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Abstract Programmed death-ligand 1 (PD-L1) expression is currently used in the clinic to assess eligibility for immune-checkpoint inhibitors via the tumor proportion score (TPS), but its efficacy is limited by high interobserver variability. Multiple papers have presented systems for the automatic quantification of TPS, but none report on the task of determining cell-level PD-L1 expression and often reserve their evaluation to a single PD-L1 monoclonal antibody or clinical center. In this paper, we report on a deep learning algorithm for detecting PD-L1 negative and positive tumor cells at a cellular level and evaluate it on a cell-level reference standard established by six readers on a multi-centric, multi PD-L1 assay dataset. This reference standard also provides for the first time a benchmark for computer vision algorithms. In addition, in line with other papers, we also evaluate our algorithm at slide-level by measuring the agreement between the algorithm and six pathologists on TPS quantification. We find a moderately low interobserver agreement at cell-level level (mean reader-reader F1 score = 0.68) which our algorithm sits slightly under (mean reader-AI F1 score = 0.55), especially for cases from the clinical center not included in the training set. Despite this, we find good AI-pathologist agreement on quantifying TPS compared to the interobserver agreement (mean reader-reader Cohen’s kappa = 0.54, 95% CI 0.26–0.81, mean reader-AI kappa = 0.49, 95% CI 0.27—0.72). In conclusion, our deep learning algorithm demonstrates promise in detecting PD-L1 expression at a cellular level and exhibits favorable agreement with pathologists in quantifying the tumor proportion score (TPS). We publicly release our models for use via the Grand-Challenge platform.

Personalization of treatment offers the opportunity to treat patients more effectively based on their dominant disease-specific features. The increasing number and types of treatment, and the high costs associated with these treatments, however, demand new approaches that improve patient selection while reducing treatment-associated costs to ensure sustainable healthcare. The DEDICATION-1 trial has been designed to investigate the non-inferiority of lower dosing regimens when compared to standard of care dosing regimens as a potential effective treatment cost reduction strategy to reduce costs of treatment with expensive immune checkpoint inhibitors in non-small cell lung cancer. If non-inferiority is confirmed, lower dosing regimens could be implemented for all therapeutic indications of pembrolizumab. The cost savings obtained within the trial are partly reinvested in biomarker research to improve the personalization of pembrolizumab treatment. The implementation of these biomarkers will potentially lead to additional cost savings by preventing ineffective pembrolizumab exposure, thereby further reducing the financial pressure on healthcare systems. The concepts discussed within this perspective can be applied both to other anticancer agents, as well as to treatments prescribed outside the oncology field.

Abstract Background Lung cancer is the leading cause of cancer death worldwide. With the growing number of targeted therapies and the introduction of immuno-oncology (IO), personalized medicine has become standard of care in patients with metastatic disease. The development of predictive and prognostic biomarkers is of great importance. Mutational signatures harbor potential clinical value as predictors of therapy response in cancer. Here we set out to investigate particular mutational processes by assessing mutational signatures and associations with clinical features, tumor mutational burden (TMB) and targetable mutations. Methods In this retrospective study, we studied tumor DNA from patients with non-small cell lung cancer (NSCLC) irrespective of stage. The samples were sequenced using a 2 megabase (Mb) gene panel. On each sample TMB was determined and defined as the total number of single nucleotide mutations per Mb (mut/Mb) including non-synonymous mutations. Mutational signature profiling was performed on tumor samples in which at least 30 somatic single base substitutions (SBS) were detected. Results In total 195 samples were sequenced. Median total TMB was 10.3 mut/Mb (range 0–109.3). Mutational signatures were evaluated in 76 tumor samples (39%; median TMB 15.2 mut/Mb). SBS signature 4 (SBS4), associated with tobacco smoking, was prominently present in 25 of 76 samples (33%). SBS2 and/or SBS13, both associated with activity of the AID/APOBEC family of cytidine deaminases, were observed in 11 of 76 samples (14%). SBS4 was significantly more present in early stages (I and II) versus advanced stages (III and IV; P = .005). Conclusion In a large proportion of NSCLC patients tissue panel sequencing with a 2 Mb panel can be used to determine the mutational signatures. In general, mutational signature SBS4 was more often found in early versus advanced stages of NSCLC. Further studies are needed to determine the clinical utility of mutational signature analyses.

Background Immunotherapy is currently part of the standard of care for patients with advanced-stage non-small cell lung cancer (NSCLC). However, many patients do not respond to this treatment, therefore combination strategies are being explored to increase clinical benefit. The PEMBRO-RT trial combined the therapeutic programmed cell death 1 (PD-1) antibody pembrolizumab with stereotactic body radiation therapy (SBRT) to increase the overall response rate and study the effects on the tumor microenvironment (TME).Methods Here, immune infiltrates in the TME of patients included in the PEMBRO-RT trial were investigated. Tumor biopsies of patients treated with pembrolizumab alone or combined with SBRT (a biopsy of the non-irradiated site) at baseline and during treatment were stained with multiplex immunofluorescence for CD3, CD8, CD20, CD103 and FoxP3 for lymphocytes, pan-cytokeratin for tumors, and HLA-ABC expression was determined.Results The total number of lymphocytes increased significantly after 6 weeks of treatment in the anti-PD-1 group (fold change: 1.87, 95% CI: 1.06 to 3.29) and the anti-PD-1+SBRT group (fold change: 2.29, 95% CI: 1.46 to 3.60). The combination of SBRT and anti-PD-1 induced a 4.87-fold increase (95% CI: 2.45 to 9.68) in CD103+ cytotoxic T-cells 6 weeks on treatment and a 2.56-fold increase (95% CI: 1.03 to 6.36) after anti-PD-1 therapy alone. Responders had a significantly higher number of lymphocytes at baseline than non-responders (fold difference 1.85, 95% CI: 1.04 to 3.29 for anti-PD-1 and fold change 1.93, 95% CI: 1.08 to 3.44 for anti-PD-1+SBRT).Conclusion This explorative study shows that that lymphocyte infiltration in general, instead of the infiltration of a specific lymphocyte subset, is associated with response to therapy in patients with NSCLC.Furthermore, anti-PD-1+SBRT combination therapy induces an immunological abscopal effect in the TME represented by a superior infiltration of cytotoxic T cells as compared with anti-PD-1 monotherapy.

Pulmonary hypertension (PH) with complicating chronic lung diseases and/or hypoxia falls into group 3 of the updated classification of PH. Patients with chronic obstructive lung disease (COPD), diffuse lung disease (such as idiopathic pulmonary fibrosis (IPF)) and with sleep disordered breathing are particularly exposed to the risk of developing PH. Although PH in such a context is usually mild, a minority of patients exhibit severe haemodynamic impairment, defined by a mean pulmonary arterial pressure (mPAP) of ≥35 mmHg or mPAP values ranging between 25 mmHg and 35 mmHg with a low cardiac index (

Background: The finding of a renal mass on imaging is suggestive of metastatic non-small cell lung cancer in the presence of a lung tumor but can also have another origin. Case Report: We describe the case of a patient diagnosed with stage IV lung cancer based on a renal metastasis. A second opinion including review of histopathological data and additional imaging followed by lung surgery and cryoablation of the kidney lesion revealed two tumors of different origins, non-small cell lung cancer and a renal cell carcinoma. Discussion: The presence of a renal mass diagnosed on a CT scan in a patient with lung cancer is not always synonymous with metastatic disease. Confirmation of diagnosis by tissue sampling is mandatory, especially if a synchronous primary tumor is possible.

Background: Mutational analysis of the Epidermal Growth Factor Receptor (EGFR) and K-ras genes to select non-small cell lung cancer (NSCLC) patients for treatment with novel EGFR tyrosine kinase inhibitors is an appealing possibility currently under investigation. Although frozen tumor tissue would probably be the optimal source for analysis, the most common source of tumor material is fixed and paraffin embedded (FPE) archival specimens. Here, we evaluate how different procedures of tissue sample processing and preservation may affect the outcome of EGFR and K-ras mutation analysis. Furthermore, we compare the sensitivity of the analysis using genomic DNA (gDNA) versus RNA. Methods: We used PCR amplification and direct sequencing to analyze EGFR and K-ras genes in paired FPE and frozen tumor samples corresponding to 47 NSCLC patients. In frozen samples, the analysis was carried out using both gDNA and RNA extracted in parallel. Results: Whereas 100% of frozen samples were successfully amplified, the rate of successful PCR amplification in FPE samples was approximately 50%. We detected three previously described EGFR point mutations in 2 samples. In ten other samples, a K-ras mutation was observed. These mutations were detected in DNA extracted from frozen samples as well as in DNA obtained from FPE tissue. In addition, 10 nucleotide changes, were detected in FPE samples that were not detected in the frozen specimens. Upon re-analysis, these nucleotide changes could not be confirmed and were most likely the result of paraffin embedding and fixation procedures. All mutations found in gDNA were also detected in the corresponding RNA and, in two cases, the presence of the mutant allele was easier to identify by using RNA. Conclusions: Our results indicate that RNA extracted from frozen tissue is the preferred source for EGFR and K-ras mutation testing. When analyzing FPE samples, reducing the size of the amplified fragments would increase PCR success rate, and care should be taken to control for false-positive results.

Rationale: In severe idiopathic pulmonary arterial hypertension, iPAH, pulmonary vascular resistance is increased due to remodeling of the small (resistance) arteries. Most information on arterial remodeling is limited to assessments of averaged increases in wall thickness. Quantitative information on the number of arteries affected and their internal diameter decrease in relation to vessel size is limited. Our objective was therefore to quantify numbers of affected small arteries and their internal diameter decrease for the differently sized vessels. Methods: Internal and external arterial diameters were measured in 5 controls and 6 iPAH subjects. Resistance arteries (13 to 500 μm) were classified in Strahler orders (1–8), and the number fraction of affected vessels and their internal diameter decrease calculated. Results: In iPAH not all resistance arteries are affected, on average about 70% of arteries have diameters not different from the control subjects, with the number of affected arteries varying between 20 and 50%. Within each order the diameters of affected vessels vary greatly and are decreased to 70-20% of control with on average to about 60% of control. We conclude that narrowing of resistance arteries a feature of iPAH and is heterogeneous: not all arteries are narrowed, and internal diameters of narrowed arteries, even within single orders vary largely. Determination of total vessel numbers of arteries and of veins is necessary to gain insight into the possible role of rarefaction and of changes in the venous system.

Background: Mediastinal lymphadenopathy in combination with lung cancer is suggestive for lymph node metastases but can also have other origins. Case report: We describe a patient diagnosed with stage IV lung cancer presenting with parenchymal lesions and enlarged mediastinal lymph nodes. A second opinion including FDG-PET scan review and a mediastinoscopy followed by surgery revealed tumor specimens originating from a single primary tumor with a sarcoid-like reaction in the mediastinal lymph nodes, changing the diagnosis from metastasized to resectable lung cancer. Discussion: PET positive lesions are not always synonymous with metastatic disease in the presence of a malignant tumor. Conscientious review of FDG-PET scans and tissue sampling are therefore mandatory to determine definitive staging and subsequent interventions.

Background: Fibrosis is associated with various cardiac pathologies and dysfunction. Current quantification methods are time-consuming and laborious. We describe a semi-automated quantification technique for myocardial fibrosis and validated this using traditional methods.

Abstract: Until recently, the division of pulmonary carcinomas into small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC) was adequate for therapy selection. Due to the emergence of new treatment options subtyping of NSCLC and predictive testing have become mandatory. A practical approach to the new requirements involving interaction between pulmonologist, oncologist and molecular pathology to optimize patient care is described. The diagnosis of lung cancer involves (i) the identification and complete classification of malignancy, (ii) immunohistochemistry is used to predict the likely NSCLC subtype (squamous cell vs. adenocarcinoma), as in small diagnostic samples specific subtyping is frequently on morphological grounds alone not feasible (NSCLC-NOS), (iii) molecular testing. To allow the extended diagnostic and predictive examination (i) tissue sampling should be maximized whenever feasible and deemed clinically safe, reducing the need for re-biopsy for additional studies and (ii) tissue handling, processing and sectioning should be optimized. Complex diagnostic algorithms are emerging, which will require close dialogue and understanding between pulmonologists and others who are closely involved in tissue acquisition, pathologists and oncologists who will ultimately, with the patient, make treatment decisions. Personalized medicine not only means the choice of treatment tailored to the individual patient, but also reflects the need to consider how investigative and diagnostic strategies must also be planned according to individual tumour characteristics. [Copyright &y& Elsevier]