Immunoactivating the tumor microenvironment enhances immunotherapy as predicted by integrative computational model

Popel, Aleksander S.

doi:10.1073/pnas.2001050117

Cited by 26 publications

(19 citation statements)

References 19 publications

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“…Proximity between tumor cells and immune cells is essential, though not entirely sufficient for immunotherapy efficacy, as tumors can avoid destruction by immune escape mechanisms such as downregulation of antigens, recruitment of immune suppressors, and upregulation of receptors that downregulate tumor-infiltrating lymphocytes (TILs) [ 4 , 5 ]. It is well known that the success of ICIs depends upon the mobilization of the immune system within the TME where cancer cells interact with stromal cells [ 5 , 6 ]. Therefore, the development of a biomarker detection modality inclusive of both cell proliferation and inflammation biomarkers is necessary to improve patient management.…”

Section: Introductionmentioning

confidence: 99%

Integration of tumor inflammation, cell proliferation, and traditional biomarkers improves prediction of immunotherapy resistance and response

Pabla¹,

Seager²,

Roey³

et al. 2021

Biomark Res

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Background Contemporary to the rapidly evolving landscape of cancer immunotherapy is the equally changing understanding of immune tumor microenvironments (TMEs) which is crucial to the success of these therapies. Their reliance on a robust host immune response necessitates clinical grade measurements of immune TMEs at diagnosis. In this study, we describe a stable tumor immunogenic profile describing immune TMEs in multiple tumor types with ability to predict clinical benefit from immune checkpoint inhibitors (ICIs). Methods A tumor immunogenic signature (TIGS) was derived from targeted RNA-sequencing (RNA-seq) and gene expression analysis of 1323 clinical solid tumor cases spanning 35 histologies using unsupervised analysis. TIGS correlation with ICI response and survival was assessed in a retrospective cohort of NSCLC, melanoma and RCC tumor blocks, alone and combined with TMB, PD-L1 IHC and cell proliferation biomarkers. Results Unsupervised clustering of RNA-seq profiles uncovered a 161 gene signature where T cell and B cell activation, IFNg, chemokine, cytokine and interleukin pathways are over-represented. Mean expression of these genes produced three distinct TIGS score categories: strong (n = 384/1323; 29.02%), moderate (n = 354/1323; 26.76%), and weak (n = 585/1323; 44.22%). Strong TIGS tumors presented an improved ICI response rate of 37% (30/81); with highest response rate advantage occurring in NSCLC (ORR = 36.6%; 16/44; p = 0.051). Similarly, overall survival for strong TIGS tumors trended upward (median = 25 months; p = 0.19). Integrating the TIGS score categories with neoplastic influence quantified via cell proliferation showed highly proliferative and strong TIGS tumors correlate with significantly higher ICI ORR than poorly proliferative and weak TIGS tumors [14.28%; p = 0.0006]. Importantly, we noted that strong TIGS and highly [median = not achieved; p = 0.025] or moderately [median = 16.2 months; p = 0.025] proliferative tumors had significantly better survival compared to weak TIGS, highly proliferative tumors [median = 7.03 months]. Importantly, TIGS discriminates subpopulations of potential ICI responders that were considered negative for response by TMB and PD-L1. Conclusions TIGS is a comprehensive and informative measurement of immune TME that effectively characterizes host immune response to ICIs in multiple tumors. The results indicate that when combined with PD-L1, TMB and cell proliferation, TIGS provides greater context of both immune and neoplastic influences on the TME for implementation into clinical practice.

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Section: Introductionmentioning

confidence: 99%

Integration of tumor inflammation, cell proliferation, and traditional biomarkers improves prediction of immunotherapy resistance and response

Pabla¹,

Seager²,

Roey³

et al. 2021

Biomark Res

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“…Many efforts are currently made to better identify patients who would be eligible for these new drugs [ 130 , 131 ]. Additionally, the numerous updates of limited current imaging criteria illustrate the needs of new tools to better characterize the immune ecosystem of tumors to improve treatment strategies [ 132 , 133 ]. Immune checkpoint-targeted radiolabeled monoclonal antibodies (IC-PET) and fibroblast activation protein-targeted radiolabeled inhibitors (FAPi-PET) are two serious candidates in this field.…”

Section: Pet Molecular Imaging: the Promising Clinical Perspective Of Radioligand Molecular Imaging And Therapymentioning

confidence: 99%

PET Molecular Imaging: A Holistic Review of Current Practice and Emerging Perspectives for Diagnosis, Therapeutic Evaluation and Prognosis in Clinical Oncology

Duclos

Iep

Gomez

et al. 2021

IJMS

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PET/CT molecular imaging has been imposed in clinical oncological practice over the past 20 years, driven by its two well-grounded foundations: quantification and radiolabeled molecular probe vectorization. From basic visual interpretation to more sophisticated full kinetic modeling, PET technology provides a unique opportunity to characterize various biological processes with different levels of analysis. In clinical practice, many efforts have been made during the last two decades to standardize image analyses at the international level, but advanced metrics are still under use in practice. In parallel, the integration of PET imaging with radionuclide therapy, also known as radiolabeled theranostics, has paved the way towards highly sensitive radionuclide-based precision medicine, with major breakthroughs emerging in neuroendocrine tumors and prostate cancer. PET imaging of tumor immunity and beyond is also emerging, emphasizing the unique capabilities of PET molecular imaging to constantly adapt to emerging oncological challenges. However, these new horizons face the growing complexity of multidimensional data. In the era of precision medicine, statistical and computer sciences are currently revolutionizing image-based decision making, paving the way for more holistic cancer molecular imaging analyses at the whole-body level.

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“…This heterogeneity hampers the effect of highly specific therapies. Thus, revealing the patient-specific microenvironment at the primary tumor level and at the distant metastatic site will allow for a better prediction of therapy response and potentially enable consecutive tailoring of therapy regimen [ 18 , 19 , 20 ]. The TME in this context provides targets for novel therapies aiming at normalization of the microenvironment to facilitate successful treatment of cancer patients [ 21 , 22 , 23 ].…”

Section: Formation Of the Tumor Microenvironmentmentioning

confidence: 99%

Tumor-Associated Macrophages—Implications for Molecular Oncology and Imaging

et al. 2021

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Tumor-associated macrophages (TAMs) represent the largest group of leukocytes within the tumor microenvironment (TME) of solid tumors and orchestrate the composition of anti- as well as pro-tumorigenic factors. This makes TAMs an excellent target for novel cancer therapies. The plasticity of TAMs resulting in varying membrane receptors and expression of intracellular proteins allow the specific characterization of different subsets of TAMs. Those markers similarly allow tracking of TAMs by different means of molecular imaging. This review aims to provides an overview of the origin of tumor-associated macrophages, their polarization in different subtypes, and how characteristic markers of the subtypes can be used as targets for molecular imaging and theranostic approaches.

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Immunoactivating the tumor microenvironment enhances immunotherapy as predicted by integrative computational model

Cited by 26 publications

References 19 publications

Integration of tumor inflammation, cell proliferation, and traditional biomarkers improves prediction of immunotherapy resistance and response

Integration of tumor inflammation, cell proliferation, and traditional biomarkers improves prediction of immunotherapy resistance and response

PET Molecular Imaging: A Holistic Review of Current Practice and Emerging Perspectives for Diagnosis, Therapeutic Evaluation and Prognosis in Clinical Oncology

Tumor-Associated Macrophages—Implications for Molecular Oncology and Imaging

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