Low tumor interleukin-1β expression predicts a limited effect of adjuvant platinum-based chemotherapy for patients with completely resected lung adenocarcinoma: An identification and validation study

INTRODUCTION AND OBJECTIVES

Adjuvant platinum-based chemotherapy for completely resected non-small cell lung cancer is associated with modest improvement in survival; nevertheless, no validated biomarker exists for predicting the benefit or harm of adjuvant platinum-based chemotherapy.

MATERIALS AND METHODS

We simultaneously measured 27 cytokines in operative tumor specimens from a discovery cohort (n = 97) by multiplex immunoassay; half of the patients received adjuvant platinum-based chemotherapy, and the other half were observed. We tested possible prognostic and predictive factors in multivariate Cox models for overall survival (OS) and relapse-free survival (RFS), and a tree-based method was applied to detect predictive factors with respect to RFS. The results were validated in an independent validation cohort (n = 93).

RESULTS

Fifty-two of 97 (54 %) patients in the discovery cohort and 50 of 93 (54 %) in the validation cohort received adjuvant chemotherapy; forty-four (85 %) patients in the discovery cohort and 37 (74 %) in the validation cohort received four cycles as planned. In patients with low IL-1β-expressing tumors, RFS and OS were worse after adjuvant chemotherapy than after observation. The limited effect of adjuvant chemotherapy for patients with low IL-1β-expressing tumors was confirmed in the validation cohort. Additionally, RFS and OS were prolonged by adjuvant chemotherapy only in patients with high IL-1β-expressing tumors in the validation cohort.

CONCLUSIONS

This study identified and validated low tumor IL-1β expression as a potential biomarker of a limited response to adjuvant platinum-based chemotherapy after complete resection of pulmonary adenocarcinoma. This finding has the potential to inform adjuvant treatment decisions.

PITX2 as a Sensitive and Specific Marker of Midgut Neuroendocrine Tumors: Results from a Cohort of 1157 Primary Neuroendocrine Neoplasms

As neuroendocrine tumors (NETs) often present as metastatic lesions, immunohistochemical assignment to a site of origin is one of the most important tasks in their pathologic assessment. Because a fraction of NETs eludes the typical expression profiles of their primary localization, additional sensitive and specific markers are required to improve diagnostic certainty. We investigated the expression of the transcription factor Pituitary Homeobox 2 (PITX2) in a large-scale cohort of 909 NET and 248 neuroendocrine carcinomas (NEC) according to the immunoreactive score (IRS) and correlated PITX2 expression groups with general tumor groups and primary localization. PITX2 expression (all expression groups) was highly sensitive (98.1%) for midgut-derived NET, but not perfectly specific, as non-midgut NET (especially pulmonary/duodenal) were quite frequently weak or moderately positive. The specificity rose to 99.5% for a midgut origin of NET if only a strong PITX2 expression was considered, which was found in only 0.5% (one pancreatic/one pulmonary) of non-midgut NET. In metastases of midgut-derived NET, PITX2 was expressed in all cases (87.5% strong, 12.5% moderate), whereas CDX2 was negative or only weakly expressed in 31.3% of the metastases. In NEC, a fraction of cases (14%) showed a weak or moderate PITX2 expression, which was not associated with a specific tumor localization. Our study independently validates PITX2 as a very sensitive and specific immunohistochemical marker of midgut-derived NET in a very large collective of neuroendocrine neoplasms. Therefore, our data argue toward implementation into diagnostic panels applied for NET as a firstline midgut marker.

Transbronchial cryobiopsy using the ultrathin 1.1 mm cryoprobe with ultrathin bronchoscopy under radial endobronchial ultrasound guidance for diagnosis of peripheral pulmonary lesions

INTRODUCTION

Today, the increasing number of incidentally detected peripheral pulmonary lesions (PPL) within and outside lung cancer screening trials is a diagnostic challenge. This fact encourages further improvement of diagnostic procedures to increase the diagnostic yield of transbronchial biopsy, which has been shown to have a low complication rate. The purpose of this study was to evaluate the safety and feasibility of a new ultrathin 1.1 cryoprobe that can be placed through an ultrathin bronchoscope using fluoroscopy and radial EBUS navigation for assessing PPLs.

METHODS

35 patients with PPL less than 4 cm in diameter were prospectively enrolled to receive transbronchial cryobiopsies (TBCB) using the ultrathin 1.1 mm cryoprobe. Navigation to the PPL was accomplished with the UTB. Under radial endobronchial ultrasonography (rEBUS) and fluoroscopy guidance up to 4 cryobiopsies were obtained. The samples sizes of the biopsies were compared to a historic collective derived from a 1.9 mm cryoprobe and standard forceps. The feasibility and safety of the procedure, the cumulative and overall diagnostic yield and the cryobiopsy sizes were evaluated.

RESULTS

After detection with the rEBUS, TBCB were collected from 35 PPL, establishing a diagnosis in 25 cases, corresponding to an overall diagnostic yield of 71.4%. There was no difference in diagnostic yield for PPL < 20mm or ≥ 20mm. All cryobiopsies were representative with a mean tissue area of 11.9  4,3 mm2, which was significantly larger compared to the historic collective (p=0.003). Six mild and four moderate bleeding events and one case of pneumothorax were observed.

CONCLUSION

Using the ultrathin 1.1mm cryoprobe combined with an ultrathin bronchoscope for rEBUS-guided TBCB of PPL is feasible and safe. This diagnostic approach improves bronchoscopic techniques for diagnosing peripheral lung lesions and may contribute to improve diagnosis of lung cancer even in small PPL.

CYFRA 21-1, CA 125 and CEA provide additional prognostic value in NSCLC patients with stable disease at first CT scan

BACKGROUND

Serum tumor markers (STM) may complement imaging and provide additional clinical information for patients with non-small cell lung cancer (NSCLC).

OBJECTIVE

To determine whether STMs can predict outcomes in patients with stable disease (SD) after initial treatment.

METHODS

This single-center, prospective, observational trial enrolled 395 patients with stage III/IV treatment-naïve NSCLC; of which 263 patients were included in this analysis. Computed Tomography (CT) scans were performed and STMs measured before and after initial treatment (two cycles of chemotherapy and/or an immune checkpoint inhibitor or tyrosine kinase inhibitor); analyses were based on CT and STM measurements obtained at first CT performed after cycle 2 only PFS and OS were analyzed by Kaplan-Meier curves and Cox-proportional hazard models.

RESULTS

When patients with SD (n = 100) were split into high- and low-risk groups based on CYFRA 21-1, CEA and CA 125 measurements using an optimized cut-off, a 4-fold increase risk of progression or death was estimated for high- vs low-risk SD patients (PFS, HR 4.17; OS, 3.99; both p < 0.0001). Outcomes were similar between patients with high-risk SD or progressive disease (n = 35) (OS, HR 1.17) and between patients with low-risk SD or partial response (n = 128) (PFS, HR 0.98; OS, 1.14).

CONCLUSIONS

STMs can provide further guidance in patients with indeterminate CT responses by separating them into high- and low-risk groups for future PFS and OS events.

Prognostic value of tumor markers ProGRP, NSE and CYFRA 21-1 in patients with small cell lung cancer and chemotherapy-induced remission

BACKGROUND

Despite successful response to first line therapy, patients with small-cell lung cancer (SCLC) often suffer from early relapses and disease progression.

OBJECTIVE

To investigate the relevance of serum tumor markers for estimation of prognosis at several time points during the course of disease.

METHODS

In a prospective, single-center study, serial assessments of progastrin-releasing peptide (ProGRP), neuron-specific enolase (NSE), cytokeratin-19 fragments (CYFRA 21-1) and carcino-embryogenic antigen (CEA) were performed during and after chemotherapy in 232 SCLC patients, and correlated with therapy response and overall survival (OS).

RESULTS

ProGRP, NSE and CYFRA 21-1 levels decreased quickly after the first chemotherapy cycle and correlated well with the radiological response. Either as single markers or in combination they provided valuable prognostic information regarding OS at all timepoints investigated: prior to first-line therapy, after two treatment cycles in patients with successful response to first-line therapy, and prior to the start of second-line therapy. Furthermore, they were useful for continuous monitoring during and after therapy and often indicated progressive disease several months ahead of radiological changes.

CONCLUSIONS

The results indicate the great potential of ProGRP, NSE and CYFRA 21-1 for estimating prognosis and monitoring of SCLC patients throughout the course of the disease.

Prognostic Impact of the Immune-Cell Infiltrate in N1-Positive Non-Small-Cell Lung Cancer

INTRODUCTION

The tumoral immune milieu plays a crucial role for the development of non-small-cell lung cancer (NSCLC) and may influence individual prognosis. We analyzed the predictive role of immune cell infiltrates after curative lung cancer surgery.

MATERIALS AND METHODS

The tumoral immune-cell infiltrate from 174 patients with pN1 NSCLC and adjuvant chemotherapy was characterized using immunofluorescence staining. The density and distribution of specific immune cells in tumor center (TU), invasive front (IF) and normal tissue (NORM) were correlated with clinical parameters and survival data.

RESULTS

Tumor specific survival (TSS) of all patients was 69.9% at 5 years. The density of tumor infiltrating lymphocytes (TIL) was higher in TU and IF than in NORM. High TIL density in TU (low vs. high: 62.0% vs. 86.7%; p = .011) and the presence of cytotoxic T-Lymphocytes (CTLs) in TU and IF were associated with improved TSS (positive vs. negative: 90.6% vs. 64.7% p = .024). High TIL-density correlated with programmed death-ligand 1 expression levels ≥50% (p < .001). Multivariate analysis identified accumulation of TIL (p = .016) and low Treg density (p = .003) in TU as negative prognostic predictors in squamous cell carcinoma (p = .025), whereas M1-like tumor- associated macrophages (p = .019) and high programmed death-ligand 1 status (p = .038) were associated with better survival in adenocarcinoma.

CONCLUSION

The assessment of specific intratumoral immune cells may serve as a prognostic predictor in pN1 NSCLC. However differences were observed related to adenocarcinoma or squamous cell carcinoma histology. Prospective assessment of the immune-cell infiltrate and further clarification of its prognostic relevance could assist patient selection for upcoming perioperative immunotherapies.

Preliminary results from the EMoLung clinical study showing early lung cancer detection by the LC score

BACKGROUND

Lung cancer (LC) causes more deaths worldwide than any other cancer type. Despite advances in therapeutic strategies, the fatality rate of LC cases remains high (95%) since the majority of patients are diagnosed at late stages when patient prognosis is poor. Analysis of the International Association for the Study of Lung Cancer (IASLC) database indicates that early diagnosis is significantly associated with favorable outcome. However, since symptoms of LC at early stages are unspecific and resemble those of benign pathologies, current diagnostic approaches are mostly initiated at advanced LC stages.

METHODS

We developed a LC diagnosis test based on the analysis of distinct RNA isoforms expressed from the GATA6 and NKX2-1 gene loci, which are detected in exhaled breath condensates (EBCs). Levels of these transcript isoforms in EBCs were combined to calculate a diagnostic score (the LC score). In the present study, we aimed to confirm the applicability of the LC score for the diagnosis of early stage LC under clinical settings. Thus, we evaluated EBCs from patients with early stage, resectable non-small cell lung cancer (NSCLC), who were prospectively enrolled in the EMoLung study at three sites in Germany.

RESULTS

LC score-based classification of EBCs confirmed its performance under clinical conditions, achieving a sensitivity of 95.7%, 91.3% and 84.6% for LC detection at stages I, II and III, respectively.

CONCLUSIONS

The LC score is an accurate and non-invasive option for early LC diagnosis and a valuable complement to LC screening procedures based on computed tomography.

Krebs von den Lungen-6 as a Potential Predictive Biomarker in Fibrosing Interstitial Lung Diseases

BACKGROUND

As fibrosing interstitial lung diseases (fILDs) are associated with high mortality, monitoring of disease activity under treatment is highly relevant. Krebs von den Lungen-6 (KL-6) is associated with the presence and severity of different fILDs, mainly in Asian patient populations.

OBJECTIVES

Our aim was to evaluate KL-6 as a predictive biomarker in fILDs in Caucasian patients.

METHODS

Consecutive patients with fILDs were recruited prospectively and serum concentrations of KL-6 were measured at baseline (BL), after 6 and 12 months (6 Months, 12 Months). Clinical characteristics including pulmonary function tests were assessed at 6-monthly visits and correlated with KL-6 BL levels as well as with KL-6 level changes.

RESULTS

A total of 47 fILD patients were included (mean age: 65 years, 68% male). KL-6 levels at BL were significantly higher in fILD patients than in healthy controls (n = 44, mean age: 45, 23% male) (ILD: 1,757 ± 1960 U/mL vs. control: 265 ± 107 U/mL, p < 0.0001). However, no differences were noted between ILD subgroups. KL-6 decreased significantly under therapy (6M∆BL-KL6: -486 ± 1,505 mean U/mL, p = 0.032; 12M∆BL-KL6: -547 ± 1,782 mean U/mL, p = 0.041) and KL-6 level changes were negatively correlated with changes in pulmonary function parameters (forced vital capacity [FVC]: r = -0.562, p < 0.0001; DLCOSB: r = -0.405, p = 0.013). While neither absolute KL-6 levels at BL nor KL-6 level changes were associated with ILD progression (FVC decline ≥10%, DLCOSB decline ≥15% or death), patients with a stable FVC showed significantly decreasing KL-6 levels (p = 0.022).

CONCLUSIONS

A decline of KL-6 under therapy correlated with a clinically relevant stabilization of lung function. Thus, KL-6 might serve as a predictive biomarker, which however must be determined by larger prospective cohorts.

Implementation of deep learning in liver pathology optimizes diagnosis of benign lesions and adenocarcinoma metastasis

INTRODUCTION

Differentiation of histologically similar structures in the liver, including anatomical structures, benign bile duct lesions, or common types of liver metastases, can be challenging with conventional histological tissue sections alone. Accurate histopathological classification is paramount for the diagnosis and adequate treatment of the disease. Deep learning algorithms have been proposed for objective and consistent assessment of digital histopathological images.

MATERIALS AND METHODS

In the present study, we trained and evaluated deep learning algorithms based on the EfficientNetV2 and ResNetRS architectures to discriminate between different histopathological classes. For the required dataset, specialized surgical pathologists annotated seven different histological classes, including different non-neoplastic anatomical structures, benign bile duct lesions, and liver metastases from colorectal and pancreatic adenocarcinoma in a large patient cohort. Annotation resulted in a total of 204.159 image patches, followed by discrimination analysis using our deep learning models. Model performance was evaluated on validation and test data using confusion matrices.

RESULTS

Evaluation of the test set based on tiles and cases revealed overall highly satisfactory prediction capability of our algorithm for the different histological classes, resulting in a tile accuracy of 89% (38 413/43 059) and case accuracy of 94% (198/211). Importantly, the separation of metastasis versus benign lesions was certainly confident on case level, confirming the classification model performed with high diagnostic accuracy. Moreover, the whole curated raw data set is made publically available.

CONCLUSIONS

Deep learning is a promising approach in surgical liver pathology supporting decision making in personalized medicine.

Corrigendum: Deep learning for the detection of anatomical tissue structures and neoplasms of the skin on scanned histopathological tissue sections

[This corrects the article DOI: 10.3389/fonc.2022.1022967.].

Lung Adenocarcinoma Diagnosed at a Younger Age Is Associated with Advanced Stage, Female Sex, and Ever-Smoker Status, in Patients Treated with Lung Resection

To date, the factors which affect the age at diagnosis of lung adenocarcinoma are not fully understood. In our study, we examined the relationships of age at diagnosis with smoking, pathological stage, sex, and year of diagnosis in a discovery (n = 1694) and validation (n = 1384) series of lung adenocarcinoma patients who had undergone pulmonary resection at hospitals in the Milan area and at Thoraxklinik (Heidelberg), respectively. In the discovery series, younger age at diagnosis was associated with ever-smoker status (OR = 1.5, p = 0.0035) and advanced stage (taking stage I as reference: stage III OR = 1.4, p = 0.0067; stage IV OR = 1.7, p = 0.0080), whereas older age at diagnosis was associated with male sex (OR = 0.57, p < 0.001). Analysis in the validation series confirmed the ever versus never smokers' association (OR = 2.9, p < 0.001), the association with highest stages (stage III versus stage I OR = 1.4, p = 0.0066; stage IV versus stage I OR = 2.0, p = 0.0022), and the male versus female sex association (OR = 0.78, p = 0.032). These data suggest the role of smoking in affecting the natural history of the disease. Moreover, aggressive tumours seem to have shorter latency from initiation to clinical detection. Finally, younger age at diagnosis is associated with the female sex, suggesting that hormonal status of young women confers risk to develop lung adenocarcinoma. Overall, this study provided novel findings on the mechanisms underlying age at diagnosis of lung adenocarcinoma.

Imaging Mass Spectrometry for the Classification of Melanoma Based on BRAF/NRAS Mutational Status

Mutations of the oncogenes v-raf murine sarcoma viral oncogene homolog B1 (BRAF) and neuroblastoma RAS viral oncogene homolog (NRAS) are the most frequent genetic alterations in melanoma and are mutually exclusive. BRAF V600 mutations are predictive for response to the two BRAF inhibitors vemurafenib and dabrafenib and the mitogen-activated protein kinase kinase (MEK) inhibitor trametinib. However, inter- and intra-tumoral heterogeneity and the development of acquired resistance to BRAF inhibitors have important clinical implications. Here, we investigated and compared the molecular profile of BRAF and NRAS mutated and wildtype melanoma patients' tissue samples using imaging mass spectrometry-based proteomic technology, to identify specific molecular signatures associated with the respective tumors. SCiLSLab and R-statistical software were used to classify peptide profiles using linear discriminant analysis and support vector machine models optimized with two internal cross-validation methods (leave-one-out, k-fold). Classification models showed molecular differences between BRAF and NRAS mutated melanoma, and identification of both was possible with an accuracy of 87-89% and 76-79%, depending on the respective classification method applied. In addition, differential expression of some predictive proteins, such as histones or glyceraldehyde-3-phosphate-dehydrogenase, correlated with BRAF or NRAS mutation status. Overall, these findings provide a new molecular method to classify melanoma patients carrying BRAF and NRAS mutations and help provide a broader view of the molecular characteristics of these patients that may help understand the signaling pathways and interactions involving the altered genes.

[Interstitial lung diseases : Classification, differential diagnosis and treatment approaches in a heterogeneous group of chronic lung disorders]

Interstitial lung diseases (ILD) comprise a heterogeneous group of chronic lung disorders of different etiologies that can not only affect the interstitium but also the alveolar space and the bronchial system. According to the "Global Burden of Disease Study" there has been an increase in incidence over the last decades and it is expected that the number of ILD-associated deaths will double over the next 20 years. ILD are grouped into those of unknown cause, e.g. idiopathic pulmonary fibrosis (IPF), and ILD of known cause, which include drug-induced and connective tissue disease-associated ILD as well as granulomatous ILD such as sarcoidosis and hypersensitivity pneumonitis. In addition, some ILD present a progressive fibrosing phenotype, which influences therapeutic decisions. Predominantly inflammatory entities are treated with immunosuppressives, whereas predominantly fibrosing ILD are treated with antifibrotic drugs; in some cases, a combination of both is necessary. The spectrum of differential diagnoses in ILD is broad, but definite diagnosis is essential for treatment selection; therefore, the multidisciplinary ILD board plays a pivotal role.

A Comparison of Different Sample Processing Protocols for MALDI Imaging Mass Spectrometry Analysis of Formalin-Fixed Multiple Myeloma Cells

Sample processing of formalin-fixed specimens constitutes a major challenge in molecular profiling efforts. Pre-analytical factors such as fixative temperature, dehydration, and embedding media affect downstream analysis, generating data dependent on technical processing rather than disease state. In this study, we investigated two different sample processing methods, including the use of the cytospin sample preparation and automated sample processing apparatuses for proteomic analysis of multiple myeloma (MM) cell lines using imaging mass spectrometry (IMS). In addition, two sample-embedding instruments using different reagents and processing times were considered. Three MM cell lines fixed in 4% paraformaldehyde were either directly centrifuged onto glass slides using cytospin preparation techniques or processed to create paraffin-embedded specimens with an automatic tissue processor, and further cut onto glass slides for IMS analysis. The number of peaks obtained from paraffin-embedded samples was comparable between the two different sample processing instruments. Interestingly, spectra profiles showed enhanced ion yield in cytospin compared to paraffin-embedded samples along with high reproducibility compared to the sample replicate.

Computational pathology in 2030: a Delphi study forecasting the role of AI in pathology within the next decade

BACKGROUND

Artificial intelligence (AI) is rapidly fuelling a fundamental transformation in the practice of pathology. However, clinical integration remains challenging, with no AI algorithms to date in routine adoption within typical anatomic pathology (AP) laboratories. This survey gathered current expert perspectives and expectations regarding the role of AI in AP from those with first-hand computational pathology and AI experience.

METHODS

Perspectives were solicited using the Delphi method from 24 subject matter experts between December 2020 and February 2021 regarding the anticipated role of AI in pathology by the year 2030. The study consisted of three consecutive rounds: 1) an open-ended, free response questionnaire generating a list of survey items; 2) a Likert-scale survey scored by experts and analysed for consensus; and 3) a repeat survey of items not reaching consensus to obtain further expert consensus.

FINDINGS

Consensus opinions were reached on 141 of 180 survey items (78.3%). Experts agreed that AI would be routinely and impactfully used within AP laboratory and pathologist clinical workflows by 2030. High consensus was reached on 100 items across nine categories encompassing the impact of AI on (1) pathology key performance indicators (KPIs) and (2) the pathology workforce and specific tasks performed by (3) pathologists and (4) AP lab technicians, as well as (5) specific AI applications and their likelihood of routine use by 2030, (6) AI's role in integrated diagnostics, (7) pathology tasks likely to be fully automated using AI, and (8) regulatory/legal and (9) ethical aspects of AI integration in pathology.

INTERPRETATION

This systematic consensus study details the expected short-to-mid-term impact of AI on pathology practice. These findings provide timely and relevant information regarding future care delivery in pathology and raise key practical, ethical, and legal challenges that must be addressed prior to AI's successful clinical implementation.

FUNDING

No specific funding was provided for this study.

Biological injection therapy with leukocyte-poor platelet-rich plasma induces cellular alterations, enhancement of lubricin, and inflammatory downregulation in vivo in human knees: A controlled, prospective human clinical trial based on mass spectrometry imaging analysis

Objective

To investigate the in vivo biological effects of leukocyte-poor platelet-rich plasma (LpPRP) treatment in human synovial layer to establish the cellular basis for a prolonged clinical improvement.

Methods

Synovial tissues (n = 367) were prospectively collected from patients undergoing arthroscopic surgery. Autologous-conditioned plasma, LpPRP, was injected into the knees of 163 patients 1-7 days before surgery to reduce operative trauma and inflammation, and to induce the onset of regeneration. A total of 204 patients did not receive any injection. All samples were analyzed by mass spectrometry imaging. Data analysis was evaluated by clustering, classification, and investigation of predictive peptides. Peptide identification was done by tandem mass spectrometry and database matching.

Results

Data analysis revealed two major clusters belonging to LpPRP-treated (LpPRP-1) and untreated (LpPRP-0) patients. Classification analysis showed a discrimination accuracy of 82%-90%. We identified discriminating peptides for CD45 and CD29 receptors (receptor-type tyrosine-protein phosphatase C and integrin beta 1), indicating an enhancement of musculoskeletal stem cells, as well as an enhancement of lubricin, collagen alpha-1-(I) chain, and interleukin-receptor-17-E, dampening the inflammatory reaction in the LpPRP-1 group following LpPRP injection.

Conclusions

We could demonstrate for the first time that injection therapy using "autologic-conditioned biologics" may lead to cellular changes in the synovial membrane that might explain the reported prolonged beneficial clinical effects. Here, we show in vivo cellular changes, possibly based on muscular skeletal stem cell alterations, in the synovial layer. The gliding capacities of joints might be improved by enhancing of lubricin, anti-inflammation by activation of interleukin-17 receptor E, and reduction of the inflammatory process by blocking interleukin-17.

Multimodal Lung Cancer Subtyping Using Deep Learning Neural Networks on Whole Slide Tissue Images and MALDI MSI

Artificial intelligence (AI) has shown potential for facilitating the detection and classification of tumors. In patients with non-small cell lung cancer, distinguishing between the most common subtypes, adenocarcinoma (ADC) and squamous cell carcinoma (SqCC), is crucial for the development of an effective treatment plan. This task, however, may still present challenges in clinical routine. We propose a two-modality, AI-based classification algorithm to detect and subtype tumor areas, which combines information from matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) data and digital microscopy whole slide images (WSIs) of lung tissue sections. The method consists of first detecting areas with high tumor cell content by performing a segmentation of the hematoxylin and eosin-stained (H&E-stained) WSIs, and subsequently classifying the tumor areas based on the corresponding MALDI MSI data. We trained the algorithm on six tissue microarrays (TMAs) with tumor samples from N = 232 patients and used 14 additional whole sections for validation and model selection. Classification accuracy was evaluated on a test dataset with another 16 whole sections. The algorithm accurately detected and classified tumor areas, yielding a test accuracy of 94.7% on spectrum level, and correctly classified 15 of 16 test sections. When an additional quality control criterion was introduced, a 100% test accuracy was achieved on sections that passed the quality control (14 of 16). The presented method provides a step further towards the inclusion of AI and MALDI MSI data into clinical routine and has the potential to reduce the pathologist's work load. A careful analysis of the results revealed specific challenges to be considered when training neural networks on data from lung cancer tissue.

Deep learning for the detection of anatomical tissue structures and neoplasms of the skin on scanned histopathological tissue sections

Basal cell carcinoma (BCC), squamous cell carcinoma (SqCC) and melanoma are among the most common cancer types. Correct diagnosis based on histological evaluation after biopsy or excision is paramount for adequate therapy stratification. Deep learning on histological slides has been suggested to complement and improve routine diagnostics, but publicly available curated and annotated data and usable models trained to distinguish common skin tumors are rare and often lack heterogeneous non-tumor categories. A total of 16 classes from 386 cases were manually annotated on scanned histological slides, 129,364 100 x 100 µm (~395 x 395 px) image tiles were extracted and split into a training, validation and test set. An EfficientV2 neuronal network was trained and optimized to classify image categories. Cross entropy loss, balanced accuracy and Matthews correlation coefficient were used for model evaluation. Image and patient data were assessed with confusion matrices. Application of the model to an external set of whole slides facilitated localization of melanoma and non-tumor tissue. Automated differentiation of BCC, SqCC, melanoma, naevi and non-tumor tissue structures was possible, and a high diagnostic accuracy was achieved in the validation (98%) and test (97%) set. In summary, we provide a curated dataset including the most common neoplasms of the skin and various anatomical compartments to enable researchers to train, validate and improve deep learning models. Automated classification of skin tumors by deep learning techniques is possible with high accuracy, facilitates tumor localization and has the potential to support and improve routine diagnostics.

Tuft cell-like carcinomas: novel cancer subsets present in multiple organs sharing a unique gene expression signature

BACKGROUND

Tuft cells are chemosensory epithelial cells playing a role in innate immunity. Recent studies revealed cancers with a tuft cell-like gene expression signature in the thorax. We wondered whether this signature might also occur in extrathoracic cancers.

METHODS

We examined mRNA expression of tuft cell markers (POU2F3, GFI1B, TRPM5, SOX9, CHAT, and AVIL) in 19 different types of cancers in multiple extrathoracic organs with The Cancer Genome Atlas (TCGA) (N = 6322). Four different extrathoracic cancers in our local archives (N = 909) were analysed by immunohistochemistry.

RESULTS

Twenty-two (0.35%) extrathoracic tumours with co-expression of POU2F3 and other tuft cell markers were identified in various TCGA datasets. Twelve of the 22 "tuft cell-like tumours" shared poor differentiation and a gene expression pattern, including KIT, anti-apoptotic BCL2, and ionocyte-associated genes. In our archival cases, eleven (1.21%) tumours co-expressing POU2F3, KIT, and BCL2 on immunohistochemistry, i.e., were presumable tuft cell-like cancers. In three among five TCGA cohorts, the tuft cell-like cancer subsets expressed SLFN11, a promising biomarker of PARP inhibitor susceptibility.

CONCLUSIONS

Tuft cell-like carcinomas form distinct subsets in cancers of many organs. It appears warranted to investigate their shared gene expression signature as a predictive biomarker for novel therapeutic strategies.

Analysis of RANK-c interaction partners identifies TRAF3 as a critical regulator of breast cancer aggressiveness

Breast cancer is a highly heterogeneous disease both at the histological and molecular levels. We have previously shown that RANK-c is a regulator of NF-κB signaling and exerts a suppressive effect on aggressive properties of ER negative breast cancer cells, while there is an opposite effect on ER positive cell lines. In order to identify molecular determinants that govern the opposing function of RANK-c in breast cancer cells we employed the two cell lines with the highest degree of phenotypic divergence upon RANK-c-expression (SKBR3 and BT474) and identified proteins that interact with RANK-c by affinity-enrichment mass spectrometry (AE-MS) analysis. Annotating enriched proteins with NF-κB signaling pathway revealed TRAF3 as an interacting partner of RANK-c in SKBR3 cell protein lysates, but not in BT474 breast cancer cells in which RANK-c induces cell aggressiveness. To determine the role of TRAF3 in the phenotype of BT474-RANK-c cells, we reconstructed the TRAF3/RANK-c interaction both in parental BT474 and RANK-c expressing cells and tested for aggressive properties through colony formation, migration and invasion assays. TRAF3 forced expression was able to reverse BT474 phenotypic changes imposed by RANK-c, rendering cells less aggressive. Finally, TRAF3 gene expression data and TRAF3 immunohistochemical (IHC) analysis on breast cancer samples indicated that TRAF3 expression correlates with Overall Survival (OS), Recurrence Free Survival (RFS) and several clinicopathological parameters (histological grade, proliferation index) of breast cancer disease.

Proteogenomics refines the molecular classification of chronic lymphocytic leukemia

Cancer heterogeneity at the proteome level may explain differences in therapy response and prognosis beyond the currently established genomic and transcriptomic-based diagnostics. The relevance of proteomics for disease classifications remains to be established in clinically heterogeneous cancer entities such as chronic lymphocytic leukemia (CLL). Here, we characterize the proteome and transcriptome alongside genetic and ex-vivo drug response profiling in a clinically annotated CLL discovery cohort (n = 68). Unsupervised clustering of the proteome data reveals six subgroups. Five of these proteomic groups are associated with genetic features, while one group is only detectable at the proteome level. This new group is characterized by accelerated disease progression, high spliceosomal protein abundances associated with aberrant splicing, and low B cell receptor signaling protein abundances (ASB-CLL). Classifiers developed to identify ASB-CLL based on its characteristic proteome or splicing signature in two independent cohorts (n = 165, n = 169) confirm that ASB-CLL comprises about 20% of CLL patients. The inferior overall survival in ASB-CLL is also independent of both TP53- and IGHV mutation status. Our multi-omics analysis refines the classification of CLL and highlights the potential of proteomics to improve cancer patient stratification beyond genetic and transcriptomic profiling.

Lorlatinib and compound mutations in ALK+ large-cell neuroendocrine lung carcinoma: a case report

Large-cell neuroendocrine lung carcinoma (LCNEC) is a high-grade neoplasm with median survival of 1 year and limited therapeutic options. Here, we report the unusual case of a 47-yr-old female smoker with stage IV LCNEC featuring EML4-ALK variant 2 (E20:A20), wild-type TP53/RB1, and low tumor mutational burden of 3.91 mut/Mb. Despite early progression within 3 mo under crizotinib, a durable response was achieved with alectinib. Oligoprogression in the left breast 10 mo later was treated by surgery, followed by a switch to ceritinib upon multifocal progression and detection of ALK:p.V1180L in the mastectomy specimen, but without success. Another rebiopsy revealed ALK:p.L1196M, but the tumor did not respond to brigatinib or carboplatin/pemetrexed, before stabilization under lorlatinib. Diffuse progression 8 mo later with detection of ALK :p.L1196M/p.G1202R and p.L1196M/ p.D1203N evolving from the previous p.L1196M did not respond to chemoimmunotherapy, and the patient succumbed with an overall survival (OS) of 37 mo. This case illustrates the importance of molecular profiling for LCNEC regardless of smoking status, and the superiority of next-generation ALK inhibitors compared to crizotinib for ALK+ cases. Lorlatinib retained efficacy in the heavily pretreated setting, whereas its upfront use could possibly have prevented the stepwise emergence of compound ALK mutations. Furthermore, the disease course was more aggressive and OS shorter compared to the V2/TP53wt ALK+ lung adenocarcinoma, whereas crizotinib, ceritinib, and brigatinib did not confer the benefit expected according to next-generation sequencing results, which also underline the need for more potent drugs against ALK in the high-risk setting of neuroendocrine histology.

Cellular dissociation grading on biopsies of pulmonary squamous cell carcinoma provides prognostic information across all stages and is congruent with resection specimen grading

Grading of squamous cell carcinomas (SCCs) based on tumour budding and cell nest size has been termed cellular dissociation grading (CDG) and was suggested as a robust outcome predictor when assessed in biopsies and resections of various extrapulmonary SCCs. In pulmonary SCC (pSCC), this has so far been shown only for resected cancers. As most lung cancers are inoperable, it is of utmost importance to clarify whether the prognostic impact of CDG is retained in the biopsy setting. Two independent pSCC biopsy cohorts from Munich (n = 134, non-resected) and Heidelberg (n = 135, resected) were assessed. Tumour budding and cell nest size measures were assembled into the three-tiered CDG system (G1-G3). Data were correlated with clinicopathological parameters and overall- (OS), disease-specific- (DSS), and disease-free survival (DFS). Interobserver variability and concordance between biopsy and resection specimen were also investigated. CDG was highly congruent between biopsy and resection specimens (κ = 0.77, p < 0.001). In both pSCC cohorts, biopsy-derived CDG strongly impacted on OS, DSS, and DFS (e.g. DFS: p < 0.001). In multivariate survival analyses, CDG remained a stage independent predictor of survival in both cohorts (DFS: p < 0.001 respectively; hazard ratio Munich cohort: CDG-G2: 4.31, CDG-G3; 5.14; Heidelberg cohort: CDG-G2: 5.87, CDG-G3: 9.07). Interobserver agreement for CDG was almost perfect (κ = 0.84, p < 0.001). We conclude that assessment of CDG based on tumour budding and cell nest size is feasible on pSCC biopsies and harbours stage independent prognostic information in resectable as well as non-resectable pSCC. Integration of this grading approach into clinicopathological routine should be considered.

Intratumoral Heterogeneity and Immune Modulation in Lung Adenocarcinoma in Female Smokers and Never Smokers

SIGNIFICANCE

Single-cell analysis of healthy lung tissue and lung cancer reveals distinct tumor cell populations, including cells with differential immune modulating capacity between smokers and never smokers, which could guide future therapeutic strategies.

Drug-microenvironment perturbations reveal resistance mechanisms and prognostic subgroups in CLL

The tumour microenvironment and genetic alterations collectively influence drug efficacy in cancer, but current evidence is limited and systematic analyses are lacking. Using chronic lymphocytic leukaemia (CLL) as a model disease, we investigated the influence of 17 microenvironmental stimuli on 12 drugs in 192 genetically characterised patient samples. Based on microenvironmental response, we identified four subgroups with distinct clinical outcomes beyond known prognostic markers. Response to multiple microenvironmental stimuli was amplified in trisomy 12 samples. Trisomy 12 was associated with a distinct epigenetic signature. Bromodomain inhibition reversed this epigenetic profile and could be used to target microenvironmental signalling in trisomy 12 CLL. We quantified the impact of microenvironmental stimuli on drug response and their dependence on genetic alterations, identifying interleukin 4 (IL4) and Toll‐like receptor (TLR) stimulation as the strongest actuators of drug resistance. IL4 and TLR signalling activity was increased in CLL‐infiltrated lymph nodes compared with healthy samples. High IL4 activity correlated with faster disease progression. The publicly available dataset can facilitate the investigation of cell‐extrinsic mechanisms of drug resistance and disease progression.

WNT4 overexpression and secretion in thymic epithelial tumors drive an autocrine loop in tumor cells in vitro

Background

WNT4-driven non-canonical signaling is crucial for homeostasis and age-related involution of the thymus. Abnormal WNT signaling is important in many cancers, but the role of WNT signaling in thymic tumors is largely unknown.

Materials &amp; Methods

Expression and function of WNT4 and FZD6 were analyzed using qRT–PCR, Western blot, ELISA, in biopsies of non-neoplastic thymi (NT), thymoma and thymic carcinomas. ShRNA techniques and functional assays were used in primary thymic epithelial cells (pTECs) and TC cell line 1889c. Cells were conventionally (2D) grown and in three-dimensional (3D) spheroids.

Results

In biopsy, WHO classified B3 thymomas and TCs showed increased WNT4 expression compared with NTs. During short-term 2D culture, WNT4 expression and secretion declined in neoplastic pTECs but not in 3D spheroids or medium supplemented with recombinant WNT4 cultures. Under the latter condition, the growth of pTECs was accompanied by increased expression of non-canonical targets RAC1 and JNK. Down-regulation of WNT4 by shRNA induced cell death in pTECs derived from B3 thymomas and led to decreased RAC1, but not JNK protein phosphorylation. Pharmacological inhibition of NF-κB decreased both RAC1 and JNK phosphorylation in neoplastic pTECs.

Conclusions

Lack of the age-related decline of non-canonical WNT4 expression in TETs and restoration of declining WNT4 expression through exogeneous WNT4 or 3D culture of pTECs hints at an oncogenic role of WNT4 in TETs and is compatible with the WNT4 autocrine loop model. Crosstalk between WNT4 and NF-κB signaling may present a promising target for combined interventions in TETs.

Robust subtyping of non-small cell lung cancer whole sections through MALDI mass spectrometry imaging

Subtyping of the most common non-small cell lung cancer (NSCLC) tumor types adenocarcinoma (ADC) and squamous cell carcinoma (SqCC) is still a challenge in the clinical routine and a correct diagnosis is crucial for an adequate therapy selection. Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) has shown potential for NSCLC subtyping but is subject to strong technical variability and has only been applied to tissue samples assembled in tissue microarrays (TMAs). To our knowledge, a successful transfer of a classifier from TMAs to whole sections, which are generated in the standard clinical routine, has not been presented in the literature as of yet. We introduce a classification algorithm using extensive preprocessing and a classifier (either a neural network or a linear discriminant analysis (LDA)) to robustly classify whole sections of ADC and SqCC lung tissue. The classifiers were trained on TMAs and validated and tested on whole sections. Vital for a successful application on whole sections is the extensive preprocessing and the use of whole sections for hyperparameter selection. The classification system with the neural network/LDA results in 99.0%/98.3% test accuracy on spectra level and 100.0%/100.0% test accuracy on whole section level, respectively, and, therefore, provides a powerful tool to support the pathologist's decision making process. The presented method is a step further towards a clinical application of MALDI MSI and artificial intelligence for subtyping of NSCLC tissue sections.

Major clinical benefit from adjuvant chemotherapy for stage II–III non-small cell lung cancer patients aged 75 years or older: a propensity score-matched analysis

Background

Data are currently insufficient to support the use of adjuvant chemotherapy (ACT) after surgical resection for stage II or III non-small cell lung cancer (NSCLC) in patients aged ≥ 75 years. In this study we evaluated efficacy and safety profile of ACT in this population.

Methods

We retrospectively evaluated 140 patients ≥ 75 years who underwent curative surgical resection for stage II–III NSCLC from 2010 to 2018 with an indication to ACT according to current guidelines. A propensity score-matched analysis was performed to avoid cofounding biases.

Results

Thirty of 140 patients (21%) received ACT. Most patients (n = 24, 80%) received carboplatin in combination with vinorelbine, while 5 patients (17%) received cisplatin plus vinorelbine and one patient (3%) carboplatin plus gemcitabine. The occurrence of adverse events led to treatment discontinuation in 8 (27%) cases, while 19 (63%) patients completed 4 chemotherapy cycles. Common reported adverse events with ACT were anemia (n = 20, 67%), neutropenia (n = 18, 60%), thrombocytopenia (n = 9, 30%), renal impairment (n = 4, 13%) and transaminase elevation (n = 4, 13%). No toxic deaths occurred. The median follow-up was 67 months (IQR: 53–87). ACT was associated with a significant benefit in both relapse-free survival (median 36 vs. 18.5 months, p = 0.049) and overall survival (median not reached [NR] vs. 33.5 months, p = 0.023) in a propensity score-matched analysis which controlled for cofounders.

Conclusion

ACT confers a survival benefit after curative resection of stage II–III NSCLC in selected patients aged 75 years or older with a manageable toxicity profile.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12890-022-02043-6.

Quality of Online Information on Multiple Myeloma Available for Laypersons

Online information can increase patients’ competence and engagement. However, there are concerns regarding invalid information. Overall, 300 websites and 50 YouTube videos on multiple myeloma (MM) were evaluated. The websites did not differ between the search engines or search ranks. The median time since the last update was 9 months. The 63 unique websites showed a poor general quality (median JAMA score 2 of 4, only 18% with a valid HON certificate). The patient- (user-) focused quality was medium to poor (median sum DISCERN score 41 out of 80 points). The overall reading level was difficult requiring at least a 12th US school grade. The content level was low (median 24 out of 73 points). Sixteen percent contained misleading/wrong facts. Websites provided by foundation/advocacies showed a significantly higher general and patient- (user-) focused quality. For videos, the median time since upload was 18 months. Judged by the HON foundation score ~80% of videos showed a medium general quality. The patient- (user-) focused quality was medium to poor (median sum DISCERN score 43 points). The content level was very low (median 8 points). MM relevant websites and videos showed a medium to low general, patient- (user-) focused and content quality. Therefore, incorporation of quality indices and regular review is warranted.

Multicenter Evaluation of Tissue Classification by Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging

Many studies have demonstrated that tissue phenotyping (tissue typing) based on mass spectrometric imaging data is possible; however, comprehensive studies assessing variation and classifier transferability are largely lacking. This study evaluated the generalization of tissue classification based on Matrix Assisted Laser Desorption/Ionization (MALDI) mass spectrometric imaging (MSI) across measurements performed at different sites. Sections of a tissue microarray (TMA) consisting of different formalin-fixed and paraffin-embedded (FFPE) human tissue samples from different tumor entities (leiomyoma, seminoma, mantle cell lymphoma, melanoma, breast cancer, and squamous cell carcinoma of the lung) were prepared and measured by MALDI-MSI at different sites using a standard protocol (SOP). Technical variation was deliberately introduced on two separate measurements via a different sample preparation protocol and a MALDI Time of Flight mass spectrometer that was not tuned to optimal performance. Using standard data preprocessing, a classification accuracy of 91.4% per pixel was achieved for intrasite classifications. When applying a leave-one-site-out cross-validation strategy, accuracy per pixel over sites was 78.6% for the SOP-compliant data sets and as low as 36.1% for the mistuned instrument data set. Data preprocessing designed to remove technical variation while retaining biological information substantially increased classification accuracy for all data sets with SOP-compliant data sets improved to 94.3%. In particular, classification accuracy of the mistuned instrument data set improved to 81.3% and from 67.0% to 87.8% per pixel for the non-SOP-compliant data set. We demonstrate that MALDI-MSI-based tissue classification is possible across sites when applying histological annotation and an optimized data preprocessing pipeline to improve generalization of classifications over technical variation and increasing overall robustness.

Early Assessment of Chemotherapy Response in Advanced Non-Small Cell Lung Cancer with Circulating Tumor DNA

Monitoring treatment efficacy early during therapy could enable a change in treatment to improve patient outcomes. We report an early assessment of response to treatment in advanced NSCLC using a plasma-only strategy to measure changes in ctDNA levels after one cycle of chemotherapy. Plasma samples were collected from 92 patients with Stage IIIB-IV NSCLC treated with first-line chemo- or chemoradiation therapies in an observational, prospective study. Retrospective ctDNA analysis was performed using next-generation sequencing with a targeted 198-kb panel designed for lung cancer surveillance and monitoring. We assessed whether changes in ctDNA levels after one or two cycles of treatment were associated with clinical outcomes. Subjects with ≤50% decrease in ctDNA level after one cycle of chemotherapy had a lower 6-month progression-free survival rate (33% vs. 58%, HR 2.3, 95% CI 1.2 to 4.2, log-rank p = 0.009) and a lower 12-month overall survival rate (25% vs. 70%, HR 4.3, 95% CI 2.2 to 9.7, log-rank p < 0.001). Subjects with ≤50% decrease in ctDNA level after two cycles of chemotherapy also had shorter survival. Using non-invasive liquid biopsies to measure early changes in ctDNA levels in response to chemotherapy may help identify non-responders before standard-of-care imaging in advanced NSCLC.

Synoviale Veränderungen bei Erkrankungen des rheumatologischen Formenkreises und Differenzialdiagnosen

Die Untersuchung synovialer Veränderungen kann zur Diagnose von Gelenkerkrankungen und von systemischen Erkrankungen beitragen. Die Domäne der histopathologischen Diagnostik stellt die Abgrenzung tumoröser von entzündlichen Läsionen dar. Daneben können Kristallarthropathien und bestimmte Stoffwechselerkrankungen sicher diagnostiziert werden. Unter dem histologischen Bild einer granulomatösen Synovialitis können neben einer mykobakteriellen Infektion Sarkoidosen und Fremdkörperreaktionen sowie selten genetische Erkrankungen beobachtet werden. Amyloidosen können auch in der Tunica synovialis subtypisiert werden. Molekulare Methoden erlauben die schnelle und sichere Diagnostik septischer Arthritiden und eine Keimtypisierung. Mittels dieser Methoden können auch reaktive Arthritiden klassifiziert werden, da auch hier häufig DNA oder RNA bestimmter Keime in Gewebe oder Gelenkflüssigkeit nachgewiesen werden kann. Die Diagnose der rheumatoiden Arthritis basiert auf den American College of Rheumatology(ACR)-Kriterien. Molekulare Methoden, wie die Mikro-RNA-Technologie oder proteomische Methoden können die Diagnose unterstützen.

Transmembrane serine protease 2 is a prognostic factor for lung adenocarcinoma

Transmembrane serine protease 2 (TMPRSS2) has been intensively investigated during the current Sars-CoV-2 pandemic as a virus activating protease. Furthermore, TMPRSS2 is an oncogenic gene associated with several cancer entities. Co-expression of TMPRSS2 and serpin family A member 1 (SERPINA1) (encoding alpha-1-antitrypsin; AAT) has been reported in the human lung. Recently, AAT was identified as a novel TMPRSS2 inhibitor. We previously reported that lower SERPINA1 expression in tumor tissues and higher levels of plasma AAT are associated with worse survival of patients with non-small cell lung cancer (NSCLC). In the present study, we sought to examine TMPRSS2 and SERPINA1/AAT expression in tumor and adjacent lung tissues from 347 NSCLC patients. Based on clinical data and gene expression analysis, we performed Cox regression for the survival analysis, and correlated TMPRSS2 and AAT protein levels in tissue samples by immunohistochemical and western blot analyses. We found that lower TMPRSS2 expression in tumor compared to adjacent non-tumor tissues is linked to a poor overall survival in patients with adenocarcinoma (ADC) and those who are current smokers. IHC staining of TMPRSS2 validated our findings in regard to overall survival while we did not observe a correlation with AAT staining. Based on western blot analyses, we found only a slight negative correlation between full-length TMPRSS2 and AAT in non-tumor tissues, which seems to be related to smoking status. Taken together, we demonstrated that TMPRSS2 is a prognostic factor in patients with lung ADC; however, a link between AAT and TMPRSS2 proteins warrants further investigation.

Histological and Molecular Plasticity of ALK-positive Non-Small-Cell Lung Cancer under Targeted Therapy - a Case Report

With medical progress in cancer therapy, tyrosine kinase inhibitors (TKIs) became a standard of care for many cancer types. But the broad range of possible targeted therapies was accompanied by a plethora of potential resistance mechanisms, of which many have still to be identified. Here, we present the case of a patient with an EML4–ALK translocated non-small-cell lung cancer treated with four different TKIs. Her tumor developed not only a well-known ALK–TKI resistance mutation but also underwent a histological transformation from adenocarcinoma to squamous cell carcinoma. To confirm a shared monoclonal origin of the phenotypically different tumors, a phylogenetic reconstruction was conducted: This revealed a cluster of mutations including NFE2L2, KMT2D, and MLH1, which are possible triggering events for the transformation.

Detection of SARS-CoV-2 by Mass Spectrometry

Amplification of viral ribonucleic acid by real-time reverse transcriptase polymerase chain reaction is the gold standard to detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, alternative reliable, fast, and cost-effective methods for the detection of SARS-CoV-2 are still needed. In this chapter, the mass spectrometry-based detection of amplified polymerase chain reaction products of SARS-CoV-2 genes from oral or nasopharyngeal swabs is described. The respective SARS-CoV-2 test has previously been shown to meet standard quality criteria and was therefore approved by the authorities in Europe and the USA.

TRAF6 prevents fatal inflammation by homeostatic suppression of MALT1 protease

[Figure: see text].

Simultaneous targeting of TGF-β/PD-L1 synergizes with radiotherapy by reprogramming the tumor microenvironment to overcome immune evasion

Localized radiotherapy (RT) induces an immunogenic antitumor response that is in part counterbalanced by activation of immune evasive and tissue remodeling processes, e.g., via upregulation of programmed cell death-ligand 1 (PD-L1) and transforming growth factor β (TGF-β). We report that a bifunctional fusion protein that simultaneously inhibits TGF-β and PD-L1, bintrafusp alfa (BA), effectively synergizes with radiotherapy, leading to superior survival in multiple therapy-resistant murine tumor models with poor immune infiltration. The BA + RT (BART) combination increases tumor-infiltrating leukocytes, reprograms the tumor microenvironment, and attenuates RT-induced fibrosis, leading to reconstitution of tumor immunity and regression of spontaneous lung metastases. Consistently, the beneficial effects of BART are in part reversed by depletion of cytotoxic CD8⁺ T cells. Intriguingly, targeting of the TGF-β trap to PD-L1⁺ endothelium and the M2/lipofibroblast-like cell compartment by BA attenuated late-stage RT-induced lung fibrosis. Together, the results suggest that the BART combination has the potential to eradicate therapy-resistant tumors while sparing normal tissue, further supporting its clinical translation.

Association of the advanced lung cancer inflammation index (ALI) with immune checkpoint inhibitor efficacy in patients with advanced non-small-cell lung cancer

Background

The advanced lung cancer inflammation index [ALI: body mass index × serum albumin/neutrophil-to-lymphocyte ratio (NLR)] reflects systemic host inflammation, and is easily reproducible. We hypothesized that ALI could assist guidance of non-small-cell lung cancer (NSCLC) treatment with immune checkpoint inhibitors (ICIs).

Patients and methods

This retrospective study included 672 stage IV NSCLC patients treated with programmed death-ligand 1 (PD-L1) inhibitors alone or in combination with chemotherapy in 25 centers in Greece and Germany, and a control cohort of 444 stage IV NSCLC patients treated with platinum-based chemotherapy without subsequent targeted or immunotherapy drugs. The association of clinical outcomes with biomarkers was analyzed with Cox regression models, including cross-validation by calculation of the Harrell's C-index.

Results

High ALI values (>18) were significantly associated with longer overall survival (OS) for patients receiving ICI monotherapy [hazard ratio (HR) = 0.402, P < 0.0001, n = 460], but not chemo-immunotherapy (HR = 0.624, P = 0.111, n = 212). Similar positive correlations for ALI were observed for objective response rate (36% versus 24%, P = 0.008) and time-on-treatment (HR = 0.52, P < 0.001), in case of ICI monotherapy only. In the control cohort of chemotherapy, the association between ALI and OS was weaker (HR = 0.694, P = 0.0002), and showed a significant interaction with the type of treatment (ICI monotherapy versus chemotherapy, P < 0.0001) upon combined analysis of the two cohorts. In multivariate analysis, ALI had a stronger predictive effect than NLR, PD-L1 tumor proportion score, lung immune prognostic index, and EPSILoN scores. Among patients with PD-L1 tumor proportion score ≥50% receiving first-line ICI monotherapy, a high ALI score >18 identified a subset with longer OS and time-on-treatment (median 35 and 16 months, respectively), similar to these under chemo-immunotherapy.

Conclusions

The ALI score is a powerful prognostic and predictive biomarker for patients with advanced NSCLC treated with PD-L1 inhibitors alone, but not in combination with chemotherapy. Its association with outcomes appears to be stronger than that of other widely used parameters. For PD-L1-high patients, an ALI score >18 could assist the selection of cases that do not need addition of chemotherapy.

•

ALI is prognostic and predictive for patients with advanced NSCLC treated with immunotherapy monotherapy, but not chemo-immunotherapy.

•

Its association with outcomes is stronger than that of other parameters (PD-L1 TPS, NLR, lung immune prognostic index, EPSILoN).

•

For PD-L1-high patients, an ALI score >18 could assist the selection of cases that do not need addition of chemotherapy.

Canonical NF-κB Promotes Lung Epithelial Cell Tumour Growth by Downregulating the Metastasis Suppressor CD82 and Enhancing Epithelial-to-Mesenchymal Cell Transition

Simple Summary

Canonical NF-κB signalling pathway acts as a tumour promoter in several types of cancer including non-small cell lung cancer (NSCLC), but the mechanism(s) by which it contributes to NSCLC is still under investigation. We show here that NF-κB RelA/p65 is required for the tumour growth of human NSCLC cells grown in vivo as xenografts in immune-compromised mice. RNA-seq transcriptome profile analysis identified the metastasis suppressor CD82/KAI1/TSPAN27 as a canonical NF-κB target. Loss of CD82 correlated with malignancy. RelA/p65 stimulates cell migration and epithelial-to-mesenchymal cell transition (EMT), mediated, in part, by CD82/KAI1, through integrin-mediated signalling, thus, identifying a mechanism mediating NF-κB RelA/p65 lung tumour promoting function.

Abstract

Background: The development of non-small cell lung cancer (NSCLC) involves the progressive accumulation of genetic and epigenetic changes. These include somatic oncogenic KRAS and EGFR mutations and inactivating TP53 tumour suppressor mutations, leading to activation of canonical NF-κB. However, the mechanism(s) by which canonical NF-κB contributes to NSCLC is still under investigation. Methods: Human NSCLC cells were used to knock-down RelA/p65 (RelA/p65^KD) and investigate its impact on cell growth, and its mechanism of action by employing RNA-seq analysis, qPCR, immunoblotting, immunohistochemistry, immunofluorescence and functional assays. Results: RelA/p65^KD reduced the proliferation and tumour growth of human NSCLC cells grown in vivo as xenografts in immune-compromised mice. RNA-seq analysis identified canonical NF-κB targets mediating its tumour promoting function. RelA/p65^KD resulted in the upregulation of the metastasis suppressor CD82/KAI1/TSPAN27 and downregulation of the proto-oncogene ROS1, and LGR6 involved in Wnt/β-catenin signalling. Immunohistochemical and bioinformatics analysis of human NSCLC samples showed that CD82 loss correlated with malignancy. RelA/p65^KD suppressed cell migration and epithelial-to-mesenchymal cell transition (EMT), mediated, in part, by CD82/KAI1, through integrin-mediated signalling involving the mitogenic ERK, Akt1 and Rac1 proteins. Conclusions: Canonical NF-κB signalling promotes NSCLC, in part, by downregulating the metastasis suppressor CD82/KAI1 which inhibits cell migration, EMT and tumour growth.

Real-world implementation of sequential targeted therapies for EGFR-mutated lung cancer

Background:

Epidermal growth factor receptor-mutated (EGFR⁺) non-small-cell lung cancer (NSCLC) patients failing tyrosine kinase inhibitors (TKI) can benefit from next-line targeted therapies, but implementation is challenging.

Methods:

EGFR⁺ NSCLC patients treated with first/second-generation (1G/2G) TKI at our institution with a last follow-up after osimertinib approval (February 2016), were analyzed retrospectively, and the results compared with published data under osimertinib.

Results:

A total of 207 patients received erlotinib (37%), gefitinib (16%) or afatinib (47%). The median age was 66 years, with a predominance of female (70%), never/light-smokers (69%). T790M testing was performed in 174/202 progressive cases (86%), positive in 93/174 (53%), and followed by osimertinib in 87/93 (94%). Among the 135 deceased patients, 94 (70%) received subsequent systemic treatment (43% chemotherapy, 39% osimertinib), while 30% died without, either before (4%) or after progression, due to rapid clinical deterioration (22%), patient refusal of further therapy (2%), or severe competing illness (2%). Lack of subsequent treatment was significantly (4.5x, p < 0.001) associated with lack of T790M testing, whose most frequent cause (in approximately 50% of cases) was also rapid clinical decline. Among the 127 consecutive patients with failure of 1G/2G TKI started after November 2015, 47 (37%) received osimertinib, with a median overall survival of 36 months versus 24 and 21 months for patients with alternative and no subsequent therapies (p = 0.003).

Conclusion:

Osimertinib after 1G/2G TKI failure prolongs survival, but approximately 15% and 30% of patients forego molecular retesting and subsequent treatment, respectively, mainly due to rapid clinical deterioration. This is an important remediable obstacle to sequential TKI treatment for EGFR⁺ NSCLC. It pertains also to other actionable resistance mechanisms emerging under 1G/2G inhibitors or osimertinib, whose rate for lack of next-line therapy is similar (approximately 35% in the FLAURA/AURA3 trials), and highlights the need for closer monitoring alongside broader profiling of TKI-treated EGFR⁺ NSCLC in the future.

Cytoreductive Thoracic Surgery Combined with Hyperthermic Chemoperfusion for Pleural Malignancies: A Single-Center Experience

BACKGROUND

Lung-sparing cytoreductive surgery by extended pleurectomy and decortication (EPD) in combination with hyperthermic intrathoracic chemoperfusion (HITOC) forms a promising treatment strategy for malignant pleural mesothelioma and recurrent pleural thymic malignancies.

OBJECTIVES

The objective of this study was to scrutinize the surgical procedure and perioperative patient management with emphasis on perioperative morbidity and local tumor control.

METHODS

In 2014, a standardized EPD and HITOC procedure was implemented at the Thoraxklinik Heidelberg. This retrospective analysis included clinical data of consecutive patients with pleural mesothelioma and pleural metastasized malignancies treated by EPD and HITOC. The surgical procedure, perioperative management, lung function data, and progression-free survival (PFS) were analyzed.

RESULTS

In the time range between April 2, 2014 and July 2018, 76 patients with pleural malignancies have been treated with EPD and HITOC, and were analyzed retrospectively. It included 61 patients with pleural mesothelioma and 15 patients with pleural metastases of thymic malignancies (12), non-small cell lung cancer (1), colorectal carcinoma (1), and sarcoma (1). Perioperative morbidity following EPD and HITOC treatments represented 23.7% of overall malignancies, while 30- and 90-day mortality were 0 and 1.3%, respectively. Median PFS lasted 18.4 months for mesothelioma and 72.2 months for thymic malignancies.

CONCLUSION

Combining EPD with HITOC can be performed in patients with either pleural mesothelioma or pleural metastases resulting in low perioperative morbidity and mortality as well as remarkable local tumor control.

Comprehensive Dissection of Treatment Patterns and Outcome for Patients With Metastatic Large-Cell Neuroendocrine Lung Carcinoma

BACKGROUND

Large-cell neuroendocrine lung carcinoma (LCNEC) is a rare pulmonary neoplasm with poor prognosis and limited therapeutic options.

METHODS

We retrospectively analyzed all patients with metastatic LCNEC in the records of a large German academic center since 2010.

RESULTS

191 patients were identified with a predominance of male (68%) smokers (92%) and a median age of 65 years. The single most important factor associated with outcome was the type of systemic treatment, with a median overall survival (OS) of 26.4 months in case of immune checkpoint inhibitor administration (n=13), 9.0 months for other patients receiving first-line platinum doublets (n=129), and 4.0 months with non-platinum chemotherapies (n=17, p<0.01). Other patient characteristics independently associated with longer OS were a lower baseline serum LDH (hazard ratio [HR] 0.54, p=0.008) and fewer initial metastatic sites (HR 0.52, p=0.006), while the platinum drug type (cisplatin vs. carboplatin) and cytotoxic partner (etoposide vs. paclitaxel), patients' smoking status and baseline levels of tumor markers (NSE, CYFRA 21-1, CEA) did not matter. 12% (23/191) of patients forewent systemic treatment, mainly due to tumor-related clinical deterioration (n=13), while patient refusal of therapy (n=5) and severe concomitant illness (n=5) were less frequent. The attrition between successive treatment lines was approximately 50% and similar for platinum-based vs. other therapies, but higher in case of a worse initial ECOG status or higher serum LDH (p<0.05). 19% (36/191) of patients had secondary stage IV disease and showed fewer metastatic sites, better ECOG status and longer OS (median 12.6 vs. 8.7 months, p=0.030). Among the 111 deceased patients with palliative systemic treatment and complete follow-up, after exclusion of oligometastatic cases (n=8), administration of local therapies (n=63 or 57%) was associated with a longer OS (HR 0.58, p=0.008), but this association did not persist with multivariable testing.

CONCLUSIONS

Highly active systemic therapies, especially immunotherapy and platinum doublets, are essential for improved outcome in LCNEC and influence OS stronger than clinical disease parameters, laboratory results and other patient characteristics. The attrition between chemotherapy lines is approximately 50%, similar to other NSCLC. Patients with secondary metastatic disease have a more favorable clinical phenotype and longer survival.

Local Radiation Therapy Before and During Induction Delays Stem Cell Mobilization and Collection in Multiple Myeloma Patients

In multiple myeloma, local radiation therapy (RT) of osseous lesions before peripheral blood stem cell (PBSC) mobilization is assumed to impair the PBSC mobilization and collection. However, the results of previously published studies are inconsistent and do not evaluate detailed metrics of RT and PBSC outcome parameters. In total, 352 patients undergoing PBSC mobilizations and RT in first-line treatment were evaluated. Patients were grouped into RT (n = 283) and no RT (n = 69) before PBSC mobilization. Except for the International Staging System score, both groups were homogeneous regarding the first diagnosis characteristics, first-line treatments, and response parameters. RT metrics (RT yes versus no, volume of irradiated hematopoietic bone marrow [BM], biologically equivalent doses in 2 Gy fractions [EQD2]) were analyzed for the following PBSC outcome parameters: achievement of the PBSC collection goal, CD34+ cell collection yield, duration of the mobilization phase, and number of leukapheresis (LP) sessions to reach the collection goal. No statistically significant differences in the percentage of collection failures to reach at least 3 sufficient PBSC transplants were identified comparing patients with (n = 32 [11%]) and without RT (n = 4 [6%]) before PBSC mobilization (P = .265). However, patients with RT before PBSC mobilization showed a significant prolongation of the PBSC mobilization (median 1 day, P =.026) and required a higher number of LP sessions to reach the collection goal (median 1 LP, P < .001) compared with patients who received RT after PBSC mobilization. Moreover, patients with RT before PBSC mobilization reached a significantly lower CD34+ cell collection result (mean 8.94 versus 9.81 × 10⁶/kg body weight [bw], P = .002). No correlation was identified between the overall CD34+ cell yield and the volume of irradiated hematopoietic BM or EQD2, respectively. In the RT before PBSC mobilization group, patients who required more than 1 LP session to reach the PBSC collection goal after RT had a significantly higher percentage of radiated hematopoietic BM compared to those who required only 1 LP session (mean 9.7% versus 7.2%, P = .002). Overall, our study indicates a negative impact of RT on PBSC mobilization and collection. Apart from emergency settings, it might be beneficial to postpone RT to a post-PBSC collection time point. © 2021 American Society for Blood and Marrow Transplantation. Published by Elsevier Inc. All rights reserved.

Therapeutic and Prognostic Implications of Immune-Related Adverse Events in Advanced Non-Small-Cell Lung Cancer

Introduction

PD-(L)1 inhibitors have improved prognosis of non-small-cell lung cancer (NSCLC), but can also cause immune-related adverse events (irAEs) that complicate management.

Methods

We analyzed NSCLC patients receiving PD-(L)1 inhibitors from 2012 to 2020 in a German academic center.

Results

IrAE showed comparable frequencies in stage IV (198/894 or 22%) vs. III (14/45 or 31%, p = 0.15), after anti-PD-(L)1 monotherapy vs. chemoimmunotherapy (139/483 vs. 58/213, p = 0.75), and across treatment lines. In stage IV, irAE occurred after 3.1 months in median, affected multiple organs (median 2) in 27/894 patients and were associated with PD-L1 positivity (25 vs. 14%, p = 0.003), lower neutrophil-to-lymphocyte ratios (29 vs. 17%, p < 0.001 for NLR dichotomized at 5), better ECOG status (26 vs. 18% for 0 vs. 1, p = 0.004), but not related to age, sex, smoking and palliative radiotherapy. Two hundred thirty two irAEs occurred mostly in endocrine glands (4.9%), lungs (4.4%), the musculoskeletal system (4.2%), colon (4.1%), liver (3.7%), and skin (2.6%), while pneumonitis was most frequent with durvalumab following definitive chemoradiation (16% or 7/45, p < 0.01). IrAE severity was grade 1 in 11%, 2 in 41%, 3 in 36%, and 4 in 11% events, while two were lethal (<1%, myocarditis and pneumonitis). Therapy was suspended in 72%, while steroids were initiated in 66% and complemented by other immunosuppressants in 6%, with longest treatment duration for rheumatic events (mean >3 months), and average cumulative prednisone doses >700 mg for all organs, except for skin. Patients developing irAE had longer progression-free (PFS) and overall survival (OS) in multivariable 12/14-week landmark analyses including ECOG status, treatment line, treatment type, PD-L1 TPS, and NLR (median PFS 17 vs. 10 months, HR = 0.68, p = 0.009; median OS 37 vs. 15 months, HR = 0.40, p < 0.001), regardless of grade. OS was longest with skin (95% at 2 years) and shortest with pneumonitis, hepatitis, neurologic, and cardiologic irAE (38, 37, 28, and 0% at 2 years, p < 0.001).

Conclusions

Approximately one-fourth of immunotherapy-treated NSCLC patients develop irAEs, most of which necessitate treatment suspension and steroids. Despite more frequent occurrence with PD-L1 positive tumors, lower NLR, and better ECOG PS, irAEs are independently associated with longer survival, especially when affecting the skin. Lethality is below 1%.

Imaging Mass Spectrometry-Based Proteomic Analysis to Differentiate Melanocytic Nevi and Malignant Melanoma

The discrimination of malignant melanoma from benign nevi may be difficult in some cases. For this reason, immunohistological and molecular techniques are included in the differential diagnostic toolbox for these lesions. These methods are time consuming when applied subsequently and, in some cases, no definitive diagnosis can be made. We studied both lesions by imaging mass spectrometry (IMS) in a large cohort (n = 203) to determine a different proteomic profile between cutaneous melanomas and melanocytic nevi. Sample preparation and instrument setting were tested to obtain optimal results in term of data quality and reproducibility. A proteomic signature was found by linear discriminant analysis to discern malignant melanoma from benign nevus (n = 113) with an overall accuracy of >98%. The prediction model was tested in an independent set (n = 90) reaching an overall accuracy of 93% in classifying melanoma from nevi. Statistical analysis of the IMS data revealed mass-to-charge ratio (m/z) peaks which varied significantly (Area under the receiver operating characteristic curve > 0.7) between the two tissue types. To our knowledge, this is the largest IMS study of cutaneous melanoma and nevi performed up to now. Our findings clearly show that discrimination of melanocytic nevi from melanoma is possible by IMS.