Sex-Related Differences in Metastatic Melanoma Patients Treated with Immune Checkpoint Inhibition.

Objectives: We aimed to investigate sex-related differences in patients with advanced melanoma treated with ICI by linking the assessment of inflammatory response in peripheral blood, onset of immune-related adverse events IRAEs during therapy and treatment response in short- and long-term. Methods: For the purpose of this single-center retrospective study metastatic melanoma patients treated with ICI were included. Baseline patient characteristics, blood sample tests and the onset of immune-related adverse events IRAEs were documented based on clinical records. The short-term treatment response was assessed with 18F-2-Fluor-2-desoxy-D-glucose Positron Emission Tomography/Computed Tomography FDG-PET/CT scans performed six months after initiation of ICI. The overall survival OS and progression-free survival PFS were used as endpoints to assess the long-term response to immunotherapy. Results: In total, 103 patients with advanced melanoma (mean age 68 ± 13.83 years) were included, 29 women (mean age 60.41 ± 14.57 years) and 74 men (mean age 65.66 ± 13.34 years). The primary tumor was located on a lower extremity in one out of three women and on the head/neck in one out of three men (p < 0.001). While the superficial spreading (41%) and nodular (36%) melanoma subtypes represented together 77% of the cases in male population, women showed a more heterogenous distribution of melanoma subtypes with the superficial spreading (35%), nodular (23%), acral lentiginous (19%) and mucosal (12%) melanoma subtypes being most frequent in female population (p < 0.001). Most differences between women and men with regards to inflammatory parameters were observed six months after initiation of ICI with a higher median NLR (p = 0.038), lower counts of lymphocytes (p = 0.004) and thrombocytes (p = 0.089) in addition to lower counts of erythrocytes (p < 0.001) and monocytes (p < 0.001) in women towards men. IRAEs were more frequent in women towards men (p = 0.013). Women were more likely to display endocrinological IRAEs, such as thyroiditis being the most frequent adverse event in women. Interestingly IRAEs of the gastrointestinal tract were the most frequent ones in men. Finally, men with advanced melanoma showed a significantly better response to immunotherapy in short- (p = 0.015) and long-term (OS p = 0.015 and PFS p < 0.001) than women. In fact, every fourth man died during the course of the disease, while every second woman did not survive. (p = 0.001). Conclusion: Men with advanced melanoma showed a significantly better response to immunotherapy in short- and long-term than women. Higher immune activation in peripheral blood before and after initiation ICI might be linked to favorable treatment response during and after ICI in favor of men and decoupled from the onset of IRAEs. Given the significantly higher immunotoxicity and worse outcome experienced by women compared to men the use of ICI should be chosen carefully in women with advanced melanoma.

Inflammatory Blood Parameters as Biomarkers for Response to Immune Checkpoint Inhibition in Metastatic Melanoma Patients.

Objectives: We aimed to investigate whether inflammatory parameters in peripheral blood at baseline and during the first six months of treatment could predict the short- and long-term outcomes of metastatic melanoma patients treated with immune checkpoint inhibitors (ICIs). Methods: This single-center retrospective study considered patients with metastatic melanoma treated with either single or dual checkpoint inhibition. Blood sample tests were scheduled together with 18F-2-fluor-2-desoxy-D-glucose positron emission tomography/computed tomography (FDG-PET/CT) scans at baseline and at three and six months after initiation of ICI treatment. The short-term response to ICIs was assessed using FDG-PET/CT scans. The long-term response to ICIs was assessed using the overall survival OS and progression-free survival PFS as endpoints. Results: A total of 100 patients with metastatic melanoma were included (female, n = 31; male, n = 69). The median age was 68 years (interquartile range (IQR): 53−74 years). A total of 82% of the cohort displayed a disease control (DC), while 18% presented a progressive disease (PD) after six months of ICIs. Patients with DC after six months of ICIs showed a lower median of the neutrophils-to-lymphocytes ratio (NLR) toward patients with PD, with no significant prediction power of NLR neither in the short nor in the long term. The count of neutrophils at the baseline time point (TP 0) (p = 0.037) and erythrocytes three months after treatment start (TP 1) (p = 0.010) were strong predictive parameters of a DC six months after treatment start. Erythrocytes (p < 0.001) and lymphocytes (p = 0.021) were strong biomarkers predictive of a favorable OS. Erythrocytes (p = 0.013) and lymphocytes (p = 0.017) also showed a significant prediction power for a favorable PFS. Conclusions: Inflammatory blood parameters predicted the short- and long-term response to ICIs with a strong predictive power. Our results suggested the validation of inflammatory blood parameters as biomarkers that predict immunotherapies' efficacity in metastatic melanoma patients. However, confounding factors that interfere with myelopoiesis should also be taken into consideration.

Correction: Kudura et al. Prediction of Early Response to Immune Checkpoint Inhibition Using FDG-PET/CT in Melanoma Patients. Cancers 2021, 13, 3830.

The authors wish to make the following corrections to this paper [...].

Improved Survival Prediction by Combining Radiological Imaging and S-100B Levels Into a Multivariate Model in Metastatic Melanoma Patients Treated With Immune Checkpoint Inhibition.

Purpose: We explored imaging and blood bio-markers for survival prediction in a cohort of patients with metastatic melanoma treated with immune checkpoint inhibition. Materials and Methods: 94 consecutive metastatic melanoma patients treated with immune checkpoint inhibition were included into this study. PET/CT imaging was available at baseline (Tp0), 3 months (Tp1) and 6 months (Tp2) after start of immunotherapy. Radiological response at Tp2 was evaluated using iRECIST. Total tumor burden (TB) at each time-point was measured and relative change of TB compared to baseline was calculated. LDH, CRP and S-100B were also analyzed. Cox proportional hazards model and logistic regression were used for survival analysis. Results: iRECIST at Tp2 was significantly associated with overall survival (OS) with C-index=0.68. TB at baseline was not associated with OS, whereas TB at Tp1 and Tp2 provided similar predictive power with C-index of 0.67 and 0.71, respectively. Appearance of new metastatic lesions during follow-up was an independent prognostic factor (C-index=0.73). Elevated LDH and S-100B ratios at Tp2 were significantly associated with worse OS: C-index=0.73 for LDH and 0.73 for S-100B. Correlation of LDH with TB was weak (r=0.34). A multivariate model including TB change, S-100B, and appearance of new lesions showed the best predictive performance with C-index=0.83. Conclusion: Our analysis shows only a weak correlation between LDH and TB. Additionally, baseline TB was not a prognostic factor in our cohort. A multivariate model combining early blood and imaging biomarkers achieved the best predictive power with regard to survival, outperforming iRECIST.

NTCP Modeling for High-Grade Temporal Radionecroses in a Large Cohort of Patients Receiving Pencil Beam Scanning Proton Therapy for Skull Base and Head and Neck Tumors.

PURPOSE: To develop a normal tissue complication probability model including clinical and dosimetric parameters for high-grade temporal lobe radionecroses (TRN) after pencil beam scanning proton therapy. METHODS AND MATERIALS: We included data on 299 patients with skull base and head and neck tumors treated with pencil-beam scan proton therapy, with a total dose of ≥60 GyRBE (relative biological effectiveness) from May 2004 to November 2018. We considered 9 clinical and 27 dosimetric parameters for the structure-wise modeling of high-grade (grade ≥2) TRN. After eliminating strongly cross-correlated variables, we generated logistic regression models using least absolute shrinkage and selection operator regression. We performed bootstrapping to assess parameter selection robustness and evaluated model performance via cross-correlation by assessing the area under the curve of receiver operating characteristic curves and calibration with a Hosmer-Lemeshow test statistic. RESULTS: After a median radiologic follow-up of 51.5 months (range, 4-190), 27 patients (9%) developed grade ≥2 TRN. Eleven patients had bitemporal necrosis, resulting in 38 events in 598 temporal lobes for structure-wise analysis. During our bootstrapping analysis, we found that the highest selection frequency was for prescription dose, followed by age, V40Gy (%), hypertension, and dose to at least 1 cc (D1cc) (Gy) in the temporal lobe. During our cross-validation, we found that age*prescription-dose*D1cc (Gy)*hypertension was superior in all described test statistics. We built full cohort structure-wise and patient-wise models with maximum area under the curve of receiver operating characteristic curves of 0.79 (structure-wise) and 0.76 (patient-wise). CONCLUSIONS: While developing a logistic regression normal tissue complication probability model to predict grade ≥2 TRN, the best fit was found for the model containing age, prescription dose, D1cc (Gy), and hypertensive blood pressure as risk factors. External validation will be the next step to improve generalizability and potential introduction into clinical routine.

Prediction of Early Response to Immune Checkpoint Inhibition Using FDG-PET/CT in Melanoma Patients.

We aimed to investigate, whether 18F-2-fluoro-2-desoxy-D-glucose positron emission tomography/computed tomography (FDG-PET/CT) scans performed at baseline (time point 0; TP 0) and three months after initiation of immunotherapy (time point 1; TP 1) can be used on a metastasis- and patient-level to predict the response to immune-checkpoint inhibition using FDG-PET/CT six months after treatment start (time point 2; TP 2) in metastatic melanoma patients. This single-center retrospective study considered metastatic melanoma patients treated with immune checkpoint inhibition from TP 0 to TP 2. An analysis on a metastasis- and patient-level was carried out. Tumor volume, standardized uptake values SUV (mean, maximum, and peak), metabolic tumor volume MTV and total lesion glycolysis TLG of each included metastasis were recorded at each time point, respectively TP 0, TP 1 and TP 2. Total tumor volume, total metabolic tumor volume and total lesion glycolysis per patient were also calculated at TP 0, TP 1 and TP 2. Treatment response was assessed at metastasis- and patient-level based on FDG-PET/CT scans at TP 2. 612 melanoma metastases in 111 patients were included. The analysis on a metastasis-level showed that metastatic SUVpeak at TP 1 and volume variation between TP 0 and TP 1 were the strongest negative predictive biomarkers for response. However, at TP 0, metastatic SUVmean and SUVpeak indicated a low negative prediction power, whereas initial metastatic volume was not a predictive biomarker. Also, melanoma metastases located in bone structures had a negative influence on the outcome at TP 2, particularly in women. The analysis on a patient-level showed, that total tumor volume, total metastatic tumor volume and total lesion glycolysis of all metastases three months after treatment initiation were strong negative predictive biomarkers for response to immunotherapy six months after initiation. Age and female sex were also found to be negative predictive biomarkers with lower predictive power. Interestingly, total tumor volume at TP 0 and number of metastases at TP 0 as well as the occurrence of early immune-related adverse events between TP 0 and TP 2 did not have any predictive value for early treatment response. FDG-PET/CT performed for treatment response assessment three months after initiation of immune checkpoint inhibition in metastatic melanoma patients can also be used to predict early response to treatment. On a metastasis-level SUV peak and volume variation of metastases are strong outcome predictive biomarkers. On a patient-level total tumor volume and semiquantitative parameters such as total metabolic tumor volume MTV and total lesion glycolysis TLG of all metastases are promising outcome predictive biomarkers. Also, early complete response on a metastasis- and patient-level seems to be predictive for lasting complete response.

Preselection of robust radiomic features does not improve outcome modelling in non-small cell lung cancer based on clinical routine FDG-PET imaging.

BACKGROUND: Radiomics is a promising tool for identifying imaging-based biomarkers. Radiomics-based models are often trained on single-institution datasets; however, multi-centre imaging datasets are preferred for external generalizability owing to the influence of inter-institutional scanning differences and acquisition settings. The study aim was to determine the value of preselection of robust radiomic features in routine clinical positron emission tomography (PET) images to predict clinical outcomes in locally advanced non-small cell lung cancer (NSCLC). METHODS: A total of 1404 primary tumour radiomic features were extracted from pre-treatment [18F]fluorodeoxyglucose (FDG)-PET scans of stage IIIA/N2 or IIIB NSCLC patients using a training cohort (n = 79; prospective Swiss multi-centre randomized phase III trial SAKK 16/00; 16 centres) and an internal validation cohort (n = 31; single centre). Robustness studies investigating delineation variation, attenuation correction and motion were performed (intraclass correlation coefficient threshold > 0.9). Two 12-/24-month event-free survival (EFS) and overall survival (OS) logistic regression models were trained using standardized imaging: (1) with robust features alone and (2) with all available features. Models were then validated using fivefold cross-validation, and validation on a separate single-centre dataset. Model performance was assessed using area under the receiver operating characteristic curve (AUC). RESULTS: Robustness studies identified 179 stable features (13%), with 25% stable features for 3D versus 4D acquisition, 31% for attenuation correction and 78% for delineation. Univariable analysis found no significant robust features predicting 12-/24-month EFS and 12-month OS (p value > 0.076). Prognostic models without robust preselection performed well for 12-month EFS in training (AUC = 0.73) and validation (AUC = 0.74). Patient stratification into two risk groups based on 12-month EFS was significant for training (p value = 0.02) and validation cohorts (p value = 0.03). CONCLUSIONS: A PET-based radiomics model using a standardized, multi-centre dataset to predict EFS in locally advanced NSCLC was successfully established and validated with good performance. Prediction models with robust feature preselection were unsuccessful, indicating the need for a standardized imaging protocol.

Targeting Treatment Resistance in Head and Neck Squamous Cell Carcinoma - Proof of Concept for CT Radiomics-Based Identification of Resistant Sub-Volumes.

PURPOSE: Radiomics has already been proposed as a prognostic biomarker in head and neck cancer (HNSCC). However, its predictive power in radiotherapy has not yet been studied. Here, we investigated a local radiomics approach to distinguish between tumor sub-volumes with different levels of radiosensitivity as a possible target for radiation dose intensification. MATERIALS AND METHODS: Of 40 patients (n=28 training and n=12 validation) with biopsy confirmed locally recurrent HNSCC, pretreatment contrast-enhanced CT images were registered with follow-up PET/CT imaging allowing identification of controlled (GTVcontrol) vs non-controlled (GTVrec) tumor sub-volumes on pretreatment imaging. A bi-regional model was built using radiomic features extracted from pretreatment CT in the GTVrec and GTVcontrol to differentiate between those regions. Additionally, concept of local radiomics was implemented to perform detection task. The original tumor volume was divided into sub-volumes with no prior information on the location of recurrence. Radiomic features from those sub-volumes were then used to detect recurrent sub-volumes using multivariable logistic regression. RESULTS: Radiomic features extracted from non-controlled regions differed significantly from those in controlled regions (training AUC = 0.79 CI 95% 0.66 - 0.91 and validation AUC = 0.88 CI 95% 0.72 - 1.00). Local radiomics analysis allowed efficient detection of non-controlled sub-volumes both in the training AUC = 0.66 (CI 95% 0.56 - 0.75) and validation cohort 0.70 (CI 95% 0.53 - 0.86), however performance of this model was inferior to bi-regional model. Both models indicated that sub-volumes characterized by higher heterogeneity were linked to tumor recurrence. CONCLUSION: Local radiomics is able to detect sub-volumes with decreased radiosensitivity, associated with location of tumor recurrence in HNSCC in the pre-treatment CT imaging. This proof of concept study, indicates that local CT radiomics can be used as predictive biomarker in radiotherapy and potential target for dose intensification.

Malignancy Rate of Indeterminate Findings on FDG-PET/CT in Cutaneous Melanoma Patients.

BACKGROUND: The use of 18F-2-Fluor-2-desoxy-D-glucose Positron Emission Tomography/Computed Tomography FDG-PET/CT in clinical routine for staging, treatment response monitoring and post treatment surveillance in metastatic melanoma patients has noticeably increased due to significant improvement of the overall survival rate in melanoma patients. However, determining the dignity of the findings with increased metabolic activity on FDG-PET/CT can be sometimes challenging and may need further investigation. PURPOSE: We aimed to investigate the malignancy rate of indeterminate findings on FDG-PET/CT in metastatic cutaneous melanoma patients. METHODS: This single-center retrospective study included cutaneous melanoma patients who underwent FDG-PET/CT in clinical routine between 2015 and 2017 with findings reported as indeterminate and therefore requiring further evaluation. The dignity of the included findings was determined by subsequent imaging and, if required, additional histopathology. The impact of the outcome on the clinical management was also reported. RESULTS: A total of 842 FDG-PET/CT reports of 244 metastatic cutaneous melanoma patients were reviewed. Sixty indeterminate findings were included. Almost half of all indeterminate findings were lymph nodes, lung nodules and cerebral lesions. In total, 43.3% of all included findings proved to be malignant. 81% of all malignant lesions were metastases of cutaneous melanoma, while 19% of all malignant lesions could be attributed to other primary malignancies, such as lung, breast, thyroid and colorectal cancers. Malignant findings influenced clinical management in 60% of the cases. CONCLUSION: Indeterminate findings on FDG-PET/CT in metastatic cutaneous melanoma patients should be further investigated. Almost one out of every two indeterminate findings on FDG-PET/CT is malignant. The majority of the findings are melanoma manifestations, however, in a significant percentage, other primary tumors are found. Upon verification, patient management is changed in most cases.

Impact of Low-Dose Irradiation of the Lung and Heart on Toxicity and Pulmonary Function Parameters after Thoracic Radiotherapy.

OBJECTIVE: To assess the impact of (low) dose irradiation to the lungs and heart on the incidence of pneumonitis and pulmonary function changes after thoracic radiotherapy (RT). Methods/Material: Data of 62 patients treated with curative thoracic radiotherapy were analyzed. Toxicity data and pulmonary function tests (PFTs) were obtained before RT and at 6 weeks, at 12 weeks, and at 6 months after RT. PFTs included ventilation (e.g., vital capacity) and diffusion parameters (e.g., diffusion capacity for carbon monoxide (DLCO)). Dosimetric data of the lung and heart were extracted to assess the impact of dose on PFT changes and radiation pneumonitis (RP). RESULTS: No statistically significant correlations between dose parameters and changes in ventilation parameters were found. There were statistically significant correlations between DLCO and low-dose parameters of the lungs (V5Gy-V30Gy (%)) and irradiation of the heart during the follow-up up to 6 months after RT, as well as a temporary correlation of the V60Gy (%) on the blood gas parameters at 12 weeks after RT. On multivariate analysis, both heart and lung parameters had a significant impact on DLCO. There was no statistically significant influence of any patient or treatment-related (including dose parameters) factors on the incidence of ≥G2 pneumonitis. CONCLUSION: There seems to be a lasting impact of low dose irradiation to the lung as well as irradiation to the heart on the DLCO after thoracic radiotherapy. No influence on RP was found in this analysis.

Dosimetric analysis of local failures in skull-base chordoma and chondrosarcoma following pencil beam scanning proton therapy.

BACKGROUND: Despite combined modality treatment involving surgery and radiotherapy, a relevant proportion of skull-base chordoma and chondrosarcoma patients develop a local recurrence (LR). This study aims to analyze patterns of recurrence and correlate LR with a detailed dosimetric analysis. METHODS: 222 patients were treated with proton radiotherapy for chordoma (n = 151) and chondrosarcoma (n = 71) at the PSI between 1998 and 2012. All patients underwent surgery, followed by pencil-beam scanning proton therapy to a mean dose of 72.5 ± 2.2GyRBE. A retrospective patterns of recurrence analysis was performed: LR were contoured on follow-up MRI, registered with planning-imaging and the overlap with initial target structures (GTV, PTVhigh-dose, PTVlow-dose) was calculated. DVH parameters of planning structures and recurrences were calculated and correlated with LR using univariate and multivariate cox regression. RESULTS: After a median follow-up of 50 months, 35 (16%) LR were observed. Follow-up MRI imaging was available for 27 (77%) of these recurring patients. Only one (3.7%) recurrence was located completely outside the initial PTV (surgical pathway recurrence). The mean proportions of LR covered by the initial target structures were 48% (range 0-86%) for the GTV, 70% (range 0-100%) for PTVhigh and 83% (range 0-100%) for PTVlow. In the univariate analysis, the following DVH parameters were significantly associated with LR: GTV(V < 66GyRBE, p = 0.01), GTV(volume, p = 0.02), PTVhigh(max, p = 0.02), PTVhigh(V < 66GyRBE, p = 0.03), PTVhigh(V < 59GyRBE, p = 0.02), PTVhigh(volume, p = 0.01) and GTV(D95, p = 0.05). In the multivariate analysis, only histology (chordoma vs. chondrosarcoma, p = 0.01), PTVhigh(volume, p = 0.05) and GTV(V < 66GyRBE, p = 0.02) were independent prognostic factors for LR. CONCLUSION: This study identified DVH parameters, which are associated with the risk of local recurrence after proton therapy using pencil-beam scanning for patients with skull-base chordoma and chondrosarcoma.

A tumor-immune interaction model for hepatocellular carcinoma based on measured lymphocyte counts in patients undergoing radiotherapy.

PURPOSE: The impact of radiation therapy on the immune system has recently gained attention particularly when delivered in combination with immunotherapy. However, it is unclear how different treatment fractionation regimens influence the interaction between the immune system and radiation. The goal of this work was to develop a mathematical model that quantifies both the immune stimulating as well as the immunosuppressive effects of radiotherapy and simulates the effects of different fractionation regimens based on patient data. METHODS AND MATERIALS: The framework describes the temporal evolution of tumor cells, lymphocytes, and inactivated dying tumor cells releasing antigens during radiation therapy, specifically modeling how recruited lymphocytes inhibit tumor progression. The parameters of the model were partly taken from the literature and in part extracted from blood samples (circulating lymphocytes: CLs) collected from hepatocellular carcinoma patients undergoing radiotherapy and their outcomes. The dose volume histograms to circulating lymphocytes were calculated with a probability-based model. RESULTS: Based on the fitted parameters, the model enabled a study into the depletion and recovery of CLs in patients as a function of fractionation regimen. Our results quantify the ability of short fractionation regimens to lead to shorter periods of lymphocyte depletion and predict faster recovery after the end of treatment. The model shows that treatment breaks between fractions can prolong the period of lymphocyte depletion and should be avoided. CONCLUSIONS: This study introduces a mathematical model for tumor-immune interactions using clinically extracted radiotherapy patient data, which can be applied to design trials aimed at minimizing lymphocyte depleting effects in radiation therapy.

Radiomics, Tumor Volume, and Blood Biomarkers for Early Prediction of Pseudoprogression in Patients with Metastatic Melanoma Treated with Immune Checkpoint Inhibition.

PURPOSE: We assessed the predictive potential of positron emission tomography (PET)/CT-based radiomics, lesion volume, and routine blood markers for early differentiation of pseudoprogression from true progression at 3 months. EXPERIMENTAL DESIGN: 112 patients with metastatic melanoma treated with immune checkpoint inhibition were included in our study. Median follow-up duration was 22 months. 716 metastases were segmented individually on CT and 2[18F]fluoro-2-deoxy-D-glucose (FDG)-PET imaging at three timepoints: baseline (TP0), 3 months (TP1), and 6 months (TP2). Response was defined on a lesion-individual level (RECIST 1.1) and retrospectively correlated with FDG-PET/CT radiomic features and the blood markers LDH/S100. Seven multivariate prediction model classes were generated. RESULTS: Two-year (median) overall survival, progression-free survival, and immune progression-free survival were 69% (not reached), 24% (6 months), and 42% (16 months), respectively. At 3 months, 106 (16%) lesions had progressed, of which 30 (5%) were identified as pseudoprogression at 6 months. Patients with pseudoprogressive lesions and without true progressive lesions had a similar outcome to responding patients and a significantly better 2-year overall survival of 100% (30 months), compared with 15% (10 months) in patients with true progressions/without pseudoprogression (P = 0.002). Patients with mixed progressive/pseudoprogressive lesions were in between at 53% (25 months). The blood prediction model (LDH+S100) achieved an AUC = 0.71. Higher LDH/S100 values indicated a low chance of pseudoprogression. Volume-based models: AUC = 0.72 (TP1) and AUC = 0.80 (delta-volume between TP0/TP1). Radiomics models (including/excluding volume-related features): AUC = 0.79/0.78. Combined blood/volume model: AUC = 0.79. Combined blood/radiomics model (including volume-related features): AUC = 0.78. The combined blood/radiomics model (excluding volume-related features) performed best: AUC = 0.82. CONCLUSIONS: Noninvasive PET/CT-based radiomics, especially in combination with blood parameters, are promising biomarkers for early differentiation of pseudoprogression, potentially avoiding added toxicity or delayed treatment switch.

Abscopal effects of radiotherapy and combined mRNA-based immunotherapy in a syngeneic, OVA-expressing thymoma mouse model.

BACKGROUND: Tumor metastasis and immune evasion present major challenges of cancer treatment. Radiotherapy can overcome immunosuppressive tumor microenvironments. Anecdotal reports suggest abscopal anti-tumor immune responses. This study assesses abscopal effects of radiotherapy in combination with mRNA-based cancer vaccination (RNActive®). METHODS: C57BL/6 mice were injected with ovalbumin-expressing thymoma cells into the right hind leg (primary tumor) and left flank (secondary tumor) with a delay of 4 days. Primary tumors were irradiated with 3 × 2 Gy, while secondary tumors were shielded. RNA and combined treatment groups received mRNA-based RNActive® vaccination. RESULTS: Radiotherapy and combined radioimmunotherapy significantly delayed primary tumor growth with a tumor control in 15 and 53% of mice, respectively. In small secondary tumors, radioimmunotherapy significantly slowed growth rate compared to vaccination (p = 0.002) and control groups (p = 0.01). Cytokine microarray analysis of secondary tumors showed changes in the cytokine microenvironment, even in the non-irradiated contralateral tumors after combination treatment. CONCLUSION: Combined irradiation and immunotherapy is able to induce abscopal responses, even with low, normofractionated radiation doses. Thus, the combination of mRNA-based vaccination with irradiation might be an effective regimen to induce systemic anti-tumor immunity.