<img height="1" width="1" src="https://www.facebook.com/tr?id=1582471781774081&amp;ev=PageView &amp;noscript=1">

Researchers Digest up Stomach Cancer

Stomach cancer is the third biggest cancer killer worldwide, with new therapies proving difficult to develop due to the diversity of the disease, and a classification system which has limited clinical use. However, newly published research has broken down stomach cancer into 4 bite sized portions, each with their own distinguishing features, with the hope of improving patient classification and guiding the use of targeted therapies.

Stomach cancer (also known as gastric cancer) is a leading cause of cancer death worldwide. In 2012 it was the world’s third biggest cancer killer causing more than 720,000 deaths, and this year in the US alone its estimated there will be over 22,000 cases with almost 11,000 deaths from the disease. Around 80% of patients are too advanced for surgery at diagnosis, and with overall current 5-year survival rates only around 20 to 25%, there is an unmet need for new and improved therapies.

Research into stomach cancer (95% of which are adenocarcinomas) has been hampered by the diversity within individual tumors, and the presence of different pathological forms of the disease. Current pathological classification systems for stomach cancer have also not shown much clinical utility for guiding development of new treatments or therapeutic regimens. However, recent research published in Nature by The Cancer Genome Atlas Research Network (whose work on identifying oncogenic drivers in lung adenocarcinoma was featured recently in our blog) is hoping to alter both how we classify and treat stomach cancer, by digesting the disease into 4 different and manageable subtypes.

The new research analyzed samples from 295 untreated gastric adenocarcinoma patients using six molecular platforms including copy number analysis, whole exome sequencing, and messenger RNA sequencing. The analysis revealed the 4 subsets of the disease (each with distinct genomic features) which can be used as a molecular classification system:

  • Tumors positive for Epstein-Barr virus (EBV), which also had recurrent PIK3CA mutations and overexpression of JAK2, PD-L1, and PD-L2 (9% of tumors)
  • Microsatellite unstable tumors, with hypermutation rates due to malfunctioning DNA repair mechanisms (22%)
  • Genomically stable tumors, with a diffuse histology and common CDH1 and RHOA mutations (20%)
  • Tumors with chromosomal instability, which showed intestinal histology, TP53 mutation, and RTK-RAS activation (50%).

It is hoped by the study authors that identification of these subtypes can offer an improved method of patient classification and stratification, and provide new focus for targeted therapies, and the EBV subgroup of tumors was of particular interest for this aim.

EBV has been detected previously in a minority of gastric adenocarcinomas, but in this study was linked to particular molecular characteristics that already have targeted therapies approved, or in late stage clinical trials. PI3K inhibitors are in late stage clinical trials for a variety of cancer types, with the first inhibitor recently approved for treatment of CLL, whilst JAK2 inhibitors are approved for myelofibrosis and are being studied in a variety of cancer types. Trials of these agents in EBV positive stomach cancer could identify a new therapeutic option. The much anticipated immunotherapeutic anti-PD-1 agents (the first of which has recently been approved in the US) could also prove useful in this stomach cancer subtype due to the overexpression of the ligands PD-L1 and PD-L2.

With each of the other subgroups also having potentially druggable targets identified, new clinical trial strategies for targeted agents could be opened up for the majority of stomach cancer patients, and poor survival rates eaten into.

Crown Bioscience supports research into stomach cancer through the use of our large collection of clinically relevant Xenograft and Patient-Derived Xenograft (PDX) models available for drug discovery and translational sciences. We have the largest commercially available collection of PDX models (HuPrime®), which contains a large and diverse collection of gastric cancer PDXs. All HuPrime models are well-characterized and are easily searchable through our free, online database (HuBase™) which can be used to identify relevant models to interrogate biomarkers, pathways, and efficacy.

Contact us today at busdev@crownbio.com to discover how we can transform your gastric cancer research.

Related Posts