Biopsy-to-Surgery TIL Dynamics Reveal Persistent Immune Infiltration in Residual Triple-Negative Breast Cancer

Breast cancer is not a single disease but a collection of different conditions, each with its own behavior and response to treatment. One particularly aggressive form, known as triple-negative breast cancer, lacks the specific receptors that many common drugs target, making it harder to treat. However, this type of cancer has a unique relationship with the body's immune system. Inside these tumors, the body often sends in its own defense forces: white blood cells called lymphocytes. Scientists have long known that the presence of these cells, which they call tumor-infiltrating lymphocytes, is generally a good sign. In many cases, a higher number of these immune cells before treatment begins is linked to a better outcome, suggesting the body is already fighting back. This observation led doctors to consider measuring these cells as a way to predict how well a patient might respond to therapy, especially when new treatments involving immune system boosters were introduced.

The central question for researchers has been whether simply counting these immune cells before treatment starts is enough to predict the future. Does a high count guarantee success, or is the story more complex? A new study from Sweden investigated this by looking at the immune landscape not just at the beginning, but also after treatment had finished. The researchers focused on patients who received either standard chemotherapy or a newer combination of chemotherapy and an immune-boosting drug called pembrolizumab. By comparing tissue samples taken before treatment with those taken after surgery, they sought to understand how the immune environment changed as the cancer responded to the drugs. Their work reveals that the story of the immune system is not static; it is a dynamic process where the direction of change matters just as much as the starting point.

The study examined tissue from 73 patients with triple-negative breast cancer. Half of these patients received standard chemotherapy, while the others received the newer combination therapy. For every patient, the team analyzed two specific samples: a small biopsy taken before any treatment began, and the larger surgical specimen removed after the treatment course was complete. In the lab, a specialist pathologist carefully counted the immune cells within the tissue samples, looking at the stroma, which is the supportive tissue surrounding the tumor cells. The goal was to see if the number of immune cells at the start could predict whether the cancer would disappear completely or leave behind some remaining disease.

The results showed that the initial count of immune cells was not a reliable crystal ball. The researchers found no clear connection between how many immune cells were present before treatment and how well the patient responded. Some patients with very high numbers of immune cells at the start still had cancer remaining after surgery, while others with lower numbers achieved a complete response. This suggests that looking at a single snapshot of the immune system before treatment begins does not tell the whole story about how the body will react to the drugs.

However, the picture changed dramatically when the researchers looked at what happened after treatment. They discovered that the immune landscape in the remaining tissue was strongly linked to the amount of cancer left behind. In patients whose cancer disappeared completely, the number of immune cells in the tissue dropped significantly from the pre-treatment biopsy to the post-surgery sample. It was as if the immune army, having successfully cleared the battlefield, began to stand down. In contrast, in patients who still had cancer remaining, the immune cells did not disappear. Instead, they often stayed at the same level or even increased in number. This persistent or growing presence of immune cells in the residual tumor suggested that the immune system was still engaged, but perhaps unable to finish the job or effectively control the remaining cancer cells.

This pattern held true regardless of whether the patient received standard chemotherapy or the newer combination therapy. The researchers calculated the difference between the before and after counts for each patient and found a clear trend: those who achieved a complete response saw a decline in immune cells, while those with residual disease saw stable or rising numbers. This indicates that the immune microenvironment evolves differently depending on the treatment outcome. The presence of many immune cells after treatment does not automatically mean the treatment worked; in fact, in this context, it often signaled that the cancer was still there.

The study also looked at how these immune changes related to other factors like the size of the remaining tumor and the stage of the disease. The findings reinforced that the change in immune cell numbers was closely tied to the burden of remaining cancer. While the researchers could not determine the exact reason why immune cells persisted in the resistant tumors, they noted that this observation challenges the simple idea that more immune cells always equal better immunity. It is possible that in these resistant cases, the immune cells are present but are not functioning correctly, or they are trapped in a state where they cannot destroy the cancer.

By comparing the before and after samples, the researchers were able to see the journey of the immune system through the treatment process. They found that the most successful outcomes were marked by a quieting of the immune response as the tumor vanished, whereas unsuccessful outcomes were marked by a continued, perhaps futile, immune presence. This distinction is crucial because it suggests that doctors might gain more insight by looking at how the immune system changes during therapy rather than just measuring it once at the start. The study concludes that the immune microenvironment in triple-negative breast cancer is not a fixed trait but a dynamic feature that shifts with treatment response, offering a new way to understand why some patients respond well while others do not.