Purpose: To develop quantitative molecular imaging biomarkers of immune-related adverse event (irAE) development in malignant melanoma (MM) patients receiving immune-checkpoint inhibitors (ICI) imaged with ¹⁸F-FDG PET/CT. Methods: ¹⁸F-FDG PET/CT images of 58 MM patients treated with anti-PD-1 or anti-CTLA-4 ICI were retrospectively analyzed for indication of irAE. Three target organs, most commonly affected by irAE, were considered: bowel, lung, and thyroid. Patient charts were reviewed to identify which patients experienced irAE, irAE grade, and time to irAE diagnosis. Target organs were segmented using a convolutional neural network (CNN), and novel quantitative imaging biomarkers — SUV percentiles (SUV_X%) of ¹⁸F-FDG uptake within the target organs — were correlated with the clinical irAE status. Area under the receiver-operating characteristic curve (AUROC) was used to quantify irAE detection performance. Patients who did not experience irAE were used to establish normal ranges for target organ ¹⁸F-FDG uptake. Results: A total of 31% (18/58) patients experienced irAE in the three target organs: bowel (n=6), lung (n=5), and thyroid (n=9). Optimal percentiles for identifying irAE were bowel (SUV_95%, AUROC=0.79), lung (SUV_95%, AUROC=0.98), and thyroid (SUV_75%, AUROC=0.88). Optimal cut-offs for irAE detection were bowel (SUV_95%>2.7 g/mL), lung (SUV_95%>1.7 g/mL), and thyroid (SUV_75%>2.1 g/mL). Normal ranges (95% confidence interval) for the SUV percentiles in patients without irAE were bowel [1.74, 2.86 g/mL], lung [0.73, 1.46 g/mL], and thyroid [0.86, 1.99 g/mL]. Conclusions: Increased ¹⁸F-FDG uptake within irAE-affected organs provides predictive information about the development of irAE in MM patients receiving ICI and represents a potential quantitative imaging biomarker for irAE. Some irAE can be detected on ¹⁸F-FDG PET/CT well before clinical symptoms appear.

Objective. To determine whether pre-treatment brain metabolic network patterns measured with ¹⁸F-FDG PET are associated with treatment response and survival in cancer patients. Approach. Exploratory retrospective study of two independent cohorts: stage III breast cancer patients treated with neoadjuvant chemotherapy and stage IV melanoma patients treated with anti-PD-1 immunotherapy. Metabolic brain network scores were derived from pre-treatment ¹⁸F-FDG PET scans and evaluated for their ability to stratify good versus poor responders using ROC analysis (AUC). Longitudinal changes in network scores were assessed across follow-up, and progression-free survival (PFS) and overall survival (OS) analyses were performed in the melanoma cohort. Main results. Specific brain networks were associated with treatment outcome; the cognition/language network was the strongest predictor (AUC > 0.84 for distinguishing good vs. poor responders in both cohorts). Good responders showed lower cognition/language scores than poor responders and healthy controls. Longitudinally, cognition/language scores remained stable in good responders, while poor responders exhibited a gradual convergence toward the scores observed in good responders. In the melanoma cohort, lower cognition/language scores were significantly associated with longer PFS and OS. Significance. These findings indicate that metabolic brain network patterns, particularly the cognition/language network, may serve as noninvasive biomarkers linked to treatment efficacy and survival in oncology. The results support a possible complex interaction between brain metabolism, immune response, and clinical outcomes. Key limitations include the retrospective design and lack of direct immune-function and psychometric measures; prospective, multimodal studies are needed to validate these observations and elucidate underlying mechanisms.

Background: Adjuvant nivolumab has become the new standard of care for patients with oesophageal and gastroesophageal junction cancer (OEC/GEJC) following neoadjuvant chemoradiotherapy (neoCRT) and surgical resection. In Slovenia, this treatment has been in use since January 2022. Here, we report the first Slovenian real-world experience with adjuvant nivolumab. Patients and methods: We conducted a retrospective, observational cohort study of patients with OEC/GEJC who received adjuvant nivolumab after neoCRT and radical resection between January 2022 and December 2023. Data on patient characteristics, treatment completion, disease progression, and immune-related adverse events (irAEs) were collected from medical records and analysed via descriptive statistics. Results: A total of 17 patients were included. The median follow-up was 34.6 months (range 11.2–55.7). The cohort included 14 (82%) males, with a mean age of 59 years. The Eastern Cooperative Oncology Group (ECOG) performance status was 0 for 15 (88%) patients and 1 for 2 (12%) patients. The tumor location was the esophagus in 9 (53%) patients and the gastroesophageal junction in 8 (47%) patients. At diagnosis, 13 (76%) patients were stage III (8th TNM classification). Histology revealed adenocarcinoma (AC) in 12 (71%) patients and squamous cell carcinoma (SCC) in 5 (29%) patients. Only 6 (35%) patients completed one year of adjuvant nivolumab. Treatment was discontinued in 5 (29%) patients due to disease progression and in 6 (35%) patients due to irAEs. Overall, 11 (65%) patients experienced irAEs of any grade. Grade 3 or 4 irAEs occurred in 4 (24%) patients: myocarditis G4 in 1 (6%) patient and colitis G3 in 3 (18%) patients. No irAE-related deaths were reported. The median disease-free survival (DFS) was 21.4 months (95% confidence interval [CI], 14.6–28.9). Conclusions: Real-world data from Slovenia indicate that 65% of patients discontinued adjuvant nivolumab prematurely due to disease progression or irAEs. These findings highlight the need for careful patient selection and monitoring when using adjuvant immunotherapy in this population.

Imunski sistem je ključen pri nadzoru nastanka in rasti malignih celic. Z imunoterapijo z zaviralci imunskih kontrolnih točk je imunski sistem postal eden pomembnejših tarč onkološkega zdravljenja. Sorazmerno visok delež onkoloških bolnikov na to zdravljenje še vedno ne odgovori. Črevesna mikrobiota bi glede na zadnja spoznanja lahko postala način premagovanja odpornosti na imunoterapijo. Možni načini modulacije mikrobiote so prehranska strategija, probiotiki in fekalna transplantacija mikrobiote. Ovire pri raziskovanju mikrobiote in njene uporabe pri zdravljenju z zaviralci imunskih kontrolnih točk so zaenkrat nestandardizirani pristopi k analizi mikrobiote, geografske razlike v mikrobioti, vpliv kulture ter načina življenja itd. V teku so številne predklinične in klinične raziskave, nekatere že z obetavnimi rezultati. Z obdelavo mikrobiote bi bila lahko obravnava onkoloških bolnikov še bolj personalizirana in holistična.

With immune checkpoint inhibitors becoming the mainstay of systemic therapy in both metastatic and early-stage settings across many cancer types, the management of immune-related adverse events has emerged as a central priority of modern oncological supportive care. These toxicities can substantially impair the quality of life of cancer patients, including those who achieve long-term survival. Consequently, there is a pressing need to develop reliable predictive biomarkers to better tailor immune checkpoint inhibitor treatment and optimize patient selection. This review summarizes several of the most promising predictive biomarkers currently under investigation, including genetic factors; peripheral blood parameters and their ratios; autoantibodies; cytokines and chemokines; cytomegalovirus serostatus; gut microbiome characteristics; body composition metrics; molecular imaging features; and tumour- and patient-related factors such as cancer type, gender, and physical activity. Because single biomarkers have limited predictive value, multi-omics prediction models and composite immune-cell scores are increasingly demonstrating greater potential. However, none of these candidate biomarkers have yet undergone sufficient validation to support their incorporation into routine clinical practice.