Deciphering high risk molecular alterations in gastrointestinal malignancy utilizing an extreme outlier strategy

摘要

The widespread adoption of next-generation sequencing (NGS) technologies has enabled cancer physicians and researchers alike to gain profound insight into the molecular underpinnings of malignant tumors, allowing appreciation of the heterogeneity in disease pathogenesis and its dependency on distinct genetic alterations [ ]. This molecular understanding is particularly relevant in patients with gastrointestinal (GI) cancers, where outcomes are relatively dismal with standard multimodality cancer treatment (e.g., surgery, chemotherapy, radiotherapy, etc.) compared with many other solid cancers [ ]. However, although the clinical heterogeneity of many GI cancers (e.g., metastatic colorectal cancer [CRC], gastric cancer, etc.) is well studied, the molecular basis of this variability remains poorly understood. To this end, several groups have attempted to navigate this genotype-phenotype chasm by utilizing pivotal genomic drivers [ ] and gene expression classifiers [ , ] to define molecular high-risk phenotypes. However, based on what we are continually learning about the molecular landscape of GI malignancy, these platforms provide a relatively myopic understanding of the picture.