Evaluating the impact of age on immune checkpoint therapy biomarkers

Erbe, Rossin; Wang, Zheyu; Wu, Sharon; Xiu, Joanne; Zaidi, Neeha; La, Jennifer; Tuck, David; Fillmore, Nathanael; Giraldo, Nicolás A.; Topper, Michael J.; Baylin, Stephen B.; Lippman, Marc E.; Isaacs, Claudine; Basho, Reva; Serebriiskii, Ilya G.; Lenz, Heinz‐Josef; Astsaturov, Igor; Marshall, John L.; Taverna, Josephine A.; Lee, Jerry; Jaffee, Elizabeth M.; Torres, Evanthia T. Roussos; Weeraratna, Ashani T.; Easwaran, Hariharan; Fertig, Elana J.

doi:10.1016/j.celrep.2021.109599

Cited by 41 publications

(40 citation statements)

References 63 publications

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“…Further, since the TMB and age showed positive interaction, older patients had relatively higher TMB. This is consistent with a recent study showing that TMB increases with age, while the T cell receptor decreases (49). This provides unique insights into clinical prognostic diagnosis.…”

Section: Discussionsupporting

confidence: 92%

Immune subtype identification and multi-layer perceptron classifier construction for breast cancer

et al. 2022

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IntroductionBreast cancer is a heterogeneous tumor. Tumor microenvironment (TME) has an important effect on the proliferation, metastasis, treatment, and prognosis of breast cancer.MethodsIn this study, we calculated the relative proportion of tumor infiltrating immune cells (TIICs) in the breast cancer TME, and used the consensus clustering algorithm to cluster the breast cancer subtypes. We also developed a multi-layer perceptron (MLP) classifier based on a deep learning framework to detect breast cancer subtypes, which 70% of the breast cancer research cohort was used for the model training and 30% for validation.ResultsBy performing the K-means clustering algorithm, the research cohort was clustered into two subtypes. The Kaplan-Meier survival estimate analysis showed significant differences in the overall survival (OS) between the two identified subtypes. Estimating the difference in the relative proportion of TIICs showed that the two subtypes had significant differences in multiple immune cells, such as CD8, CD4, and regulatory T cells. Further, the expression level of immune checkpoint molecules (PDL1, CTLA4, LAG3, TIGIT, CD27, IDO1, ICOS) and tumor mutational burden (TMB) also showed significant differences between the two subtypes, indicating the clinical value of the two subtypes. Finally, we identified a 38-gene signature and developed a multilayer perceptron (MLP) classifier that combined multi-gene signature to identify breast cancer subtypes. The results showed that the classifier had an accuracy rate of 93.56% and can be robustly used for the breast cancer subtype diagnosis.ConclusionIdentification of breast cancer subtypes based on the immune signature in the tumor microenvironment can assist clinicians to effectively and accurately assess the progression of breast cancer and formulate different treatment strategies for different subtypes.

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Section: Discussionsupporting

confidence: 92%

Immune subtype identification and multi-layer perceptron classifier construction for breast cancer

et al. 2022

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“…Moreover, aging influences the inflammatory microenvironment. It was found that there is a significant increase in M2-phenotype macrophage infiltrates with increasing age in 6642 breast cancer patients [ 44 ]. With regard to low-dose ASA treatment, ASA causes the formation of anti-inflammatory lipoxins through the acetylation of COX-2 [ 45 ].…”

Section: Discussionmentioning

confidence: 99%

“…Macrophage infiltrates account for approximately 18% of all cells in meningiomas, and their number positively correlates with the WHO grade [ 57 , 58 ]. A retrospective immunohistochemical study of 30 intracranial meningiomas by Proctor et al [ 44 ] revealed that M2 macrophages have a pro-tumoral role, and recurring or WHO grade 2 meningiomas include significantly more M2 macrophages compared to WHO grade 1 meningiomas or primary meningiomas. Conversely, M1 macrophages may act tumoricidal due to the induction of inflammatory reactions via cytotoxic cytokines and leukocyte recruitment, which potentially impede the meningioma growth [ 59 , 60 , 61 ].…”

Section: Discussionmentioning

confidence: 99%

Low-Dose Acetylsalicylic Acid Treatment in Non-Skull-Base Meningiomas: Impact on Tumor Proliferation and Seizure Burden

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et al. 2022

Cancers

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MIB-1 index is an important predictor of meningioma progression and was found to be correlated with COX-2 expression. However, the impact of low-dose acetylsalicylic acid (ASA) on MIB-1 index and clinical symptoms is unclear. Between 2009 and 2022, 710 patients with clinical data, tumor-imaging data, inflammatory laboratory (plasma fibrinogen, serum C-reactive protein) data, and neuropathological reports underwent surgery for primary cranial WHO grade 1 and 2 meningioma. ASA intake was found to be significantly associated with a low MIB-1 labeling index in female patients ≥ 60 years. Multivariable analysis demonstrated that female patients ≥ 60 years with a non-skull-base meningioma taking ASA had a significantly lower MIB-1 index (OR: 2.6, 95%: 1.0–6.6, p = 0.04). Furthermore, the intake of ASA was independently associated with a reduced burden of symptomatic epilepsy at presentation in non-skull-base meningiomas in both genders (OR: 3.8, 95%CI: 1.3–10.6, p = 0.03). ASA intake might have an anti-proliferative effect in the subgroup of elderly female patients with non-skull-base meningiomas. Furthermore, anti-inflammatory therapy seems to reduce the burden of symptomatic epilepsy in non-skull-base meningiomas. Further research is needed to investigate the role of anti-inflammatory therapy in non-skull-base meningiomas.

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“… 75-77 Targeting these pathways has been suggested as a potential strategy to prevent and treat cancer. 78 A recently published manuscript examined the correlation between age and predictive markers of ICIs response, observing increased TMB and decreased T-cell receptor diversity with aging 79 …”

Section: Characteristics Of the Older Adult Population: Finding The A...mentioning

confidence: 99%

Immune Checkpoint Inhibitors: The Unexplored Landscape of Geriatric Oncology

et al. 2022

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Cancer is classically considered a disease of aging, with over half of all new cancer diagnoses occurring in patients over the age of 65 years. Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment, yet the participation of older adults with cancer in ICI trials has been suboptimal, particularly at the extremes of age. Despite significant improvement in treatment response and an improved toxicity profile when compared with conventional cytotoxic chemotherapies, many cancers develop resistance to ICIs, and these drugs are not free of toxicities. This becomes particularly important in the setting of older adults with cancer, who are generally frailer and harbor more comorbidities than do their younger counterparts. Immunosenescence, a concept involving age-related changes in immune function, may also play a role in differential responses to ICI treatment in older patients. Data on ICI treatment response in older adult with cancers remains inconclusive, with multiple studies revealing conflicting results. The molecular mechanisms underlying response to ICIs in older cancer patients are poorly understood, and predictors of response that can delineate responders from non-responders remain to be elucidated. In this review, we explore the unique geriatric oncology population by analyzing existing retrospective datasets, and we also sought to highlight potential cellular, inflammatory, and molecular changes associated with aging as potential biomarkers for response to ICIs.

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Evaluating the impact of age on immune checkpoint therapy biomarkers

Abstract: Highlights d We investigate the relationship of patient age and ICB therapy biomarkers d Favorable ICB biomarkers are generally more prevalent in elderly patients d The CAMA web application provides a multi-omics atlas of aging in cancer

Cited by 41 publications

References 63 publications

Immune subtype identification and multi-layer perceptron classifier construction for breast cancer

Immune subtype identification and multi-layer perceptron classifier construction for breast cancer

Low-Dose Acetylsalicylic Acid Treatment in Non-Skull-Base Meningiomas: Impact on Tumor Proliferation and Seizure Burden

Immune Checkpoint Inhibitors: The Unexplored Landscape of Geriatric Oncology

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