1. Academic Validation
  2. The expressed mutational landscape of microsatellite stable colorectal cancers

The expressed mutational landscape of microsatellite stable colorectal cancers

  • Genome Med. 2021 Sep 1;13(1):142. doi: 10.1186/s13073-021-00955-2.
Anita Sveen 1 2 3 Bjarne Johannessen 1 2 Ina A Eilertsen 1 2 3 Bård I Røsok 2 4 Marie Gulla 1 2 Peter W Eide 1 2 Jarle Bruun 1 2 Kushtrim Kryeziu 1 2 Leonardo A Meza-Zepeda 5 6 Ola Myklebost 5 7 Bjørn A Bjørnbeth 2 4 Rolf I Skotheim 1 2 8 Arild Nesbakken 2 3 4 Ragnhild A Lothe 9 10 11
Affiliations

Affiliations

  • 1 Department of Molecular Oncology, Institute for Cancer Research, Oslo University Hospital, P.O. Box 4953 Nydalen, NO-0424, Oslo, Norway.
  • 2 K.G. Jebsen Colorectal Cancer Research Centre, Division for Cancer Medicine, Oslo University Hospital, P.O. Box 4953 Nydalen, NO-0424, Oslo, Norway.
  • 3 Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, P.O. Box 1171 Blindern, NO-0318, Oslo, Norway.
  • 4 Department of Gastrointestinal Surgery, Oslo University Hospital, P.O. Box 4950, NO-0424, Oslo, Norway.
  • 5 Department of Tumor Biology, Institute for Cancer Research, Oslo University Hospital, P.O. Box 4953 Nydalen, NO-0424, Oslo, Norway.
  • 6 Genomics Core Facility, Department of Core Facilities, Institute for Cancer Research, Oslo University Hospital, P.O. Box 4953 Nydalen, NO-0424, Oslo, Norway.
  • 7 Department of Clinical Science, University of Bergen, P.O. Box 7804, NO-5020, Bergen, Norway.
  • 8 Department of Informatics, Faculty of Mathematics and Natural Sciences, University of Oslo, P.O. Box 1032 Blindern, NO-0315, Oslo, Norway.
  • 9 Department of Molecular Oncology, Institute for Cancer Research, Oslo University Hospital, P.O. Box 4953 Nydalen, NO-0424, Oslo, Norway. [email protected].
  • 10 K.G. Jebsen Colorectal Cancer Research Centre, Division for Cancer Medicine, Oslo University Hospital, P.O. Box 4953 Nydalen, NO-0424, Oslo, Norway. [email protected].
  • 11 Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, P.O. Box 1171 Blindern, NO-0318, Oslo, Norway. [email protected].
Abstract

Background: Colorectal Cancer is the 2nd leading cause of cancer-related deaths with few patients benefiting from biomarker-guided therapy. Mutation expression is essential for accurate interpretation of mutations as biomarkers, but surprisingly, little has been done to analyze somatic Cancer mutations on the expression level. We report a large-scale analysis of allele-specific mutation expression.

Methods: Whole-exome and total RNA sequencing was performed on 137 samples from 121 microsatellite stable colorectal cancers, including multiregional samples of primary and metastatic tumors from 4 patients. Data were integrated with allele-specific resolution. Results were validated in an independent set of 241 colon cancers. Therapeutic associations were explored by pharmacogenomic profiling of 15 cell lines or patient-derived organoids.

Results: The median proportion of expressed mutations per tumor was 34%. Cancer-critical mutations had the highest expression frequency (gene-wise mean of 58%), independent of frequent allelic imbalance. Systematic deviation from the general pattern of expression levels according to allelic frequencies was detected, including preferential expression of mutated alleles dependent on the mutation type and target gene. Translational relevance was suggested by correlations of KRAS/NRAS or TP53 mutation expression levels with downstream oncogenic signatures (p < 0.03), overall survival among patients with stage II and III Cancer (KRAS/NRAS: hazard ratio 6.1, p = 0.0070), and targeted drug sensitivity. The latter was demonstrated for EGFR and MDM2 inhibition in pre-clinical models.

Conclusions: Only a subset of mutations in microsatellite stable colorectal cancers were expressed, and the "expressed mutation dose" may provide an opportunity for more fine-tuned biomarker interpretations.

Keywords

Allele-specific mutation expression; Colorectal cancer; Drug screening; Exome sequencing; Mutant allele fraction; Patient-derived organoids; Pharmacogenomics; RNA sequencing.

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