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Liquid Biopsy Approach Identifies Mutations to Predict Ovarian Cancer Treatment Response


NEW YORK (GenomeWeb) – Researchers at the University of Helsinki have demonstrated that circulating tumor DNA (ctDNA) can be used to find clinically actionable alterations in high-grade serous ovarian cancer (HGSOC) patients undergoing chemotherapy treatment, and that detecting these mutations can predict which patients will have better or worse outcomes.  

The team believes that clinicians could eventually apply the ctDNA analysis approach — which identifies changes in variant allele frequency in ctDNA samples — to help them optimize treatment for patients.  

In order to treat HGSOC, oncologists usually prescribe a combination of cytoreductive surgery and platinum-paclitaxel chemotherapy as a first wave of treatment. While initial response can be positive, most patients usually relapse after several months and have limited treatment options.

The Helsinki team turned to liquid biopsy to potentially identify these relapse-prone patients because of its potential to more safely and accurately glean information about the tumor genome.

"The sample taken at diagnosis may not reflect the tumor composition at relapse," explained Sampsa Hautaniemi, director of the systems oncology research program at the University of Helsinki. "Analyzing ctDNA is minimally invasive [and] helps us detect genomic alterations in late-stage ovarian cancers, where taking biopsies from the tumor is difficult if not impossible."

In a proof-of-concept study published in Journal of Clinical Oncology last week, Hautaniemi and his team sought to demonstrate a clinical workflow for reliable detection of ctDNA alterations in this cancer type, and to test the utility of using these alterations to guide HGSOC treatment.

The team analyzed a total of 78 plasma samples from 12 patients with ovarian or primary peritoneal HGSOC before, during, and after chemotherapy treatment.

"We wanted to determine the congruence between mutations and copy numbers detected in fresh tissues and [those detected in] ctDNA samples from the same patient," Hautaniemi said. "We also wanted to know if we're able to use the information from ctDNA in … clinical decision making."

Hautaniemi's team decided to search specifically for genes, subclones, and mutations that survive five to six rounds of chemotherapy and surgery.   

After performing initial venous whole blood collection and chemotherapy treatment, the researchers stratified the group into poor and good responder categories based on their platinum-free intervals. They then collected additional venous whole blood samples from each patient, extracted ctDNA from these plasma samples, and sent them to BGI for sequencing using its Oseq cancer panel to examine more than 500 actionable genes.

The researchers then analyzed the longitudinal datasets using the University of Helsinki's open-access ctDNA-tailored bioinformatics analysis pipeline, including variant and copy number alteration calling and filtering.

Afterward, the team validated potential clinically actionable mutations using immunohistochemistry and in situ hybridization. The researchers then ranked the genetic alterations according to the European Society for Medical Oncology scale for clinically actionability of molecular targets.

Hautaniemi's group identified 265 mutations in 185 genes and copy number alterations in 113 genes that passed its calling and filtering criteria.

"We were surprised that we identified copy number [alterations] because it's pretty hard to detect copy numbers from panel data," Hautaniemi noted.

The study authors reported that they found high concordance between mutations and copy number alterations detected in ctDNA and those found in tumor samples. Additionally, the team detected alterations linked to clinically available drugs in seven patients.

Most importantly, the team found evidence that changes in ctDNA mutational profiles may be something that can help doctors identify patients who are more or less likely to relapse.

Hautaniemi explained that if his team selected two time points — such as before and after therapy — and saw that the mutation profile was similar, then the patient would do poorly and soon relapse. However, if the team saw a big drop in the patient's variant allele frequency (VAF), then they expect the patient to improve and respond well to therapy. At the same time, Hautaniemi noted that his team will need to verify and finetune the result in bigger cohorts.

"The good-responding patients showed significantly fewer mutations and a higher proportion of mutations with decreasing VAF when compared with the poor-responding patients," the study authors said. "The results suggest that the changes in VAFs detected from ctDNA samples can be used for the early identification of patients with poor response to chemotherapy."

Compared to the high-responding patient group, poor-responding patients also had enriched transcription, p53, chromatin regulation, and DNA double-stranded break repair pathways.

Apart from testing the possibility of response prediction, the investigators also reported on potentially actionable findings from the liquid biopsy data. Prioritizing and interpreting the 265 mutations and 113 copy number alterations using the group's in-house Translational Oncology Knowledgebase, Hautaniemi's team found four major targetable processes in seven patients, including mammalian target of rapamycin (mTOR) in two patients, DNA repair in three patients, epidermal growth factor receptor (EGFR) in three patients, and cyclin dependent kinases in one patient.

The group also identified an ERBB2 amplification in the ctDNA of an individual with platinum-resistant HGSOC. They decided to alter the patient's treatment to include trastuzumab with reduced doses of platinum and paclitaxel. The team saw that using trastuzumab in the patient successfully led to a significant tumor shrinkage and normalization of the cancer antigen 125 tumor marker.

"Although the number of patients in … our study remains small because of the low number of patients with ERBB2-amplifiedHGSOC, these results warrant testing ERBB2 amplification from relapsed HGSOC patients with advanced disease," the study authors noted.

According to the study authors, the results as a whole add to growing evidence that clinicians could potentially use ctDNA to guide therapeutic decisions.

Hautaniemi acknowledged that one of the main hurdles his team encountered while developing the approach involved maintaining fresh-frozen tumor sample purity.

"When a surgeon is extracting the tumor [sample], especially after chemotherapy, it might have a bit of stromal cells within the immune cell," Hautaniemi said. "So, the actual fraction of ovarian tumor cells we receive [can] be pretty low."

Hautaniemi believes that future studies may also uncover new ovarian cancer targets, and lead to assays for diagnostic, prognostic, and potentially predictive purposes.

"Ovarian cancer is a copy number-based disease, and there are no big driver mutations that can be targeted, unlike in colorectal cancer and lung cancer," Hautaniemi explained. "CtDNA is a good proxy, and the only way at the moment, to count what mutations and what copy number alterations are available to track."

While Hautaniemi's team has only tested the pipeline for HGSOC, he believes that researchers could use the method and database — which contains information on copy number and somatic mutations — to provide prognostic and targeted treatment information for other forms of cancer.

Hautaniemi said that while his team has begun some discussion with pharmaceutical and biotech companies, it does not have any current plans to commercialize the ctDNA analysis pipeline. However, the team has received an open-source license from the University of Helsinki, allowing the software to be used for commercial purposes in the future.

Hautaniemi explained that his team decided on an open-source approach because the group is "pro-open science and believes the method should be able to be used widely and freely." Hautaniemi noted that he would be thrilled if "other groups used our technology or methods to make the data more informative."

Several other academic groups and commercial entities are using ctDNA to detect and monitor ovarian cancer patients, and those with other tumor types like colorectal cancer and melanoma.

For instance, researchers at the University of Cambridge, led by James Brenton, are applying patient-specific digital PCR TP53 mutation assays to quantify the amount of ctDNA present in serial blood samples in HGSOC patients. They saw that the portion of tumor DNA in the patients' blood could predict treatment response and time to diseases progression.

Brenton is also part of Cambridge, UK-based firm Inivata, which offers a liquid biopsy next generation sequencing test to detect actionable mutations, currently targeted toward patients with lung cancer.