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Metastatic Tumor Profiles Lead to Potential Treatment Targets

By Labmedica International staff writers
Posted on 05 Nov 2019
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Image: The HiSeq X Series incorporates patterned flow cell technology to generate an exceptional level of throughput for whole-genome sequencing (Photo courtesy of Illumina).
Image: The HiSeq X Series incorporates patterned flow cell technology to generate an exceptional level of throughput for whole-genome sequencing (Photo courtesy of Illumina).
Metastatic cancer is a major cause of death and is associated with poor treatment efficacy. A better understanding of the characteristics of late-stage cancer is required to help adapt personalized treatments, reduce overtreatment and improve outcomes.

In recent years, several large-scale whole-genome sequencing (WGS) analysis efforts have yielded valuable insights into the diversity of the molecular processes that drive different types of adult and pediatric cancer and have fuelled the promises of genome-driven oncology care.

A large team of scientists led by the Hartwig Medical Foundation (Amsterdam, The Netherlands) included in a study patients with advanced cancer not curable by local treatment options and being candidates for any type of systemic treatment and any line of treatment were included as part of two clinical studies. Core needle biopsies were sampled from the metastatic lesion, or when considered not feasible or not safe, from the primary tumor site and frozen in liquid nitrogen. A single 6-μm section was collected for haematoxylin and eosin (H&E) staining and estimation of tumor cellularity by an experienced pathologist and 25 sections of 20-μm were collected in a tube for DNA isolation.

The investigators isolated DNA from biopsies (>30% tumor cellularity) and blood) using the DSP DNA Midi kit for blood and QIAsymphony DSP DNA Mini kit for tissue (Qiagen, Hilden, Germany). A total of 50–200 ng of DNA (sheared to average fragment length of 450nt) was used as input for TruSeq Nano LT library preparation (Illumina, San Diego, CA, USA). Barcoded libraries were sequenced as pools on the Illumina HiSeqX generating 2 × 150 read pairs using standard settings. Several other methods were performed to elucidate the study.

The scientists sequenced the genomes of 2,520 tumor samples and matched normal tissue from 2,399 individuals with metastatic cancer. By sifting through more than 70 million somatic changes in the tumors, including point mutations, small insertions and deletions, copy number shifts, and other features, they distinguished between mutations present at earlier stages of disease and those that cropped up during treatment. The sequences uncovered somatic mutation differences from one cancer type to the next, for example, including large numbers of point mutations in tumors stemming from lung cancer or melanoma. They also highlighted driver gene changes and recurrently mutated genes that seem to be important in the metastatic cancer setting.

In more than half of metastases, for example, the team unearthed whole-genome duplication events, with as many as 80% of esophageal tumors showing these duplications. Meanwhile, some 62% of patients had alterations that were flagged as clinically actionable; either using approved treatments or experimental drugs. The alterations identified in 18% of the patients led to on-label treatment strategies, the team reported, while roughly 13% had mutations that might be amenable to off-label treatment. Another 31% of the cases involved tumor alterations that coincided with eligibility for specific clinical trials.

The authors concluded that their results demonstrated that whole-genome sequencing analysis of metastatic cancer can provide novel and relevant insights, and are instrumental in addressing some of the key challenges in precision medicine in cancer and that the sample set profiled for the current study provides a valuable complementary resource to whole-genome sequence-based data of primary tumors. The study was published on October 23, 2019, in the journal Nature.

Related Links:
Hartwig Medical Foundation
Qiagen
Illumina



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