When a patient is newly diagnosed with breast cancer, one of the most commonly asked questions relates to their prognosis. Determining prognosis in these patients is based on multiple factors, including age, race, receptor expression, biomarkers, tumor stage, and genetics.1,2 These prognostic factors should ideally have substantial prospective and retrospective clinical data to support their validity and reproducibility.3 In addition, the factors should be readily available to most patients and physicians and be easily interpretable.

These prognostic factors can help health care professionals provide more concrete numbers to patients regarding mortality and recurrence risk. Most patients with breast cancer who recur will do so within the first 5 years after diagnosis. The highest risk of recurrence is typically between the first and second year after diagnosis; the recurrence rate is 15.2%, with an overall annual risk of 10.4% during the first 5 years.4 If patients show no evidence of recurrence after 5 years, they still have a risk of recurrence of up to 19% for an additional decade.5

As clinical trial data continue to accumulate in breast cancer,there is a constant search for additional prognostic markers that could potentially improve therapy and better predict patient outcomes.

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One new prognostic marker that is gaining steam is tumor-infiltrating lymphocytes (TILs).6 Prior studies have evaluated the role of measuring the amount of immune cells within the breast tissue by using hematoxylin and eosin (H&E) staining. Higher numbers of TILs seen in both early-stage triple-negative breast cancer (TNBC) and human epidermal growth factor receptor 2 (HER2)-positive breast cancers have been associated with better clinical outcomes.7 As the immunotherapy landscape continues to evolve, there is interest in whether the immune system could be playing a more substantial role in breast cancer.

Loi and colleagues set out to evaluate the prognostic value of TILs in TNBC by conducting a pooled analysis of 9 studies that had reported the percentage infiltration of stromally located TILs (sTILs).

The 9 studies analyzed included 2148 patients. The mean patient age was 50 years, with one-third of the patients determined to be node negative. The mean sTILs level was 23%, however, there was a relatively high standard deviation of 20% (range, 0%-95%).  The median sTILs was 15% (interquartile range10%-30%). Lower levels of sTILs were found in older patients (P =.001), lower histologic grade (P =.001), patients with more nodal involvement (P =.02) and more extensive tumor burden (P =.01). Specific quantities/levels of sTILs were not provided in the main article.

In addition, the study evaluated the prognostic value of sTILs by calculating the invasive disease-free survival (iDFS) as the primary end point along with the distant disease-free survival (D-DFS) and overall survival (OS) as the secondary end points. Each 10% increment increase in sTILs showed statistically significant improvement in these end points based on hazard ratios (HRs): iDFS 0.87 (95% CI, 0.83-0.91), D-DFS 0.83 (95% CI, 0.79-0.88) and OS 0.84 (95% CI 0.79-0.89). When the authors chose a cutoff of sTILs or at least 30% in node-negative patients, there was a correlation with the 3-year prognostic values: iDFS 92% (95% CI, 89%-98%), D-DFS 97% (95% CI, 95%-99%) and OS 99% (95% CI, 97%-100%).

Based on these data, the authors suggested that sTILs be incorporated into routine use for TNBC prognostication as a reliable biomarker. As more studies continue to collect information on sTILs in clinical trials, it will be interesting to see if the data remain reproducible, as well as how quickly it may be incorporated into future oncology guidelines and in clinical use.

References

  1. Gasparini G, Pozza F, Harris AL. Evaluating the potential usefulness of new prognostic and predictive indicators in node-negative breast cancer patients. J Natl Cancer Inst. 1993;85(15):1206–1219.
  2. Hayes DF, Trock B, Harris AL. Assessing the clinical impact of prognostic factors: when is “statistically significant” clinically useful? Breast Cancer Res Treat. 1998;52(1-3):305-319.
  3. Sargent DJ, Conley BA, Allegra C, Collette L. Clinical trial designs for predictive marker validation in cancer treatment trials. J Clin Oncol. 2005;23(9):2020.
  4. Colleoni M, Sun Z, Price KN, et al. Annual hazard rates of recurrence for breast cancer during 24 years of follow-up: results from the International Breast Cancer Study Group Trials I to V. J Clin Oncol. 2016;34(9):927–935.
  5. Brewster AM, Hortobagyi GN, Broglio KR, et al. Residual risk of breast cancer recurrence 5 years after adjuvant therapy. J Natl Cancer Inst. 2008;100(16):1179–1183.
  6. Loi S, Drubat D, Adams S, et al. Tumor-infiltrating lymphocytes and prognosis: a pooled individual patient analysis of early-stage triple-negative breast cancers. J Clin Oncol. 2019;37(7):559-569.
  7. Savas P, Salgado R, Denkert C, et al. Clinical relevance of host immunity in breast cancer: from TILs to the clinic. Nat Rev Clin Oncol. 2016;13(4):228-241.