Intra/intertumoral heterogeneity assessed by blood-based next generation sequencing (NGS) to predict inferior survival outcome compared to intratumoral heterogeneity assessed by tissue-based NGS in advanced stage non-small cell lung cancer (NSCLC).

e20550 Background: Intratumoral heterogeneity (ITH) refers to the presence of multiple, genetically diverse cell subpopulations within a single tumor. While higher heterogeneity has been linked to worse outcomes in various cancers, traditional tissue biopsies may not capture the full diversity. In contrast, blood biopsies can theoretically sample multiple tumor sites and thus offer a more comprehensive view of ITH. Methods: This study included advanced NSCLC patients who underwent both blood-based NGS (collected between October 2020 and February 2024) and tissue-based NGS before treatment. Using mutant-allele tumor heterogeneity (MATH) approach, both blood-based (bMATH) and tissue-based (tMATH) ITH were calculated, then performed survival analyses by dividing patients into tertiles based on bMATH, tMATH, and highest allele frequency (HAF) on blood-based NGS. Results: In total, 102 patients met the inclusion criteria, with 58 having sufficient data to compute bMATH and 51 for tMATH. The median follow-up period was 12 months. Treatment regimens included immune checkpoint inhibitor (ICI) therapy combined with chemotherapy (31 patients), ICIs alone (25), targeted therapy (35), and cytotoxic chemotherapy (11); 63 received first-line treatment, while 39 received second-line or beyond therapy. Median interval between blood NGS and the start of treatment was 15 days (interquartile range (IQR) 8-28). Median interval between tissue NGS and the start of treatment was 77 days (IQR 24-243). Those in the highest bMATH tertile (top 33%) exhibited numerically shorter progression-free survival (PFS) (p=0.06, mPFS 9 vs 29 mo, HR 0.49, 95% CI 0.23-1.05) than the two lower tertiles and no difference in overall survival (OS). By contrast, sorting patients by the top tertile of tMATH or HAF from blood-based NGS did not reveal notable differences in either OS or PFS. A moderate positive correlation emerged between bMATH and the ratio of blood TMB to tissue TMB (Spearman’s r = 0.33, p = 0.02). Conclusions: The findings indicate that higher intratumor heterogeneity measured by bMATH is associated with worse PFS in advanced NSCLC, whereas tMATH and HAF did not show significant prognostic value. This suggests that blood-based MATH may provide a more representative assessment of ITH. bMATH (1st) N 20 mOS (months, 95% CI) 9.5 (4-38) HR (95% CI) Ref. p-value Ref. bMATH (2nd &3rd) 38 15.0 (9-27) 0.68 (0.38 - 1.29) 0.23 bMATH (1st) N 20 mPFS (months, 95% CI) 9 (4-NR) HR (95% CI) Ref. p-value Ref. bMATH (2nd &3rd) 38 29 (10-NR) 0.49 (0.23-1.05) 0.06 tMATH (1st) N 17 mOS (months, 95% CI) 8 (4-NA) HR (95% CI) Ref. p-value Ref. tMATH (2nd &3rd) 34 12 (7-25) 0.89 (0.45-1.78) 0.75 tMATH (1st) N 17 mPFS (months, 95% CI) 38 (29-NR) HR (95% CI) Ref. p-value Ref. tMATH (2nd &3rd) 34 11 (9-NR) 1.64 (0.59-4.55) 0.34

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Publication Details

Journal
Journal of Clinical Oncology
Published
2025-05-28
DOI
https://doi.org/10.1200/jco.2025.43.16_suppl.e20550
Primary Topic
Cancer Genomics and Diagnostics
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article
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article

Intra/intertumoral heterogeneity assessed by blood-based next generation sequencing (NGS) to predict inferior survival outcome compared to intratumoral heterogeneity assessed by tissue-based NGS in advanced stage non-small cell lung cancer (NSCLC).

Seung Ah Yoo, Leeseul Kim, J KIM, Young Kwang Chae et al.
Journal of Clinical Oncology
Cancer Genomics and Diagnostics
article

Intra/intertumoral heterogeneity assessed by blood-based next generation sequencing (NGS) to predict inferior survival outcome compared to intratumoral heterogeneity assessed by tissue-based NGS in advanced stage non-small cell lung cancer (NSCLC).

Seung Ah Yoo, Leeseul Kim, J KIM, Young Kwang Chae, Jong-Woo Kim
article en

Abstract

e20550 Background: Intratumoral heterogeneity (ITH) refers to the presence of multiple, genetically diverse cell subpopulations within a single tumor. While higher heterogeneity has been linked to worse outcomes in various cancers, traditional tissue biopsies may not capture the full diversity. In contrast, blood biopsies can theoretically sample multiple tumor sites and thus offer a more comprehensive view of ITH. Methods: This study included advanced NSCLC patients who underwent both blood-based NGS (collected between October 2020 and February 2024) and tissue-based NGS before treatment. Using mutant-allele tumor heterogeneity (MATH) approach, both blood-based (bMATH) and tissue-based (tMATH) ITH were calculated, then performed survival analyses by dividing patients into tertiles based on bMATH, tMATH, and highest allele frequency (HAF) on blood-based NGS. Results: In total, 102 patients met the inclusion criteria, with 58 having sufficient data to compute bMATH and 51 for tMATH. The median follow-up period was 12 months. Treatment regimens included immune checkpoint inhibitor (ICI) therapy combined with chemotherapy (31 patients), ICIs alone (25), targeted therapy (35), and cytotoxic chemotherapy (11); 63 received first-line treatment, while 39 received second-line or beyond therapy. Median interval between blood NGS and the start of treatment was 15 days (interquartile range (IQR) 8-28). Median interval between tissue NGS and the start of treatment was 77 days (IQR 24-243). Those in the highest bMATH tertile (top 33%) exhibited numerically shorter progression-free survival (PFS) (p=0.06, mPFS 9 vs 29 mo, HR 0.49, 95% CI 0.23-1.05) than the two lower tertiles and no difference in overall survival (OS). By contrast, sorting patients by the top tertile of tMATH or HAF from blood-based NGS did not reveal notable differences in either OS or PFS. A moderate positive correlation emerged between bMATH and the ratio of blood TMB to tissue TMB (Spearman’s r = 0.33, p = 0.02). Conclusions: The findings indicate that higher intratumor heterogeneity measured by bMATH is associated with worse PFS in advanced NSCLC, whereas tMATH and HAF did not show significant prognostic value. This suggests that blood-based MATH may provide a more representative assessment of ITH. bMATH (1st) N 20 mOS (months, 95% CI) 9.5 (4-38) HR (95% CI) Ref. p-value Ref. bMATH (2nd &3rd) 38 15.0 (9-27) 0.68 (0.38 - 1.29) 0.23 bMATH (1st) N 20 mPFS (months, 95% CI) 9 (4-NR) HR (95% CI) Ref. p-value Ref. bMATH (2nd &3rd) 38 29 (10-NR) 0.49 (0.23-1.05) 0.06 tMATH (1st) N 17 mOS (months, 95% CI) 8 (4-NA) HR (95% CI) Ref. p-value Ref. tMATH (2nd &3rd) 34 12 (7-25) 0.89 (0.45-1.78) 0.75 tMATH (1st) N 17 mPFS (months, 95% CI) 38 (29-NR) HR (95% CI) Ref. p-value Ref. tMATH (2nd &3rd) 34 11 (9-NR) 1.64 (0.59-4.55) 0.34

Journal of Clinical OncologyVol. 43(16_suppl)
Northwestern University (US), University of Chicago (US), Northwestern Memorial Hospital (US), Catholic University of Korea (KR)
Openalex Percentile: Top 84%
Cancer Genomics and Diagnostics
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