Role of genomic instability in immunotherapy with checkpoint inhibitors.

Yaghmour, George; Pandey, Manjari; Ireland, Catherine G.; Patel, Kruti; Nunnery, Sarah Elizabeth; Powell, Daniel J.; Baum, Scott; Wiedower, Eric; Schwartzberg, Lee S.; Martin, Michael

doi:10.1200/jco.2016.34.15_suppl.3052

Cited by 15 publications

(24 citation statements)

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“…Several lines of evidence point to increased efficacy of these strategies in malignant clones with high levels of genomic instability [98]. These genetically unstable malignant clones create higher levels of neo-antigens which can stimulate immune recognition of the malignant clone [99].…”

Section: Biologic Mechanisms For Flt3 Itd Genomic Instabilitymentioning

confidence: 99%

Genomic instability is a principle pathologic feature of FLT3 ITD kinase activity in acute myeloid leukemia leading to clonal evolution and disease progression

Rebechi

Pratz

2017

Leukemia & Lymphoma

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Acute Myeloid Leukemia with FLT3 ITD mutations are associated with a poor prognosis characterized by a higher relapse rate, shorter relapse free survival, and decreased likelihood of response to therapy at relapse. FLT3 ITD signaling drives cell proliferation and survival. FLT3 ITD AML disease progression is associated with cytogenetic evolution and acquired tyrosine kinase inhibitor (TKI) resistance suggesting a potential role of genomic instability. There is growing evidence demonstrating a relationship between FLT3 signaling and increased DNA damage, specifically through increased reactive oxygen species (ROS) resulting in double strand breaks (DSB), as well as impaired DNA repair, involving deficiencies in the non-homologous end joining (NHEJ), alternative non-homologous end joining (ALT NHEJ) and homologous recombination (HR) pathways. The role of genomic instability in the pathogenesis of FLT3 ITD AML warrants further examination as it offers potential therapeutic targets.

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Section: Biologic Mechanisms For Flt3 Itd Genomic Instabilitymentioning

confidence: 99%

Genomic instability is a principle pathologic feature of FLT3 ITD kinase activity in acute myeloid leukemia leading to clonal evolution and disease progression

Rebechi

Pratz

2017

Leukemia & Lymphoma

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“…Roszik et al [34] also found that OS was higher in patients treated with ipilimumab who had a high predicted TMB (> 100) compared to those with a low predicted TMB (≤100). Johnson et al [33] and Yaghmour et al [28] found that patients with a high TMB had higher OS and PFS than those with intermediate TMB or low TMB treated with nivolumab, pembrolizumab, or atezolizumab.…”

Section: Discussionmentioning

confidence: 99%

“…Finally, Yaghmour et al [28] investigated patients who had solid tumors, were treated with any checkpoint inhibitor, and had undergone next-generation sequencing. This study reported that OS was significantly higher in patients who were in the top quintile for TMB (hazard ratio [HR] = 5.78; 95% CI, 1.40-15.12).…”

Section: Nsclcmentioning

confidence: 99%

“…Yaghmour et al [28] reported that OS was higher in patients with a TMB in the top quintile (median genomic alterations = 16.5) than OS in patients with a TMB in the lower quintiles (median genomic alterations = 2) (HR = 3.29; 95% CI, 0.75-25.53). Patients were treated with nivolumab, pembrolizumab, or ipilimumab.…”

Section: Melanomamentioning

confidence: 99%

“…Roszik et al [34] also found that OS was higher in patients treated with ipilimumab who had a high predicted TMB (> 100) compared to those with a low predicted TMB (≤100) (median = undefined vs 582 days, P < 0.006). Additionally, Johnson et al [33] and Yaghmour et al [28] found that patients with a high TMB (> 23.1 mutations/ megabase) had higher OS and PFS than those with intermediate TMB (3.3-23.1 mutations/megabase) or low TMB (< 3.3 mutations/megabase) (OS: median = not reached vs. 300 days vs. 375 days, P < 0.001; PFS: median = not reached vs. 89 days vs. 86 days, P < 0.001). Patients were treated with nivolumab, pembrolizumab, or atezolizumab.…”

Section: Melanomamentioning

confidence: 99%

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Targeted literature review on use of tumor mutational burden status and programmed cell death ligand 1 expression to predict outcomes of checkpoint inhibitor treatment

Krieger¹,

Pearson²,

Bell³

et al. 2020

Diagn Pathol

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Background: To achieve optimal outcomes, an individual approach is needed in the treatment and care of patients. The potential value of tumor mutational burden (TMB) status and/or programmed cell death ligand 1 (PD-L1) expression as biomarkers to predict which patients are most likely to respond to checkpoint inhibitors has been explored in many studies. The goal of this targeted literature review is to identify data available for TMB status and/or PD-L1 expression that predict response to checkpoint inhibitors and/or anti-cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) antibodies. Methods: Targeted literature searches were performed using electronic medical databases (MEDLINE, Embase, and BIOSIS) and internet searches of specified sites. Bibliographies of key systematic literature reviews and meta-analyses also were reviewed for studies of interest.Results: The review identified 27 studies of non-small cell lung cancer (NSCLC), 40 studies of melanoma, 10 studies of urothelial cancer, and 5 studies of renal cell cancer indications. Studies also were identified in other cancer types, e.g., colorectal, breast, gastric, and Merkel cell cancer and squamous-cell carcinoma of the head and neck. Twelve trials, including six in NSCLC and four in melanoma, evaluated TMB as a predictor of outcomes. A TMB of ≥10 mutations per megabase was shown to be an effective biomarker in the CheckMate 227 study. PD-L1 expression was included in the majority of identified studies and was found to predict response in in melanoma and in all types of NSCLC. Prediction of response was not a prespecified analysis in some studies; others had small sample sizes and wide confidence intervals. A clear predictive trend for PD-L1 expression was not identified in renal, breast, gastric, or Merkel cell cancer.Conclusion: Based on data contained in this review, assessment of TMB status and PD-L1 expression may help enhance the prediction of response to checkpoint inhibition in some tumors, such as NSCLC and melanoma. In this rapidly growing area of research, further exploratory biomarkers are being investigated including tumor-infiltrating lymphocytes, immune profiling (e.g., effector T cells or regulatory T cells), epigenetic signatures, T-cell receptor repertoire, proteomics, microbiome, and metabolomics.

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Biochemical Aspects of PD-L1 Regulation in Cancer Immunotherapy

Zhang

Dang

Ren

et al. 2018

Trends in Biochemical Sciences

171

126

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PD-L1, frequently expressed in human cancers, engages with PD-1 on immune cells and contributes to cancer immune evasion. As such, antibodies blocking the PD-1/PD-L1 interaction reactivate cytotoxic T cells to eradicate cancer cells. However, a majority of cancer patients fail to respond to PD-1/PD-L1 blockade with unclear underlying mechanism(s). Recent studies revealed that PD-L1 expression levels on tumor cells might affect the clinical response to anti-PD-1/PD-L1 therapies. Hence, understanding molecular mechanisms for controlling PD-L1 expression will be important to improve the clinical response rate and efficacy of PD-1/PD-L1 blockade. In this review, we primarily focus on summarizing PD-L1 regulation and its potential roles in regulating anti-tumor immune response, with purpose to optimize anti-PD-1/PD-L1 therapies, benefiting a wider cancer patient population.

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Role of genomic instability in immunotherapy with checkpoint inhibitors.

Cited by 15 publications

References 0 publications

Genomic instability is a principle pathologic feature of FLT3 ITD kinase activity in acute myeloid leukemia leading to clonal evolution and disease progression

Genomic instability is a principle pathologic feature of FLT3 ITD kinase activity in acute myeloid leukemia leading to clonal evolution and disease progression

Targeted literature review on use of tumor mutational burden status and programmed cell death ligand 1 expression to predict outcomes of checkpoint inhibitor treatment

Biochemical Aspects of PD-L1 Regulation in Cancer Immunotherapy

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