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McGill University Software Identifies Molecular Links in Tumor, Blood Transcription Profiles


NEW YORK (GenomeWeb) – Using newly-developed software called Matched Interactions across Tissues or MixT, an international team of researchers has shown links between molecular processes in breast cancer and immune system cells in the blood that they say could result in new ways to treat and monitor breast cancer.

The results move "the community beyond the barriers of most previous molecular studies that focused exclusively on immune cells in the tumor microenvironment," Vanessa Dumeaux, a senior researcher in the computational biology laboratory at Concordia University in Canada and the lead author on a PLOS Computational Biology paper describing MixT, said in statement. It provides "a broader picture of how our bodies and immune system respond to the challenges of the presence of a particular tumor."

MixT uses computational and statistical methods to find and investigate links between gene expression in different body tissues. For the current study, the researchers applied the software to tumor and blood transcriptional profiles from breast cancer patients in what they claim is the first large-scale effort to study the molecular relationships between patients' systemic immune response and primary tumors. According to the paper, their analysis showed active processes in patients' immune responses that were relevant to breast cancer immunogenicity and that varied according to the tumor subtype.

Dumeaux, who was a research scientist in the breast cancer informatics laboratory at McGill University at the time of the study, explained in an interview that the MixT study grew out of her long-standing interest in how the breast cancer environment influences disease diagnosis and prognosis. For the past 15 years, Dumeaux has been involved with the Norwegian Women and Cancer (NOWAC) study, which tracks 34 percent of all Norwegian women born between 1943 and 1957. The study, which launched in 1991, includes 170,000 women from Norway and has collected detailed data on their health and lifestyle, as well as a biobank of samples, including blood.

Previous studies have provided "several lines of evidence that show that tumor gene expression profile or DNA profile or even histology can tell us something about the disease and how harmful it is, but it doesn't give the whole picture," she said. "We wanted to investigate how the patient responds to the presence of a tumor and see how that response influences the prognosis of the disease. So the basic motivation [was] to zoom out and take the patient as a whole."

Moreover, while some existing studies have looked at gene-gene interactions within tumor cells and the immediate environment, no studies have looked at interactions between tumor gene expression and circulating blood cell gene expression. "[Since] blood contains immune cells … and immune cells are the first [responders] of the patient, we thought that [was] a good thing to focus on [to get a sense] of how patients respond," Dumeaux explained. Also, "we know that genes interact in groups to overexpress or underexpress the pathway, so we wanted to focus on a group of genes [rather] than a single gene to look at those interactions."

For the current study, Dumeaux and colleagues used MixT to analyze gene expression in blood and tumor samples from 173 breast cancer patients and 282 controls. They sought to explore whether genes that are tightly co-expressed in the primary tumor were also co-expressed in the patients' systemic response.

First, they profiled the tumor cells and blood cells independently — each profile measured the expression of 16,782 unique genes, according to the paper. The researchers then used the MixT software to group genes in an unsupervised manner, and then they annotated the genes to see if they were enriched for certain pathways. Lastly, the researchers looked for overlaps between groups of genes in pathways in tumor cells and in immune cells.

The researchers also found that many genes involved in immune-related processes, such as T-cell co-stimulation and inflammation, showed "very strong co-expression" in tumor genes. In addition, their analysis showed variations in immune response across tumor subtypes. "Not every tumor subtype will be associated the same way with the systemic response," Dumeaux said. "High inflammation in a certain subtype [could] mean low inflammation in blood compared to another [subtype] … it's not like one response fits all the subtypes." For example, the researchers found immune system-suppressing processes operating in conjunction with certain breast cancer subtypes, such as the basal breast cancer subtype, that were not present in other subtypes.

Furthermore, the study showed that what's found in the tumor profile may not be mirrored in the blood cells. For example, simply because a patient has high inflammation at the tumor site does not mean there will be high levels of inflammation in the blood cells. "That's very important for biomarker studies because we tend to think that if it's like this in the tumor, then it will be like this in blood cells, but that's not how it works, actually," Dumeaux said. Lastly, they also showed, unsurprisingly, that the systemic response of a breast cancer patient is important when the tumor subtype is highly immunogenic.

The importance of focusing on the systemic response, in addition to local immune activity, is crucial to ongoing efforts to develop more effective immunotherapies, as well as new cancer vaccines, Dumeaux noted. She believes a more in-depth study of the pathways that tumor and immune cells have in common could yield candidates for new therapies and treatments. Such therapies would "basically boost the systemic immunity that has been shut down in some way by the tumor," she said. Clinicians could also monitor patients' response to immunotherapies or standard therapies by looking at how immune pathways change in response to treatment.

Dumeaux also believes that clinicians can potentially use those same immune pathways to diagnose recurrence in the future. She pointed to a recent study in Cell by researchers at Stanford University and elsewhere that looked at the immune response in mice that received immunotherapy. That study showed that the mice responded well to therapy by looking at systemic immunity function post treatment. 

Dumeaux and her colleagues are now looking at applying the MixT methodology to different matched tissues, though she declined to provide details at this time. They also plan to publish a paper providing details about the underlying algorithms and methods used in the software at a later date.