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Abstract 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.

Abstract Tuft cells are chemosensory epithelial cells in the respiratory tract and several other organs. Recent studies revealed tuft cell-like gene expression signatures in some pulmonary adenocarcinomas, squamous cell carcinomas (SQCC), small cell carcinomas (SCLC), and large cell neuroendocrine carcinomas (LCNEC). Identification of their similarities could inform shared druggable vulnerabilities. Clinicopathological features of tuft cell-like (tcl) subsets in various lung cancer histotypes were studied in two independent tumor cohorts using immunohistochemistry (n = 674 and 70). Findings were confirmed, and additional characteristics were explored using public datasets (RNA seq and immunohistochemical data) (n = 555). Drug susceptibilities of tuft cell-like SCLC cell lines were also investigated. By immunohistochemistry, 10–20% of SCLC and LCNEC, and approximately 2% of SQCC expressed POU2F3, the master regulator of tuft cells. These tuft cell-like tumors exhibited “lineage ambiguity” as they co-expressed NCAM1, a marker for neuroendocrine differentiation, and KRT5, a marker for squamous differentiation. In addition, tuft cell-like tumors co-expressed BCL2 and KIT, and tuft cell-like SCLC and LCNEC, but not SQCC, also highly expressed MYC. Data from public datasets confirmed these features and revealed that tuft cell-like SCLC and LCNEC co-clustered on hierarchical clustering. Furthermore, only tuft cell-like subsets among pulmonary cancers significantly expressed FOXI1, the master regulator of ionocytes, suggesting their bidirectional but immature differentiation status. Clinically, tuft cell-like SCLC and LCNEC had a similar prognosis. Experimentally, tuft cell-like SCLC cell lines were susceptible to PARP and BCL2 co-inhibition, indicating synergistic effects. Taken together, pulmonary tuft cell-like cancers maintain histotype-related clinicopathologic characteristics despite overlapping unique molecular features. From a therapeutic perspective, identification of tuft cell-like LCNECs might be crucial given their close kinship with tuft cell-like SCLC.

Abstract 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

Proteomics can be used to refine cancer classification. Here, the authors characterise chronic lymphocytic leukaemia patients by proteogenomics, and identified a subtype of patients with poor prognosis associated with aberrant B cell receptor signalling.

Abstract 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.

Abstract 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.

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.

Abstract 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.

ObjectiveTo 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.MethodsSynovial 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.ResultsData 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.ConclusionsWe 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.

Summary: 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.

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.

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.

BackgroundWNT4-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 & MethodsExpression 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.ResultsIn 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.ConclusionsLack 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.

Abstract Background Synaptophysin, chromogranin and CD56 are recommended markers to identify pulmonary tumors with neuroendocrine differentiation. Whether the expression of these markers in pulmonary adenocarcinoma and pulmonary squamous cell carcinoma is a prognostic factor has been a matter of debate. Therefore, we investigated retrospectively a large cohort to expand the data on the role of synaptophysin, chromogranin and CD56 in non-small cell lung cancer lacking morphological features of neuroendocrine differentiation. Methods A cohort of 627 pulmonary adenocarcinomas (ADC) and 543 squamous cell carcinomas (SqCC) lacking morphological features of neuroendocrine differentiation was assembled and a tissue microarray was constructed. All cases were stained with synaptophysin, chromogranin and CD56. Positivity was defined as > 1% positive tumor cells. Data was correlated with clinico-pathological features including overall and disease free survival. Results 110 (18%) ADC and 80 (15%) SqCC were positive for either synaptophysin, chromogranin, CD56 or a combination. The most commonly positive single marker was synaptophysin. The least common positive marker was chromogranin. A combination of ≤2 neuroendocrine markers was positive in 2–3% of ADC and 0–1% of SqCC. There was no significant difference in overall survival in tumors with positivity for neuroendocrine markers neither in ADC (univariate: P = 0.4; hazard ratio [HR] = 0.867; multivariate: P = 0.5; HR = 0.876) nor in SqCC (univariate: P = 0.1; HR = 0.694; multivariate: P = 0.1, HR = 0.697). Likewise, there was no significant difference in disease free survival. Conclusions We report on a cohort of 1170 cases that synaptophysin, chromogranin and CD56 are commonly expressed in ADC and SqCC and that their expression has no impact on survival, supporting the current best practice guidelines.

Tyrosine kinase inhibitors (TKIs) represent the standard treatment for patients with non-small cell lung cancer (NSCLC) harboring epidermal growth factor receptor (EGFR) mutations. The duration of the response is, however, limited in time owing to the development of resistance mechanisms to both first- and second-generation agents such as MET oncogene amplification. This report describes the successful results obtained with the combination of the third-generation TKI osimertinib with the multitargeted TKI and MET inhibitor crizotinib in a patient with EGFR-mutant NSCLC with emerging MET amplification with a tolerable toxicity profile.

Sarcomas are morphologically heterogeneous tumours rendering their classification challenging. Here the authors developed a classifier using DNA methylation data from several soft tissue and bone sarcoma subtypes, which has the potential to improve classification for research and clinical purposes.

Abstract Background High-dose (HD) chemotherapy followed by autologous blood stem-cell transplantation (ASCT) is the standard treatment for multiple myeloma (MM) patients. However, the collection of sufficient peripheral blood stem cell (PBSC) grafts can be challenging, and the question arises whether reinfusion of low-dose grafts will lead to a hematopoietic recovery. Methods The hematopoietic recovery of 148 MM patients who underwent HD melphalan chemotherapy and received PBSC transplants with varying CD34+ cells doses (3–4 × 106 [n = 86], 2–2.5 × 106 [n = 53],

BackgroundLarge-cell neuroendocrine lung carcinoma (LCNEC) is a rare pulmonary neoplasm with poor prognosis and limited therapeutic options.MethodsWe retrospectively analyzed all patients with metastatic LCNEC in the records of a large German academic center since 2010.Results191 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

IntroductionPD-(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.MethodsWe analyzed NSCLC patients receiving PD-(L)1 inhibitors from 2012 to 2020 in a German academic center.ResultsIrAE 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 (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).ConclusionsApproximately 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%.

The differentiation and function of regulatory T (Treg) cells are critically controlled by T cell receptor (TCR) signaling. Here the authors show that CARD11-BCL10-MALT1 (CBM) complexes are dispensable for effector Treg conversion under inflammatory conditions but are critical for mediating Treg suppressive activity in a MALT1 paracaspase-dependent manner.

Abstract Background Cholangiocarcinoma (CCA) may arise in the intra- or extrahepatic biliary tract and is associated with a poor prognosis. Despite recent advances, to date there is still no established targeted therapeutic approach available. Non-surgical therapeutic agents are urgently needed, as most patients are non-eligible to surgical resection. Anti-PD-L1 therapy prevents cancer cells from evading the immune system and has emerged as a new treatment option in several cancer entities. Recently, PD-L1 expression has been analyzed in comparably small CCA patient cohorts. However, a systematic validation of different PD-L1 antibodies has not been performed in CCA so far. Methods We stained a tissue microarray consisting of 170 patients, including 72 intrahepatic cholangiocarcinomas (iCCAs), 57 perihilar cholangiocarcinomas (pCCAs) and 41 distal cholangiocarcinomas (dCCAs) by immunohistochemistry and evaluated PD-L1 positivity in tumor and stromal cells. We analyzed three different PD-L1 antibodies (clones 28–8, SP142, and SP263) that are frequently used and recommended for predictive diagnostic testing in other cancer types. Results For PD-L1 antibody clone SP263, 5% of iCCAs, 4% of pCCAs and 3% of dCCAs exhibited PD-L1 expression on tumor cells, thereby showing the highest frequencies of PD-L1 positivity. Accordingly, highest PD-L1 positivity rates of stromal cells with 31% in iCCA, 40% in pCCA and 61% in dCCA were detected for clone SP263. Agreement of PD-L1 positivity in tumor cells was moderate for clone 28–8 and SP263 (κ = 0.44) and poor between 28-8 and SP142 (κ = 0.13), as well as SP142 and SP263 (κ = 0.11), respectively. Statistical analyses of PD-L1 expression (clone SP263) on tumor cells with clinicopathological data revealed a positive correlation with shortened overall survival in CCA patients. Conclusions Selection of appropriate PD-L1 antibodies and careful evaluation of immunohistochemical staining patterns have a significant impact on PD-L1 testing in CCA. Clinical trials are necessary to investigate the putative beneficial effects of PD-L1 targeted immunotherapy in CCA patients.

Cancer-related deaths are very commonly attributed to complications from metastases to neighboring as well as distant organs. Dissociate response in the treatment of pancreatic adenocarcinoma is one of the main causes of low treatment success and low survival rates. This behavior could not be explained by transcriptomics or genomics; however, differences in the composition at the protein level could be observed. We have characterized the proteomic composition of primary pancreatic adenocarcinoma and distant metastasis directly in human tissue samples, utilizing mass spectrometry imaging. The mass spectrometry data was used to train and validate machine learning models that could distinguish both tissue entities with an accuracy above 90%. Model validation on samples from another collection yielded a correct classification of both entities. Tentative identification of the discriminative molecular features showed that collagen fragments (COL1A1, COL1A2, and COL3A1) play a fundamental role in tumor development. From the analysis of the receiver operating characteristic, we could further advance some potential targets, such as histone and histone variations, that could provide a better understanding of tumor development, and consequently, more effective treatments.

BackgroundMetastatic epidermal growth factor receptor-mutated (EGFR+) non-small-cell lung cancer (NSCLC) can present de novo or following previous nonmetastatic disease (secondary). Potential differences between these two patient subsets are unclear at present.MethodsWe retrospectively analyzed characteristics of tyrosine kinase inhibitor (TKI)-treated patients with de novo vs. secondary metastatic EGFR+ NSCLC until December 2019 (n = 401).ResultsDe novo metastatic disease was 4× more frequent than secondary (n = 83/401), but no significant differences were noted regarding age (median 66 vs. 70 years), sex (65% vs. 65% females), smoking history (67% vs. 62% never/light-smokers), and histology (both >95% adenocarcinoma). Patients with secondary metastatic disease showed a better ECOG performance status (PS 0–1 67%–32% vs. 46%–52%, p = 0.003), fewer metastatic sites (mean 1.3 vs. 2.0, p < 0.001), and less frequent brain involvement (16% vs. 28%, p = 0.022) at the time of stage IV diagnosis. Progression-free survival (PFS) under TKI (median 17 for secondary vs. 12 months for de novo, p = 0.26) and overall survival (OS, 29 vs. 25 months, respectively, p = 0.47) were comparable. EGFR alterations (55% vs. 60% exon 19 deletions), TP53 mutation rate at baseline (47% vs. 43%, n = 262), and T790M positivity at the time of TKI failure (51% vs. 56%, n = 193) were also similar. OS according to differing characteristics, e.g., presence or absence of brain metastases (19–20 or 30–31 months, respectively, p = 0.001), and ECOG PS 0 or 1 or 2 (32–34 or 20–23 or 5–7 months, respectively, p < 0.001), were almost identical for de novo and secondary metastatic disease.ConclusionsDespite the survival advantage reported in the pre-TKI era for relapsed NSCLC, molecular features and outcome of TKI-treated metastatic EGFR+ tumors are currently independent of preceding nonmetastatic disease. This simplifies design of outcome studies and can assist prognostic considerations in everyday management of patients with secondary metastatic EGFR+ tumors.

BackgroundAnaplastic lymphoma kinase-rearranged non-small-cell lung cancer (ALK+ NSCLC) is a model disease for use of targeted therapies (TKI), which are administered sequentially to maximize patient survival.MethodsWe retrospectively analyzed the flow of 145 consecutive TKI-treated ALK+ NSCLC patients across therapy lines. Suitable patients that could not receive an available next-line therapy (“attrition”) were determined separately for various treatments, based on the approval status of the respective targeted drugs when each treatment failure occurred in each patient.ResultsAt the time of analysis, 70/144 (49%) evaluable patients were still alive. Attrition rates related to targeted treatments were approximately 25-30% and similar for administration of a second-generation (2G) ALK inhibitor (22%, 17/79) or any subsequent systemic therapy (27%, 27/96) after crizotinib, and for the administration of lorlatinib (27%, 6/22) or any subsequent systemic therapy (25%, 15/61) after any 2G TKI. The rate of chemotherapy implementation was 67% (62/93). Both administration of additional TKI (median overall survival [mOS] 59 vs. 41 months for multiple vs. one TKI lines, logrank p=0.002), and chemotherapy (mOS 41 vs. 16 months, logrank p

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

Immune checkpoint blockade (ICB) expands the therapeutic options for metastatic lung cancer nowadays representing a standard frontline strategy as monotherapy or combination therapy, as well as an option in oncogene-addicted NSCLC after exhaustion of targeted therapies. Predictive markers are urgently needed, since only a minority of patients benefits from ICB, while serious adverse effects of immunotoxicity may occur. The study cohort included 43 ICB-treated metastatic lung adenocarcinoma showing long-term response (n = 16), rapid progression (n = 21) or intermediate patterns of response (n = 6). Lung biopsies acquired before initiation of ICB were analyzed by targeted mRNA expression profiling of 770 genes. Level and proportions of 14 immune cell types were estimated using characteristic gene expression signatures. Abundance of B cells (HR = 0.66, p = .00074), CD45+ cells (HR = 0.61, p = .01) and total TILs (HR = 0.62, p = .025) was associated with prolonged progression-free survival after ICB treatment. In a ROC analysis, B cells (AUC = 0.77, p = .0055) and CD45+ cells (AUC = 0.73, p = .019) predicted benefit of ICB, which was not the case for PD-L1 mRNA (AUC = 0.54, p = .72) and PD-L1 protein expression (AUC = 0.68, p = .082). Clustering of 79 candidate predictive markers identified among 770 investigated genes revealed two distinct predictive clusters which included cytotoxic cell or macrophage markers, respectively. In summary, targeted gene expression profiling was feasible using routine diagnostics biopsies. This study proposes B cells and total TILs as complementary predictors of ICB benefit in NSCLC. While further preferably prospective validation is required, gene expression profiling could be integrated in the routine diagnostic work-up complementing existing NGS protocols.

Background: Segmentation is, in many Pathomics projects, an initial step. Usually, in supervised settings, well-annotated and large datasets are required. Regarding the rarity of such datasets, unsupervised learning concepts appear to be a potential solution. Against this background, we tested for a small dataset on lung cancer tissue microarrays (TMA) if a model (i) first can be in a previously published unsupervised setting and (ii) secondly can be modified and retrained to produce meaningful labels, and (iii) we finally compared this approach to standard segmentation models. Methods: (ad i) First, a convolutional neuronal network (CNN) segmentation model is trained in an unsupervised fashion, as recently described by Kanezaki et al. (ad ii) Second, the model is modified by adding a remapping block and is retrained on an annotated dataset in a supervised setting. (ad iii) Third, the segmentation results are compared to standard segmentation models trained on the same dataset. Results: (ad i–ii) By adding an additional mapping-block layer and by retraining, models previously trained in an unsupervised manner can produce meaningful labels. (ad iii) The segmentation quality is inferior to standard segmentation models trained on the same dataset. Conclusions: Unsupervised training in combination with subsequent supervised training offers for histological images here no benefit.

Among neonates, tested positive for SARS-CoV-2, the majority of infections occur through postpartum transmission. Only few reports describe intrauterine or intrapartum SARS-CoV-2 infections in newborns. To understand the route of transmission, detection of the virus or virus nucleic acid in the placenta and amniotic tissue are of special interest. Current methods to detect SARS-CoV-2 in placental tissue are immunohistochemistry, electron microscopy, in-situ hybridization, polymerase chain reaction (PCR) and next-generation sequencing. Recently, we described an alternative method for the detection of viral ribonucleic acid (RNA), by combination of reverse transcriptase-PCR and mass spectrometry (MS) in oropharyngeal and oral swabs. In this report, we could detect SARS-CoV-2 in formal-fixed and paraffin-embedded (FFPE) placental and amniotic tissue by multiplex RT-PCR MS. Additionally, we could identify the British variant (B.1.1.7) of the virus in this tissue by the same methodology. Combination of RT-PCR with MS is a fast and easy method to detect SARS-CoV-2 viral RNA, including specific variants in FFPE tissue.

Abstract Background Non-small cell lung cancer (NSCLC) and melanoma are frequent entities in routine diagnostics. Whereas the differential diagnosis is usually straight forward based on histomorphology, it can be challenging in poorly differentiated tumors as melanoma may mimic various histological patterns. Distinction of the two entities is of outmost importance as both are treated differently. HMB45 and MelanA are recommended immunohistological markers for melanoma in this scenario. SOX10 has been described as an additional marker for melanoma. However, comprehensive large-scale data about the expression of melanoma markers in NSCLC tumor tissue specimen are lacking so far. Methods Therefore, we analyzed the expression of these markers in 1085 NSCLC tumor tissue samples. Tissue microarrays of NSCLC cases were immunohistochemically stained for HMB45, MelanA, and SOX10. Positivity of a marker was defined as ≥1% positive tumor cells. Results In 1027 NSCLC tumor tissue samples all melanoma as well as conventional immunohistochemical markers for NSCLC could be evaluated. HMB45, MelanA, and SOX10 were positive in 1 (

Abstract Background Earlier epidemiological studies indicate that associations between obesity and breast cancer risk may not only depend on menopausal status and use of exogenous hormones, but might also differ by tumor subtype. Here, we evaluated whether obesity is differentially associated with the risk of breast tumor subtypes, as defined by 6 immunohistochemical markers (ER, PR, HER2, Ki67, Bcl-2 and p53, separately and combined), in the prospective EPIC-Germany Study (n = 27,012). Methods Formalin-fixed and paraffin-embedded (FFPE) tumor tissues of 657 incident breast cancer cases were used for histopathological analyses. Associations between BMI and breast cancer risk across subtypes were evaluated by multivariable Cox regression models stratified by menopausal status and hormone therapy (HT) use. Results Among postmenopausal non-users of HT, higher BMI was significantly associated with an increased risk of less aggressive, i.e. ER+, PR+, HER2-, Ki67low, Bcl-2+ and p53- tumors (HR per 5 kg/m2: 1.44 [1.10, 1.90], p = 0.009), but not with risk of more aggressive tumor subtypes. Among postmenopausal users of HT, BMI was significantly inversely associated with less aggressive tumors (HR per 5 kg/m2: 0.68 [0.50, 0.94], p = 0.018). Finally, among pre- and perimenopausal women, Cox regression models did not reveal significant linear associations between BMI and risk of any tumor subtype, although analyses by BMI tertiles showed a significantly lower risk of less aggressive tumors for women in the highest tertile (HR: 0.55 [0.33, 0.93]). Conclusion Overall, our results suggest that obesity is related to risk of breast tumors with lower aggressiveness, a finding that requires replication in larger-scale analyses of pooled prospective data.

Abstract All isocitrate dehydrogenase (IDH) mutant solid neoplasms exhibit highly elevated levels of D-2-hydroxyglutarate (D-2HG). Detection of 2HG in tumor tissues currently is performed by gas or liquid chromatography-mass spectrometry (GC- or LC-MS) or biochemical detection. While these methods are highly accurate, a considerable amount of time for tissue preparation and a relatively high amount of tissue is required for testing. We here present a rapid approach to detect 2HG in brain tumor tissue based on matrix-assisted laser desorption ionization - time of flight mass spectrometry (MALDI-TOF). We analyzed 26 brain tumor samples with known IDH1 or IDH2 mutation and compared readouts to those from 28 brain tumor samples of wildtype IDH status. IDH mutant samples exhibited a clear positive signal for 2HG which was not observed in any of the IDH wildtype tumors. Our analytical pipeline allowed for 2HG detection in less than 5 min. Data were validated by determining 2HG levels in all tissues with a biochemical assay. In conclusion, we developed a protocol for rapid detection of 2HG levels and illustrate the possibility to use MALDI-TOF for the detection of metabolites on frozen tissue sections in a diagnostic setting.

Glycosylation is the most prevalent and varied form of post-translational protein modifications. Protein glycosylation regulates multiple cellular functions, including protein folding, cell adhesion, molecular trafficking and clearance, receptor activation, signal transduction, and endocytosis. In particular, membrane proteins are frequently highly glycosylated, which is both linked to physiological processes and of high relevance in various disease mechanisms. The cellular glycome is increasingly considered to be a therapeutic target. Here we describe a new strategy to compare membrane glycoproteomes, thereby identifying proteins with altered glycan structures and the respective glycosites. The workflow started with an optimized procedure for the digestion of membrane proteins followed by the lectin-based isolation of glycopeptides. Since alterations in the glycan part of a glycopeptide cause mass alterations, analytical size exclusion chromatography was applied to detect these mass shifts. N-glycosidase treatment combined with nanoUPLC-coupled mass spectrometry identified the altered glycoproteins and respective glycosites. The methodology was established using the colon cancer cell line CX1, which was treated with 2-deoxy-glucose—a modulator of N-glycosylation. The described methodology is not restricted to cell culture, as it can also be adapted to tissue samples or body fluids. Altogether, it is a useful module in various experimental settings that target glycan functions.

Abstract Background Aberrations in histone post-translational modifications (hPTMs) have been linked with various pathologies, including cancer, and could not only represent useful biomarkers but also suggest possible targetable epigenetic mechanisms. We have recently developed an approach, termed pathology tissue analysis of histones by mass spectrometry (PAT-H-MS), that allows performing a comprehensive and quantitative analysis of histone PTMs from formalin-fixed paraffin-embedded pathology samples. Despite its great potential, the application of this technique is limited by tissue heterogeneity. Methods In this study, we further implemented the PAT-H-MS approach by coupling it with techniques aimed at reducing sample heterogeneity and selecting specific portions or cell populations within the samples, such as manual macrodissection and laser microdissection (LMD). Results When applied to the analysis of a small set of breast cancer samples, LMD-PAT-H-MS allowed detecting more marked changes between luminal A-like and triple negative patients as compared with the classical approach. These changes included not only the already known H3 K27me3 and K9me3 marks, but also H3 K36me1, which was found increased in triple negative samples and validated on a larger cohort of patients, and could represent a potential novel marker distinguishing breast cancer subtypes. Conclusions These results show the feasibility of applying techniques to reduce sample heterogeneity, including laser microdissection, to the PAT-H-MS protocol, providing new tools in clinical epigenetics and opening new avenues for the comprehensive analysis of histone post-translational modifications in selected cell populations.

Background: Amplification of viral ribonucleic acid (RNA) by real-time reverse transcriptase polymerase chain reaction (rRT-PCR) is the gold standard to detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Since the initial outbreak, strategies to detect and isolate patients have been important to avoid uncontrolled viral spread. Although testing capacities have been upscaled, there is still a need for reliable high throughput test systems, specifically those that require alternative consumables. Therefore, we tested and compared two different methods for the detection of viral PCR products: rRT-PCR and mass spectrometry (MS). Methods: Viral RNA was isolated and amplified from oro- or nasopharyngeal swabs. A total of 22 samples that tested positive and 22 samples that tested negative for SARS-CoV-2 by rRT-PCR were analyzed by MS. Results of the rRT-PCR and the MS protocol were compared. Results: Results of rRT-PCR and the MS test system were in concordance in all samples. Time-to-results was faster for rRT-PCR. Hands-on-time was comparable in both assays. Conclusions: MS is a fast, reliable and cost-effective alternative for the detection of SARS-CoV-2 from oral and nasopharyngeal swabs.

Investigation of the molecular dynamics in lung cancer is crucial for the development of new treatment strategies. Fibroblast growth factor (FGF) 14 belongs to the FGF family, which might play a crucial role in cancer progression. We analyzed lung adenocarcinoma (LUAC) patients samples and found that FGF14 was downregulated, correlating with reduced survival and oncogenic mutation status. FGF14 overexpression in lung cancer cell lines resulted in decreased proliferation, colony formation, and migration, as well as increased expression of epithelial markers and a decreased expression of mesenchymal markers, indicating a mesenchymal to epithelial transition in vitro. We verified these findings using small interfering RNA against FGF14 and further confirmed the suppressive effect of FGF14 in a NOD.Cg-Prkdcscid Il2rgtm1Wjl/SzJ immunodeficient xenograft tumor model. Moreover, FGF14 overexpressing tumor cell RNA sequencing data suggests that genes affected by FGF14 were related to the extracellular matrix, playing a role in proliferation and migration. Notably, newly identified FGF14 target genes, adenosine deaminase RNA specific B1 (ADARB1), collagen and calcium-binding epidermal growth factor domain-containing protein 1 (CCBE1), α1 chain of collagen XI (COL11A1), and mucin 16 (MUC16) expression was negatively correlated with overall survival when FGF14 was downregulated in LUAC. These findings led us to suggest that FGF14 regulates proliferation and migration in LUAC.

The paracaspase Malt1 is a central regulator of antigen receptor signaling that is frequently mutated in human lymphoma. As a scaffold, it assembles protein complexes for NF-κB activation, and its proteolytic domain cleaves negative NF-κB regulators for signal enforcement. Still, the physiological functions of Malt1-protease are unknown. We demonstrate that targeted Malt1-paracaspase inactivation induces a lethal inflammatory syndrome with lymphocyte-dependent neurodegeneration in vivo. Paracaspase activity is essential for regulatory T cell (Treg) and innate-like B cell development, but it is largely dispensable for overcoming Malt1-dependent thresholds for lymphocyte activation. In addition to NF-κB inhibitors, Malt1 cleaves an entire set of mRNA stability regulators, including Roquin-1, Roquin-2, and Regnase-1, and paracaspase inactivation results in excessive interferon gamma (IFNγ) production by effector lymphocytes that drive pathology. Together, our results reveal distinct threshold and modulatory functions of Malt1 that differentially control lymphocyte differentiation and activation pathways and demonstrate that selective paracaspase blockage skews systemic immunity toward destructive autoinflammation.