Researchers have developed a new cheap method that can identify highly heterogeneous tumors that tend to be very aggressive


Researchers at Karolinska Institutet in Sweden have developed a new, cheap method that can identify highly heterogeneous tumors that tend to be very aggressive, and therefore need to be treated more aggressively.

The technique is presented in the scientific journal Nature Communications.

A common feature of cancer cells is alterations in the number of copies in which each chromosome or gene is present in the genome – a phenomenon known as copy number alterations or CNAs.

Within the same tumor, cells belonging to different anatomical parts of the tumor may carry different CNAs. tumors with many CNAs are typically very aggressive and tend to reform more often, even after harsh treatments.

Now, the Bienko-Crosetto Laboratory at Karolinska Institutet and Science for Life Laboratory (SciLifeLab) in Sweden have developed a new genomic method, named CUTseq, which can assess the amount and type of CNAs in many different parts of the same tumor, at a much lower cost than existing technologies.

“I expect that CUTseq will find many useful applications in cancer diagnostics,” says Nicola Crosetto, senior researcher at the Department of Medical Biochemistry and Biophysics, Karolinska Institutet, and one of the senior authors of the paper.

“Multi-region tumor sequencing is going to be increasingly used in the diagnostic setting, in order to identify patients with highly heterogeneous tumors that need to be treated more aggressively. I believe that our method can play a leading role here.”

The method works with DNA extracted from multiple biopsies and even from very small portions of thin tissue sections – the type of sample that pathologists commonly rely on to make a diagnosis of cancer under the microscope.

By tagging the DNA extracted from multiple regions of the same tumor sample with unique molecular barcodes, a comprehensive picture of the heterogeneity of CNAs in a tumor can be obtained with a single sequencing experiment.

Applications of CUTseq are not only limited to cancer diagnostics, according to the researchers behind the new method.

“For example, CUTseq could be used as a platform for cell line authentication and to monitor genome stability in large cell line repositories and biobanks,” says Magda Bienko, senior researcher at the same department and the other senior author of the paper.

“It could also be applied in ecology, as an alternative to other reduced representation genome sequencing methods, such as RAD-seq, to assess biodiversity in a cost-effective way.”

Leiomyosarcoma (LMS) is a malignant neoplasm derived from smooth muscle that represents one of the most common subtypes of soft tissue sarcoma12.

Though the vast majority of LMS cases are sporadic, predisposing factors include Li-Fraumeni syndrome, hereditary retinoblastoma and radiation exposure34.

There are no oncogenic single nucleotide variants (SNVs) that characterize LMS, though loss of tumor suppressors including TP53RB1 and PTEN are commonly seen, as are multiple copy number alterations (CNAs)58.

LMS is frequently a clinically aggressive disease, and patients are at high risk for local and metastatic relapse following initial complete resection910. Efforts to improve outcomes for patients would benefit from more reliable indicators of high-risk disease and biomarkers of response to therapy.

Detection of circulating tumor DNA (ctDNA) has emerged as a new approach for identifying oncogenic mutations, measuring disease burden, clinical prognostication, and assessing tumor response to therapy1112.

Most ctDNA assays have been developed to detect SNVs that are highly recurrent in many types of carcinomas13.

Though the lack of recurrent SNVs in LMS limits efforts at targeted sequencing, the numerous CNAs characteristic of this disease represent an ideal target for detection.

A next-generation sequencing approach using ultra-low passage whole genome sequencing (ULP-WGS) can detect CNAs in cell-free DNA, indicating the tumor fraction of ctDNA present in blood1415.

Previous studies have shown that ctDNA can be detected in cell-free DNA samples sequenced at a minimum coverage of 0.1X across the whole genome14.

Sequencing for ULP-WGS uses the standard Illumina next-generation sequencing platform without modifications or special adaptions.

The ichorCNA algorithm is used to detect megabase-scale CNAs from ULP-WGS data in which ctDNA comprises as little as 3% of the total cell-free DNA extracted from a plasma sample14.

In the present study, we evaluated plasma from patients with uterine and extrauterine LMS for the presence of ctDNA using ULP-WGS.

Paired resected tumors from each patient were also sequenced when available (29/30 patients), enabling the identification and comparison of CNAs between primary tumors and ctDNA. We related the tumor fraction of cell-free DNA with the clinical status of the patient’s disease.

Finally, we found that longitudinal measurements of ctDNA declined with tumor resection in one patient and in another patient became detectable at the time of disease recurrence. These results suggest that monitoring ctDNA may have clinical utility in establishing the diagnosis, estimating prognosis, measuring treatment response and performing surveillance for relapse in patients with LMS.

More information:Nature Communications (2019). DOI: 10.1038/s41467-019-12570-2

Journal information: Nature Communications
Provided by Karolinska Institutet


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