Predictive value of ENLIGHT-DP in patients with metastatic lung adenocarcinoma treated with immune checkpoint inhibitors and platinum chemotherapy directly from histopathology slides using inferred transcriptomics
Introduction Immune checkpoint inhibitors (ICI) have improved outcomes in non-small cell lung cancer (NSCLC). Nevertheless, the clinical benefit of ICI as monotherapy or in combination with chemotherapy remains widely varied and existing biomarkers have limited predictive value. We present an analys...
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BMJ Publishing Group
2025-01-01
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| Series: | Journal for ImmunoTherapy of Cancer |
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| author | Eli Pikarsky Anna Elia Gal Dinstag Omer Tirosh Tuvik Beker Ranit Aharonov Hovav Nechushtan Leon Gugel Yaron Kinar Michael Tabi Tzivia Gottlieb Aron Popovtzer Johnathan Arnon Yakir Rottenberg Philip Blumenfeld |
| author_facet | Eli Pikarsky Anna Elia Gal Dinstag Omer Tirosh Tuvik Beker Ranit Aharonov Hovav Nechushtan Leon Gugel Yaron Kinar Michael Tabi Tzivia Gottlieb Aron Popovtzer Johnathan Arnon Yakir Rottenberg Philip Blumenfeld |
| author_sort | Eli Pikarsky |
| collection | DOAJ |
| description | Introduction Immune checkpoint inhibitors (ICI) have improved outcomes in non-small cell lung cancer (NSCLC). Nevertheless, the clinical benefit of ICI as monotherapy or in combination with chemotherapy remains widely varied and existing biomarkers have limited predictive value. We present an analysis of ENLIGHT-DP, a novel transcriptome-based biomarker directly from histopathology slides, in patients with lung adenocarcinoma (LUAD) treated with ICI and platinum-based chemotherapy.Methods We retrospectively scanned high-resolution H&E slides from pretreatment tumor-tissue samples of 50 patients with metastatic LUAD treated with first-line ICI with (46) or without (4) platinum-based chemotherapy and applied our ENLIGHT-DP pipeline to generate, in a blinded manner, an individual prediction score. ENLIGHT-DP predicts response to ICI and targeted therapies given H&E slide scans in two steps: (1) predict individual messenger RNA expression directly from high-resolution H&E scanned slides using DeepPT, a digital-pathology-based algorithm. (2) Use these values as input to ENLIGHT, a transcriptome-based platform that predicts response to ICI and targeted therapies derived from drug-specific networks of gene expressions. We then unblinded the clinical outcomes and evaluated the predictive value of ENLIGHT-DP in comparison to programmed death ligand (PD-L)-1 and tumor mutational burden (TMB).Results ENLIGHT-DP is predictive of response to treatment with receiver operating characteristic (ROC) area under the curve (AUC) of 0.69 (p=0.01) and outperforms both TMB and PD-L1 expression with ROC AUC of 0.52 and 0.46, respectively. Using a predetermined binary cut-off (established on independent cohorts) for patients predicted to respond to ICI, ENLIGHT-DP achieves 100% positive predictive value (PPV) and 44% sensitivity, superior to both PD-L1>50% (65% PPV and 38% sensitivity) and TMB-high (82% PPV and 26% sensitivity). ENLIGHT-DP was highly predictive in PD-L1<1% and TMB-low outlier groups with ROC AUC of 0.88 and 0.80, respectively (p value<0.05). ENLIGHT-DP is the only biomarker in this cohort significantly correlated with progression-free survival (HR: 0.45, 95% CI: 0.2 to 0.99, p=0.048).Conclusion We demonstrate the application of ENLIGHT-DP, a transcriptome-based biomarker for accurate prediction of treatment of LUAD with ICI and platinum-based chemotherapy, outperforming PD-L1 and TMB, and relying solely on accessible H&E scanned slides. Further studies on different tumor types, ICI monotherapy and bigger NSCLC cohorts are warranted. |
| format | Article |
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| institution | Kabale University |
| issn | 2051-1426 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | BMJ Publishing Group |
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| series | Journal for ImmunoTherapy of Cancer |
| spelling | doaj-art-3db18ee966054ef3bbf77c0979de93732025-01-14T23:20:13ZengBMJ Publishing GroupJournal for ImmunoTherapy of Cancer2051-14262025-01-0113110.1136/jitc-2024-010132Predictive value of ENLIGHT-DP in patients with metastatic lung adenocarcinoma treated with immune checkpoint inhibitors and platinum chemotherapy directly from histopathology slides using inferred transcriptomicsEli Pikarsky0Anna Elia1Gal Dinstag2Omer Tirosh3Tuvik Beker4Ranit Aharonov5Hovav Nechushtan6Leon Gugel7Yaron Kinar8Michael Tabi9Tzivia Gottlieb10Aron Popovtzer11Johnathan Arnon12Yakir Rottenberg13Philip Blumenfeld14The Lautenberg Center for Immunology and Cancer Research, Hebrew University of Jerusalem Faculty of Medicine, Jerusalem, IsraelPathology, Hadassah Medical Center, Jerusalem, IsraelPangea Biomed, Tel Aviv, Israel2 Pangea Biomed, Tel Aviv, Israel2 Pangea Biomed, Tel Aviv, Israel1Pangea Biomed, Tel Aviv, IsraelOncology, Hadassah Medical Center, Jerusalem, Israel1Pangea Biomed, Tel Aviv, Israel1Pangea Biomed, Tel Aviv, Israel2Hadassah Medical Center and Faculty of Medicine in Hebrew University of Jerusalem, Jerusalem, Israel1Pangea Biomed, Tel Aviv, Israel2Hadassah Medical Center and Faculty of Medicine in Hebrew University of Jerusalem, Jerusalem, Israel2Hadassah Medical Center and Faculty of Medicine in Hebrew University of Jerusalem, Jerusalem, IsraelSharett Institue of Oncology, Hadassah Hebrew University Medical Center, Jerusalem, IsraelSharett Institue of Oncology, Hadassah Hebrew University Medical Center, Jerusalem, IsraelIntroduction Immune checkpoint inhibitors (ICI) have improved outcomes in non-small cell lung cancer (NSCLC). Nevertheless, the clinical benefit of ICI as monotherapy or in combination with chemotherapy remains widely varied and existing biomarkers have limited predictive value. We present an analysis of ENLIGHT-DP, a novel transcriptome-based biomarker directly from histopathology slides, in patients with lung adenocarcinoma (LUAD) treated with ICI and platinum-based chemotherapy.Methods We retrospectively scanned high-resolution H&E slides from pretreatment tumor-tissue samples of 50 patients with metastatic LUAD treated with first-line ICI with (46) or without (4) platinum-based chemotherapy and applied our ENLIGHT-DP pipeline to generate, in a blinded manner, an individual prediction score. ENLIGHT-DP predicts response to ICI and targeted therapies given H&E slide scans in two steps: (1) predict individual messenger RNA expression directly from high-resolution H&E scanned slides using DeepPT, a digital-pathology-based algorithm. (2) Use these values as input to ENLIGHT, a transcriptome-based platform that predicts response to ICI and targeted therapies derived from drug-specific networks of gene expressions. We then unblinded the clinical outcomes and evaluated the predictive value of ENLIGHT-DP in comparison to programmed death ligand (PD-L)-1 and tumor mutational burden (TMB).Results ENLIGHT-DP is predictive of response to treatment with receiver operating characteristic (ROC) area under the curve (AUC) of 0.69 (p=0.01) and outperforms both TMB and PD-L1 expression with ROC AUC of 0.52 and 0.46, respectively. Using a predetermined binary cut-off (established on independent cohorts) for patients predicted to respond to ICI, ENLIGHT-DP achieves 100% positive predictive value (PPV) and 44% sensitivity, superior to both PD-L1>50% (65% PPV and 38% sensitivity) and TMB-high (82% PPV and 26% sensitivity). ENLIGHT-DP was highly predictive in PD-L1<1% and TMB-low outlier groups with ROC AUC of 0.88 and 0.80, respectively (p value<0.05). ENLIGHT-DP is the only biomarker in this cohort significantly correlated with progression-free survival (HR: 0.45, 95% CI: 0.2 to 0.99, p=0.048).Conclusion We demonstrate the application of ENLIGHT-DP, a transcriptome-based biomarker for accurate prediction of treatment of LUAD with ICI and platinum-based chemotherapy, outperforming PD-L1 and TMB, and relying solely on accessible H&E scanned slides. Further studies on different tumor types, ICI monotherapy and bigger NSCLC cohorts are warranted.https://jitc.bmj.com/content/13/1/e010132.full |
| spellingShingle | Eli Pikarsky Anna Elia Gal Dinstag Omer Tirosh Tuvik Beker Ranit Aharonov Hovav Nechushtan Leon Gugel Yaron Kinar Michael Tabi Tzivia Gottlieb Aron Popovtzer Johnathan Arnon Yakir Rottenberg Philip Blumenfeld Predictive value of ENLIGHT-DP in patients with metastatic lung adenocarcinoma treated with immune checkpoint inhibitors and platinum chemotherapy directly from histopathology slides using inferred transcriptomics Journal for ImmunoTherapy of Cancer |
| title | Predictive value of ENLIGHT-DP in patients with metastatic lung adenocarcinoma treated with immune checkpoint inhibitors and platinum chemotherapy directly from histopathology slides using inferred transcriptomics |
| title_full | Predictive value of ENLIGHT-DP in patients with metastatic lung adenocarcinoma treated with immune checkpoint inhibitors and platinum chemotherapy directly from histopathology slides using inferred transcriptomics |
| title_fullStr | Predictive value of ENLIGHT-DP in patients with metastatic lung adenocarcinoma treated with immune checkpoint inhibitors and platinum chemotherapy directly from histopathology slides using inferred transcriptomics |
| title_full_unstemmed | Predictive value of ENLIGHT-DP in patients with metastatic lung adenocarcinoma treated with immune checkpoint inhibitors and platinum chemotherapy directly from histopathology slides using inferred transcriptomics |
| title_short | Predictive value of ENLIGHT-DP in patients with metastatic lung adenocarcinoma treated with immune checkpoint inhibitors and platinum chemotherapy directly from histopathology slides using inferred transcriptomics |
| title_sort | predictive value of enlight dp in patients with metastatic lung adenocarcinoma treated with immune checkpoint inhibitors and platinum chemotherapy directly from histopathology slides using inferred transcriptomics |
| url | https://jitc.bmj.com/content/13/1/e010132.full |
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