Impact of intratumor heterogeneity (ITH) on survival outcomes in patients with non-small cell lung cancer (NSCLC) with high tumor mutational burden (TMB-H)
ASCO 2024
Stanislav Fridland, Hye Sung Kim, Young Kwang Chae
Background: Heterogeneity among cancer cells within a tumor significantly impacts cancer development and resistance to treatment. Currently, no standard measure exists for assessing ITH in routine clinical settings. In this study, we applied a quantitative metric to assess intratumor genetic diversity in NSCLC, using a large, multicenter database.
Methods: We accessed the Tempus database for next-generation sequencing results from patients with NSCLC who underwent immune checkpoint inhibitor (ICIs) monotherapy as their first-line treatment. We calculated the mutant-allele tumor heterogeneity (MATH), defined as the ratio of the distribution’s range to the median of mutant-allele fractions across tumor-specific mutated loci. The primary outcomes were progression-free survival (PFS) and overall survival (OS).
Results: A total of 160 pembrolizumab Significant differences in PFS between high and low MATH groups (MATH-H and MATH-L, respectively), using the 50th percentile as the cutoff, were observed among patients with stage 4 adenocarcinoma who had TMB-H above the 25th percentile (Table). In this subgroup, with 27 patients in the MATH-H/TMB-H group and 22 in the MATH-L/TMB-H group, the MATH-H/TMB-H group showed improved PFS (median PFS 5.19 vs. 1.61 months; p = 0.02). Differences in PFS were also observed among patients with TP53, KEAP1, and MET mutations (p < 0.001, p = 0.02, and p = 0.004, respectively). TP53 mutations were found in 27.6% of the MATH-H group and 27.8% of the MATH-L group, KEAP1 mutations in 8.2% and 10.1%, respectively, and MET mutations in 5.1% and 8.9%, respectively. No significant PFS differences were found in groups with low TMB, other stages, or squamous histology.
Conclusions: Our findings suggest that higher genetic diversity within stage 4 TMB-H lung adenocarcinoma, as quantified by MATH, might be linked to improved clinical outcomes among those who receive pembrolizumab as first-line therapy and supports further exploration of MATH as a predictive/prognostic biomarker.
| MATH-H/TMB > 25th% | MATH-L/TMB > 25th% | P-value | MATH-H/TMB > 50th% | MATH-L/TMB > 50th% | P-value | MATH-H/TMB > 75th% | MATH-L/TMB > 75th% | P-value | |
|---|---|---|---|---|---|---|---|---|---|
| Age | |||||||||
| [Q1-Q3] | 73.0 [68.0-79.75] | 76.0 [71.0-83.0] | 0.35 | 73.0 [69.75-79.0] | 73.5 [66.75-81.0] | 0.85 | 75.0 [70.0-79.0] | 3.5 [59.0-83.0] | 0.73 |
| PFS [Q1-Q3] | 4.97 [2.71-11.23] | 2.34 [1.25-5.83] | 0.03 | 4.34 [2.5-9.05] | 2.68 [1.5-7.94] | 0.39 | 5.63 [3.0-14.73] | 4.06 [2.01-11.6] | 0.41 |
| OS | |||||||||
| [Q1-Q3] | 33.11 [24.38-43.58] | 27.53 [18.18-32.81] | 0.10 | 33.11 [27.13-44.23] | 27.92 [16.19-36.72] | 0.16 | 33.11 [30.02-43.58] | 27.92 [17.94-36.15] | 0.24 |
| TMB | |||||||||
| [Q1-Q3] | 8.83 [7.14-10.57] | 5.77 [4.96-7.48] | < 0.001 | 9.02 [7.4-11.05] | 8.84 [7.21-11.02] | 0.67 | 11.33 [9.4-12.86] | 11.31 [9.51-12.29] | 0.76 |
| MATH | |||||||||
| [Q1-Q3] | 60.83 [50.31-70.78] | 26.72 [18.11-37.11] | < 0.001 | 62.74 [56.17-70.61] | 39.12 [26.47-45.91] | < 0.001 | 61.84 [59.64-66.72] | 41.25 [33.85-45.66] | < 0.001 |
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