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Abstract Background In patients with resectable stage III non-small cell lung cancer (NSCLC), induction chemoimmunotherapy followed by surgical resection has shown unprecedented rates of pathological response and event-free survival. However, a triple-induction including radiochemotherapy and immunotherapy followed by surgical resection has not been routinely established in clinical practice. Case presentation We report the case of a 47-year-old patient with stage IIIA NSCLC who was treated in a combined concept including induction concurrent radiochemotherapy, followed by 4 cycles of pembrolizumab and subsequent intrapericardial left-sided pneumonectomy. Histological analysis revealed a pathological complete response. Conclusions The case demonstrates that the combination of neoadjuvant chemo-, radio- and immunotherapy in advanced NSCLC may lead to a relevant down-staging and may enable a R0-resection of a borderline resectable tumor. However, the combination of four different treatment modalities requires resilience and a good performance status. A triple induction treatment may be a promising option for selected patients with locally advanced NSCLC and good performance status.

Abstract This study aimed to evaluate the diagnostic accuracy of Node Reporting and Data System (Node-RADS) in discriminating between normal, reactive, and metastatic axillary LNs in patients with melanoma who underwent SARS-CoV-2 vaccination. Patients with proven melanoma who underwent a 2-[18F]-fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography (2-[18F]-FDG PET/CT) between February and April 2021 were included in this retrospective study. Primary melanoma site, vaccination status, injection site, and 2-[18F]-FDG PET/CT were used to classify axillary LNs into normal, inflammatory, and metastatic (combined classification). An adapted Node-RADS classification (A-Node-RADS) was generated based on LN anatomical characteristics on low-dose CT images and compared to the combined classification. 108 patients were included in the study (54 vaccinated). HALNs were detected in 42 patients (32.8%), of whom 97.6% were vaccinated. 172 LNs were classified as normal, 30 as inflammatory, and 14 as metastatic using the combined classification. 152, 22, 29, 12, and 1 LNs were classified A-Node-RADS 1, 2, 3, 4, and 5, respectively. Hence, 174, 29, and 13 LNs were deemed benign, equivocal, and metastatic. The concordance between the classifications was very good (Cohen’s k: 0.91, CI 0.86–0.95; p-value

Abstract Immune checkpoint inhibitor treatment has the potential to prolong survival in non-small cell lung cancer (NSCLC), however, some of the patients develop resistance following initial response. Here, we analyze the immune phenotype of matching tumor samples from a cohort of NSCLC patients showing good initial response to immune checkpoint inhibitors, followed by acquired resistance at later time points. By using imaging mass cytometry and whole exome and RNA sequencing, we detect two patterns of resistance¨: One group of patients is characterized by reduced numbers of tumor-infiltrating CD8+ T cells and reduced expression of PD-L1 after development of resistance, whereas the other group shows high CD8+ T cell infiltration and high expression of PD-L1 in addition to markedly elevated expression of other immune-inhibitory molecules. In two cases, we detect downregulation of type I and II IFN pathways following progression to resistance, which could lead to an impaired anti-tumor immune response. This study thus captures the development of immune checkpoint inhibitor resistance as it progresses and deepens our mechanistic understanding of immunotherapy response in NSCLC.

Abstract To evaluate whether a machine learning classifier can evaluate image quality of maximum intensity projection (MIP) images from F18-FDG-PET scans. A total of 400 MIP images from F18-FDG-PET with simulated decreasing acquisition time (120 s, 90 s, 60 s, 30 s and 15 s per bed-position) using block sequential regularized expectation maximization (BSREM) with a beta-value of 450 and 600 were created. A machine learning classifier was fed with 283 images rated “sufficient image quality” and 117 images rated “insufficient image quality”. The classification performance of the machine learning classifier was assessed by calculating sensitivity, specificity, and area under the receiver operating characteristics curve (AUC) using reader-based classification as the target. Classification performance of the machine learning classifier was AUC 0.978 for BSREM beta 450 and 0.967 for BSREM beta 600. The algorithm showed a sensitivity of 89% and 94% and a specificity of 94% and 94% for the reconstruction BSREM 450 and 600, respectively. Automated assessment of image quality from F18-FDG-PET images using a machine learning classifier provides equivalent performance to manual assessment by experienced radiologists.

Abstract Background Carcinoid heart disease is a rare disease which develops in patients with functional neuroendocrine tumors in an advanced tumor state. Patients diagnosed with carcinoid heart disease have a poor longtime prognosis with respect to morbidity and mortality and long-term data on patient outcomes are lacking. Methods and results In this retrospective study, we analyzed outcomes of 23 patients with carcinoid heart disease enrolled into the SwissNet database. We observed that early diagnosis with echocardiographic surveillance of carcinoid heart disease during the course of the neuroendocrine tumor disease was beneficial to overall survival of patients. Conclusion Through nationwide patient enrollment, the SwissNet registry is a powerful data tool to identify, follow-up and evaluate long-term patient outcomes in patients with rare neuroendocrine tumor driven pathologies including carcinoid heart syndrome with observational methods enabling better therapy optimization to improve patient`s long-term perspectives and survival. In line with the current ESMO recommendations, our data proposes that heart echocardiography should be included as part of the general physical assessment in patients with newly diagnosed NET.

Background Few tissue biomarkers exist to date that could enrich patient with cancer populations to benefit from immune checkpoint blockade by programmed cell death protein 1/ligand-1 (PD-/L-1) inhibitors. PD-L1 expression has value in this context in some tumor types but is an imperfect predictor of clinical benefit. In malignant pleural mesothelioma, PD-L1 expression is not predictive of the benefit from PD-1 blockade. We aimed to identify novel markers in malignant pleural mesothelioma to select patients better.Methods We performed a multiplex-immune histochemistry analysis of tumor samples from the phase III PROMISE-meso study, which randomized 144 pretreated patients to receive either pembrolizumab or standard second-line chemotherapy. Our panel focused on CD8+T cell, CD68+macrophages, and the expression of PD-1 and PD-L1 on these and cancer cells. We analyzed single and double positive cells within cancer tissues (infiltrating immune cells) and in the stroma. In addition, we performed cell neighborhood analysis. The cell counts were compared with clinical outcomes, including responses, progression-free and overall survivals.Results We confirmed the absence of predictive value for PD-L1 in this cohort of patients. Furthermore, total CD8 T cells, CD68+macrophages, or inflammatory subtypes (desert, excluded, inflamed) did not predict outcomes. In contrast, PD-1-expressing CD8+T cells (exhausted T cells) and PD-1-expressing CD68+macrophages were both independent predictors of progression-free survival benefit from pembrolizumab. Patients with tumors simultaneously harboring PD1+T cells and PD-1+macrophages benefited the most from immune therapy.Conclusion We analyzed a large cohort of patients within a phase III study and found that not only PD-1+CD8 T cells but also PD-1+CD68+ macrophages are predictive. This data provides evidence for the first time for the existence of PD-1+macrophages in mesothelioma and their clinical relevance for immune checkpoint blockade.

Background CheckMate 817, a phase 3B study, evaluated flat-dose nivolumab plus weight-based ipilimumab in patients with metastatic non-small cell lung cancer (NSCLC). Here, in this research, we report on first-line treatment in patients with Eastern Cooperative Oncology Group (ECOG) performance status (PS) 0–1 (cohort A) and special populations (cohort A1: ECOG PS 2; or ECOG PS 0–1 with untreated brain metastases, renal impairment, hepatic impairment, or controlled HIV infection).Methods Cohorts A and A1 received nivolumab 240 mg every 2 weeks plus ipilimumab 1 mg/kg every 6 weeks. The primary endpoint was the incidence of grade 3–4 and grade 5 immune-mediated adverse events (IMAEs; adverse events (AEs) deemed potentially immune-related, occurring

BackgroundAnaplastic lymphoma kinase (ALK) rearrangements are known oncogenic drivers in non-small cell lung cancer (NSCLC). Few case reports described the occurrence of such rearrangements in large cell neuroendocrine carcinomas (LCNECs) of the lung without information on clinical responses to ALK tyrosine kinase inhibitors (TKIs) in these cases. Currently, neuroendocrine tumors of the lungs are not screened for ALK rearrangements.MethodsTo illustrate the clinical impact of molecular characterization in LCNECs, we report the disease course in three patients with ALK-rearranged metastatic LCNEC from our clinical routine, as well as their treatment response to ALK TKIs (index cases). To gain insight into the prevalence of ALK rearrangements in neuroendocrine tumors of the lung, we analyzed a retrospective cohort of 436 tumor biopsies including LCNEC (n = 61), small cell lung cancer (SCLC) (n = 206), typical (n = 91) and atypical (n = 69) carcinoids, and mixed histology (n = 9) for the presence of ALK rearrangements using a sequential diagnostic algorithm. ALK immunohistochemistry (IHC) was evaluable in 362 cases; fluorescence in situ hybridization (FISH) was evaluable in 28 out of the 35 IHC-positive cases, followed by next-generation sequencing (NGS) that was available in 12 cases.ResultsWithin the retrospective cohort, ALK IHC was positive in 35 out of 362 (9.7%) evaluable samples. FISH was positive in 3 out of the 28 (10.7%) evaluable cases: 2 with atypical carcinoids and 1 with LCNEC. Additionally, the 3 index cases showed positive ALK IHC, which was confirmed by NGS. Within the retrospective cohort, NGS confirmed the presence of an ALK genomic rearrangement in one FISH-positive atypical carcinoid where material was sufficient for sequencing. Two out of three patients with metastatic ALK-rearranged LCNEC received up-front treatment with the ALK TKI alectinib and showed rapid tumor response at all metastatic sites, including multiple brain metastases.ConclusionsALK rearrangements represent rare but targetable oncogenic driver alterations in LCNEC. Contrarily to NSCLC, the detection of ALK rearrangements in neuroendocrine tumors of the lung is challenging, since ALK IHC can lead to false-positive results and therefore needs confirmation by FISH or NGS. Up-front comprehensive molecular profiling with NGS should be performed in metastatic LCNEC in order not to miss actionable genomic alterations.

The coronavirus disease 2019 (COVID-19) pandemic has had a severe impact on oncological and thoracic surgical practice worldwide. In many hospitals, the care of COVID-19 patients required a reduction of elective surgery, to avoid viral transmission within the hospital, and to save and preserve personnel and material resources. Cancer patients are more susceptible to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection and are at an increased risk of a severe course of disease. In many patients with lung cancer, this risk is further increased owing to comorbidities, older age and a pre-existing lung disease. Surgical resection is an important part of the treatment in patients with early stage or locally advanced non-small cell lung cancer, but the treatment of these patients during the COVID-19 pandemic becomes a challenging balance between the risk of patient exposure to SARS-CoV-2 and the need to provide timely and adequate cancer treatment despite limited hospital capacities. This manuscript aims to provide an overview of the surgical treatment of lung cancer patients during the COVID-19 pandemic including the triage and prioritisation as well as the surgical approach, and our own experience with cancer surgery during the first pandemic wave. We furthermore aim to highlight the risk and potential consequences of delayed lung cancer treatment due to the deferral of surgery, screening appointments and follow-up visits. With much attention being diverted to COVID-19, it is important to retain awareness of cancer patients, maintain oncological surgery and avoid treatment delay during the pandemic.

Objectives: The objective of this study was to assess the feasibility and accuracy of a fully automated artificial intelligence (AI) powered coronary artery calcium scoring (CACS) method on ungated CT in oncologic patients undergoing 18F-FDG PET/CT. Methods: A total of 100 oncologic patients examined between 2007 and 2015 were retrospectively included. All patients underwent 18F-FDG PET/CT and cardiac SPECT myocardial perfusion imaging (MPI) by 99mTc-tetrofosmin within 6 months. CACS was manually performed on non-contrast ECG-gated CT scans obtained from SPECT-MPI (i.e., reference standard). Additionally, CACS was performed using a cloud-based, user-independent tool (AI-CACS) on ungated CT scans from 18F-FDG-PET/CT examinations. Agatston scores from the manual CACS and AI-CACS were compared. Results: On a per-patient basis, the AI-CACS tool achieved a sensitivity and specificity of 85% and 90% for the detection of CAC. Interscore agreement of CACS between manual CACS and AI-CACS was 0.88 (95% CI: 0.827, 0.918). Interclass agreement of risk categories was 0.8 in weighted Kappa analysis, with a reclassification rate of 44% and an underestimation of one risk category by AI-CACS in 39% of cases. On a per-vessel basis, interscore agreement of CAC scores ranged from 0.716 for the circumflex artery to 0.863 for the left anterior descending artery. Conclusions: Fully automated AI-CACS as performed on non-contrast free-breathing, ungated CT scans from 18F-FDG-PET/CT examinations is feasible and provides an acceptable to good estimation of CAC burden. CAC load on ungated CT is, however, generally underestimated by AI-CACS, which should be taken into account when interpreting imaging findings.