Cancer drug response and results can be predicted by changes in cell clumps

A retrospective study based on a patient-derived organ model showed that subtle changes in cell volume can be used as functional biomarkers to predict patient response to cancer drugs
.

This diagnostic test based on the "functional precision medicine" method can match patients with the most effective existing treatment methods, and is especially useful for cancers and drugs that lack genomic biomarkers

"The idea behind functional precision medicine is that for cancer, you can take out the patient's tumor cells, give them the drugs that the patient may get, and predict what will happen before giving them to the patient," Harvard University Medical School associate professor, the research Said Keith Ligan, MD, senior co-author and director of the Dana-Farber Patient Derivative Model Center
.

Dr.
Scott Manalis, senior author of the study, professor in the Department of Bioengineering and Mechanical Engineering, and member of the Koch Institute for Comprehensive Cancer Research, said that the new in vitro technology includes removing tumor cells from patients and treating cells with drugs.
Measuring changes in cell quality can be applied to various cancers and drug treatments
.

Manalis said: "Basically all anti-cancer drugs used clinically directly or indirectly prevent the growth of cancer cells
.

" "This is why we believe that measuring quality can provide a general interpretation of the mechanism of many different types of drugs

In the current study, the researchers verified the response of 69 patients with aggressive brain cancer (glioblastoma) neurosphere models to the chemotherapy drug temozolomide using existing matching data on patient survival and genomics.
A new method
.

This paper is entitled "Using single-cell clumps for functional drug susceptibility testing to predict the treatment outcome of the neurosphere model of patient-derived cancer
.

" The results of the study were published in the journal Cell Reports

Nearly 13,000 Americans are diagnosed with glioblastoma every year
.

Although radiotherapy and chemotherapy prolong survival, most patients will die within one to two years

Temozolomide is a drug that inhibits the progression of the cell cycle and is only effective for one of the two patients with glioblastoma
.

A gene methylation called MGMT is currently used to predict whether patients will respond to drugs, but due to other genetic factors, this marker cannot provide reliable predictions for all patients

In the new method, the team used a technique developed by the Manalis laboratory to allow single cells to flow through vibrating microchannels and weigh with extremely high accuracy
.

In an early study, the team used this technique to calculate the growth rate of individual cancer cells in glioblastoma and lymphoblastic leukemia over time after multiple treatments with one drug

The current research uses a simpler, faster, and high-throughput system that can measure the subtle changes in the mass distribution of single cells between drug-treated and untreated cancer cells to predict patient survival
.

The authors report that by simply measuring the quality of 2000 live glioblastoma cells before and after treatment with temozolomide, they can accurately predict whether a patient will respond to the drug

The authors point out that quality measurement is as accurate as MGMT methylation markers in predicting patient response to drugs, but it has the additional advantage of acting in patients whose genetic markers cannot reveal sensitivity to temozolomide
.

"Most cancers simply don't have genomic markers
that can be used .

We believe that this functional approach can work in the absence of any genomic marker selection," Manalis said

"Ideally, we would test the drugs that patients are most likely to get, but we would also test alternatives: Ligan also served as director of neuropathology at Brigham and Women's Hospital and Boston Children's Hospital.
Pathology consultant at Boston Children's Hospital
.

Manalis and Ligon co-founded a company called Travera, which licensed the technology
.
They hope that this method can be used to develop clinically validated laboratory tests to predict the best treatment options for patients
.