In a new study entitled “Beyond immune density: critical role of spatial heterogeneity in estrogen receptor-negative breast cancer,” researchers developed a new test based on automated spatial imaging and statistics that measures ER-negative breast cancer patients’ immune responses with increased accuracy by determining immune “hotspots” within the tumor. The study was published in the journal Modern Pathology.
Patients can be diagnosed with different types of breast cancer according to their response to certain hormones. While 75% of all breast cancers are positive for estrogen-receptor, i.e., its growth is dependent on the hormone estrogen and is associated with a good prognosis when treated with hormone therapy, estrogen-receptor (ER)-negative patients exhibit a poor prognosis.
In this study, a team of researchers at The Institute of Cancer Research in London analyzed tumor samples from 245 women with ER-negative breast cancer with a novel combination of tools: a high-throughput imaging analysis allied with a spatial statistics. While with the former technique the authors generated a spatial recognition of where within the tumor cancer and immune cells are localized, the latter method allowed researchers to detect and quantify immune “hotspots” (where there is a particular elevated concentration of these cells). Notably, understanding the spatial recognition of these immune hotspots in a systematic way is critical, since it is suggested that higher infiltration yields more favorable clinical outcomes of ER-negative breast cancer patients.
The team discovered that the immune response against tumors is better assessed by determining immune hotspots (where immune cells are surrounding cancer cells), rather then just measuring the total number of immune cells present within the tumor. When the team divided the participants in their study according to the numbers of immune hotspots detected, they observed women with high higher hotspots lived longer (approximately 91 months before cancer turned metastatic), when compared to those with lower numbers (an average of 64 months).
In light of this finding, the authors developed a new strategy that determines with increased accuracy patients’ immune responses against tumors, which can predict patients’ survival in a more accurate way.
Dr. Yinyin Yuan, principal investigator in the Computational Pathology and Integrative Genomics group at The Institute of Cancer Research and study lead author commented in a press release, “Our research is aiming to develop completely new ways of telling apart more and less aggressive cancers, based on how successful the immune system is in keeping tumors in check. We have shown that to measure the strength of an immune response to a cancer, we need to assess not just how many immune cells there are, but whether these are clustered together into cancer-busting hotspots. By analyzing the complex ways in which the immune system interacts with cancer cells, we can split women with breast cancer into two groups, who might need different types of treatment.”
Professor Paul Workman, Chief Executive, The Institute of Cancer Research, added, “This study has found an ingenious way to generate and understand data from images of biopsy samples, which are already taken from patients but not analyzed in a mathematical way. The interaction between the immune system and cancer is extraordinarily complex, and something we are only just beginning to understand. But just as there are high hopes for immunotherapy as a future cancer treatment, we also believe that this new way of measuring immune reaction could be used to tailor treatment more effectively to individual patients.”
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