Thymomas and thymic carcinomas (TC) are malignant thymic epithelial tumors (TETs) with poor outcome, if non-resectable. Metabolic signatures of TETs have not yet been studied and may offer new therapeutic options. Metabolic profiles of snap-frozen thymomas (WHO types A, AB, B1, B2, B3, n = 12) and TCs (n = 3) were determined by high resolution magic angle spinning 1H nuclear magnetic resonance (HRMAS 1H-NMR) spectroscopy. Metabolite-based prediction of active KEGG metabolic pathways was achieved with MetPA. In relation to metabolite-based metabolic pathways, gene expression signatures of TETs (n = 115) were investigated in the public “The Cancer Genome Atlas” (TCGA) dataset using gene set enrichment analysis. Overall, thirty-seven metabolites were quantified in TETs, including acetylcholine that was not previously detected in other non-endocrine cancers. Metabolite-based cluster analysis distinguished clinically indolent (A, AB, B1) and aggressive TETs (B2, B3, TCs). Using MetPA, six KEGG metabolic pathways were predicted to be activated, including proline/arginine, glycolysis and glutathione pathways. The activated pathways as predicted by metabolite-profiling were generally enriched transcriptionally in the independent TCGA dataset. Shared high lactic acid and glutamine levels, together with associated gene expression signatures suggested a strong “Warburg effect”, glutaminolysis and redox homeostasis as potential vulnerabilities that need validation in a large, independent cohort of aggressive TETs. If confirmed, targeting metabolic pathways may eventually prove as adjunct therapeutic options in TETs, since the metabolic features identified here are known to confer resistance to cisplatin-based chemotherapy, kinase inhibitors and immune checkpoint blockers, i.e., currently used therapies for non-resectable TETs.

Background/Aim: The aim of the study was to identify predictors of long-term survival and propose an improved risk stratification in patients with pulmonary germ-cell metastases admitted for pulmonary metastasectomy. Patients and Methods: Thirty-four patients admitted to the Division of Thoracic Surgery Munich, Germany, from 04/1994 until 09/2017 were retrospectively analyzed. The impact of clinical parameters on survival was calculated using Kaplan–Meier, multivariate Cox regression analysis and receiver-operator curves. Results: Ten-year overall survival was 75.3%. Elevated American Society of Anesthesiologists score, metachronous metastasis, embryonal histology, intrathoracic lymph node involvement, brain metastases and thoracic wall infiltration were significant predictors of reduced survival. With the independent predictors (embryonal histology, metachronous metastasis and thoracic wall infiltration), a germinal non-seminomatous lung metastasis risk of death score (GLUMER) was calculated, accurately predicting survival (area under curve=0.8839, p=0.0023). Conclusion: In patients with pulmonary germ-cell metastases, intrathoracic lymph node involvement, embryonal carcinoma, metachronous metastasis and thoracic wall infiltration represent negative predictors of long-term survival. The GLUMER score might represent a promising tool for use in adapted follow-up care in high-risk patients.

This study aimed to evaluate the diagnostic accuracy and false positivity rate of lymph node (LN) staging assessed by integrated 18F-fluorodeoxyglucose positron emission computed tomography (18F-FDG-PET/CT) in patients with operable lung cancer to the tumor histology. In total, 129 consecutive patients with non-small-cell lung cancer (NSCLC) undergoing anatomical lung resections were included. Preoperative LN staging was evaluated in the relationship to the histology of the resected specimens (group 1: lung adenocarcinoma/LUAD; group 2: squamous cell carcinoma/SQCA). Statistical analysis was performed by the Mann–Whitney U-test, the chi² test, and binary logistic regression analysis. To establish an easy-to-use algorithm for the identification of LN false positivity, a decision tree including clinically meaningful parameters was generated. In total, 77 (59.7%) and 52 (40.3%) patients were included in the LUAD and SQCA groups, respectively. SQCA histology, non-G1 tumors, and tumor SUVmax > 12.65 were identified as independent predictors of LN false positivity in the preoperative staging. The corresponding ORs and their 95% CIs were 3.35 [1.10–10.22], p = 0.0339; 4.60 [1.06–19.94], p = 0.0412; and 2.76 [1.01–7.55], and p = 0.0483. The preoperative identification of false-positive LNs is an important aspect of the treatment regimen for patients with operable lung cancer; thus, these preliminary findings should be further evaluated in larger patient cohorts.

Our study aimed to identify predictors for the effectiveness of tumor regression in lung cancer patients undergoing neoadjuvant treatment and cancer resections. Patients admitted between 2016 and 2022 were included in the study. Based on the histology of the tumor, patients were categorized into a lung adenocarcinoma group (LUAD) and squamous cell carcinoma group (SQCA). Ninety-five patients with non-small-cell lung cancer were included in the study. A total of 58 (61.1%) and 37 (38.9%) patients were included in the LUAD and SQCA groups, respectively. Additionally, 9 (9.5%), 56 (58.9%), and 30 (31.6%) patients were categorized with a tumor regression score of I, II, and III, respectively. In multivariable analyses, histology of the primary tumor (SQCA), lymph node size in the preoperative CT scan (>1.7 cm), and absolute tumor size reduction after neoadjuvant treatment (>2.6 cm) independently predict effectiveness of tumor regression (OR [95% confidence interval, p-value] of 6.88 [2.40–19.77, p < 0.0001], 3.13 [1.11–8.83, p = 0.0310], and 3.76 [1.20–11.81, p = 0.0233], respectively). Age > 70 years, extended resection > one lobe, and tumor recurrence or metastasis were identified as significant independent predictors of reduced overall survival. Assessment of tumor size before and after neoadjuvant treatment might help to identify high-risk patients with decreased survival and to improve patient management and care.

This study aimed to identify risk factors for major postoperative complications (TMM) and their impact on overall survival in patients aged ≥80 years undergoing lung cancer surgery, a group at increased risk of morbidity. A total of 88 patients aged ≥80 years who underwent anatomical lung resections were retrospectively analyzed. Postoperative complications were classified into minor or no complications (TMM 0–2) and major (TMM ≥ 3) complications. Logistic regression analysis was performed to identify independent predictors of major complications. Kaplan–Meier estimates were used to measure overall survival. Major complications occurred in 24 patients (27.3%). Multivariable regression analysis identified perioperative blood transfusion as an independent risk factor for major complications (p = 0.0009). Patients with major complications exhibited significantly reduced overall survival (p = 0.0009). Subgroup analysis revealed that patients who underwent minimally invasive surgery had significantly better survival (p = 0.01). Moreover, perioperative transfusion correlated with diminished overall survival (p = 0.0027). In patients aged ≥80 years undergoing lung resections, the occurrence of major postoperative complications is associated with significantly impaired survival. Minimally invasive surgical approaches and blood conservation strategies may mitigate complications and enhance long-term outcomes in this high-risk group.

Our study aimed to identify predictors for the effectiveness of tumor regression in lung cancer patients undergoing neoadjuvant treatment and cancer resections. Patients admitted between 2016 and 2022 were included in the study. Based on the histology of the tumor, patients were categorized into lung adenocarcinoma group (LUAD), and squamous cell carcinoma group (SQCA). Ninety-five patients with non-small cell lung cancer were included in the study. Fifty-eight (61.1%) and 37 (38.9%) patients were included in the LUAD and SQCA groups, respectively. Nine (9.5%), 56 (58.9%), and 30 (31.6%) patients were categorized with a tumor regression score of I, II, and III respectively. In multivariable analyses, histology of the primary tumor (SQCA), lymph node size in the preoperative CT scan (>1.7cm) and absolute tumor size reduction after neoadjuvant treatment (>2.6 cm) independently predict effectiveness of tumor regression (OR, [95% Confidence interval, p-value] of 6.88 [2.40-19.77, p70 years, extended resection >one lobe, and tumor recurrence or metastasis were identified as significant independent predictors of reduced overall survival. Assessment of tumor size before and after neoadjuvant treatment might help to identify high-risk patients with decreased survival and to improve patient management and care.