We are excited to highlight two recent publications that applied the power of Linked-Reads and the Chromium__™ Genome Solution to genetically characterize gastric and triple-negative breast cancer. In both cases, the researchers discovered complex genomic rearrangements that they associated with the amplification of oncogenic driver genes, showcasing the importance of being able to reliably detect these critical structural variants (SVs) in cancer progression.
Genomic structural changes are prevalent in cancer pathogenesis
Cancer is a complicated disease with multiple factors contributing to its incidence and progression. The primary mode of treatment still involves administering cytotoxic chemotherapy, damaging both diseased and healthy cells and carrying with it various undesirable side-effects. Developing a better understanding of the pathogenesis of different types of cancers will lead to more targeted therapies as well as the fine-tuning of current existing therapies. Genetic alterations have been increasingly implicated in the development and progression of cancers, and targeting these alterations will be crucial. Importantly, the genomic instability that leads to these complex structural rearrangements has the effect of altering gene expression for molecules involved in cancer progression, and easily identifying these rearrangements will have a significant impact on future treatment options.
Genomic rearrangements in gastric cancer
Stephanie Greer and her colleagues identified oncogenic rearrangements in gastric cancer metastases using Linked-Read technology. Tissue samples were characterized from two different metastatic, diffuse gastric tumors present in the same individual. They detected unique and highly complex tandem duplications in the fibroblast growth factor receptor 2 (FGFR2) gene in both tumors, with unique structural changes specific to each metastatic site. Importantly, the primary tumor did not contain these complex SVs, indicating that these rearrangements leading to the amplification of FGFR2 occurred independently and are involved in the metastatic mechanisms of these tumors. Read more about their findings in their Genome Medicine publication and in a guest blog post by first author Stephanie Greer.
Genomic alterations in triple-negative breast cancer
Triple negative breast cancer (TNBC) is characterized by the lack of therapeutic targets common to other breast cancers, limiting treatment options. Enhanced expression of TGFA, a gene that encodes one of the high affinity ligands for the epidermal growth factor receptor (EGFR), has been associated with breast cancer development and progression. Kawazu and colleagues set out to investigate the mechanism of TGFA activation in part by using Linked-Read technology, as well as conduct analysis related to other actively functioning oncogenes in TNBC samples. They found that SVs were associated with oncogenic driver events. Tumor suppressor genes were also found to be frequently disrupted by SVs in these TNBC tissues.The researchers used Linked-Reads to confirm break-points of an inverted rearrangement on chromosome 8 within consistent haplotype blocks. The expected chromosome structure, based on Linked-Read analysis, was corroborated with three-color fluorescence in situ hybridization. Importantly, SVs encompassing regulatory regions of the TGFA gene were associated with high levels of TGFA, further solidifying these SVs as a potential therapeutic target. Read more about the team’s findings here.
Linked-Reads for complex structural variant detection
Historically, short-read sequencing has been highly informative for detecting point mutations and copy number alterations, but has not been useful for determining structural changes that span larger DNA segments. With the advent of Linked-Read technology, researchers can now take advantage of the accuracy and efficiency of short-read sequencing, while preserving long-range and haplotype information, enabling the discovery and detection of complex SVs. In the research highlighted here, multiple complex structural variants were detected across megabases of DNA, including intrachromosomal changes, SVs that crossed over centromeres, and tandem duplications that were completely unique to each metastatic gastric tumor site. The ability to reliably detect clinically actionable SVs has the potential to unlock new therapeutic targets and help advance the way we treat cancer.