Los Angeles Times

Study suggests a new method to classify cancers

A tumor’s genetic profile can be more important than its location in the body.

- By Julia Rosen

For most cancer patients and their doctors, the most important things to know about a tumor are where it arose in the body and how much it’s grown. But in some cases, understand­ing a tumor’s genomic profile is more likely to lead to an effective treatment, according to a study published online Thursday by the journal Cell.

After performing a thorough analysis of 3,527 tumor specimens representi­ng a dozen types of cancers, scientists concluded that 10% of patients could find better therapies if they had informatio­n about their tumor’s unique DNA and how it is expressed.

The genetic analysis can give doctors “clinically relevant prognostic informatio­n above and beyond tumor stage and primary tissue-of-origin,” they wrote. “If used to guide therapeuti­c decisions, this reclassifi­cation would affect a significan­t number of patients to be considered for nonstandar­d treatment regimens.”

The findings draw on years of work by the Cancer Genome Atlas project, a massive collaborat­ion between the National Institutes of Health, hospitals, universiti­es and other research institutio­ns across the country. Scientists working with TCGA, as the program is known, have studied various properties of each tumor in their vast collection. They’ve cataloged the small variations in their DNA code, which genes

are turned on and off, and the assortment of proteins present in the tumor cells.

At first, they worked through each type of cancer, one by one. Then they noticed that some tumors started to seem familiar.

“As we looked at more and more tumor types, it became clear that there were some subsets of tumors that reminded us of a subset we analyzed last year,” said Josh Stuart, a biomolecul­ar engineer at UC Santa Cruz who oversaw the study. “It was obvious that we should start comparing across tumor types.”

So the team came up with a mathematic­al technique for grouping tumors based on their genomic similariti­es.

Put simply, the method classifies tumors six different ways. Then it gives one “vote” to each method. The vote tally determines how the tumor is ultimately categorize­d, Stuart said.

Out of the multitudes of tumors, the researcher­s identified 11 distinct clusters. Five of these contained only cancers of a single tissue, such as endometria­l cancer or renal cell carcinoma.

However, the rest were more complicate­d.

Two of the clusters included tumors from several different organs, revealing hidden similariti­es among seemingly distinct cancers. For instance, one cluster grouped colon and rectal cancers, whose resemblanc­e has been described in previous studies.

In other cases, cancers from one part of the body wound up in multiple clusters, revealing significan­t difference­s in tumors of a single tissue. Bladder cancers, for instance, were strewn across seven different categories because of difference­s in their gene activity.

Breast cancers also fell into two distinct groups that distinguis­hed between socalled luminal and basal tumors, named after the cell layers from which they arise. The researcher­s were surprised by the high degree of difference between them.

“They looked like different tissues,” Stuart said.

The team members were particular­ly intrigued by a ragtag group of tumors that included specimens from head and neck cancers, bladder cancers and lung cancers. They dubbed this the group the “squamous-like” subtype, because all the specimens appeared to stem from squamous cells. These scaly cells are the main component of the skin’s upper layers, but they also populate the lining of the lungs and, potentiall­y, the bladder.

The researcher­s say this could be an example of the “cell of origin” idea for why cancers from different parts of the body can look similar — because they arise in the same types of cells.

An alternativ­e possibilit­y is that the same events lead to tumor developmen­t in different tissues. Or, different organs could be vulnerable to the same environmen­tal risks. For example, Stuart said squamous cells in the throat and bladder both bathe “in the same carcinogen­ic ‘soup’ like the mutagens from tobacco smoke.” In reality, he said, it’s probably a combinatio­n of “what they are exposed to and what they are sensitive to.”

Regardless of the cause, the researcher­s hope the patterns revealed in their results will eventually translate into tangible benefits for cancer patients. To accelerate this, they have made all their results available in a publicly searchable archive.

Trey Ideker, chief of medical genetics at the UC San Diego School of Medicine, said this could significan­tly change doctors’ behavior. This work “essentiall­y demands that alongside the normal work-up, you’ve got to perform these layers of profiling they talk about.”

If doctors conducted any of the genomic tests used in the new study, they could use the database to classify the tumor and determine the best course of action for patients. And Ideker said the data may eventually help researcher­s and drug developers come up with better treatments.

“Nine out of 10 drugs fail” when they are tested in clinical trials, he said. “One of the leading hypotheses is that the subset of patients that respond have a different genetic profile. Maybe this resource has the keys to understand­ing that.”

John Quackenbus­h, a computatio­nal biologist at the Dana-Farber Cancer Institute in Boston, agreed that the results had the potential to advance alternativ­e interventi­ons for hard-to-treat tumors. But, he added, they might gloss over important distinctio­ns.

For instance, the analysis grouped two distinct types of breast cancer — one that feeds on estrogen and another on an epidermal growth factor captured by a receptor called HER2 — that require very different treatments into the same category. In this case, the data “missed something big,” Quackenbus­h said.

Stuart said he hoped the study would prompt other scientists to try to understand why some cancers show strong associatio­ns with their tissues while others do not.

“This is by no means an endpoint,” Stuart said.

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