How a combination of inflammation and nutrition markers can identify patients who won't benefit from immunotherapy
The advent of immunotherapy has fundamentally transformed melanoma treatment, turning a diagnosis that was once a near-certain death sentence into a manageable condition for many. Drugs like nivolumab (marketed as Opdivo) work by releasing the natural brakes on the immune system, empowering the body's own T-cells to recognize and destroy cancer cells.
For some patients, this approach leads to remarkable, long-lasting remissions. The 10-year results from the landmark CheckMate 067 trial show just how profound this effect can be: the median overall survival for patients treated with a nivolumab-containing regimen was 71.9 months, a dramatic improvement over the older standard of care 3 .
However, this breakthrough comes with a significant catch. Immunotherapy doesn't work for everyone. Approximately 34% of patients experience early disease progression within the first 60 days of starting treatment, deriving no benefit while still being exposed to potential side effects 1 . This reality has created an urgent quest in oncology: finding a way to predict who will respond to treatment before it begins.
Anti-PD-1 checkpoint inhibitor that enables the immune system to attack melanoma cells by blocking the PD-1 pathway.
In the context of cancer treatment, "early progressive disease" (EPD) is precisely defined. For melanoma patients on nivolumab, it means that their cancer continues to grow or spread within the first 60 days of starting therapy, as measured by standardized criteria 1 .
Immunotherapy can cause severe immune-related adverse effects that impact various organ systems.
For patients with aggressive disease, weeks spent on an ineffective treatment can be costly.
Identifying non-responders early allows oncologists to pivot more quickly to other options.
In 2019, a crucial study published in the International Journal of Clinical Oncology provided a major advance in solving this prediction problem. Researchers conducted a retrospective analysis of 39 patients with unresectable melanoma who were treated with nivolumab 1 .
The study included 39 consecutive patients with either cutaneous (17 patients) or mucosal (22 patients) melanoma, all treated with nivolumab 1 .
Researchers defined EPD as disease progression within 60 days according to standardized solid tumor response criteria 1 .
The team investigated multiple potential biomarkers, focusing particularly on measures of inflammatory and nutritional status.
Using multivariate analysis, they identified which factors independently correlated with early progression, then developed a simple index score based on these factors 1 .
The analysis revealed two powerful predictors of early progression:
The researchers combined these two measures to create the Melanoma Inflammation Index (MII) - a simple 0-2 score based on how many of these risk factors a patient has.
| MII Score | Risk Category | Risk Factors | Early Progression Rate |
|---|---|---|---|
| 0 | Low Risk | None | 0% |
| 1 | Intermediate Risk | One | 50% |
| 2 | High Risk | Both (Low BMI + High CAR) | 83% |
EPD = Early Progressive Disease 1
The power of the MII score lies in how its components reflect the underlying biology of cancer:
This protein increases in response to inflammation. Cancer creates an inflammatory environment that can suppress immune cell function and promote tumor growth. A high CRP suggests this hostile environment is active, making it harder for immunotherapy to work 1 .
This key blood protein reflects nutritional status. Low levels indicate cachexia - the wasting syndrome often seen in advanced cancer where the body breaks down muscle and fat. This metabolic state hinders the immune system's ability to mount an effective attack 1 .
A low BMI (<20) often correlates with poor nutrition and cancer-related wasting, reinforcing the message that the body's resources are depleted 1 .
In essence, the MII captures a crucial reality: the success of immunotherapy depends not only on the drug's mechanism but on the patient's underlying physiological state. A body battling inflammation and nutritional depletion has fewer resources to mount an effective anti-cancer immune response, even when the brakes on the immune system have been released.
While the MII represents a significant advance, it's part of a broader landscape of biomarker research. Scientists are investigating multiple approaches to predict immunotherapy outcomes:
Cancers with more genetic mutations may be more visible to the immune system. Studies have confirmed that higher TMB correlates with better response to combination immunotherapy .
This protein, sometimes found on tumor cells, can inhibit immune attacks. Its relationship with outcomes is complex, but tumors with higher PD-L1 expression generally respond better to PD-1 inhibitors like nivolumab .
The presence of immune cells within tumors suggests the immune system is already engaged. "Brisk" TIL patterns (diffuse infiltration) are associated with better survival outcomes 5 .
| Biomarker | What It Measures | Predictive Value |
|---|---|---|
| MII Score | Patient's inflammatory & nutritional status | High MII predicts early progression on nivolumab |
| Tumor Mutation Burden | Number of mutations in tumor DNA | Higher TMB correlates with better immunotherapy response |
| PD-L1 Expression | Presence of PD-L1 protein on tumor cells | Higher expression generally predicts better response to anti-PD-1 drugs |
| BRAF Mutation | Specific genetic mutation in melanoma | Does not reliably predict immunotherapy response; important for targeted therapy |
The MII score exemplifies a shift toward more personalized cancer care. By using simple, readily available clinical measures, it helps identify patients unlikely to benefit from standard immunotherapy, potentially sparing them unnecessary toxicity and allowing earlier transition to alternative treatments.
Such as fianlimab (LAG-3 inhibitor) + cemiplimab, showing a 57% response rate in early trials 2 .
Including tumor-infiltrating lymphocyte (TIL) therapy and engineered TCR-T cells 2 .
The quest to predict immunotherapy success continues, but the MII score represents a significant step forward - demonstrating that sometimes, the most powerful insights come not from complex genetic analyses, but from thoughtful interpretation of simple clinical measures that reflect the fundamental battle between cancer and the human body that hosts it.