Morphologic Features of Invasion in Lung Adenocarcinoma: Diagnostic Pitfalls

Reproducibility of pulmonary invasive adenocarcinoma diagnosis is poor when applying the World Health Organization (WHO) classification. In this article, we aimed first to explain by 3-dimensional morphology why simple pattern recognition induces pitfalls for the assessment of invasion as applied in the current WHO classification of pulmonary adenocarcinomas. The underlying iatrogenic-induced morphologic alterations in collapsed adenocarcinoma in situ overlap with criteria for invasive adenocarcinoma. Pitfalls in seemingly acinar and papillary carcinoma are addressed with additional cytokeratin 7 and elastin stains. In addition, we provide more stringent criteria for a better reproducible and likely generalizable classification.

Pathology of Surgically Resected Lung Cancers Following Neoadjuvant Therapy

In around 30% of patients, non-small cell lung cancer is diagnosed at an advanced but resectable stage. Adding systemic therapy has shown clear benefit over surgery alone in locally advanced disease, and currently, chemo-immunotherapy in the adjuvant or neoadjuvant setting is the new standard for patients without targetable mutations. One major advantage of the neoadjuvant approach is the possibility of an immediate evaluation of the treatment effect, highlighting the role of pathology as an important contributor at the forefront of clinical decision-making and research. This review provides a summary and an update on current guidelines for histological evaluation of treatment effect after neoadjuvant therapy, also known as regression grading, and discusses newer data focusing on areas of evolving questions and controversies, such as the gross examination of the tumor and tumor bed, weighted versus unweighted evaluation approaches, discussion of histologic tumor type-specific cut-offs for major pathologic response, assessment of lymph nodes and regression grading after immunotherapy and targeted therapy. As no data or recommendations exist on regression grading of multiple tumor nodules, a practical approach is recommended. Lastly, we will touch on additional tissue biomarkers and summarize recent advances in the ardently discussed field of using circulating tumor DNA for the evaluation of treatment response.

Genomic Staging of Multifocal Lung Squamous Cell Carcinomas Is Independent of the Comprehensive Morphologic Assessment

INTRODUCTION

Morphologic and molecular data for staging of multifocal lung squamous cell carcinomas (LSCCs) are limited. In this study, whole exome sequencing (WES) was used as the gold standard to determine whether multifocal LSCC represented separate primary lung cancers (SPLCs) or intrapulmonary metastases (IPMs). Genomic profiles were compared with the comprehensive morphologic assessment.

METHODS

WES was performed on 20 tumor pairs of multifocal LSCC and matched normal lymph nodes using the Illumina NovaSeq6000 S4-Xp (Illumina, San Diego, CA). WES clonal and subclonal analysis data were compared with histologic assessment by 16 thoracic pathologists. In addition, the immune gene profiling of the study cases was characterized by the HTG EdgeSeq Precision Immuno-Oncology Panel.

RESULTS

By WES data, 11 cases were classified as SPLC and seven cases as IPM. Two cases were technically suboptimal. Analysis revealed marked genomic and immunogenic heterogeneity, but immune gene expression profiles highly correlated with mutation profiles. Tumors classified as IPM have a large number of shared mutations (ranging from 33.5% to 80.7%). The agreement between individual morphologic assessments for each case and WES was 58.3%. One case was unanimously interpreted morphologically as IPM and was in agreement with WES. In a further 17 cases, the number of pathologists whose morphologic interpretation was in agreement with WES ranged from two (one case) to 15 pathologists (one case) per case. Pathologists showed a fair interobserver agreement in the morphologic staging of multiple LSCCs, with an overall kappa of 0.232.

CONCLUSIONS

Staging of multifocal LSCC based on morphologic assessment is unreliable. Comprehensive genomic analyses should be adopted for the staging of multifocal LSCC.

Current challenges and practical aspects of molecular pathology for non-small cell lung cancers

The continuing evolution of treatment options in thoracic oncology requires the pathologist to regularly update diagnostic algorithms for management of tumor samples. It is essential to decide on the best way to use tissue biopsies, cytological samples, as well as liquid biopsies to identify the different mandatory predictive biomarkers of lung cancers in a short turnaround time. However, biological resources and laboratory member workforce are limited and may be not sufficient for the increased complexity of molecular pathological analyses and for complementary translational research development. In this context, the surgical pathologist is the only one who makes the decisions whether or not to send specimens to immunohistochemical and molecular pathology platforms. Moreover, the pathologist can rapidly contact the oncologist to obtain a new tissue biopsy and/or a liquid biopsy if he/she considers that the biological material is not sufficient in quantity or quality for assessment of predictive biomarkers. Inadequate control of algorithms and sampling workflow may lead to false negative, inconclusive, and incomplete findings, resulting in inappropriate choice of therapeutic strategy and potentially poor outcome for patients. International guidelines for lung cancer treatment are based on the results of the expression of different proteins and on genomic alterations. These guidelines have been established taking into consideration the best practices to be set up in clinical and molecular pathology laboratories. This review addresses the current predictive biomarkers and algorithms for use in thoracic oncology molecular pathology as well as the central role of the pathologist, notably in the molecular tumor board and her/his participation in the treatment decision-making. The perspectives in this setting will be discussed.

Impact of template-based synoptic reporting on completeness of surgical pathology reports

Synoptic reporting increases completeness and standardization of surgical pathology reports and thereby contributes to an increased quality of clinical cancer care. Nevertheless, its widespread practical implementation remains a challenge, which is in part related to the effort required for setup and maintenance of database structures. This prompted us to assess the effect of a simple template-based, database-free system for synoptic reporting on completeness of surgical pathology reports. For this purpose, we analyzed 200 synoptic reports (100 colon and 100 lung cancer resections each) for completeness as required by the pertinent College of American Pathologists (CAP) protocols and compared these to a control dataset of 200 narrative reports. Introduction of template-based synoptic reporting resulted in improved completeness (98% of mandatory data elements) as compared to narrative reports (77%). Narrative reports showed a high degree of completeness for data elements covered by previously existing dictation templates. In conclusion, template-based synoptic reporting without underlying database structure can be a useful transitory phase in the implementation of synoptic reporting. It can result in a similar degree of completeness as reported in the literature for database solutions and provides other benefits of synoptic reporting while facilitating its implementation.

Pulmonary squamous cell carcinoma and lymphoepithelial carcinoma - morphology, molecular characteristics and differential diagnosis

Squamous cell carcinoma (SCC) comprises one of the major groups of non-small-cell carcinoma of the lung, and is subtyped into keratinising, non-keratinising and basaloid SCC. SCC can readily be diagnosed using histomorphology alone in keratinising SCC. Confirmatory immunohistochemical analyses should always be applied in non-keratinising and basaloid tumours to exclude differential diagnoses, most prominently adenocarcinoma and high-grade neuroendocrine carcinoma, which may have important therapeutic consequences. According to the World Health Organisation (WHO) classification 2015, the diagnosis of SCC can be rendered in resections of morphologically ambiguous tumours with squamous immunophenotype. In biopsies and cytology preparations in the same setting the current guidelines propose a diagnosis of 'non-small-cell carcinoma, favour SCC' in TTF1-negative and p40-positive tumours to acknowledge a possible sampling bias and restrict extended immunohistochemical evaluation in order to preserve tissue for molecular testing. Most SCC feature a molecular 'tobacco-smoke signature' with enrichment in GG > TT mutations, in line with the strong epidemiological association of SCC with smoking. Targetable mutations are extremely rare but they do occur, in particular in younger and non- or light-smoking patients, warranting molecular investigations. Lymphoepithelial carcinoma (LEC) is a poorly differentiated SCC with a syncytial growth pattern and a usually prominent lymphoplasmacytic infiltrate and frequent Epstein-Barr virus (EBV) association. In this review, we describe the morphological and molecular characteristics of SCC and LEC and discuss the most pertinent differential diagnoses.

Swiss digital pathology recommendations: results from a Delphi process conducted by the Swiss Digital Pathology Consortium of the Swiss Society of Pathology

Integration of digital pathology (DP) into clinical diagnostic workflows is increasingly receiving attention as new hardware and software become available. To facilitate the adoption of DP, the Swiss Digital Pathology Consortium (SDiPath) organized a Delphi process to produce a series of recommendations for DP integration within Swiss clinical environments. This process saw the creation of 4 working groups, focusing on the various components of a DP system (1) scanners, quality assurance and validation of scans, (2) integration of Whole Slide Image (WSI)-scanners and DP systems into the Pathology Laboratory Information System, (3) digital workflow-compliance with general quality guidelines, and (4) image analysis (IA)/artificial intelligence (AI), with topic experts for each recruited for discussion and statement generation. The work product of the Delphi process is 83 consensus statements presented here, forming the basis for "SDiPath Recommendations for Digital Pathology". They represent an up-to-date resource for national and international hospitals, researchers, device manufacturers, algorithm developers, and all supporting fields, with the intent of providing expectations and best practices to help ensure safe and efficient DP usage.

Digital image analysis and artificial intelligence in pathology diagnostics-the Swiss view

Digital pathology (DP) is increasingly entering routine clinical pathology diagnostics. As digitization of the routine caseload advances, implementation of digital image analysis algorithms and artificial intelligence tools becomes not only attainable, but also desirable in daily sign out. The Swiss Digital Pathology Consortium (SDiPath) has initiated a Delphi process to generate best-practice recommendations for various phases of the process of digitization in pathology for the local Swiss environment, encompassing the following four topics: i) scanners, quality assurance, and validation of scans; ii) integration of scanners and systems into the pathology laboratory information system; iii) the digital workflow; and iv) digital image analysis (DIA)/artificial intelligence (AI). The current article focuses on the DIA-/AI-related recommendations generated and agreed upon by the working group and further verified by the Delphi process among the members of SDiPath. Importantly, they include the view and the currently perceived needs of practicing pathologists from multiple academic and cantonal hospitals as well as private practices.

Pathologist Computer-Aided Diagnostic Scoring of Tumor Cell Fraction: A Swiss National Study

Tumor cell fraction (TCF) estimation is a common clinical task with well-established large interobserver variability. It thus provides an ideal test bed to evaluate potential impacts of employing a tumor cell fraction computer-aided diagnostic (TCFCAD) tool to support pathologists' evaluation. During a National Slide Seminar event, pathologists (n = 69) were asked to visually estimate TCF in 10 regions of interest (ROIs) from hematoxylin and eosin colorectal cancer images intentionally curated for diverse tissue compositions, cellularity, and stain intensities. Next, they re-evaluated the same ROIs while being provided a TCFCAD-created overlay highlighting predicted tumor vs nontumor cells, together with the corresponding TCF percentage. Participants also reported confidence levels in their assessments using a 5-tier scale, indicating no confidence to high confidence, respectively. The TCF ground truth (GT) was defined by manual cell-counting by experts. When assisted, interobserver variability significantly decreased, showing estimates converging to the GT. This improvement remained even when TCFCAD predictions deviated slightly from the GT. The standard deviation (SD) of the estimated TCF to the GT across ROIs was 9.9% vs 5.8% with TCFCAD (P < .0001). The intraclass correlation coefficient increased from 0.8 to 0.93 (95% CI, 0.65-0.93 vs 0.86-0.98), and pathologists stated feeling more confident when aided (3.67 ± 0.81 vs 4.17 ± 0.82 with the computer-aided diagnostic [CAD] tool). TCFCAD estimation support demonstrated improved scoring accuracy, interpathologist agreement, and scoring confidence. Interestingly, pathologists also expressed more willingness to use such a CAD tool at the end of the survey, highlighting the importance of training/education to increase adoption of CAD systems.

Standardized Classification of Lung Adenocarcinoma Subtypes and Improvement of Grading Assessment Through Deep Learning

The histopathologic distinction of lung adenocarcinoma (LADC) subtypes is subject to high interobserver variability, which can compromise the optimal assessment of patient prognosis. Therefore, this study developed convolutional neural networks capable of distinguishing LADC subtypes and predicting disease-specific survival, according to the recently established LADC tumor grades. Consensus LADC histopathologic images were obtained from 17 expert pulmonary pathologists and one pathologist in training. Two deep learning models (AI-1 and AI-2) were trained to predict eight different LADC classes. Furthermore, the trained models were tested on an independent cohort of 133 patients. The models achieved high precision, recall, and F1 scores exceeding 0.90 for most of the LADC classes. Clear stratification of the three LADC grades was reached in predicting the disease-specific survival by the two models, with both Kaplan-Meier curves showing significance (P = 0.0017 and 0.0003). Moreover, both trained models showed high stability in the segmentation of each pair of predicted grades with low variation in the hazard ratio across 200 bootstrapped samples. These findings indicate that the trained convolutional neural networks improve the diagnostic accuracy of the pathologist and refine LADC grade assessment. Thus, the trained models are promising tools that may assist in the routine evaluation of LADC subtypes and grades in clinical practice.

Spatial metabolomics identifies distinct tumor-specific and stroma-specific subtypes in patients with lung squamous cell carcinoma

Molecular subtyping of lung squamous cell carcinoma (LUSC) has been performed at the genomic, transcriptomic, and proteomic level. However, LUSC stratification based on tissue metabolomics is still lacking. Combining high-mass-resolution imaging mass spectrometry with consensus clustering, four tumor- and four stroma-specific subtypes with distinct metabolite patterns were identified in 330 LUSC patients. The first tumor subtype T1 negatively correlated with DNA damage and immunological features including CD3, CD8, and PD-L1. The same features positively correlated with the tumor subtype T2. Tumor subtype T4 was associated with high PD-L1 expression. Compared with the status of subtypes T1 and T4, patients with subtype T3 had improved prognosis, and T3 was an independent prognostic factor with regard to UICC stage. Similarly, stroma subtypes were linked to distinct immunological features and metabolic pathways. Stroma subtype S4 had a better prognosis than S2. Subsequently, analyses based on an independent LUSC cohort treated by neoadjuvant therapy revealed that the S2 stroma subtype was associated with chemotherapy resistance. Clinically relevant patient subtypes as determined by tissue-based spatial metabolomics are a valuable addition to existing molecular classification systems. Metabolic differences among the subtypes and their associations with immunological features may contribute to the improvement of personalized therapy.

International Association for the Study of Lung Cancer Study of Reproducibility in Assessment of Pathologic Response in Resected Lung Cancers After Neoadjuvant Therapy

INTRODUCTION

Pathologic response has been proposed as an early clinical trial end point of survival after neoadjuvant treatment in clinical trials of NSCLC. The International Association for the Study of Lung Cancer (IASLC) published recommendations for pathologic evaluation of resected lung cancers after neoadjuvant therapy. The aim of this study was to assess pathologic response interobserver reproducibility using IASLC criteria.

METHODS

An international panel of 11 pulmonary pathologists reviewed hematoxylin and eosin-stained slides from the lung tumors of resected NSCLC from 84 patients who received neoadjuvant immune checkpoint inhibitors in six clinical trials. Pathologic response was assessed for percent viable tumor, necrosis, and stroma. For each slide, tumor bed area was measured microscopically, and pre-embedded formulas calculated unweighted and weighted major pathologic response (MPR) averages to reflect variable tumor bed proportion.

RESULTS

Unanimous agreement among pathologists for MPR was observed in 68 patients (81%), and inter-rater agreement (IRA) was 0.84 (95% confidence interval [CI]: 0.76-0.92) and 0.86 (95% CI: 0.79-0.93) for unweighted and weighted averages, respectively. Overall, unweighted and weighted methods did not reveal significant differences in the classification of MPR. The highest concordance by both methods was observed for cases with more than 95% viable tumor (IRA = 0.98, 95% CI: 0.96-1) and 0% viable tumor (IRA = 0.94, 95% CI: 0.89-0.98). The most common reasons for discrepancies included interpretations of tumor bed, presence of prominent stromal inflammation, distinction between reactive and neoplastic pneumocytes, and assessment of invasive mucinous adenocarcinoma.

CONCLUSIONS

Our study revealed excellent reliability in cases with no residual viable tumor and good reliability for MPR with the IASLC recommended less than or equal to 10% cutoff for viable tumor after neoadjuvant therapy.

Patterns of Carbon-Bound Exogenous Compounds Impact Disease Pathophysiology in Lung Cancer Subtypes in Different Ways

Carbon-bound exogenous compounds, such as polycyclic aromatic hydrocarbons (PAHs), tobacco-specific nitrosamines, aromatic amines, and organohalogens, are known to affect both tumor characteristics and patient outcomes in lung squamous cell carcinoma (LUSC); however, the roles of these compounds in lung adenocarcinoma (LUAD) remain unclear. We analyzed 11 carbon-bound exogenous compounds in LUAD and LUSC samples using in situ high mass-resolution matrix-assisted laser desorption/ionization Fourier-transform ion cyclotron resonance mass spectrometry imaging and performed a cluster analysis to compare the patterns of carbon-bound exogenous compounds between these two lung cancer subtypes. Correlation analyses were conducted to investigate associations among exogenous compounds, endogenous metabolites, and clinical data, including patient survival outcomes and smoking behaviors. Additionally, we examined differences in exogenous compound patterns between normal and tumor tissues. Our analyses revealed that PAHs, aromatic amines, and organohalogens were more abundant in LUAD than in LUSC, whereas the tobacco-specific nitrosamine nicotine-derived nitrosamine ketone was more abundant in LUSC. Patients with LUAD and LUSC could be separated according to carbon-bound exogenous compound patterns detected in the tumor compartment. The same compounds had differential impacts on patient outcomes, depending on the cancer subtype. Correlation and network analyses indicated substantial differences between LUAD and LUSC metabolomes, associated with substantial differences in the patterns of the carbon-bound exogenous compounds. These data suggest that the contributions of these carcinogenic compounds to cancer biology may differ according to the cancer subtypes.

Neoadjuvant treatment does not influence PD-L1 expression in stage III non-small-cell lung cancer: a retrospective analysis of tumor samples from the trials SAKK 16/96, 16/00, 16/01, and 16/14

BACKGROUND

The inclusion of immune checkpoint inhibitors (ICIs) in the treatment of operable stage III non-small-cell lung cancer is becoming a new standard. Programmed death-ligand 1 (PD-L1) protein expression on tumor cells has emerged as the most important biomarker for sensitivity to ICIs targeting the programmed cell death protein 1 (PD-1)-PD-L1 axis. Little is known about the impact of neoadjuvant treatment on PD-L1 expression.

PATIENTS AND METHODS

We assessed PD-L1 expression by immunohistochemistry (Ventana SP263 assay) on tumor cells in treatment-naive diagnostic tumor samples and matched lung resections from patients with stage III non-small-cell lung cancer included in the Swiss Group for Clinical Cancer Research (SAKK) trials 16/96, 16/00, 16/01, and 16/14. All patients received neoadjuvant chemotherapy (CT) with cisplatin/docetaxel, either as single modality (CT), with sequential radiotherapy [chemoradiation therapy (CRT)] or with the PD-L1 inhibitor durvalumab (CT + ICI).

RESULTS

Overall, 132 paired tumor samples were analyzed from patients with neoadjuvant CT (n = 69), CRT (n = 33) and CT + ICI (n = 30). For CT and CRT, PD-L1 expression before and after neoadjuvant treatment did not differ significantly (Wilcoxon test, P = 0.94). Likewise, no statistically significant difference was observed between CT and CRT for PD-L1 expression after neoadjuvant treatment (P = 0.97). For CT + ICI, PD-L1 expression before and after neoadjuvant treatment also did not differ significantly (Wilcoxon test, P > 0.99). Event-free survival and overall survival for patients with downregulation or upregulation of PD-L1 expression after neoadjuvant treatment were similar.

CONCLUSIONS

In our cohort of patients neoadjuvant treatment did not influence PD-L1 expression, irrespective of the specific neoadjuvant treatment protocol. Dynamic change of PD-L1 expression did not correlate with event-free survival or overall survival.

Overcoming the Interobserver Variability in Lung Adenocarcinoma Subtyping: A Clustering Approach to Establish a Ground Truth for Downstream Applications

CONTEXT.—

The accurate identification of different lung adenocarcinoma histologic subtypes is important for determining prognosis but can be challenging because of overlaps in the diagnostic features, leading to considerable interobserver variability.

OBJECTIVE.—

To provide an overview of the diagnostic agreement for lung adenocarcinoma subtypes among pathologists and to create a ground truth using the clustering approach for downstream computational applications.

DESIGN.—

Three sets of lung adenocarcinoma histologic images with different evaluation levels (small patches, areas with relatively uniform histology, and whole slide images) were reviewed by 17 international expert lung pathologists and 1 pathologist in training. Each image was classified into one or several lung adenocarcinoma subtypes.

RESULTS.—

Among the 4702 patches of the first set, 1742 (37%) had an overall consensus among all pathologists. The overall Fleiss κ score for the agreement of all subtypes was 0.58. Using cluster analysis, pathologists were hierarchically grouped into 2 clusters, with κ scores of 0.588 and 0.563 in clusters 1 and 2, respectively. Similar results were obtained for the second and third sets, with fair-to-moderate agreements. Patches from the first 2 sets that obtained the consensus of the 18 pathologists were retrieved to form consensus patches and were regarded as the ground truth of lung adenocarcinoma subtypes.

CONCLUSIONS.—

Our observations highlight discrepancies among experts when assessing lung adenocarcinoma subtypes. However, a subsequent number of consensus patches could be retrieved from each cluster, which can be used as ground truth for the downstream computational pathology applications, with minimal influence from interobserver variability.

Deep computational image analysis of immune cell niches reveals treatment-specific outcome associations in lung cancer

The tumor immune composition influences prognosis and treatment sensitivity in lung cancer. The presence of effective adaptive immune responses is associated with increased clinical benefit after immune checkpoint blockers. Conversely, immunotherapy resistance can occur as a consequence of local T-cell exhaustion/dysfunction and upregulation of immunosuppressive signals and regulatory cells. Consequently, merely measuring the amount of tumor-infiltrating lymphocytes (TILs) may not accurately reflect the complexity of tumor-immune interactions and T-cell functional states and may not be valuable as a treatment-specific biomarker. In this work, we investigate an immune-related biomarker (PhenoTIL) and its value in associating with treatment-specific outcomes in non-small cell lung cancer (NSCLC). PhenoTIL is a novel computational pathology approach that uses machine learning to capture spatial interplay and infer functional features of immune cell niches associated with tumor rejection and patient outcomes. PhenoTIL's advantage is the computational characterization of the tumor immune microenvironment extracted from H&E-stained preparations. Association with clinical outcome and major non-small cell lung cancer (NSCLC) histology variants was studied in baseline tumor specimens from 1,774 lung cancer patients treated with immunotherapy and/or chemotherapy, including the clinical trial Checkmate 057 (NCT01673867).

Immunogenomic analysis of human brain metastases reveals diverse immune landscapes across genetically distinct tumors

Brain metastases (BrMs) are the most common form of brain tumors in adults and frequently originate from lung and breast primary cancers. BrMs are associated with high mortality, emphasizing the need for more effective therapies. Genetic profiling of primary tumors is increasingly used as part of the effort to guide targeted therapies against BrMs, and immune-based strategies for the treatment of metastatic cancer are gaining momentum. However, the tumor immune microenvironment (TIME) of BrM is extremely heterogeneous, and whether specific genetic profiles are associated with distinct immune states remains unknown. Here, we perform an extensive characterization of the immunogenomic landscape of human BrMs by combining whole-exome/whole-genome sequencing, RNA sequencing of immune cell populations, flow cytometry, immunofluorescence staining, and tissue imaging analyses. This revealed unique TIME phenotypes in genetically distinct lung- and breast-BrMs, thereby enabling the development of personalized immunotherapies tailored by the genetic makeup of the tumors.

Immunohistochemical Detection of the Chaperone-Mediated Autophagy Markers LAMP2A and HSPA8 in Formalin-Fixed and Paraffin-Embedded Tissues

Autophagy is crucial for maintaining cellular homeostasis and its deregulation is involved in disease development, including cancer. The key players of chaperone-mediated autophagy (CMA), a particular selective subtype of autophagy, are HSPA8 and LAMP2A. Both proteins can be immunohistochemically detected in formalin-fixed paraffin-embedded (FFPE) tissue. LAMP2A is frequently overexpressed in a variety of cancers where it likely supports cancer cell survival and resistance to anti-cancer therapies in a context-dependent manner. Here we present the immunohistochemical staining protocol of antibodies against LAMP2A and HSPA8, using an automated staining system, suitable for routine diagnostics. Additionally, we also suggest a staining evaluation method.

Immunohistochemical Detection of the Autophagy Markers LC3 and p62/SQSTM1 in Formalin-Fixed and Paraffin-Embedded Tissue

Autophagy is a highly conserved cellular mechanism of "self-digestion," ensuring cellular homeostasis and playing a role in many diseases including cancer. As a stress response mechanism, it may also be involved in cellular response to therapy. LC3 and Sequestosome 1 (p62/SQSTM1) are among the most widely used markers to monitor autophagy and can be visualized in formalin-fixed and paraffin-embedded tissue by immunohistochemistry. Here we describe a validated staining protocol using an automated staining system available in many routine pathology laboratories, enabling high-throughput staining under standardized conditions.

Integrated longitudinal analysis of adult grade 4 diffuse gliomas with long-term relapse interval revealed upregulation of TGF-β signaling in recurrent tumors

BACKGROUND

Adult-type diffuse gliomas, CNS WHO grade 4 are the most aggressive primary brain tumors and represent a particular challenge of therapeutic intervention.

METHODS

In a single-center retrospective study of matched pairs of initial and post-therapeutic glioma cases with a recurrence period greater than one year, we performed whole exome sequencing combined with mRNA and microRNA expression profiling to identify processes that are altered in recurrent gliomas.

RESULTS

Mutational analysis of recurrent gliomas revealed early branching evolution in seventy-five percent of patients. High plasticity was confirmed at the mRNA and miRNA levels. SBS1 signature was reduced and SBS11 was elevated, demonstrating the effect of alkylating agent therapy on the mutational landscape. There was no evidence for secondary genomic alterations driving therapy resistance. ALK7/ACVR1C and LTBP1 were upregulated, whereas LEFTY2 was downregulated, pointing towards enhanced Tumor Growth Factor β (TGF-β) signaling in recurrent gliomas. Consistently, altered microRNA expression profiles pointed towards enhanced Nuclear Factor Kappa B and Wnt signaling that, cooperatively with TGF-β, induces epithelial to mesenchymal transition (EMT), migration and stemness. TGF-β-induced expression of pro-apoptotic proteins and repression of anti-apoptotic proteins were uncoupled in the recurrent tumor.

CONCLUSIONS

Our results suggest an important role of TGF-β signaling in recurrent gliomas. This may have clinical implication, since TGF-β inhibitors have entered clinical phase studies and may potentially be used in combination therapy to interfere with chemoradiation resistance. Recurrent gliomas show high incidence of early branching evolution. High tumor plasticity is confirmed at the level of microRNA and mRNA expression profiles.

Image analysis reveals molecularly distinct patterns of TILs in NSCLC associated with treatment outcome

Despite known histological, biological, and clinical differences between lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC), relatively little is known about the spatial differences in their corresponding immune contextures. Our study of over 1000 LUAD and LUSC tumors revealed that computationally derived patterns of tumor-infiltrating lymphocytes (TILs) on H&E images were different between LUAD (N = 421) and LUSC (N = 438), with TIL density being prognostic of overall survival in LUAD and spatial arrangement being more prognostically relevant in LUSC. In addition, the LUAD-specific TIL signature was associated with OS in an external validation set of 100 NSCLC treated with more than six different neoadjuvant chemotherapy regimens, and predictive of response to therapy in the clinical trial CA209-057 (n = 303). In LUAD, the prognostic TIL signature was primarily comprised of CD4+ T and CD8+ T cells, whereas in LUSC, the immune patterns were comprised of CD4+ T, CD8+ T, and CD20+ B cells. In both subtypes, prognostic TIL features were associated with transcriptomics-derived immune scores and biological pathways implicated in immune recognition, response, and evasion. Our results suggest the need for histologic subtype-specific TIL-based models for stratifying survival risk and predicting response to therapy. Our findings suggest that predictive models for response to therapy will need to account for the unique morphologic and molecular immune patterns as a function of histologic subtype of NSCLC.

Density patterns of tumor-infiltrating lymphocytes and association with objective response to nivolumab in patients with lung adenocarcinoma from CheckMate 057

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Background: Immune checkpoint inhibitors (ICIs) are currently approved for use as therapy in advanced stage lung adenocarcinoma (LUAD). ICIs can decrease risk of progression by up to 60% when compared to chemotherapy, but only about 20% of patients (pts) show response. Given that high levels of tumor-infiltrating lymphocytes (TILs) have been shown to be associated with better prognosis, here, we assess whether computationally derived TIL density measures on digitized H&E images can predict RECIST derived response to nivolumab in LUAD in Checkmate 057 (CM057). CM057 is a clinical trial designed to compare the overall survival of metastatic non-squamous non-small cell lung cancer subjects treated with either nivolumab or docetaxel after failing platinum-based chemotherapy. Methods: H&E-stained samples of 683 LUAD pts were collected from TCGA (n = 421), University of Bern (UBern) (n = 100), and CM057 (n = 162). Tumor response was assessed using RECIST v1.1. Samples were digitized as whole slide images. 294 pts randomly selected from TCGA formed the training set. The remaining 389 pts were used for validation in response to nivolumab in CM057 and prognosticating overall survival (OS) in UBern and TCGA. Computerized algorithms automatically identified TILs and extracted features related to quantity and compactness of TILs with respect to other surrounding nuclei. The top 6 features, determined by least absolute shrinkage and selection operator, were used to train Cox regression models that assign a death risk score to each patient. Pts with risk scores higher than the training median score were considered “high risk” or “non-responders” while pts with lower scores were considered “low risk” or “responders”. Results: The classifier predicted objective response in CM057 with an AUC = 0.61. Additionally, survival analysis showed that the model was prognostic for OS with hazard ratios of 2.38 (confidence interval (CI): 1.32-4.29, p = 0.01, n = 127) in TCGA and 2.37 (CI: 1.32-4.25, p < 0.01, n = 100) in UBern. Conclusions: A computerized image analysis model based on measurements of TIL density showed association with response to treatment in LUAD pts who received nivolumab and was prognostic of OS. Although the AUC was not high, the results suggest analysis of TILs has potential to identify pts who will respond to treatment. Future work will include training a classifier using response to treatment as endpoint and combining the TIL measures with other biomarkers like TMB or PD-L1.

Spatial metabolomics for evaluating response to neoadjuvant therapy in non-small cell lung cancer patients

Background

The response to neoadjuvant chemotherapy (NAC) differs substantially among individual patients with non‐small cell lung cancer (NSCLC). Major pathological response (MPR) is a histomorphological read‐out used to assess treatment response and prognosis in patients NSCLC after NAC. Although spatial metabolomics is a promising tool for evaluating metabolic phenotypes, it has not yet been utilized to assess therapy responses in patients with NSCLC. We evaluated the potential application of spatial metabolomics in cancer tissues to assess the response to NAC, using a metabolic classifier that utilizes mass spectrometry imaging combined with machine learning.

Methods

Resected NSCLC tissue specimens obtained after NAC (n = 88) were subjected to high‐resolution mass spectrometry, and these data were used to develop an approach for assessing the response to NAC in patients with NSCLC. The specificities of the generated tumor cell and stroma classifiers were validated by applying this approach to a cohort of biologically matched chemotherapy‐naïve patients with NSCLC (n = 85).

Results

The developed tumor cell metabolic classifier stratified patients into different prognostic groups with 81.6% accuracy, whereas the stroma metabolic classifier displayed 78.4% accuracy. By contrast, the accuracies of MPR and TNM staging for stratification were 62.5% and 54.1%, respectively. The combination of metabolic and MPR classifiers showed slightly lower accuracy than either individual metabolic classifier. In multivariate analysis, metabolic classifiers were the only independent prognostic factors identified (tumor: P = 0.001, hazards ratio [HR] = 3.823, 95% confidence interval [CI] = 1.716–8.514; stroma: P = 0.049, HR = 2.180, 95% CI = 1.004–4.737), whereas MPR (P = 0.804; HR = 0.913; 95% CI = 0.445–1.874) and TNM staging (P = 0.078; HR = 1.223; 95% CI = 0.977–1.550) were not independent prognostic factors. Using Kaplan‐Meier survival analyses, both tumor and stroma metabolic classifiers were able to further stratify patients as NAC responders (P < 0.001) and non‐responders (P < 0.001).

Conclusions

Our findings indicate that the metabolic constitutions of both tumor cells and the stroma are valuable additions to the classical histomorphology‐based assessment of tumor response.

The Octopus Sign—A New HRCT Sign in Pulmonary Langerhans Cell Histiocytosis

Background: Fibrosis in pulmonary Langerhans cell histiocytosis (PLCH) histologically comprises a central scar with septal strands and associated airspace enlargement that produce an octopus-like appearance. The purpose of this study was to identify the octopus sign on high-resolution computed tomography (HRCT) images to determine its frequency and distribution across stages of the disease. Methods: Fifty-seven patients with confirmed PLCH were included. Two experienced chest radiologists assessed disease stages as early, intermediate, or late, as well as the lung parenchyma for nodular, cystic, or fibrotic changes and for the presence of the octopus sign. Statistical analysis included Cohen’s kappa for interrater agreement and Fisher’s exact test for the frequency of the octopus sign. Results: Interobserver agreement was substantial for the octopus sign (kappa = 0.747). Significant differences in distribution of the octopus sign between stages 2 and 3 were found with more frequent octopus signs in stage 2 and fewer in stage 3. In addition, we only found the octopus sign in cases of nodular und cystic lung disease. Conclusions: The octopus sign in PLCH can be identified not only on histological images, but also on HRCT images. Its radiological presence seems to depend on the stage of PLCH.

Functional and molecular characterization of PD1+ tumor-infiltrating lymphocytes from lung cancer patients

Antibody-mediated cancer immunotherapy targets inhibitory surface molecules, such as PD1, PD-L1, and CTLA-4, aiming to re-invigorate dysfunctional T cells. We purified and characterized tumor-infiltrating lymphocytes (TILs) and their patient-matched non-tumor counterparts from treatment-naïve NSCLC patient biopsies to evaluate the effect of PD1 expression on the functional and molecular profiles of tumor-resident T cells. We show that PD1+ CD8+ TILs have elevated expression of the transcriptional regulator ID3 and that the cytotoxic potential of CD8 T cells can be improved by knocking down ID3, defining it as a potential regulator of T cell effector function. PD1+ CD4+ memory TILs display transcriptional patterns consistent with both helper and regulator function, but can robustly facilitate B cell activation and expansion. Furthermore, we show that expanding ex vivo-prepared TILs in vitro broadly preserves their functionality with respect to tumor cell killing, B cell help, and TCR repertoire. Although purified PD1+ CD8+ TILs generally maintain an exhausted phenotype upon expansion in vitro, transcriptional analysis reveals a downregulation of markers of T-cell dysfunction, including the co-inhibitory molecules PD1 and CTLA-4 and transcription factors ID3, TOX and TOX2, while genes involved in cell cycle and DNA repair are upregulated. We find reduced expression of WNT signaling components to be a hallmark of PD1+ CD8+ exhausted T cells in vivo and in vitro and demonstrate that restoring WNT signaling, by pharmacological blockade of GSK3β, can improve effector function. These data unveil novel targets for tumor immunotherapy and have promising implications for the development of a personalized TIL-based cell therapy for lung cancer.

Tumor-infiltrating lymphocytes are functionally inactivated by CD90+ stromal cells and reactivated by combined Ibrutinib and Rapamycin in human pleural mesothelioma

Rationale: Despite evidence suggesting that the tumor microenvironment (TME) in malignant pleural mesothelioma (MPM) is linked with poor prognosis, there is a lack of studies that functionally characterize stromal cells and tumor-infiltrating lymphocytes (TILs). Here, we aim to characterize the stromal subsets within MPM, investigate their relationship to TILs, and explore the potential therapeutic targets.

Methods: We curated a core set of genes defining stromal/immune signatures expressed by mesenchymal cells within the TME using molecular analysis of The Cancer Genome Atlas (TCGA) MPM cohort. Stromal and immune profiles were molecularly characterized using flow cytometry, immunohistochemistry, microarray, and functionally evaluated using T cell-activation/expansion, coculture assays and drug compounds treatment, based on samples from an independent MPM cohort.

Results: We found that a high extracellular matrix (ECM)/stromal gene signature, a high ECM score, or the ratio of ECM to an immune activation gene signature are significantly associated with poor survival in the MPM cohort in TCGA. Analysis of an independent MPM cohort (n = 12) revealed that CD8+ and CD4+ TILs were characterized by PD1 overexpression and concomitant downregulation in degranulation and CD127. This coincided with an increase in CD90+ cells that overexpressed PD-L1 and were enriched for ECM/stromal genes, activated PI3K-mTOR signaling and suppressed T cells. Protein array data demonstrated that MPM samples with high PD-L1 expression were most associated with activation of the mTOR pathway. Further, to reactivate functionally indolent TILs, we reprogrammed ex vivo TILs with Ibrutinib plus Rapamycin to block interleukin-2-inducible kinase (ITK) and mTOR pathways, respectively. The combination treatment shifted effector memory (T_EM) CD8+ and CD4+ TILs towards T cells that re-expressed CD45RA (T_EMRA) while concomitantly downregulating exhaustion markers. Gene expression analysis confirmed that Ibrutinib plus Rapamycin downregulated coinhibitory and T cell signature pathways while upregulating pathways involved in DNA damage and repair and immune cell adhesion and migration.

Conclusions: Our results suggest that targeting the TME may represent a novel strategy to redirect the fate of endogenous TILs with the goal of restoring anti-tumor immunity and control of tumor growth in MPM.

COVID-19 Pulmonary Pathology: The Experience of European Pulmonary Pathologists throughout the First Two Waves of the Pandemic

Autoptic studies of patients who died from COVID-19 constitute an important step forward in improving our knowledge in the pathophysiology of SARS-CoV-2 infection. Systematic analyses of lung tissue, the organ primarily targeted by the disease, were mostly performed during the first wave of the pandemic. Analyses of pathological lesions at different times offer a good opportunity to better understand the disease and how its evolution has been influenced mostly by new SARS-CoV-2 variants or the different therapeutic approaches. In this short report we summarize responses collected from a questionnaire survey that investigated important pathological data during the first two pandemic waves (spring-summer 2020; autumn-winter 2020–2021). The survey was submitted to expert lung pathologists from nine European countries involved in autoptic procedures in both pandemic waves. The frequency of each lung lesion was quite heterogeneous among the participants. However, a higher frequency of pulmonary superinfections, both bacterial and especially fungal, was observed in the second wave compared to the first. Obtaining a deeper knowledge of the pathological lesions at the basis of this complex and severe disease, which change over time, is crucial for correct patient management and treatment. Autoptic examination is a useful tool to achieve this goal.

The effect of neoadjuvant therapy on PD-L1 expression and CD8+lymphocyte density in non-small cell lung cancer

PD-L1 expression is the routine clinical biomarker for the selection of patients to receive immunotherapy in non-small cell lung cancer (NSCLC). However, the application and best timing of immunotherapy in the resectable setting is still under investigation. We aimed to study the effect of chemotherapy on PD-L1 expression and tumor infiltrating lymphocytes (TILs), which is to date still poorly understood. Our retrospective, single-centre neoadjuvant cohort comprised 96 consecutive patients with NSCLC resected 2000-2016 after neoadjuvant therapy, including paired diagnostic chemo-naïve specimens in 53 cases. A biologically matched surgical cohort of 114 primary resected cases was included. PD-L1 expression, CD8 + TILs density and tertiary lymphoid structures were assessed on whole slides and correlated with clinico-pathological characteristics and survival. Seven/53 and 12/53 cases had lower respectively higher PD-L1 expressions after neoadjuvant therapy. Most cases (n = 34) showed no changes in PD-L1 expression, the majority of these harboring PD-L1 < 1% in both samples (21/34 [61.8%]). Although CD8 + TILs density was significantly higher after chemotherapy (p = 0.031) in resections compared to diagnostic biopsies, this might be due to sampling and statistical bias. No difference in PD-L1 expression or CD8 + TILs density was detected when comparing the neoadjuvant and surgical cohort. In univariable analyses, higher CD8 + TILs density, higher numbers of tertiary lymphoid structures but not PD-L1 expression were significantly associated with longer survival. Increased PD-L1 expression after neoadjuvant chemotherapy was not significantly associated with shorter 5-year survival, but the number of cases was very low. In multivariable analysis, only pT category and age remained independent prognostic factors. In summary, PD-L1 expression was mostly unchanged after neoadjuvant chemotherapy compared to diagnostic biopsies. The sample size of cases with changed PD-L1 expression was too small to draw conclusions on any prognostic value.

Mutational profiles of primary pulmonary adenocarcinoma and paired brain metastases disclose the importance of KRAS mutations

BACKGROUND

Brain metastases present a significant complication in lung cancer with an unmet therapeutic need.

METHODS

In this single-centre, retrospective study, we genotyped a clinico-pathologically well-annotated cohort of consecutively resected brain metastases of lung adenocarcinomas and paired primary tumours, diagnosed from 2000 to 2015, using the Ion Torrent Oncomine Comprehensive Cancer Panel v3.

RESULTS

Among 444 consecutive brain metastases, 210 (49%) originated from lung cancer. Analysis was successful in 111 samples, including 54 pairs of brain metastasis and primary tumour. Most driver alterations were preserved in brain metastases. Private alterations exclusive to primary tumours, brain metastases or both sites (intersecting cases) were present in 22%, 26% and 26% of cases, respectively. Seven percent had no shared mutations. KRAS mutations were more frequent in primary tumours metastasised to the brain (32/55, 58%) compared to TCGA (33%, p < 0.005) and own data from routine diagnostics, independent from clinical or pathological characteristics. Fourteen cases showed alterations in the EGFR signalling pathway including additional KRAS alterations that were private to brain metastases. KRAS G12C was detected most frequently (26% of patients) and KRAS G12C and G13C variants were significantly enriched in brain metastases. Synchronous and metachronous cases had a similar mutation profile.

CONCLUSIONS

Our results suggest an important role of KRAS alterations in the pathobiology of brain metastases from lung adenocarcinomas. This has direct therapeutic implications as inhibitors selectively targeting KRAS G12C are entering the clinics.

Delta-Like Protein 3 Expression in Paired Chemonaive and Chemorelapsed Small Cell Lung Cancer Samples

Rovalpituzumab tesirine (Rova-T), an antibody-drug conjugate directed against Delta-like protein 3 (DLL3), is under development for patients with small cell lung cancer (SCLC). DLL3 is expressed on the majority of SCLC samples. Because SCLC is rarely biopsied in the course of disease, data regarding DLL3 expression in relapses is not available. The aim of this study was to investigate the expression of DLL3 in chemorelapsed (but untreated with Rova-T) SCLC samples and compare the results with chemonaive counterparts. Two evaluation methods to assess DLL3 expression were explored. Additionally, we assessed if DLL3 expression of chemorelapsed and/or chemonaive samples has prognostic impact and if it correlates with other clinicopathological data. The study included 30 paired SCLC samples, which were stained with an anti DLL3 antibody. DLL3 expression was assessed using tumor proportion score (TPS) and H-score and was categorized as DLL3 low (TPS < 50%, H-score ≤ 150) and DLL3 high (TPS ≥ 50%, H-score > 150). Expression data were correlated with clinicopathological characteristics. Kaplan–Meier curves were used to illustrate overall survival (OS) depending on DLL3 expression in chemonaive and chemorelapsed samples, respectively, and depending on dynamics of expression during course of therapy. DLL3 was expressed in 86.6% chemonaive and 80% chemorelapsed SCLC samples without significant differences between the two groups. However, the extent of expression varied in a substantial proportion of pairs (36.6% with TPS, 43.3% with H-score), defined as a shift from low to high or high to low expression. TPS and H-score provided comparable results. There were no profound correlations with clinicopathological data. Survival analysis revealed a trend toward a more favorable OS in DLL low-expressing chemonaive SCLC (p = 0.57) and, in turn, in DLL3 high-expressing chemorelapsed SCLC (p = 0.42) as well as in SCLC demonstrating a shift from low to high expression (p = 0.56) without being statistically significant. This is the first study to investigate DLL3 expression in a large cohort of rare paired chemonaive-chemorelapsed SCLC specimens. Comparative analysis revealed that DLL3 expression was not stable during the course of therapy, suggesting therapy-based alterations. Unlike in chemonaive samples, a high DLL3 expression in chemorelapsed samples indicated a trend for a more favorable prognosis. Our results highlight the importance to investigate DLL3 in latest chemorelapsed SCLC tumor tissue.

Patterns of carbon-bound exogenous compounds in lung cancer patients and association with disease pathophysiology

Asymptomatic anthracosis is the accumulation of black carbon particles in adult human lungs. It is a common occurrence, but the pathophysiological significance of anthracosis is debatable. Using in situ high mass resolution matrix-assisted laser desorption/ionization (MALDI) fourier-transform ion cyclotron resonance (FT-ICR) mass spectrometry imaging analysis, we discovered noxious carbon-bound exogenous compounds, such as polycyclic aromatic hydrocarbons (PAHs), tobacco-specific nitrosamines, or aromatic amines, in a series of 330 lung cancer patients in highly variable and unique patterns. The characteristic nature of carbon-bound exogenous compound had a strong association with patient outcome, tumor progression, the tumor immune microenvironment, PD-L1 expression, and DNA damage. Spatial correlation network analyses revealed substantial differences in the metabolome of tumor cells compared to tumor stroma depending on carbon-bound exogenous compounds. Overall, the bioactive pool of exogenous compounds is associated with several changes in lung cancer pathophysiology and correlates with patient outcome. Given the high prevalence of anthracosis in the lungs of adult humans, future work should investigate the role of carbon-bound exogenous compounds in lung carcinogenesis and lung cancer therapy.

Chaperone-Mediated Autophagy Markers LAMP2A and HSPA8 in Advanced Non-Small Cell Lung Cancer after Neoadjuvant Therapy

In recent years autophagy has attracted the attention of researchers from many medical fields, including cancer research, and certain anti-macroautophagy drugs in combination with cytotoxic or targeted therapies have entered clinical trials. In the present study, we focused on a less explored subtype of autophagy, i.e., chaperone-mediated autophagy (CMA), with the key proteins LAMP2A and HSPA8 (HSC70), and their immunohistochemical evaluation with previously extensively validated antibodies. We were interested in whether the marker expression is influenced by the antecedent therapy, and its correlation with survival on a cohort of patients with non-small cell lung cancer (NSCLC) after neoadjuvant therapy and matched primary resected tumors. In concordance with our previous study, we did not find any intratumoral heterogeneity, nor correlation between the two parameters, nor correlation between the markers and any included pathological parameters. Surprisingly, the expression of both markers was also independent to tumor response or administered neoadjuvant treatment. In the survival analysis, the results were only significant for LAMP2A, where higher levels were associated with longer 5-year overall survival and disease-free survival for the mixed group of adenocarcinomas and squamous cell carcinomas (p < 0.0001 and p = 0.0019 respectively) as well as the squamous cell carcinoma subgroup (p = 0.0001 and p = 0.0001 respectively). LAMP2A was also an independent prognostic marker in univariate and multivariate analysis.

A prognostic and predictive computational pathology image signature for added benefit of adjuvant chemotherapy in early stage non-small-cell lung cancer

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Poster presentation at the USCAP 108th Annual Meeting, March 16–21, 2019.

Background

We developed and validated a prognostic and predictive computational pathology risk score (CoRiS) using H&E stained tissue images from patients with early-stage non-small cell lung cancer (ES-NSCLC).

Methods

1330 patients with ES-NSCLC were acquired from 3 independent sources and divided into four cohorts D_1-4. D₁ comprised 100 surgery treated patients and was used to identify prognostic features via an elastic-net Cox model to predict overall and disease-free survival. CoRiS was constructed using the Cox model coefficients for the top features. The prognostic performance of CoRiS was evaluated on D₂ (N=331), D₃ (N=657) and D₄ (N=242). Patients from D₂ and D₃ which comprised surgery + chemotherapy were used to validate CoRiS as predictive of added benefit to adjuvant chemotherapy (ACT) by comparing survival between different CoRiS defined risk groups.

Findings

CoRiS was found to be prognostic on univariable analysis, D₂ (hazard ratio (HR) = 1.41, adjusted (adj.) P = .01) and D₃ (HR = 1.35, adj. P < .001). Multivariable analysis showed CoRiS was independently prognostic, D₂ (HR = 1.41, adj. P < .001) and D₃ (HR = 1.35, adj. P < .001), after adjusting for clinico-pathologic factors. CoRiS was also able to identify high-risk patients who derived survival benefit from ACT D₂ (HR = 0.42, adj. P = .006) and D₃ (HR = 0.46, adj. P = .08).

Interpretation

CoRiS is a tissue non-destructive, quantitative and low-cost tool that could potentially help guide management of ES-NSCLC patients.

Autochthonous Case of Pulmonary Histoplasmosis, Switzerland

In Europe, pulmonary histoplasmosis is rarely diagnosed except in travelers. We report a probable autochthonous case of severe chronic pulmonary histoplasmosis in an immunocompetent man in Switzerland without travel history outside of Europe. Diagnosis was achieved by histopathology, fungal culture, and serology, but the source of the infection remains speculative.

Increased LAMP2A levels correlate with a shorter disease-free survival of HER2 negative breast cancer patients and increased breast cancer cell viability

Chaperone Mediated Autophagy (CMA) is a selective autophagy pathway deregulated in many cancers. In this study, we were aiming at understanding the importance of CMA in breast cancer. To this end, we examined the expression of the CMA markers HSP8 and LAMP2A in different breast cancer cell lines and found a wide range of LAMP2A expression levels across the cell lines analyzed. Next, we applied a specific immunohistochemical staining protocol to a tissue microarray derived from a cohort of 365 breast cancer patients. Therefore, we were able to find a correlation of high LAMP2A but not HSPA8 (HSC70) with worse disease free survival in patients with HER2 negative tumors (p = 0.026) which was independent prognostic parameter from pT category, pN category and grading in a multivariate model (HR = 1.889; 95% CI = 1.039-3.421; p = 0.037). In line, low LAMP2A levels decrease proliferation of the breast cancer cell lines T47D and MCF-7 in vitro. Our data suggest that LAMP2A supports a more severe breast cancer cell phenotype.

CRISPR-Mediated Kinome Editing Prioritizes a Synergistic Combination Therapy for FGFR1-Amplified Lung Cancer

Oncogenic activation of the FGFR pathway is frequent in lung and other cancers. However, due to drug resistance, pharmacological blockage of aberrant FGFR signaling has provided little clinical benefit in patients with FGFR-amplified tumors. The determining factors for the limited efficacy of FGFR-targeted therapy remain incompletely understood. In this study, we performed kinome-wide CRISPR/Cas9 loss-of-function screens in FGFR1-amplified lung cancer cells treated with an FGFR inhibitor. These screens identified PLK1 as a potent synthetic lethal target that mediates a resistance mechanism by overriding DNA damage and cell-cycle arrest upon FGFR1 inhibition. Genetic and pharmacological antagonism of PLK1 in combination with FGFR inhibitor therapy synergized to enhance antiproliferative effects and drove cancer cell death in vitro and in vivo through activation of the γH2AX-CHK-E2F1 axis. These findings suggest a previously unappreciated role for PLK1 in modulating FGFR1 inhibitor sensitivity and demonstrate a synergistic drug combination for treating FGFR1-amplified lung cancer. SIGNIFICANCE: The identification of PLK1 as a potent synthetic lethal target for FGFR-targeted therapy provides an innovative rationale for the treatment of lung and other FGFR1-amplified cancers.

ALK inhibition activates LC3B-independent, protective autophagy in EML4-ALK positive lung cancer cells

ALK inhibitors effectively target EML4-ALK positive non-small cell lung cancer, but their effects are hampered by treatment resistance. In the present study, we asked whether ALK inhibition affects autophagy, and whether this may influence treatment response. Whereas the impact of targeted therapies on autophagic activity previously have been assessed by surrogate marker proteins such as LC3B, we here thoroughly examined effects on functional autophagic activity, i.e. on the sequestration and degradation of autophagic cargo, in addition to autophagic markers. Interestingly, the ALK inhibitor Ceritinib decreased mTOR activity and increased GFP-WIPI1 dot formation in H3122 and H2228 EML4-ALK+ lung cancer cells, suggesting autophagy activation. Moreover, an mCherry-EGFP-LC3B based assay indicated elevated LC3B carrier flux upon ALK inhibition. In accordance, autophagic cargo sequestration and long-lived protein degradation significantly increased upon ALK inhibition. Intriguingly, autophagic cargo flux was dependent on VPS34 and ULK1, but not LC3B. Co-treating H3122 cells with Ceritinib and a VPS34 inhibitor or Bafilomycin A1 resulted in reduced cell numbers. Moreover, VPS34 inhibition reduced clonogenic recovery of Ceritinib-treated cells. In summary, our results indicate that ALK inhibition triggers LC3B-independent macroautophagic flux in EML4-ALK+ cells to support cancer cell survival and clonogenic growth.

Performance of a diagnostic algorithm for fibrotic hypersensitivity pneumonitis. A case-control study

Background

The differential diagnosis fibrotic hypersensitivity pneumonitis (HP) versus idiopathic pulmonary fibrosis (IPF) is important but challenging. Recent diagnostic guidelines for HP emphasize including multidisciplinary discussion (MDD) in the diagnostic process, however MDD is not comprehensively available.

We aimed to establish the diagnostic accuracy and prognostic validity of a previously proposed HP diagnostic algorithm that foregoes MDD.

Methods

We tested the algorithm in patients with an MDD diagnosis of fibrotic HP or IPF (case control study) and determined diagnostic test performances for diagnostic confidences of ≥ 90% and ≥ 70%. Prognostic validity was established using Cox proportional hazards models.

Results

Thirty-one patients with fibrotic HP and 50 IPF patients were included. The algorithm-derived ≥ 90% confidence level for HP had high specificity (0.94, 95% confidence interval [CI] 0.83–0.99), but low sensitivity (0.35 [95%CI 0.19–0.55], J-index 0.29). Test performance was improved for the ≥ 70% confidence level (J-index 0.64) with a specificity of 0.90 (95%CI 0.78–0.97), and a sensitivity of 0.74 (95%CI 0.55–0.88). MDD fibrotic HP diagnosis was strongly associated with lower risk of death (adjusted hazard ratio [HR] 0.10 [0.01–0.92], p = 0.04), whereas the algorithm-derived ≥ 70% and ≥ 90% confidence diagnoses were not significantly associated with survival (adjusted HR 0.37 [0.07–1.80], p = 0.22, and adjusted HR 0.41 [0.05–3.25], p = 0.39, respectively).

Conclusion

The algorithm-derived ≥ 70% diagnostic confidence had satisfactory test performance for MDD-HP diagnosis, with insufficient sensitivity for ≥ 90% confidence. The lowest risk of death in the MDD-derived HP diagnosis validates the reference standard and suggests that a diagnostic algorithm not including MDD, might not replace the latter.

Chemotherapy-induced CDA expression renders resistant non-small cell lung cancer cells sensitive to 5'-deoxy-5-fluorocytidine (5'-DFCR)

BACKGROUND

Pemetrexed (MTA) plus cisplatin combination therapy is considered the standard of care for patients with advanced non-small-cell lung cancer (NSCLC). However, in advanced NSCLC, the 5-year survival rate is below 10%, mainly due to resistance to therapy. We have previously shown that the fraction of mesenchymal-like, chemotherapy-resistant paraclone cells increased after MTA and cisplatin combination therapy in the NSCLC cell line A549. Cytidine deaminase (CDA) and thymidine phosphorylase (TYMP) are key enzymes of the pyrimidine salvage pathway. 5'-deoxy-5-fluorocytidine (5'-DFCR) is a cytidine analogue (metabolite of capecitabine), which is converted by CDA and subsequently by TYMP into 5-fluorouracil, a chemotherapeutic agent frequently used to treat solid tumors. The aim of this study was to identify and exploit chemotherapy-induced metabolic adaptations to target resistant cancer cells.

METHODS

Cell viability and colony formation assays were used to quantify the efficacy of MTA and cisplatin treatment in combination with schedule-dependent addition of 5'-DFCR on growth and survival of A549 paraclone cells and NSCLC cell lines. CDA and TYMP protein expression were monitored by Western blot. Finally, flow cytometry was used to analyze the EMT phenotype, DNA damage response activation and cell cycle distribution over time after treatment. CDA expression was measured by immunohistochemistry in tumor tissues of patients before and after neoadjuvant chemotherapy.

RESULTS

We performed a small-scale screen of mitochondrial metabolism inhibitors, which revealed that 5'-DFCR selectively targets chemotherapy-resistant A549 paraclone cells characterized by high CDA and TYMP expression. In the cell line A549, CDA and TYMP expression was further increased by chemotherapy in a time-dependent manner, which was also observed in the KRAS-addicted NSCLC cell lines H358 and H411. The addition of 5'-DFCR on the second day after MTA and cisplatin combination therapy was the most efficient treatment to eradicate chemotherapy-resistant NSCLC cells. Moreover, recovery from treatment-induced DNA damage was delayed and accompanied by senescence induction and acquisition of a hybrid-EMT phenotype. In a subset of patient tumors, CDA expression was also increased after treatment with neoadjuvant chemotherapy.

CONCLUSIONS

Chemotherapy increases CDA and TYMP expression thereby rendering resistant lung cancer cells susceptible to subsequent 5'-DFCR treatment.

Invasive Hormographiella aspergillata infection in patients with acute myeloid leukemia: Report of two cases successfully treated and review of the literature

Hormographiella aspergillata is a rare cause of invasive mold infection, mostly described in patients with hematological malignancies. We describe two cases of invasive H. aspergillata infections in patients with acute myeloid leukemia, successfully managed with complete surgical resection of the lesions and antifungal therapy of voriconazole alone or liposomal amphotericin B, followed by voriconazole, highlighting the key role of a multidisciplinary approach for the treatment of this rare and severe invasive mold infection.

Pulmonary Histoplasmosis Mimicking Metastatic Lung Cancer: A Case Report

Histoplasmosis is a well-known endemic fungal infection but experience in non-endemic regions is often limited, which may lead to delayed diagnosis and extensive testing. The diagnosis can be especially challenging, typically when the disease first presents with pulmonary nodules accompanied by hilar and mediastinal lymphadenopathy, suggesting a much more common malignant disease. In this situation, a greater FDG uptake in draining lymph nodes in comparison with the associated lung nodule seen in [¹⁸F]FDG-PET/CT, the so-called "flip-flop fungus" sign, can help to orientate further diagnostic measures. We report a case of a 56-year-old woman living in Switzerland, a non-endemic region, whose diagnosis of imported histoplasmosis was delayed since the findings had been initially misinterpreted as pulmonary malignancy. Further, histological workup was inconclusive due to lack of specific fungal staining, leading to ineffective treatment and non-resolving disease. This paper intends to highlight the pitfalls in diagnosing Histoplasma capsulatum and presents images of particularities of fungal infections in [¹⁸F]FDG-PET/CT, which in our case showed a "flip-flop fungus" sign.

A prognostic score for non-small cell lung cancer resected after neoadjuvant therapy in comparison with the tumor-node-metastases classification and major pathological response

Studies validating the prognostic accuracy of the tumor-node-metastases (TNM) classification in patients with lung cancer treated by neoadjuvant therapy are scarce. Tumor regression, particularly major pathological response (MPR), is an acknowledged prognostic factor in this setting. We aimed to validate a novel combined prognostic score. This retrospective single-center study was conducted on 117 consecutive patients with non-small cell lung cancer resected after neoadjuvant treatment at a Swiss University Cancer Center between 2000 and 2016. All cases were clinicopathologically re-evaluated. We assessed the prognostic performance of a novel prognostic score (PRSC) combining T-category, lymph node status, and MPR, in comparison with the eighth edition of the TNM classification (TNM8), the size adapted TNM8 as proposed by the International Association for the Study of Lung Cancer (IASLC) and MPR alone. The isolated ypT-category and the combined TNM8 stages accurately differentiated overall survival (OS, stage p = 0.004) and disease-free survival (DFS, stage p = 0.018). Tumor regression had a prognostic impact. Optimal cut-offs for MPR emerged as 65% for adenocarcinoma and 10% for non-adenocarcinoma and were statistically significant for survival (OS p = 0.006, DFS p < 0.001). The PRSC differentiated between three prognostic groups (OS and DFS p < 0.001), and was superior compared to the stratification using MPR alone or the TNM8 systems, visualized by lower Akaike (AIC) and Bayesian information criterion (BIC) values. In the multivariate analyses, stage III tumors (HR 4.956, p = 0.003), tumors without MPR (HR 2.432, p = 0.015), and PRSC high-risk tumors (HR 5.692, p < 0.001) had significantly increased risks of occurring death. In conclusion, we support 65% as the optimal cut-off for MPR in adenocarcinomas. TNM8 and MPR were comparable regarding their prognostic significance. The novel prognostic score performed distinctly better regarding OS and DFS.

EpCAM+CD73+ mark epithelial progenitor cells in postnatal human lung and are associated with pathogenesis of pulmonary disease including lung adenocarcinoma

Lung injury in mice induces mobilization of discrete subsets of epithelial progenitor cells to promote new airway and alveolar structures. However, whether similar cell types exist in human lung remains unresolved. Using flow cytometry, we identified a distinct cluster of cells expressing the epithelial cell adhesion molecule (EpCAM), a cell surface marker expressed on epithelial progenitor cells, enriched in the ecto-5'-nucleotidase CD73 in unaffected postnatal human lungs resected from pediatric patients with congenital lung lesions. Within the EpCAM⁺CD73⁺ population, a small subset coexpresses integrin β4 and HTII-280. This population remained stable with age. Spatially, EpCAM⁺CD73⁺ cells were positioned along the basal membrane of respiratory epithelium and alveolus next to CD73⁺ cells lacking EpCAM. Expanded EpCAM⁺CD73⁺ cells give rise to a pseudostratified epithelium in a two-dimensional air-liquid interface or a clonal three-dimensional organoid assay. Organoids generated under alveolar differentiation conditions were cystic-like and lacked robust alveolar mature cell types. Compared with unaffected postnatal lung, congenital lung lesions were marked by clusters of EpCAM⁺CD73⁺ cells in airway and cystic distal lung structures lined by simple epithelium composed of EpCAM⁺SCGB1A1⁺ cells and hyperplastic EpCAM⁺proSPC⁺ cells. In non-small-cell lung cancer (NSCLC), there was a marked increase in EpCAM⁺CD73⁺ tumor cells enriched in inhibitory immune checkpoint molecules CD47 and programmed death-ligand 1 (PD-L1), which was associated with poor survival in lung adenocarcinoma (LUAD). In conclusion, EpCAM⁺CD73⁺ cells are rare novel epithelial progenitor cells in the human lung. Importantly, reemergence of CD73 in lung adenocarcinoma enriched in negative immune checkpoint molecules may serve as a novel therapeutic target.

Combined deletion of Glut1 and Glut3 impairs lung adenocarcinoma growth

Glucose utilization increases in tumors, a metabolic process that is observed clinically by 18F-fluorodeoxyglucose positron emission tomography (18F-FDG-PET). However, is increased glucose uptake important for tumor cells, and which transporters are implicated in vivo? In a genetically-engineered mouse model of lung adenocarcinoma, we show that the deletion of only one highly expressed glucose transporter, Glut1 or Glut3, in cancer cells does not impair tumor growth, whereas their combined loss diminishes tumor development. 18F-FDG-PET analyses of tumors demonstrate that Glut1 and Glut3 loss decreases glucose uptake, which is mainly dependent on Glut1. Using 13C-glucose tracing with correlated nanoscale secondary ion mass spectrometry (NanoSIMS) and electron microscopy, we also report the presence of lamellar body-like organelles in tumor cells accumulating glucose-derived biomass, depending partially on Glut1. Our results demonstrate the requirement for two glucose transporters in lung adenocarcinoma, the dual blockade of which could reach therapeutic responses not achieved by individual targeting.