Lung Inflammation Predictors in Combined Immune Checkpoint-Inhibitor and Radiation Therapy-Proof-of-Concept Animal Study.

PURPOSE: Combined radiotherapy (RT) and immune checkpoint-inhibitor (ICI) therapy can act synergistically to enhance tumor response beyond what either treatment can achieve alone. Alongside the revolutionary impact of ICIs on cancer therapy, life-threatening potential side effects, such as checkpoint-inhibitor-induced (CIP) pneumonitis, remain underreported and unpredictable. In this preclinical study, we hypothesized that routinely collected data such as imaging, blood counts, and blood cytokine levels can be utilized to build a model that predicts lung inflammation associated with combined RT/ICI therapy. MATERIALS AND METHODS: This proof-of-concept investigational work was performed on Lewis lung carcinoma in a syngeneic murine model. Nineteen mice were used, four as untreated controls and the rest subjected to RT/ICI therapy. Tumors were implanted subcutaneously in both flanks and upon reaching volumes of ~200 mm3 the animals were imaged with both CT and MRI and blood was collected. Quantitative radiomics features were extracted from imaging of both lungs. The animals then received RT to the right flank tumor only with a regimen of three 8 Gy fractions (one fraction per day over 3 days) with PD-1 inhibitor administration delivered intraperitoneally after each daily RT fraction. Tumor volume evolution was followed until tumors reached the maximum size allowed by the Institutional Animal Care and Use Committee (IACUC). The animals were sacrificed, and lung tissues harvested for immunohistochemistry evaluation. Tissue biomarkers of lung inflammation (CD45) were tallied, and binary logistic regression analyses were performed to create models predictive of lung inflammation, incorporating pretreatment CT/MRI radiomics, blood counts, and blood cytokines. RESULTS: The treated animal cohort was dichotomized by the median value of CD45 infiltration in the lungs. Four pretreatment radiomics features (3 CT features and 1 MRI feature) together with pre-treatment neutrophil-to-lymphocyte (NLR) ratio and pre-treatment granulocyte-macrophage colony-stimulating factor (GM-CSF) level correlated with dichotomized CD45 infiltration. Predictive models were created by combining radiomics with NLR and GM-CSF. Receiver operating characteristic (ROC) analyses of two-fold internal cross-validation indicated that the predictive model incorporating MR radiomics had an average area under the curve (AUC) of 0.834, while the model incorporating CT radiomics had an AUC of 0.787. CONCLUSIONS: Model building using quantitative imaging data, blood counts, and blood cytokines resulted in lung inflammation prediction models justifying the study hypothesis. The models yielded very-good-to-excellent AUCs of more than 0.78 on internal cross-validation analyses.

Toward prediction of abscopal effect in radioimmunotherapy: Pre-clinical investigation.

PURPOSE: Immunotherapy (IT) and radiotherapy (RT) can act synergistically, enhancing antitumor response beyond what either treatment can achieve separately. Anecdotal reports suggest that these results are in part due to the induction of an abscopal effect on non-irradiated lesions. Systematic data on incidence of the abscopal effect are scarce, while the existence and the identification of predictive signatures or this phenomenon are lacking. The purpose of this pre-clinical investigational work is to shed more light on the subject by identifying several imaging features and blood counts, which can be utilized to build a predictive binary logistic model. MATERIALS AND METHODS: This proof-of-principle study was performed on Lewis Lung Carcinoma in a syngeneic, subcutaneous murine model. Nineteen mice were used: four as control and the rest were subjected to combined RT plus IT regimen. Tumors were implanted on both flanks and after reaching volume of ~200 mm3 the animals were CT and MRI imaged and blood was collected. Quantitative imaging features (radiomics) were extracted for both flanks. Subsequently, the treated animals received radiation (only to the right flank) in three 8 Gy fractions followed by PD-1 inhibitor administrations. Tumor volumes were followed and animals exhibiting identical of better tumor growth delay on the non-irradiated (left) flank as compared to the irradiated flank were identified as experiencing an abscopal effect. Binary logistic regression analysis was performed to create models for CT and MRI radiomics and blood counts, which are predictive of the abscopal effect. RESULTS: Four of the treated animals experienced an abscopal effect. Three CT and two MRI radiomics features together with the pre-treatment neutrophil-to-lymphocyte (NLR) ratio correlated with the abscopal effect. Predictive models were created by combining the radiomics with NLR. ROC analyses indicated that the CT model had AUC of 0.846, while the MRI model had AUC of 0.946. CONCLUSIONS: The combination of CT and MRI radiomics with blood counts resulted in models with AUCs of 1 on the modeling dataset. Application of the models to the validation dataset exhibited AUCs above 0.84, indicating very good predictive power of the combination between quantitative imaging and blood counts.

Circulating Tumor Cells from Enumeration to Analysis: Current Challenges and Future Opportunities.

Circulating tumor cells (CTCs) have been recognized as a major contributor to distant metastasis. Their unique role as metastatic seeds renders them a potential marker in the circulation for early cancer diagnosis and prognosis as well as monitoring of therapeutic response. In the past decade, researchers mainly focused on the development of isolation techniques for improving the recovery rate and purity of CTCs. These developed techniques have significantly increased the detection sensitivity and enumeration accuracy of CTCs. Currently, significant efforts have been made toward comprehensive molecular characterization, ex vivo expansion of CTCs, and understanding the interactions between CTCs and their associated cells (e.g., immune cells and stromal cells) in the circulation. In this review, we briefly summarize existing CTC isolation technologies and specifically focus on advances in downstream analysis of CTCs and their potential applications in precision medicine. We also discuss the current challenges and future opportunities in their clinical utilization.

Cellular Immune Responses against Simian T-Lymphotropic Virus Type 1 Target Tax in Infected Baboons.

UNLABELLED: There are currently 5 million to 10 million human T-lymphotropic virus type 1 (HTLV-1)-infected people, and many of them will develop severe complications resulting from this infection. A vaccine is urgently needed in areas where HTLV-1 is endemic. Many vaccines are best tested in nonhuman primate animal models. As a first step in designing an effective HTLV-1 vaccine, we defined the CD8(+) and CD4(+) T cell response against simian T-lymphotropic virus type 1 (STLV-1), a virus closely related to HTLV-1, in olive baboons (Papio anubis). Consistent with persistent antigenic exposure, we observed that STLV-1-specific CD8(+) T cells displayed an effector memory phenotype and usually expressed CD107a, gamma interferon (IFN-γ), and tumor necrosis factor alpha (TNF-α). To assess the viral targets of the cellular immune response in STLV-1-infected animals, we used intracellular cytokine staining to detect responses against overlapping peptides covering the entire STLV-1 proteome. Our results show that, similarly to humans, the baboon CD8(+) T cell response narrowly targeted the Tax protein. Our findings suggest that the STLV-1-infected baboon model may recapitulate some of the important aspects of the human response against HTLV-1 and could be an important tool for the development of immune-based therapy and prophylaxis. IMPORTANCE: HTLV-1 infection can lead to many different and often fatal conditions. A vaccine deployed in areas of high prevalence might reduce the incidence of HTLV-1-induced disease. Unfortunately, there are very few animal models of HTLV-1 infection useful for testing vaccine approaches. Here we describe cellular immune responses in baboons against a closely related virus, STLV-1. We show for the first time that the immune response against STLV-1 in naturally infected baboons is largely directed against the Tax protein. Similar findings in humans and the sequence similarity between the human and baboon viruses suggest that the STLV-1-infected baboon model might be useful for developing a vaccine against HTLV-1.