Immune-Based Therapeutic Interventions for Acute Myeloid Leukemia

Perna, Fabiana; Espinoza-Gutarra, Manuel Ricardo; Bombaci, Giuseppe; Farag, Sherif; Schwartz, Jae C.

doi:10.1007/978-3-030-96376-7_8

Cited by 9 publications

(5 citation statements)

References 178 publications

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“…T cell mediated tumor killing sensitivity genes have shown strong prognostic value in several solid tumor types including lung adenocarcinoma, head and neck cancer and hepatocellular carcinoma (40,41,42). AML is highly heterogenous at the molecular level with low mutational burden, which is believed to underpin modest responses to antibody dependent checkpoint inhibitor therapy as compared to solid tumors and receptor independent T-cell directed therapies assumes high signi cance (43). Identifying GSTTK based tumor immunological subtypes can also be very valuable for predicting responses to checkpoint inhibitors and emerging immunotherapies such as CAR-T cell and bispeci c antibody therapy.…”

Section: Discussionmentioning

confidence: 99%

T Cell-Mediated Tumor Killing Sensitivity Gene Signature-Based Prognostic Score For Acute Myeloid Leukemia

Pan,

Xie,

Zeng

et al. 2024

Preprint

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Background and Objective: Acute myeloid leukemia (AML) is an aggressive, heterogenous hematopoetic malignancies with poor long-term prognosis. T-cell mediated tumor killing plays a key role in tumor immunity. Here, we explored the prognostic performance and functional significance of a T-cell mediated tumor killing sensitivity gene (GSTTK)-based prognostic score (TTKPI). Methods:Publicly available transcriptomic data for AML were obtained from TCGA and NCBI-GEO. GSTTK were identified from the TISIDB database. Signature GSTTK for AML were identified by differential expression analysis, COX proportional hazards and LASSO regression analysis and a comprehensive TTKPI score was constructed. Prognostic performance of the TTKPI was examined using Kaplan-Meier survival analysis, Receiver operating curves, and nomogram analysis. Association of TTKPI with clinical phenotypes, tumor immune cell infiltration patterns, checkpoint expression patterns were analysed. Drug docking was used to identify important candidate drugs based on the TTKPI-component genes. Results: From 401 differentially expressed GSTTK in AML, 24 genes were identified as signature genes and used to construct the TTKPI score. High-TTKPI risk score predicted worse survival and good prognostic accuracy with AUC values ranging from 75%-96%. Higher TTKPI scores were associated with older age and cancer stage, which showed improved prognostic performance when combined with TTKPI. High TTKPI was associated with lower naïve CD4 T cell and follicular helper T cell infiltrates and higher M2 macrophages/monocyte infiltration. Distinct patterns of immune checkpoint expression corresponded with TTKPI score groups. Three agents; DB11791 (Capmatinib), DB12886 (GSK-1521498) and DB14773 (Lifirafenib) were identified as candidates for AML. Conclusion: A T-cell mediated killing sensitivity gene-based prognostic score TTKPI showed good accuracy in predicting survival in AML. TTKPI corresponded to functional and immunological features of the tumor microenvironment including checkpoint expression patterns and should be investigated for precision medicine approaches.

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Section: Discussionmentioning

confidence: 99%

T Cell-Mediated Tumor Killing Sensitivity Gene Signature-Based Prognostic Score For Acute Myeloid Leukemia

Pan,

Xie,

Zeng

et al. 2024

Preprint

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“…T cell mediated tumor killing sensitivity genes have shown strong prognostic value in several solid tumor types including lung adenocarcinoma, head and neck cancer and hepatocellular carcinoma [ 48 , 64 , 65 ]. AML is highly heterogenous at the molecular level with low mutational burden, which is believed to underpin modest responses to antibody dependent checkpoint inhibitor therapy as compared to solid tumors and receptor independent T-cell directed therapies assumes high significance [ 66 ]. Identifying GSTTK based tumor immunological subtypes can also be very valuable for predicting responses to checkpoint inhibitors and emerging immunotherapies such as CAR T cell and bispecific antibody therapy.…”

Section: Discussionmentioning

confidence: 99%

T cell-mediated tumor killing sensitivity gene signature-based prognostic score for acute myeloid leukemia

Pan,

Xie,

Zeng

et al. 2024

Discov Onc

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Background and Objective Acute myeloid leukemia (AML) is an aggressive, heterogenous hematopoetic malignancies with poor long-term prognosis. T-cell mediated tumor killing plays a key role in tumor immunity. Here, we explored the prognostic performance and functional significance of a T-cell mediated tumor killing sensitivity gene (GSTTK)-based prognostic score (TTKPI). Methods Publicly available transcriptomic data for AML were obtained from TCGA and NCBI-GEO. GSTTK were identified from the TISIDB database. Signature GSTTK for AML were identified by differential expression analysis, COX proportional hazards and LASSO regression analysis and a comprehensive TTKPI score was constructed. Prognostic performance of the TTKPI was examined using Kaplan–Meier survival analysis, Receiver operating curves, and nomogram analysis. Association of TTKPI with clinical phenotypes, tumor immune cell infiltration patterns, checkpoint expression patterns were analysed. Drug docking was used to identify important candidate drugs based on the TTKPI-component genes. Results From 401 differentially expressed GSTTK in AML, 24 genes were identified as signature genes and used to construct the TTKPI score. High-TTKPI risk score predicted worse survival and good prognostic accuracy with AUC values ranging from 75 to 96%. Higher TTKPI scores were associated with older age and cancer stage, which showed improved prognostic performance when combined with TTKPI. High TTKPI was associated with lower naïve CD4 T cell and follicular helper T cell infiltrates and higher M2 macrophages/monocyte infiltration. Distinct patterns of immune checkpoint expression corresponded with TTKPI score groups. Three agents; DB11791 (Capmatinib), DB12886 (GSK-1521498) and DB14773 (Lifirafenib) were identified as candidates for AML. Conclusion A T-cell mediated killing sensitivity gene-based prognostic score TTKPI showed good accuracy in predicting survival in AML. TTKPI corresponded to functional and immunological features of the tumor microenvironment including checkpoint expression patterns and should be investigated for precision medicine approaches.

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“…Acute myeloid leukaemia (AML) is a highly aggressive and heterogeneous haematologic malignancy, deriving from the myeloid stem cell [1,2]. A better understanding of the molecular background of the disease is crucial for further enhancement of the current AML treatment and for improving relapse-free survival with novel therapies [3].…”

Section: Introductionmentioning

confidence: 99%

“…To date, in therapy-resistant or relapse post-allogenic stem cell transplantation settings, the response rate has been demonstrated to range from 22 to 72% [12][13][14]. This ambiguity may be caused by a higher heterogeneity and a lower mutational burden of AML compared to solid tumours [2]. There are also conflicting reports regarding the relationship between CTLA-4 ligands on the tumour cells-CD80/CD86 and the patients' clinical outcome.…”

Section: Introductionmentioning

confidence: 99%

Effects of Combinatory In Vitro Treatment with Immune Checkpoint Inhibitors and Cytarabine on the Anti-Cancer Immune Microenvironment in De Novo AML Patients

Bołkun,

Starosz,

Krętowska-Grunwald

et al. 2024

Cancers

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Despite substantial progress in the diagnostic and therapeutic procedures, acute myeloid leukaemia (AML) still constitutes a significant problem for patients suffering from its relapses. A comprehensive knowledge of the disease’s molecular background has led to the development of targeted therapies, including immune checkpoint inhibitors, and demonstrated beneficial effects on several types of cancer. Here, we aimed to assess in vitro the potential of the immune checkpoint blockage for supporting anti-cancer responses to the AML backbone therapy with cytarabine. PBMCs of AML patients were collected at admission and, following the therapy, eight complete remission (CR) and eight non-responders (NR) subjects were selected. We assessed the effects of the in vitro treatment of the cells with cytarabine and the immune checkpoint inhibitors: anti-CTLA-4, anti-PD-1, anti-PD-L1. The study protocol allowed us to evaluate the viability of the cancer and the immune cells, proliferation status, phenotype, and cytokine release. Anti-PD-L1 antibodies were found to exert the most beneficial effect on the activation of T cells, with a concomitant regulation of the immune balance through Treg induction. There was no direct influence on the blast cells; however, the modulation of the PD-1/PD-L1 axis supported the expansion of lymphocytes. Changes in the response between CR and NR patients might result from the differential expression of PD-1 and PD-L1, with lower levels in the latter group. The tested blockers appear to support the anti-cancer immune responses rather than directly improve the effects of cytarabine. In conclusion, checkpoint proteins’ modulators might improve the anti-cancer responses in the tumour environment.

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Immune-Based Therapeutic Interventions for Acute Myeloid Leukemia

Cited by 9 publications

References 178 publications

T Cell-Mediated Tumor Killing Sensitivity Gene Signature-Based Prognostic Score For Acute Myeloid Leukemia

T Cell-Mediated Tumor Killing Sensitivity Gene Signature-Based Prognostic Score For Acute Myeloid Leukemia

T cell-mediated tumor killing sensitivity gene signature-based prognostic score for acute myeloid leukemia

Effects of Combinatory In Vitro Treatment with Immune Checkpoint Inhibitors and Cytarabine on the Anti-Cancer Immune Microenvironment in De Novo AML Patients

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