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MIT Spinoff Travera Looks to Validate Cell Mass as Broadly Predictive Cancer Biomarker

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NEW YORK – After raising $5.5 million in an extended Series A funding round this summer, and more recently publishing a study demonstrating the potential of its cell mass-based biomarker approach, Massachusetts Institute of Technology spinoff Travera is optimistic that it will be able to validate and commercialize an assay that can match "virtually all cancer patients to virtually all cancer drugs."

Last week, MIT and Dana-Farber Cancer Institute researchers, including Travera cofounders Scott Manalis and Keith Ligon, published a paper in Cell Reports describing the biomarker's ability to predict glioblastoma patients' responses to the chemotherapy temozolomide (TMZ). In the retrospective study, researchers measured the extent to which cultured glioblastoma cells' masses changed after ex vivo treatment with TMZ and showed that these changes were associated with patients' outcomes on the treatment. The cell mass-based biomarker's predictive performance was in line with MGMT methylation, a genomic biomarker that predicts whether some, but not all, glioblastoma patients will respond to TMZ. MGMT methylation does not, for instance, work when patients have DNA mismatch repair variants of unknown significance.

"Our findings suggest cell mass is a promising functional biomarker for cancers and drugs that lack genomic biomarkers," Manalis and Ligon wrote in their Cell Reports study.

To conduct the glioblastoma study, Manalis, Ligon, and colleagues ran 69 patient-derived neurosphere models — a preserved alternative to organoids that have been shown to "preserve key phenotypic and genotypic features of the patients' tumor in vitro" — through the cell mass-measuring technology that they developed and licensed to Travera, dubbed the Suspended Microchannel Resonator, or SMR. After taking the mass measurement of the unexposed cells, the researchers exposed the glioblastoma neurospheres to TMZ, after which they ran the cells through the SMR device again. The difference in cell mass before and after TMZ, they found, allowed them to accurately predict which patients did and did not respond to TMZ.

"We found that the SMR mass assay was consistent with the MGMT biomarker and that SMR responders survived for significantly longer on therapy than non-responders did," wrote Manalis and Ligon in their study.

The study is a positive advance for Travera, a Medford, Massachusetts-based firm that launched as a venture-backed organization in early 2018 with the goal of validating and commercializing the cell mass-based biomarker. The SMR tool was initially developed in Manalis' lab at MIT and is designed to weigh individual cells to a precise degree by detecting shifts in the resonance frequency of a hollow micro-cantilever beam as cells flow through it. The resonant frequency changes in proportion to the mass of the cell, generating a precise single-cell mass measurement.

"This [tool] is a different approach in cancer, but it's actually just a different approach to measurement [broadly]," said Travera CEO Clifford Reid. "The extraordinary sensitivity of this measurement tool can detect incredibly tiny changes in cells induced by effective cancer drugs."

According to Reid, the latest paper published by Manalis and Ligon is a valuable advance in ongoing efforts to validate a functional mass biomarker that is broadly predictive of cancer treatment response. "[This paper] is a wonderful demonstration that these mass measurements, which are so different than anybody else's biomarker approach, can be as good or better than existing biomarkers," Reid said.

Reid has a background in genomics and formerly served as CEO of sequencing technology firm Complete Genomics, but pivoted to the functional biomarker space after realizing that genomic biomarkers weren't identifying best responders to most cancer drugs and therefore wouldn't be able to personalize treatment for the majority of cancer patients. One further advantage of the functional mass assay is that it can be done with samples obtained via fine-needle aspiration, which is far less invasive than widely used tissue-based biomarker testing.

Although the latest publication represents the first paper to extensively discuss the SMR, much more data are needed to prove the predictive value of the approach. The challenge when developing a functional biomarker, Reid explained, is proving that not only does it work on cells in a lab but also cells inside a patient.

For this reason, Travera is currently conducting validation studies on the functional mass assay to show that the ex vivo predictions correlate with the way the treatments and cells are behaving inside patients themselves. These studies involve cohorts of up to 300 patients with different types of cancer, including multiple myeloma, acute myeloid leukemia, breast cancer, and lung cancer. Reid called the latter two indications, breast and lung cancer, the most "commercially interesting" for the biomarker due to their prevalence and the fact that genomic biomarkers help personalize treatment only for a subset of patients.

The studies, from which initial results are expected by next year, are not interventional. Enrolled patients receive appropriate standard-of-care treatment regimens from their oncologists. Travera, meanwhile, collects cells from these patients, asks their oncologists which drugs they plan to prescribe, then treats the patients' cells in its lab with that same treatment. Researchers then compare the predictions based on the mass biomarker to patients' actual outcomes several months later. Patients' physicians are blinded to the predictions, however.

Ultimately, the idea behind using cell mass as a biomarker, according to Reid, boils down to the simple fact that "every cancer drug effectively does the same thing to a patient … it prevents cancer cells from growing." Because the biomarker approach is rooted in this fundamental premise, he continued, it doesn't matter how the drug works on a mechanistic level. Travera does not have the burden of demonstrating this.

"In theory, we should be able to run this assay for every drug, and in practice, we're finding out that that's exactly right," he said.

As Travera considers the commercial potential of the functional mass biomarker, the company is betting that its approach will beat other biomarker tests in terms of the number of cells needed for analysis and turnaround time. On the first point, Manalis and Ligon noted in their paper, the tool does not require more than a few thousand single cells. In theory, this means that Travera could test about 20 different drugs with just 50,000 cancer cells, which is only a fraction of the amount of cells needed for comprehensive genomic profiling.

In terms of turnaround time, Reid said the test returns results in two days: one day to ship the fresh cells to Travera's lab via a temperature-controlled and tracked FedEx shipper and one day to process and run the cells through the measurement. In contrast, functional tests that involve growing organoids can take several weeks to a month — time that many late-stage cancer patients do not have to spare before starting treatment. The turnaround time for tissue-based large next-generation sequencing panels can also be several weeks.

As far as the scalability of Travera's technology, Reid said it involves the same logistical steps that NGS testing at a large commercial lab would have: taking samples from patients, shipping them to a central laboratory, running the biomarker test, then sending a report with treatment recommendations back to the patient's oncologists.

"For now, we are indeed set up just like Foundation Medicine, and you've seen that scaled up pretty nicely in the US," Reid said. The main difference, he added, is that "they work with dead cells and we work with live cells." Because the cells Travera runs through its SMR cannot be frozen, the firm must keep the turnaround time under two days.

"Travera only deals with live, fresh patient tissue … we don't transform it in any way," Reid said. "Our whole value proposition is that the less you do to the patient tissue before you test it, the more likely it is to respond like it would if it were still in a patient."