, based on gene expression.

Methods:
Whole transcriptome RNA-seq of FFPE pre-treatment tumor samples was performed using NovaSeq 6000 in the BRAVERY study. Molecular features were extracted using the Txome.ai platform (Ocean Genomics Inc., PA, USA) which included transcript- and gene-level expression quantification, expression-based clustering, and structural variant calling. Efficacy of eribulin was classified as “good” if pts had a tumor reduction and/or progression-free survival (PFS) of more than 6 months, and “poor” otherwise. The differential gene expression analysis was performed between pts with “good” and “poor” using Txome.ai. In addition, BM and consensus molecular subtype (CMS) classification were performed using the model developed by Barras D, et al. (2017) and Guinney J, et al. (2015), respectively.

Results:
Among 27 pts, 26 tumor samples were available to perform RNA-seq and analyze gene expression despite low mapping rates. Patient characteristics were as follows: median age of 58.5 (range, 33–71) years; ECOG PS of 0/1 (16/10); primary tumor location of right/left (11/15); and all 26 pts had MSS/pMMR. Four and 22 pts were classified into “good” and “poor” groups, respectively. Among 52 differentially expressed genes (GENCODE v31) with false discovery rate-adjusted P- value < 0.05, the top 5 genes with the lowest P-values are provided in the table. All 4 pts in the “good” group were classified into BM2 and pts in the “poor” group were classified into BM1 (8/22) and BM2 (14/22) (p = 0.07). In addition, all but 2 pts were classified into CMS4. These two pts belong to the “poor” group with one of them classified into CMS1 and the other into CMS2.

Conclusions:
These gene expression analyses suggest that BM2 subtype could be a predictive marker for the efficacy of eribulin and some genes could be novel targets with the goal to improve prognosis of pts with BRAF V600E mt mCRC. This is the first finding for a potential biomarker in this subgroup using RNA-seq analysis tools. These findings will require additional validation. Clinical trial information: UMIN000031552.

Abstract Accepted to ASCO 2021: Discovery of a potential predictive marker for eribulin treatment and novel target genes in BRAF V600E mutant metastatic colorectal cancer using an AI-driven RNA-seq analysis platform: Translational research of the BRAVERY study (EPOC1701)

https://meetinglibrary.asco.org/record/198553/abstract

DOI:10.1200/JCO.2021.39.15_suppl.e15532

Authors:

Toshiki Masuishi, Hiroya Taniguchi, Daisuke Kotani, Hideaki Bando, Taroh Satoh, Taito Esaki, Yoshito Komatsu, Yu Sunakawa, Tomohiro Nishina, Eiji Shinozaki, Naohiro Nishida, Masato Komoda, Satoshi Yuki, Naoki Izawa, Gaurav Sharma, Stan Skrzypczak, Eric Schultz, Carl Kingsford, Akihiro Sato, Takayuki Yoshino; Aichi Cancer Center Hospital, Aichi, Japan; Department of Gastroenterology and Gastrointestinal Oncology, National Cancer Center Hospital East, Kashiwa, Japan; Department of Frontier Science for Cancer and Chemotherapy, Osaka University Graduate School of Medicine, Osaka, Japan; Department of Gastrointestinal and Medical Oncology, National Hospital Organization Kyushu Cancer Center, Fukuoka, Japan; Department of Cancer Chemotherapy, Hokkaido University Hospital Cancer Center, Sapporo, Japan; Department of Clinical Oncology, St. Marianna University School of Medicine, Kawasaki, CA, Japan; National Hospital Organization Shikoku Cancer Center, Matsuyama, Japan; Department of Gastrointestinal Oncology, Cancer Institute Hospital of Japanese Foundation for Cancer Research, Tokyo, Japan; Department of Gastroenterology and Hepatology, Hokkaido University Hospital, Sapporo, Japan; Department of Clinical Oncology, St. Marianna University School of Medicine, Kawasaki, Japan; Ocean Genomics, Inc., Pittsburgh, PA; Clinical Research Support Office, National Cancer Center Hospital East, Kashiwa, Japan; National Cancer Center Hospital East, Kashiwa, Japan

Research Funding:

Aichi Cancer Center Hospital

Methods:

Whole transcriptome RNA-seq of FFPE pre-treatment tumor samples was performed using NovaSeq 6000 in the BRAVERY study. Molecular features were extracted using the Txome.ai platform (Ocean Genomics Inc., PA, USA) which included transcript- and gene-level expression quantification, expression-based clustering, and structural variant calling. Efficacy of eribulin was classified as “good” if pts had a tumor reduction and/or progression-free survival (PFS) of more than 6 months, and “poor” otherwise. The differential gene expression analysis was performed between pts with “good” and “poor” using Txome.ai. In addition, BM and consensus molecular subtype (CMS) classification were performed using the model developed by Barras D, et al. (2017) and Guinney J, et al. (2015), respectively.

Results:

Among 27 pts, 26 tumor samples were available to perform RNA-seq and analyze gene expression despite low mapping rates. Patient characteristics were as follows: median age of 58.5 (range, 33–71) years; ECOG PS of 0/1 (16/10); primary tumor location of right/left (11/15); and all 26 pts had MSS/pMMR. Four and 22 pts were classified into “good” and “poor” groups, respectively. Among 52 differentially expressed genes (GENCODE v31) with false discovery rate-adjusted P- value < 0.05, the top 5 genes with the lowest P-values are provided in the table. All 4 pts in the “good” group were classified into BM2 and pts in the “poor” group were classified into BM1 (8/22) and BM2 (14/22) (p = 0.07). In addition, all but 2 pts were classified into CMS4. These two pts belong to the “poor” group with one of them classified into CMS1 and the other into CMS2.

Conclusions:

These gene expression analyses suggest that BM2 subtype could be a predictive marker for the efficacy of eribulin and some genes could be novel targets with the goal to improve prognosis of pts with BRAF V600E mt mCRC. This is the first finding for a potential biomarker in this subgroup using RNA-seq analysis tools. These findings will require additional validation. Clinical trial information: UMIN000031552.

Abstract Accepted to ASCO 2020: Identifying Novel Gene Targets in ICI-resistant Gastric Cancer

https://meetinglibrary.asco.org/record/186530/abstract

Authors:

Jeeyun Lee, Seung Tae Kim, Kyoung-Mee Kim, Eric Schultz, Stan Skrzypczak, Rob Patro, Carl Kingsford; Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea; Department of Pathology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea; Ocean Genomics, Inc., Pittsburgh, PA

Abstract Disclosures

Research Funding:

None

Background:
Immune checkpoint inhibition (ICI) has made significant breakthroughs in several tumor types including gastric cancer (GC) in recent years. We recently showed that single agent pembrolizumab demonstrated remarkable and durable response in MSI and EBV GC. However, the response to ICI remains low in MSS and most patients progress after initial response. We explore novel targets in ICI-resistant GC patients by analyzing pre- and post-resistant expression.

Methods:
Of the 61 patients who were enrolled onto our previously reported phase II pembrolizumab trial (NCT#02589496), whole transcriptome RNA-seq analysis of 10 paired freshly collected tissue samples (all from primary gastric tumors) was performed using TruSeq. All biopsies were performed at progression following stable disease (SD) or partial response (PR) to pembrolizumab. All patients had a MSI status of MSS and EBV negative. Molecular features were extracted using the validated Ocean Genomics, Inc. gene expression analysis pipeline, which trims reads, computes transcript- and gene-level expression, predicts structural variants, assembles novel isoforms, and computes per-sample quality control metrics, among other analyses. Samples that passed quality control, with mapping rates > 88%, were selected for analysis. Differentially expressed (DE) genes between resistant and pre-resistant samples were identified using a statistical test with a study design that accounted for the pairing of samples for each patient.

Results:
16 genes (GENCODE v31) had absolute log2-fold expression changes (L2FC) > 2, P-value < 10−5 and FDR-adjusted P-value < 0.05. Because sex was only partially controlled for, we excluded genes on the X and Y chromosomes. We also excluded non-protein encoding genes and pseudogenes. The 7 remaining genes are in the table. PDL-1 (CD274) was not identified as significantly DE (FDR-adjusted P-value > 0.9999).

Conclusions:
This is the first study to identify novel targets in pembrolizumab-resistant GC using RNA-seq algorithms beyond PDL-1.

Abstract with Samsung Medical Center Accepted to ASCO 2020: Novel Target Discovery in Pembrolizumab-Resistant Gastric Cancer Using a Comprehensive RNA-seq Analysis Pipeline.

Ocean provided the platform and expert services required to define the approach, review the analysis results, and revise the endpoint.

Ocean’s platform produced complete feature extraction, classifier generation, QC, and comprehensive reporting on 55 samples (FASTQ) and patient metadata in 19 hours, providing a 24-hour turn-around time with partner.

Novel target discovery in pembrolizumab-resistant gastric cancer using a comprehensive RNA-seq analysis pipeline.

https://meetinglibrary.asco.org/record/186530/abstract

DOI:10.1200/JCO.2020.38.15_suppl.e16541

Authors:

Jeeyun Lee, Seung Tae Kim, Kyoung-Mee Kim, Eric Schultz, Stan Skrzypczak, Rob Patro, Carl Kingsford; Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea; Department of Pathology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea; Ocean Genomics, Inc., Pittsburgh, PA Abstract Disclosures

Research Funding:

None

Background: Immune checkpoint inhibition (ICI) has made significant breakthroughs in several tumor types including gastric cancer (GC) in recent years. We recently showed that single agent pembrolizumab demonstrated remarkable and durable response in MSI and EBV GC. However, the response to ICI remains low in MSS and most patients progress after initial response. We explore novel targets in ICI-resistant GC patients by analyzing pre- and post-resistant expression. Methods: Of the 61 patients who were enrolled onto our previously reported phase II pembrolizumab trial (NCT#02589496), whole transcriptome RNA-seq analysis of 10 paired freshly collected tissue samples (all from primary gastric tumors) was performed using TruSeq. All biopsies were performed at progression following stable disease (SD) or partial response (PR) to pembrolizumab. All patients had a MSI status of MSS and EBV negative. Molecular features were extracted using the validated Ocean Genomics, Inc. gene expression analysis pipeline, which trims reads, computes transcript- and gene-level expression, predicts structural variants, assembles novel isoforms, and computes per-sample quality control metrics, among other analyses. Samples that passed quality control, with mapping rates > 88%, were selected for analysis. Differentially expressed (DE) genes between resistant and pre-resistant samples were identified using a statistical test with a study design that accounted for the pairing of samples for each patient. Results: 16 genes (GENCODE v31) had absolute log2-fold expression changes (L2FC) > 2, P-value < 10−5 and FDR-adjusted P-value < 0.05. Because sex was only partially controlled for, we excluded genes on the X and Y chromosomes. We also excluded non-protein encoding genes and pseudogenes. The 7 remaining genes are in the table. PDL-1 (CD274) was not identified as significantly DE (FDR-adjusted P-value > 0.9999). Conclusions: This is the first study to identify novel targets in pembrolizumab-resistant GC using RNA-seq algorithms beyond PDL-1.

GENE LOG2 FOLD CHANGE P-VALUE FDR-ADJUSTED
P-VALUE		 DESCRIPTION
PGA5 -4.19 8.78E-09 5.17E-05 Pepsinogen A5
MSMB -4.39 7.06E-08 3.47E-04 Microseminoprotein beta
AC104389.5 -5.08 7.06E-08 8.69E-04 Novel protein
TRIM29 2.76 1.18E-06 3.49E-03 Tripartite motif containing 29
GJB5 3.32 6.94E-06 1.57E-02 Gap junction protein beta 5
GABRP 2.56 8.13E-06 1.60E-02 Gamma-aminobutyric acid type A receptor pi subunit
SERPINB7 3.02 9.79E-06 1.80E-02 Serpin family B member 7