Novel Biomarkers Found for Bowel Cancer Treatment
By LabMedica International staff writers Posted on 03 Mar 2017 |
Image: The HiSeq 2500 high-throughput sequencing system (Photo courtesy of Illumina).
Bowel cancer is the third most common form of cancer in the world and 95% of cases are colorectal carcinomas and at an advanced stage they are one of the most common causes of death, as only some patients respond to drug treatment.
Colorectal carcinoma (CRC) represents a heterogeneous entity, with only a fraction of the tumors responding to available therapies, requiring a better molecular understanding of the disease in precision oncology. A consortium of scientists looked for biomarkers, molecules that are typical of the different tumor sub-groups and provide valuable information for diagnosis and potential treatment.
The OncoTrack consortium, a public-private consortium, has conducted one of Europe's largest collaborative academic-industry research projects to develop and assess novel approaches for identification of new markers for colon cancer. They recruited 106 CRC patients (stages I–IV) and developed a pre-clinical platform generating a compendium of drug sensitivity data totaling more than 4,000 assays testing 16 clinical drugs on patient-derived in vivo and in vitro models. This large biobank of 106 tumors, 35 organoids and 59 xenografts, with extensive omics data comparing donor tumors and derived models provided a resource for advancing our understanding of CRC.
The consortium used various techniques to accomplish their goals, including growing tumors in tissue culture systems, as well as in special mouse strains, and subsequently treated with a range of medicaments. Through this, the scientists were able to better understand the relationships between the molecular pattern and the response of the tumor to drugs. Cancer relevant gene selection was done by taking the overlap with 31 significantly mutated genes in the CRC TCGA study and 86 genes recurrently mutated in CRC from the TCGA pan-cancer analysis. Paired-end libraries were sequenced on HiSeq 2,000/2,500 instruments with v3 chemistry.
The team discovered molecules that can predict the effectiveness of two drugs commonly used to treat this disease: Cetuximab, which inhibits the receptor for the epidermal growth factor (EGFR), and the chemotherapy drug 5FU. The scientists identified the genetic composition of the tumors and analyzed their so-called transcriptome, namely the set of all ribonucleic acid (RNA) molecules synthesized in a given tissue. Based on this analysis, they were able to produce a definite molecular fingerprint for all of the tumors.
Bodo Lange, PhD, CEO at Alacris Theranostics and a co-author of the study, said, “The extensive molecular and drug sensitivity datasets generated within this study are a highly valuable resource. Our findings provide major new insights into the molecular landscape of colorectal cancer, including the identification of novel alterations, which can be further exploited for advancing understanding of this lethal tumor type and for personalizing therapies.” The study was published on February 10, 2017, in the journal Nature Communications.
Colorectal carcinoma (CRC) represents a heterogeneous entity, with only a fraction of the tumors responding to available therapies, requiring a better molecular understanding of the disease in precision oncology. A consortium of scientists looked for biomarkers, molecules that are typical of the different tumor sub-groups and provide valuable information for diagnosis and potential treatment.
The OncoTrack consortium, a public-private consortium, has conducted one of Europe's largest collaborative academic-industry research projects to develop and assess novel approaches for identification of new markers for colon cancer. They recruited 106 CRC patients (stages I–IV) and developed a pre-clinical platform generating a compendium of drug sensitivity data totaling more than 4,000 assays testing 16 clinical drugs on patient-derived in vivo and in vitro models. This large biobank of 106 tumors, 35 organoids and 59 xenografts, with extensive omics data comparing donor tumors and derived models provided a resource for advancing our understanding of CRC.
The consortium used various techniques to accomplish their goals, including growing tumors in tissue culture systems, as well as in special mouse strains, and subsequently treated with a range of medicaments. Through this, the scientists were able to better understand the relationships between the molecular pattern and the response of the tumor to drugs. Cancer relevant gene selection was done by taking the overlap with 31 significantly mutated genes in the CRC TCGA study and 86 genes recurrently mutated in CRC from the TCGA pan-cancer analysis. Paired-end libraries were sequenced on HiSeq 2,000/2,500 instruments with v3 chemistry.
The team discovered molecules that can predict the effectiveness of two drugs commonly used to treat this disease: Cetuximab, which inhibits the receptor for the epidermal growth factor (EGFR), and the chemotherapy drug 5FU. The scientists identified the genetic composition of the tumors and analyzed their so-called transcriptome, namely the set of all ribonucleic acid (RNA) molecules synthesized in a given tissue. Based on this analysis, they were able to produce a definite molecular fingerprint for all of the tumors.
Bodo Lange, PhD, CEO at Alacris Theranostics and a co-author of the study, said, “The extensive molecular and drug sensitivity datasets generated within this study are a highly valuable resource. Our findings provide major new insights into the molecular landscape of colorectal cancer, including the identification of novel alterations, which can be further exploited for advancing understanding of this lethal tumor type and for personalizing therapies.” The study was published on February 10, 2017, in the journal Nature Communications.
Latest Pathology News
- First of Its Kind Universal Tool to Revolutionize Sample Collection for Diagnostic Tests
- AI-Powered Digital Imaging System to Revolutionize Cancer Diagnosis
- New Mycobacterium Tuberculosis Panel to Support Real-Time Surveillance and Combat Antimicrobial Resistance
- New Method Offers Sustainable Approach to Universal Metabolic Cancer Diagnosis
- Spatial Tissue Analysis Identifies Patterns Associated With Ovarian Cancer Relapse
- Unique Hand-Warming Technology Supports High-Quality Fingertip Blood Sample Collection
- Image-Based AI Shows Promise for Parasite Detection in Digitized Stool Samples
- Deep Learning Powered AI Algorithms Improve Skin Cancer Diagnostic Accuracy
- Microfluidic Device for Cancer Detection Precisely Separates Tumor Entities
- Virtual Skin Biopsy Determines Presence of Cancerous Cells
- AI Detects Viable Tumor Cells for Accurate Bone Cancer Prognoses Post Chemotherapy
- First Ever Technique Identifies Single Cancer Cells in Blood for Targeted Treatments
- Innovative Blood Collection Device Overcomes Common Obstacles Related to Phlebotomy
- Intra-Operative POC Device Distinguishes Between Benign and Malignant Ovarian Cysts within 15 Minutes
- Simple Skin Biopsy Test Detects Parkinson’s and Related Neurodegenerative Diseases
- Bioinformatics Tool to Identify Chromosomal Alterations in Tumor Cells Can Improve Cancer Diagnosis