TROP-2, NECTIN-4 and predictive biomarkers in sarcomatoid and rhabdoid bladder urothelial carcinoma.

Introduction: The surface protein TROP-2/TACSTD2 and the cell adhesion protein NECTIN-4/NECTIN4 are responsible for the efficacy of anticancer therapies based on antibody-drug conjugates (ADC) targeting intracellular microtubules. In contrast with common histologic subtypes of bladder urothelial carcinoma (BUC), little is known of TROP-2 and NECTIN-4 expression in sarcomatoid and rhabdoid BUC. Aims: In this study, we aimed to analyze TROP-2 and NECTIN-4 expression and additional predictive biomarkers by immunohistochemistry and fluorescence in situ hybridization (FISH) on 35 undifferentiated BUC (28 sarcomatoid and 7 rhabdoid). Wide genomic investigation was also performed on 411 BUC cases of the PanCancer Atlas, focusing on genes related to the microtubule pathways. Results: Seven of 35 (20%) undifferentiated BUC showed expression of TROP-2. NECTIN-4 was expressed in 10 cases (29%). Seven cases (20%) co-expressed TROP-2 and NECTIN-4. HER-2 FISH was amplified in 5 cases (14%) while HER-2 immunoexpression was observed in 14 cases (40%). PD-L1 scored positive for combined proportion score (CPS) in 66% of cases and for tumor proportion score (TPS) in 51% of cases. Pan-NTRK1-2/3 was elevated in 9 cases (26%) and FGFR-2/3 was broken in 7 of 35 cases (20%). Of 28 sarcomatoid BUC, 9 (32%) were negative for all (TROP-2, NECTIN-4, PD-L1, HER-2, FGFR and pan-NTRK) biomarkers and 3 (11%) expressed all five biomarkers. Among cases with rhabdoid dedifferentiation, 1 of 7 (14%) showed activation of all biomarkers, whereas 2 of 7 (28%) showed none. The mRNA analysis identified microtubule-related genes and pathways suitable for combined ADC treatments in BUC. Conclusion: Sarcomatoid and rhabdoid BUC do harbor positive expression of the ADC targets TROP-2 or NECTIN-4 in a relatively modest subset of cases, whereas the majority do not. Different combinations of other positive biomarkers may help the choice of medical therapies. Overall, these findings have important clinical implications for targeted therapy for BUC.

Comparing deep learning and pathologist quantification of cell-level PD-L1 expression in non-small cell lung cancer whole-slide images.

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

CD34+DNAM-1brightCXCR4+ haemopoietic precursors circulate after chemotherapy, seed lung tissue and generate functional innate-like T cells and NK cells.

Background: There is little information on the trajectory and developmental fate of Lin-CD34+DNAM-1bright CXCR4+ progenitors exiting bone marrow during systemic inflammation. Objective: To study Lin-CD34+DNAM-1bright CXCR4+ cell circulation in cancer patients, to characterize their entry into involved lung tissue and to characterize their progenies. Methods: Flow cytometric analysis of PBMC from 18 patients with lung cancer on samples collected immediately before the first and the second treatment was performed to study Lin-CD34+DNAM-1bright CXCR4+ precursors. Precursors were purified (>99%) and cultured in vitro from all patients. Paired PBMC and tissue samples from patients undergoing tumor resection were analyzed by flow cytometry to assess tissue entry and compare phenotype and developmental potential of Lin-CD34+DNAM-1bright CXCR4+ cells in both compartments. Results: Significant circulation of Lin-CD34+DNAM-1bright CXCR4+ precursors was observed 20d after the first treatment. Precursors express CXC3CR1, CXCR3, CXCR1 consistent with travel towards inflamed tissues. Flowcytometric analysis of lung tissue samples showed precursor presence in all patients in tumor and neighboring uninvolved areas. Successful purification and in vitro culture from both blood and lung tissue generates a minor proportion of maturing NK cells (<10%) and a predominant proportion (>85%) of α/ß T-progenies with innate-like phenotype expressing NKG2D,NKp30,DNAM-1. Innate-like maturing T-cells in vitro are cytotoxic, can be triggered via NKR/TCR co-stimulation and display broad spectrum Th1,Th2 and Th1/Th17 cytokine production. Conclusion: In advanced stage lung cancer CD34+DNAM-1brightCXCR4+ inflammatory precursors increase upon treatment, enter involved tissues, generate functional progenies and may thus represent an additional player contributing to immune balance in the highly SDF-1/CXCR4-biased pro-metastatic tumor microenvironment.

Pathological Complete Response to Pembrolizumab plus Axitinib Combination following Serious Immune-Related Adverse Events in an Advanced Renal Cell Carcinoma Patient with a History of Rheumatoid Arthritis.

Immune checkpoint inhibitors (ICIs)-based combinations have improved survival outcomes of advanced renal cell carcinoma (RCC) patients and are currently recommended as first-line treatment options. Rheumatoid arthritis (RA) is a systemic autoimmune disease (AD) of unknown etiology characterized by a chronic inflammatory process involving joints and extra-articular organs. Patients with AD are usually excluded from large randomized clinical trials investigating immunotherapeutic drugs. Therefore, little is known about clinical outcomes of patients with a history of RA treated with ICIs in real-world practice. In the present study, we report the clinical outcome of an advanced RCC patient with a history of RA treated with pembrolizumab in combination with axitinib. The patient experienced serious immune-related adverse events (irAEs) and achieved pathological complete response following only one ICI administration. Our case report shows that ICI-based combinations can be administered efficaciously in advanced RCC patients with a history of AD. However, a close monitoring of these patients is required, given the risk of irAEs and clinical exacerbations of symptoms associated with the preexisting AD. Moreover, prospective clinical data are needed to assess the hypothesis of a correlation between the onset of irAEs and AD flares and responses and survival outcomes to ICIs.

Evolving educational landscape in pathology: a comprehensive bibliometric and visual analysis including digital teaching and learning resources.

AIMS: Pathology education is a core component of medical training, and its literature is critical for refining educational modalities. We performed a cross-sectional bibliometric analysis to explore publications on pathology education, focusing on new medical education technologies. METHODS: The analysis identified 64 pathology journals and 53 keywords. Relevant articles were collected using a web application, PaperScraper, developed to accelerate literature search. Citation data were collected from multiple sources. Descriptive statistics, with time period analysis, were performed using Microsoft Excel and visualised with Flourish Studio. Two article groups were further investigated with a bibliometric software, VOSViewer, to establish co-authorship and keyword relationships. RESULTS: 8946 citations were retrieved from 905 selected articles. Most articles were published in the last decade (447, 49.4%). The top journals were Archives of Pathology & Laboratory Medicine (184), Human Pathology (122) and the American Journal of Clinical Pathology (117). The highest number of citations was found for Human Pathology (2120), followed by Archives of Pathology & Laboratory Medicine (2098) and American Journal of Clinical Pathology (1142). Authors with different backgrounds had the greatest number of articles and citations. 12 co-authorship, 3 keyword and 8 co-citation clusters were found for the social media/online resources group, 8 co-authorship, 4 keyword and 7 co-citation clusters for the digital pathology/virtual microscopy/mobile technologies group. CONCLUSIONS: The analysis revealed a significant increase in publications over time. The emergence of digital teaching and learning resources played a major role in this growth. Overall, these findings underscore the transformative potential of technology in pathology education.

Perspective of a Pathologist on Benchmark Strategies for Artificial Intelligence Development in Organ Transplantation.

Transplant pathology of donors is a highly specialized field comprising both the evaluation of organ donor biopsy for the oncological risk transmission and to guide the organ allocation. Timing is critical in transplant procurement since organs must be recovered as soon as possible to ensure the best possible outcome for the recipient. To all this is added the fact that the evaluation of a donor causes difficulties in many cases and the impact of these assessments is paramount, considering the possible recovery of organs that would have been erroneously discarded or, conversely, the possibly correct discarding of donors with unacceptable risk profiles. In transplant pathology histology is still the gold standard for diagnosis dictating the subsequent decisions and course of clinical care. Digital pathology has played an important role in accelerating healthcare progression and nowadays artificial intelligence powered computational pathology can effectively improve diagnostic needs, supporting the quality and safety of the process. Mapping the shape of the journey would suggest a progressive approach from supervised to semi/unsupervised models, which would involve training these models directly for clinical endpoints. In machine learning, this generally delivers better performance, compensating for a potential lack in interpretability. With planning and enough confidence in the performance of learning-based methods from digital pathology and artificial intelligence, there is great potential to augment the diagnostic quality and correlation with clinical endpoints. This may improve the donor pool and vastly reduce diagnostic and prognostic errors that are known but currently are unavoidable in transplant donor pathology.

Cutting-edge technology and automation in the pathology laboratory.

One of the goals of pathology is to standardize laboratory practices to increase the precision and effectiveness of diagnostic testing, which will ultimately enhance patient care and results. Standardization is crucial in the domains of tissue processing, analysis, and reporting. To enhance diagnostic testing, innovative technologies are also being created and put into use. Furthermore, although problems like algorithm training and data privacy issues still need to be resolved, digital pathology and artificial intelligence are emerging in a structured manner. Overall, for the field of pathology to advance and for patient care to be improved, standard laboratory practices and innovative technologies must be adopted. In this paper, we describe the state-of-the-art of automation in pathology laboratories in order to lead technological progress and evolution. By anticipating laboratory needs and demands, the aim is to inspire innovation tools and processes as positively transformative support for operators, organizations, and patients.

mTOR eosinophilic renal cell carcinoma: a distinctive tumor characterized by mTOR mutation, loss of chromosome 1, cathepsin-K expression, and response to target therapy.

In the spectrum of oncocytic renal neoplasms, a subset of tumors with high-grade-appearing histologic features harboring pathogenic mutations in mammalian target of rapamycin (mTOR) and hitherto clinical indolent behavior has been described. Three cases (2F,1 M) with histologically documented metastases (lymph node, skull, and liver) were retrieved and extensively investigated by immunohistochemistry, FISH, and next-generation sequencing. Tumors were composed of eosinophilic cells with prominent nucleoli (G3 by ISUP/WHO) arranged in solid to nested architecture. Additionally, there were larger cells with perinuclear cytoplasmic shrinkage and sparse basophilic Nissl-like granules, superficially resembling the so-called spider cells of cardiac rhabdomyomas. The renal tumors, including the skull and liver metastases, showed immunoexpression PAX8, CK8-18, and cathepsin-K, and negativity for vimentin. NGS identified mTOR genetic alterations in the three cases, including the skull and liver metastases. One patient was then treated with Everolimus (mTOR inhibitors) with clinical response (metastatic tumor shrinkage). We present a distinct renal tumor characterized by high-grade eosinophilic cells, cathepsin-K immunohistochemical expression, and harboring mTOR gene mutations demonstrating a malignant potential and showing responsiveness to mTOR inhibitors.

PROACTING: predicting pathological complete response to neoadjuvant chemotherapy in breast cancer from routine diagnostic histopathology biopsies with deep learning.

BACKGROUND: Invasive breast cancer patients are increasingly being treated with neoadjuvant chemotherapy; however, only a fraction of the patients respond to it completely. To prevent overtreatment, there is an urgent need for biomarkers to predict treatment response before administering the therapy. METHODS: In this retrospective study, we developed hypothesis-driven interpretable biomarkers based on deep learning, to predict the pathological complete response (pCR, i.e., the absence of tumor cells in the surgical resection specimens) to neoadjuvant chemotherapy solely using digital pathology H&E images of pre-treatment breast biopsies. Our approach consists of two steps: First, we use deep learning to characterize aspects of the tumor micro-environment by detecting mitoses and segmenting tissue into several morphology compartments including tumor, lymphocytes and stroma. Second, we derive computational biomarkers from the segmentation and detection output to encode slide-level relationships of components of the tumor microenvironment, such as tumor and mitoses, stroma, and tumor infiltrating lymphocytes (TILs). RESULTS: We developed and evaluated our method on slides from n = 721 patients from three European medical centers with triple-negative and Luminal B breast cancers and performed external independent validation on n = 126 patients from a public dataset. We report the predictive value of the investigated biomarkers for predicting pCR with areas under the receiver operating characteristic curve between 0.66 and 0.88 across the tested cohorts. CONCLUSION: The proposed computational biomarkers predict pCR, but will require more evaluation and finetuning for clinical application. Our results further corroborate the potential role of deep learning to automate TILs quantification, and their predictive value in breast cancer neoadjuvant treatment planning, along with automated mitoses quantification. We made our method publicly available to extract segmentation-based biomarkers for research purposes.

Delphi expert consensus for whole slide imaging in thyroid cytopathology.

OBJECTIVE: Despite an increase in thyroid fine needle aspiration (FNA) and advances in whole slide imaging (WSI) adoption, digital pathology is still considered inadequate for primary diagnosis of these cases. Herein, we aim to validate the utility of WSI in thyroid FNAs employing the Delphi method strategy. METHODS: A panel of experts from seven reference cytology centres was recruited. The study consisted of two consecutive rounds: (1) an open-ended, free-response questionnaire generating a list of survey items; and (2) a consensus analysis of 80 selected shared WSIs from 80 cases by six investigators answering six morphological questions utilising a 1 to 5 Likert scale. RESULTS: High consensus was achieved for all parameters, with an overall average score of 4.27. The broad majority of items (84%) were ranked either 4 or 5 by each physician. Two badly scanned cases were responsible for more than half of the low-ranked (≤2) values (57%). Good to excellent (≥3) diagnostic confidence was reached in more than 95.2% of cases. For most cases (78%) WSI assessment was not limited by technical issues linked to the image acquisition process. CONCLUSION: This systematic Delphi study indicates broad consensus among participating physicians on the application of DP to thyroid cytopathology, supporting expert opinion that WSI is reliable and safe for primary diagnostic purposes.

Cost analysis of archives in the pathology laboratories: from safety to management.

CONTEXT: Despite the reluctance to invest and the challenging estimation of necessary supporting costs, optimising the archives seems to be one of the hottest topics in the future management of the pathology laboratories. Historically, archives were only partially designed to securely store and organise tissue specimens, and tracking systems were often flawed, posing significant risks to patients' health and legal ramifications for pathologists. OBJECTIVE: The current review explores the available data from the literature on archives' management in pathology, including comprehensive business plans, structure setup, outfit, inventories, ongoing conservation and functional charges. DATA SOURCES: Electronic searches in PubMed-MEDLINE and Embase were made to extract pertinent articles from the literature. Works about the archiving process and storage were included and analysed to extract information. Prepublication servers were ignored. Italian Institutional Regional databases for public competitive bidding processes were queried too. CONCLUSIONS: A new emergent feeling in the pathology laboratory is growing for archives management; the digital pathology era is a great opportunity to apply innovation to tracking systems and samples preservation. The main aim is a critical evaluation of the return of investment in developing automatic and tracked archiving processes for improving not only quality, efficacy and efficiency of the labs but also patients' healthcare.

Analysis of the mechanisms regulating soluble PD-1 production and function in human NK cells.

NK cells represent important effectors that play a major role in innate defences against pathogens and display potent cytolytic activity against tumor cells. An array of surface receptors finely regulate their function and inhibitory checkpoints, such as PD-1, can dampen the immune response inducing an immunosuppressive state. Indeed, PD-1 expression in human NK cells correlated with impaired effector function and tumor immune evasion. Importantly, blockade of the PD-1/PD-L1 axis has been shown to reverse NK cell exhaustion and increase their cytotoxicity. Recently, soluble counterparts of checkpoint receptors, such as soluble PD-1 (sPD-1), are rising high interest due to their biological activity and ability to modulate immune responses. It has been widely demonstrated that sPD-1 can modulate T cell effector functions and tumor growth. Tumor-infiltrating T cells are considered the main source of circulating sPD-1. In addition, recently, also stimulated macrophages have been demonstrated to release sPD-1. However, no data are present on the role of sPD-1 in the context of other innate immune cell subsets and therefore this study is aimed to unveil the effect of sPD-1 on human NK cell function. We produced the recombinant sPD-1 protein and demonstrated that it binds PD-L1 and that its presence results in increased NK cell cytotoxicity. Notably, we also identified a pathway regulating endogenous sPD-1 synthesis and release in human NK cells. Secreted endogenous sPD-1, retained its biological function and could modulate NK cell effector function. Overall, these data reveal a pivotal role of sPD-1 in regulating NK-mediated innate immune responses.

The roles of different forms of IL-15 in human melanoma progression.

Background: Melanoma is a lethal skin cancer, and the risk of developing it is increased by exposure to ultraviolet (UV) radiation. The production of cytokines such as interleukin-15 (IL-15), induced by the exposure of skin cells to UV rays, could also promote melanoma development. The aim of this study is to investigate the possible role of Interleukin-15/Interleukin-15 Receptor α (IL-15/IL-15Rα) complexes in melanoma development. Methods: The expression of IL-15/IL-15Rα complexes by melanoma cells was evaluated both ex vivo and in vitro by tissue microarray, PCR, and flow cytometry. The presence of the soluble complex (sIL-15/IL-15Rα) in the plasma of metastatic melanoma patients was detected using an ELISA assay. Subsequently, we investigated the impact of natural killer (NK) cell activation after rIL-2 starvation followed by exposure to the sIL-15/IL-15Rα complex. Finally, by analyzing public datasets, we studied the correlation between IL-15 and IL-15Rα expressions and melanoma stage, NK and T-cell markers, and overall survival (OS). Results: Analysis of a melanoma tissue microarray shows a significant increase in the number of IL-15+ tumor cells from the benign nevi to metastatic melanoma stages. Metastatic melanoma cell lines express a phorbol-12-myristate-13-acetate (PMA)-cleavable membrane-bound IL-15 (mbIL-15), whereas cultures from primary melanomas express a PMA-resistant isoform. Further analysis revealed that 26% of metastatic patients present with consistently high plasmatic levels of sIL-15/IL-15Rα. When the recombinant soluble human IL-15/IL-15Rα complex is added to briefly starved rIL-2-expanded NK cells, these cells exhibit strongly reduced proliferation and levels of cytotoxic activity against K-562 and NALM-18 target cells. The analysis of public gene expression datasets revealed that high IL-15 and IL-15Rα intra-tumoral production correlates with the high levels of expression of CD5+ and NKp46+ (T and NK markers) and significantly correlates with a better OS in stages II and III, but not in stage IV. Conclusions: Membrane-bound and secreted IL-15/IL-15Rα complexes are continuously present during progression in melanoma. It is notable that, although IL-15/IL-15Rα initially promoted the production of cytotoxic T and NK cells, at stage IV promotion of the development of anergic and dysfunctional cytotoxic NK cells was observed. In a subgroup of melanoma metastatic patients, the continuous secretion of high amounts of the soluble complex could represent a novel NK cell immune escape mechanism.

Artificial intelligence-based tools applied to pathological diagnosis of microbiological diseases.

Infectious diseases still threaten the global community, especially in resource-limited countries. An accurate diagnosis is paramount to proper patient and public health management. Identification of many microbes still relies on manual microscopic examination, a time-consuming process requiring skilled staff. Thus, artificial intelligence (AI) has been exploited for identification of microorganisms. A systematic search was carried out using electronic databases looking for studies dealing with the application of AI to pathology microbiology specimens. Of 4596 retrieved articles, 110 were included. The main applications of AI regarded malaria (54 studies), bacteria (28), nematodes (14), and other protozoa (11). Most publications examined cytological material (95, 86%), mainly analyzing images acquired through microscope cameras (65, 59%) or coupled with smartphones (16, 15%). Various deep-learning strategies were used for the analysis of digital images, achieving highly satisfactory results. The published evidence suggests that AI can be reliably utilized for assisting pathologists in the detection of microorganisms. Further technologic improvement and availability of datasets for training AI-based algorithms would help expand this field and widen its adoption, especially for developing countries.

Effect of Radio-Chemotherapy on PD-L1 Immunohistochemical Expression in Head and Neck Squamous Cell Carcinoma.

BACKGROUND: Programmed death-ligand 1 (PD-L1) checkpoint inhibitors represent a mainstay of therapy in head and neck squamous cell cancer (HNSCC). However, little is known about the influence of combined therapy on PD-L1 expression. The study aims to gather evidence on this topic. METHODS: A systematic search was carried out in electronic databases Pubmed-MEDLINE and Embase to retrieve studies on the comparison of PD-L1 expression before and after conventional therapy. Data were extracted and a quantitative analysis with pooled odds ratios (ORs) was performed when applicable. RESULTS: Of 5688 items, 15 were finally included. Only a minority of studies assessed PD-L1 with the recommended combined positive score (CPS). The results are highly heterogeneous, with some studies reporting an increase in PD-L1 expression and others reporting a decrease. Three studies allowed for quantitative analysis and showed a pooled OR of 0.49 (CI 0.27-0.90). CONCLUSIONS: From the present evidence, a clear conclusion towards an increase or decrease in PD-L1 expression after combined therapy cannot be drawn, but even with few studies available, a trend towards an increase in expression in tumor cells at a cutoff of 1% can be noted in patients undergoing platinum-based therapy. Future studies will provide more robust data on the effect of combined therapy on PD-L1 expression.

Different effects of NK cells and NK-derived soluble factors on cell lines derived from primary or metastatic pancreatic cancers.

Natural killer (NK) cells are cytotoxic lymphoid cells that play a key role in defenses against tumors. However, their function may be severely impaired in patients with pancreatic adenocarcinoma (PA). Indeed, PA cells release soluble factors, thereby generating an immunosuppressive environment that dysregulates NK-cell cytolytic function and favors tumor immune evasion. Here, we analyzed the interactions between NK and PA cells using the PANC-1 and CAPAN-1 cell lines derived from a ductal PA and metastatic lesion, respectively. Metastatic and nonmetastatic cell lines were both able to impair NK cytolytic activity. An analysis of the effect of NK cells and NK-cell-derived exosomes revealed substantial differences between the two cell lines. Thus, NK cells displayed higher cytotoxicity against nonmetastatic PA cells than metastatic PA cells in both 2D cultures and in a 3D extracellular matrix cell system. In addition, NK-derived exosomes could penetrate only PANC-1 spheroids and induce cell killing. Remarkably, when PANC-1 cells were exposed to NK-derived soluble factors, they displayed substantial changes in the expression of genes involved in epithelial-to-mesenchymal transition (EMT) and acquired resistance to NK-mediated cytolysis. These results, together with their correlation with poor clinical outcomes in PA patients, suggest that the induction of resistance to cytolysis upon exposure to NK-derived soluble factors could reflect the occurrence of EMT in tumor cells. Our data indicate that a deeper investigation of the interaction between NK cells and tumor cells may be crucial for immunotherapy, possibly improving the outcome of PA treatment by targeting critical steps of NK-tumor cell crosstalk.

Natural Language Processing to extract SNOMED-CT codes from pathological reports.

Objective: The use of standardized structured reports (SSR) and suitable terminologies like SNOMED-CT can enhance data retrieval and analysis, fostering large-scale studies and collaboration. However, the still large prevalence of narrative reports in our laboratories warrants alternative and automated labeling approaches. In this project, natural language processing (NLP) methods were used to associate SNOMED-CT codes to structured and unstructured reports from an Italian Digital Pathology Department. Methods: Two NLP-based automatic coding systems (support vector machine, SVM, and long-short term memory, LSTM) were trained and applied to a series of narrative reports. Results: The 1163 cases were tested with both algorithms, showing good performances in terms of accuracy, precision, recall, and F1 score, with SVM showing slightly better performances as compared to LSTM (0.84, 0.87, 0.83, 0.82 vs 0.83, 0.85, 0.83, 0.82, respectively). The integration of an explainability allowed identification of terms and groups of words of importance, enabling fine-tuning, balancing semantic meaning and model performance. Conclusions: AI tools allow the automatic SNOMED-CT labeling of the pathology archives, providing a retrospective fix to the large lack of organization of narrative reports.

Immunotherapy targeting inhibitory checkpoints: The role of NK and other innate lymphoid cells.

Monoclonal antibodies that target specific ligand-receptor signaling pathways and act as immune checkpoint inhibitors have been designed to remove the brakes in T cells and restore strong and long-term antitumor-immunity. Of note, many of these inhibitory receptors are also expressed by Innate Lymphoid Cells (ILCs), suggesting that also blockade of inhibitory pathways in innate lymphocytes has a role in the response to the treatment with checkpoint inhibitors. ILCs comprise cytotoxic NK cells and "helper" subsets and are important cellular components in the tumor microenvironment. In addition to killing tumor cells, ILCs release inflammatory cytokines, thus contributing to shape adaptive cell activation in the context of immunotherapy. Therefore, ILCs play both a direct and indirect role in the response to checkpoint blockade. Understanding the impact of ILC-mediated response on the treatment outcome would contribute to enhance immunotherapy efficacy, as still numerous patients resist or relapse.

Comparison of three validated PD-L1 immunohistochemical assays in urothelial carcinoma of the bladder: interchangeability and issues related to patient selection.

Different programmed cell death-ligand 1 (PD-L1) assays and scoring algorithms are being used in the evaluation of PD-L1 expression for the selection of patients for immunotherapy in specific settings of advanced urothelial carcinoma (UC). In this paper, we sought to investigate three approved assays (Ventana SP142 and SP263, and Dako 22C3) in UC with emphasis on implications for patient selection for atezolizumab/pembrolizumab as the first line of treatment. Tumors from 124 patients with invasive UC of the bladder were analyzed using tissue microarrays (TMA). Serial sections were stained with SP263 and SP142 on Ventana Benchmark Ultra and with 22C3 on Dako Autostainer Link 48. Stains were evaluated independently by two observers and scored using the combined positive score (CPS) and tumor infiltrating immune cells (IC) algorithms. Differences in proportions (DP), overall percent agreement (OPA), positive percent agreement (PPA), negative percent agreement (NPA), and Cohen κ were calculated for all comparable cases. Good overall concordance in analytic performance was observed for 22C3 and SP263 with both scoring algorithms; specifically, the highest OPA was observed between 22C3 and SP263 (89.6%) when using CPS. On the other hand, SP142 consistently showed lower positivity rates with high differences in proportions (DP) compared with 22C3 and SP263 with both CPS and IC, and with a low PPA, especially when using the CPS algorithm. In conclusion, 22C3 and SP263 assays show comparable analytical performance while SP142 shows divergent staining results, with important implications for the selection of patients for both pembrolizumab and atezolizumab.

Atlas of PD-L1 for Pathologists: Indications, Scores, Diagnostic Platforms and Reporting Systems.

BACKGROUND: Innovative drugs targeting the PD1/PD-L1 axis have opened promising scenarios in modern cancer therapy. Plenty of assays and scoring systems have been developed for the evaluation of PD-L1 immunohistochemical expression, so far considered the most reliable therapeutic predictive marker. METHODS: By gathering the opinion of acknowledged experts in dedicated fields of pathology, we sought to update the currently available evidence on PD-L1 assessment in various types of tumors. RESULTS: Robust data were progressively collected for several anatomic districts and leading international agencies to approve specific protocols: among these, TPS with 22C3, SP142 and SP263 clones in lung cancer; IC with SP142 antibody in breast, lung and urothelial tumors; and CPS with 22C3/SP263 assays in head and neck and urothelial carcinomas. On the other hand, for other malignancies, such as gastroenteric neoplasms, immunotherapy has been only recently introduced, often for particular histotypes, so specific guidelines are still lacking. CONCLUSIONS: PD-L1 immunohistochemical scoring is currently the basis for allowing many cancer patients to receive properly targeted therapies. While protocols supported by proven data are already available for many tumors, dedicated studies and clinical trials focusing on harmonization of the topic in other still only partially explored fields are surely yet advisable.