Journal of Pathology Clinical Research最新文献

{"title":"Recurrent and novel fusions detected by targeted RNA sequencing as part of the diagnostic workflow of soft tissue and bone tumours","authors":"Rafael Zago Baltazar,&nbsp;Sofie Claerhout,&nbsp;Sara Vander Borght,&nbsp;Lien Spans,&nbsp;Raphael Sciot,&nbsp;Patrick Schöffski,&nbsp;Daphne Hompes,&nbsp;Friedl Sinnaeve,&nbsp;Hazem Wafa,&nbsp;Marleen Renard,&nbsp;Mari FCM van den Hout,&nbsp;Astrid Vernemmen,&nbsp;Louis Libbrecht,&nbsp;An-Katrien De Roo,&nbsp;Filomena Mazzeo,&nbsp;Cédric van Marcke,&nbsp;Karen Deraedt,&nbsp;Claire Bourgain,&nbsp;Isabelle Vanden Bempt","doi":"10.1002/2056-4538.12376","DOIUrl":"10.1002/2056-4538.12376","url":null,"abstract":"<p>The identification of gene fusions has become an integral part of soft tissue and bone tumour diagnosis. We investigated the added value of targeted RNA-based sequencing (targeted RNA-seq, Archer FusionPlex) to our current molecular diagnostic workflow of these tumours, which is based on fluorescence <i>in situ</i> hybridisation (FISH) for the detection of gene fusions using 25 probes. In a series of 131 diagnostic samples targeted RNA-seq identified a gene fusion, <i>BCOR</i> internal tandem duplication or <i>ALK</i> deletion in 47 cases (35.9%). For 74 cases, encompassing 137 FISH analyses, concordance between FISH and targeted RNA-seq was evaluated. A positive or negative FISH result was confirmed by targeted RNA-seq in 27 out of 49 (55.1%) and 81 out of 88 (92.0%) analyses, respectively. While negative concordance was high, targeted RNA-seq identified a canonical gene fusion in seven cases despite a negative FISH result. The 22 discordant FISH-positive analyses showed a lower percentage of rearrangement-positive nuclei (range 15–41%) compared to the concordant FISH-positive analyses (&gt;41% of nuclei in 88.9% of cases). Six FISH analyses (in four cases) were finally considered false positive based on histological and targeted RNA-seq findings. For the <i>EWSR1</i> FISH probe, we observed a gene-dependent disparity (<i>p</i> = 0.0020), with 8 out of 35 cases showing a discordance between FISH and targeted RNA-seq (22.9%). This study demonstrates an added value of targeted RNA-seq to our current diagnostic workflow of soft tissue and bone tumours in 19 out of 131 cases (14.5%), which we categorised as altered diagnosis (3 cases), added precision (6 cases), or augmented spectrum (10 cases). In the latter subgroup, four novel fusion transcripts were found for which the clinical relevance remains unclear: <i>NAB2::NCOA2</i>, <i>YAP1::NUTM2B</i>, <i>HSPA8::BRAF</i>, and <i>PDE2A::PLAG1</i>. Overall, targeted RNA-seq has proven extremely valuable in the diagnostic workflow of soft tissue and bone tumours.</p>","PeriodicalId":48612,"journal":{"name":"Journal of Pathology Clinical Research","volume":"10 3","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/2056-4538.12376","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140913232","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comprehensive genomic profiling of pulmonary spindle cell carcinoma using tissue and plasma samples: insights from a real-world cohort analysis","authors":"Yi Sun,&nbsp;Shilei Qin,&nbsp;Song Wang,&nbsp;Jiaohui Pang,&nbsp;Qiuxiang Ou,&nbsp;Weiquan Liang,&nbsp;Hai Zhong","doi":"10.1002/2056-4538.12375","DOIUrl":"https://doi.org/10.1002/2056-4538.12375","url":null,"abstract":"<p>Pulmonary spindle cell carcinoma (PSCC) is a rare and aggressive non-small cell lung cancer (NSCLC) subtype with a dismal prognosis. The molecular characteristics of PSCC are largely unknown due to its rarity, which limits the diagnosis and treatment of this historically poorly characterized malignancy. We present comprehensive genomic profiling results of baseline tumor samples from 22 patients histologically diagnosed with PSCC, representing the largest cohort to date. Somatic genetic variant detection was compared between paired plasma samples and primary tumors from 13 patients within our cohort. The associations among genomic features, treatment, and prognosis were also analyzed in representative patient cases. <i>TP53</i> (54.5%), <i>TERT</i> (36.4%), <i>CDKN2A</i> (27.3%), and <i>MET</i> (22.7%) were most frequently mutated. Notably, 81.8% of patients had actionable targets in their baseline tumors, including <i>MET</i> (22.7%), <i>ERBB2</i> (13.6%), <i>EGFR</i> (9.1%), <i>KRAS</i> (9.1%), <i>ALK</i> (9.1%), and <i>ROS1</i> (4.5%). The median tumor mutation burden (TMB) for PSCC tumors was 5.5 mutations per megabase (muts/Mb). TMB-high tumors (&gt;10 muts/Mb) exhibited a significantly higher mutation frequency in genes such as <i>KRAS</i>, <i>ARID2</i>, <i>FOXL2</i>, and <i>LRP1B</i>, as well as within the DNA mismatch repair pathway. The detection rates for single nucleotide variants and structural variants were comparable between matched tumor and plasma samples, with 48.6% of genetic variants being mutually identified in both sample types. Additionally, a patient with a high mutation load and positive PD-L1 expression demonstrated a 7-month survival benefit from chemoimmunotherapy. Furthermore, a patient with an <i>ALK</i>-rearranged tumor achieved a remarkable 3-year progression-free survival following crizotinib treatment. Overall, our findings deepen the understanding of the complex genomic landscape of PSCC, revealing actionable targets amenable to tailored treatment of this poorly characterized malignancy.</p>","PeriodicalId":48612,"journal":{"name":"Journal of Pathology Clinical Research","volume":"10 3","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/2056-4538.12375","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140641929","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Histopathological tumour microenvironment score independently predicts outcome in primary operable colorectal cancer","authors":"Phimmada Hatthakarnkul,&nbsp;Kathryn Pennel,&nbsp;Peter Alexander,&nbsp;Hester van Wyk,&nbsp;Antonia Roseweir,&nbsp;Jitwadee Inthagard,&nbsp;Jennifer Hay,&nbsp;Ditte Andersen,&nbsp;Noori Maka,&nbsp;James Park,&nbsp;Campbell Roxburgh,&nbsp;Chanitra Thuwajit,&nbsp;Donald McMillan,&nbsp;Joanne Edwards","doi":"10.1002/2056-4538.12374","DOIUrl":"https://doi.org/10.1002/2056-4538.12374","url":null,"abstract":"<p>Colorectal cancer (CRC) is a heterogenous malignancy and research is focused on identifying novel ways to subtype patients. In this study, a novel classification system, tumour microenvironment score (TMS), was devised based on Klintrup–Mäkinen grade (KMG), tumour stroma percentage (TSP), and tumour budding. TMS was performed using a haematoxylin and eosin (H&amp;E)-stained section from retrospective CRC discovery and validation cohorts (<i>n</i> = 1,030, <i>n</i> = 787). TMS0 patients had high KMG, TMS1 were low for KMG, TSP, and budding, TMS2 were high for budding, or TSP and TMS3 were high for TSP and budding. Scores were assessed for association with survival and clinicopathological characteristics. Mutational landscaping and Templated Oligo-Sequencing (TempO-Seq) profiling were performed to establish differences in the underlying biology of TMS. TMS was independently prognostic in both cohorts (<i>p</i> &lt; 0.001, <i>p</i> &lt; 0.001), with TMS3 predictive of the shortest survival times. TMS3 was associated with adverse clinical features including sidedness, local and distant recurrence, higher T stage, higher N stage, and presence of margin involvement. Gene set enrichment analysis of TempO-Seq data showed higher expression of genes associated with hallmarks of cancer pathways including epithelial to mesenchymal transition (<i>p</i> &lt; 0.001), IL2 STAT5 signalling (<i>p</i> = 0.007), and angiogenesis (<i>p</i> = 0.017) in TMS3. Additionally, enrichment of immunosuppressive immune signatures was associated with TMS3 classification. In conclusion, TMS represents a novel and clinically relevant method for subtyping CRC patients from a single H&amp;E-stained tumour section.</p>","PeriodicalId":48612,"journal":{"name":"Journal of Pathology Clinical Research","volume":"10 3","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/2056-4538.12374","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140633751","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Contribution of tumour and immune cells to PD-L1 expression as a predictive biomarker in metastatic triple-negative breast cancer: exploratory analysis from KEYNOTE-119","authors":"Javier Cortes,&nbsp;Eric P Winer,&nbsp;Oleg Lipatov,&nbsp;Seock-Ah Im,&nbsp;Anthony Gonçalves,&nbsp;Eva Muñoz-Couselo,&nbsp;Keun Seok Lee,&nbsp;Peter Schmid,&nbsp;Kenji Tamura,&nbsp;Laura Testa,&nbsp;Isabell Witzel,&nbsp;Shoichiro Ohtani,&nbsp;Stephanie Hund,&nbsp;Karina Kulangara,&nbsp;Vassiliki Karantza,&nbsp;Jaime A Mejia,&nbsp;Junshui Ma,&nbsp;Petar Jelinic,&nbsp;Lingkang Huang,&nbsp;Scott K Pruitt,&nbsp;Kenneth Emancipator","doi":"10.1002/2056-4538.12371","DOIUrl":"https://doi.org/10.1002/2056-4538.12371","url":null,"abstract":"<p>The efficacy of pembrolizumab monotherapy versus chemotherapy increased with increasing programmed death ligand 1 (PD-L1) expression, as quantified by combined positive score (CPS; PD-L1 expression on both tumour cells and immune cells) in patients with previously treated metastatic triple-negative breast cancer (mTNBC) in the phase 3 KEYNOTE-119 study. This exploratory analysis was conducted to determine whether the expression of PD-L1 on tumour cells contributes to the predictive value of PD-L1 CPS in mTNBC. PD-L1 expression in tumour samples was assessed using PD-L1 IHC 22C3 pharmDx and quantified using both CPS and tumour proportion score (TPS; PD-L1 expression on tumour cells alone). Calculated immune cell density (CID) was defined as CPS minus TPS. The ability of each scoring method (CPS, TPS, and CID) to predict clinical outcomes with pembrolizumab was evaluated. With pembrolizumab, the area under the receiver operating characteristic curve was 0.69 (95% CI = 0.58–0.80) for CPS, 0.55 (95% CI = 0.46–0.64) for TPS, and 0.67 (95% CI = 0.56–0.77) for CID. After correction for cutoff prevalence, CPS performed as well as, if not better than, CID with respect to predicting objective response rate, progression-free survival, and overall survival. Data from this exploratory analysis suggest that, although PD-L1 expression on immune cells alone is predictive of response to programmed death 1 blockade in mTNBC, adding tumour PD-L1 expression assessment (i.e. CPS, which combines immune cell and tumour cell PD-L1 expression) may improve prediction. PD-L1 CPS thus remains an effective and broadly applicable uniform scoring system for enriching response to programmed death 1 blockade with pembrolizumab in mTNBC as well as other tumour types.</p>","PeriodicalId":48612,"journal":{"name":"Journal of Pathology Clinical Research","volume":"10 3","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/2056-4538.12371","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140559502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction of immunochemotherapy response for diffuse large B-cell lymphoma using artificial intelligence digital pathology","authors":"Jeong Hoon Lee,&nbsp;Ga-Young Song,&nbsp;Jonghyun Lee,&nbsp;Sae-Ryung Kang,&nbsp;Kyoung Min Moon,&nbsp;Yoo-Duk Choi,&nbsp;Jeanne Shen,&nbsp;Myung-Giun Noh,&nbsp;Deok-Hwan Yang","doi":"10.1002/2056-4538.12370","DOIUrl":"https://doi.org/10.1002/2056-4538.12370","url":null,"abstract":"<p>Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous and prevalent subtype of aggressive non-Hodgkin lymphoma that poses diagnostic and prognostic challenges, particularly in predicting drug responsiveness. In this study, we used digital pathology and deep learning to predict responses to immunochemotherapy in patients with DLBCL. We retrospectively collected 251 slide images from 216 DLBCL patients treated with rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP), with their immunochemotherapy response labels. The digital pathology images were processed using contrastive learning for feature extraction. A multi-modal prediction model was developed by integrating clinical data and pathology image features. Knowledge distillation was employed to mitigate overfitting on gigapixel histopathology images to create a model that predicts responses based solely on pathology images. Based on the importance derived from the attention mechanism of the model, we extracted histological features that were considered key textures associated with drug responsiveness. The multi-modal prediction model achieved an impressive area under the ROC curve of 0.856, demonstrating significant associations with clinical variables such as Ann Arbor stage, International Prognostic Index, and bulky disease. Survival analyses indicated their effectiveness in predicting relapse-free survival. External validation using TCGA datasets supported the model's ability to predict survival differences. Additionally, pathology-based predictions show promise as independent prognostic indicators. Histopathological analysis identified centroblastic and immunoblastic features to be associated with treatment response, aligning with previous morphological classifications and highlighting the objectivity and reproducibility of artificial intelligence-based diagnosis. This study introduces a novel approach that combines digital pathology and clinical data to predict the response to immunochemotherapy in patients with DLBCL. This model shows great promise as a diagnostic and prognostic tool for clinical management of DLBCL. Further research and genomic data integration hold the potential to enhance its impact on clinical practice, ultimately improving patient outcomes.</p>","PeriodicalId":48612,"journal":{"name":"Journal of Pathology Clinical Research","volume":"10 3","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/2056-4538.12370","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140537528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diagnosing adult and pediatric extrapulmonary tuberculosis by MPT64 antigen detection with immunohistochemistry and immunocytochemistry using reproduced polyclonal antibodies","authors":"Ole Magnus Bjørgaas Helle,&nbsp;Mala Kanthali,&nbsp;Sheeba Ishtiaq,&nbsp;Atiqa Ambreen,&nbsp;Manju Raj Purohit,&nbsp;Tehmina Mustafa","doi":"10.1002/2056-4538.12373","DOIUrl":"https://doi.org/10.1002/2056-4538.12373","url":null,"abstract":"<p>Diagnosing extrapulmonary tuberculosis (EPTB) is challenging. Immunohistochemistry or immunocytochemistry has been used to diagnose tuberculosis (TB) by detection of MPT64 antigen from various extrapulmonary specimens and has shown good diagnostic performance in our previous studies. The test can distinguish between disease caused by <i>Mycobacterium tuberculosis</i> (Mtb) complex and nontuberculous mycobacteria and can be applied on formalin-fixed paraffin-embedded tissue. As the antibodies previously used were in limited supply, a new batch of polyclonal antibodies was developed for scale-up and evaluated for the first time in this study. Our aim was to assess the diagnostic accuracy of the MPT64 test with reproduced antibodies in the high burden settings of Pakistan and India. Patients were enrolled prospectively. Samples from suspected sites of infection were collected and subjected to histopathologic and/or cytologic evaluation, routine TB diagnostics, GeneXpert MTB/RIF (Xpert), and the MPT64 antigen detection test. Patients were followed until the end of treatment. Based on a composite reference standard (CRS), 556 patients were categorized as TB cases and 175 as non-TB cases. The MPT64 test performed well on biopsies with a sensitivity and specificity of 94% and 75%, respectively, against a CRS. For cytology samples, the sensitivity was low (36%), whereas the specificity was 81%. Overall, the MPT64 test showed higher sensitivity (73%) than Xpert (38%) and Mtb culture (33%). The test performed equally well in adults and children. We found an additive diagnostic value of the MPT64 test in conjunction with histology and molecular tests, increasing the yield for EPTB. In conclusion, immunochemical staining with MPT64 antibodies improves the diagnosis of EPTB in high burden settings and could be a valuable addition to routine diagnostics.</p>","PeriodicalId":48612,"journal":{"name":"Journal of Pathology Clinical Research","volume":"10 3","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/2056-4538.12373","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140345619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The prognosis of patients treated with everolimus for advanced ER-positive, HER2-negative breast cancer is driven by molecular features","authors":"Hélène Salaün,&nbsp;Lounes Djerroudi,&nbsp;Laura Haik,&nbsp;Anne Schnitzler,&nbsp;Guillaume Bataillon,&nbsp;Gabrielle Deniziaut,&nbsp;Ivan Bièche,&nbsp;Anne Vincent-Salomon,&nbsp;Marc Debled,&nbsp;Paul Cottu","doi":"10.1002/2056-4538.12372","DOIUrl":"10.1002/2056-4538.12372","url":null,"abstract":"<p>Everolimus is widely used in patients with advanced ER-positive, HER2-negative breast cancer. We looked at alterations in the PIK3CA/AKT/mTOR pathway in a multicenter cohort as potential biomarkers of efficacy. Patients with advanced ER-positive, HER2-negative breast cancer treated with everolimus and endocrine therapy between 2012 and 2014 in two cancer centers were included. Targeted sequencing examined mutations in <i>PIK3CA</i>, <i>ESR1</i>, and <i>AKT1</i> genes. An immunochemical analysis was conducted to evaluate expression of PTEN, INPP4B, STK11, p4EBP1, and pS6. We analyzed 71 patients (44 primary tumors; 27 metastatic tissues). Median age was 63 years [58–69]. All patients had heavily pretreated advanced disease. A mutation in the PIK3CA pathway was observed in 32 samples (<i>PIK3CA</i> exons 10 and 21 and <i>AKT1</i> exon 4 in 15.5%, 24.0%, and 5.6% of samples), and in <i>ESR1</i> in 5 samples (7.0%), respectively. Most samples showed cytoplasmic expression of the PIK3CA pathway proteins. Progression-free survival was longer in patients with a pS6 or p4EBP1 histoscore ≥ median value (6.6 versus 3.7 months, <i>p</i> = 0.037), and in patients with a PTEN histoscore ≤ median value (7.1 versus 5.3 months, <i>p</i> = 0.02). Overall survival was longer in patients with pS6 ≥ 3rd quartile (27.6 versus 19.3 months, <i>p</i> = 0.038) and in patients with any mutation in the PIK3CA/AKT/mTOR pathway (27.6 versus 19.3 months, <i>p</i> = 0.011). The prognosis of patients treated with everolimus for advanced ER-positive, HER2-negative breast cancer appears primarily driven by molecular features associated with the activation of the PIK3CA/AKT/mTOR pathway.</p>","PeriodicalId":48612,"journal":{"name":"Journal of Pathology Clinical Research","volume":"10 3","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/2056-4538.12372","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140337338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A deep-learning workflow to predict upper tract urothelial carcinoma protein-based subtypes from H&E slides supporting the prioritization of patients for molecular testing","authors":"Miriam Angeloni,&nbsp;Thomas van Doeveren,&nbsp;Sebastian Lindner,&nbsp;Patrick Volland,&nbsp;Jorina Schmelmer,&nbsp;Sebastian Foersch,&nbsp;Christian Matek,&nbsp;Robert Stoehr,&nbsp;Carol I Geppert,&nbsp;Hendrik Heers,&nbsp;Sven Wach,&nbsp;Helge Taubert,&nbsp;Danijel Sikic,&nbsp;Bernd Wullich,&nbsp;Geert JLH van Leenders,&nbsp;Vasily Zaburdaev,&nbsp;Markus Eckstein,&nbsp;Arndt Hartmann,&nbsp;Joost L Boormans,&nbsp;Fulvia Ferrazzi,&nbsp;Veronika Bahlinger","doi":"10.1002/2056-4538.12369","DOIUrl":"https://doi.org/10.1002/2056-4538.12369","url":null,"abstract":"<p>Upper tract urothelial carcinoma (UTUC) is a rare and aggressive, yet understudied, urothelial carcinoma (UC). The more frequent UC of the bladder comprises several molecular subtypes, associated with different targeted therapies and overlapping with protein-based subtypes. However, if and how these findings extend to UTUC remains unclear. Artificial intelligence-based approaches could help elucidate UTUC's biology and extend access to targeted treatments to a wider patient audience. Here, UTUC protein-based subtypes were identified, and a deep-learning (DL) workflow was developed to predict them directly from routine histopathological H&amp;E slides. Protein-based subtypes in a retrospective cohort of 163 invasive tumors were assigned by hierarchical clustering of the immunohistochemical expression of three luminal (FOXA1, GATA3, and CK20) and three basal (CD44, CK5, and CK14) markers. Cluster analysis identified distinctive luminal (<i>N</i> = 80) and basal (<i>N</i> = 42) subtypes. The luminal subtype mostly included pushing, papillary tumors, whereas the basal subtype diffusely infiltrating, non-papillary tumors. DL model building relied on a transfer-learning approach by fine-tuning a pre-trained ResNet50. Classification performance was measured via three-fold repeated cross-validation. A mean area under the receiver operating characteristic curve of 0.83 (95% CI: 0.67–0.99), 0.8 (95% CI: 0.62–0.99), and 0.81 (95% CI: 0.65–0.96) was reached in the three repetitions. High-confidence DL-based predicted subtypes showed significant associations (<i>p</i> &lt; 0.001) with morphological features, i.e. tumor type, histological subtypes, and infiltration type. Furthermore, a significant association was found with programmed cell death ligand 1 (PD-L1) combined positive score (<i>p</i> &lt; 0.001) and <i>FGFR3</i> mutational status (<i>p</i> = 0.002), with high-confidence basal predictions containing a higher proportion of PD-L1 positive samples and high-confidence luminal predictions a higher proportion of <i>FGFR3</i>-mutated samples. Testing of the DL model on an independent cohort highlighted the importance to accommodate histological subtypes. Taken together, our DL workflow can predict protein-based UTUC subtypes, associated with the presence of targetable alterations, directly from H&amp;E slides.</p>","PeriodicalId":48612,"journal":{"name":"Journal of Pathology Clinical Research","volume":"10 2","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/2056-4538.12369","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140164233","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Somatic mutations in four novel genes contribute to homologous recombination deficiency in breast cancer: a real-world clinical tumor sequencing study","authors":"Yongsheng Huang,&nbsp;Yuntan Qiu,&nbsp;Linxiaoxiao Ding,&nbsp;Shuwei Ren,&nbsp;Yuanling Jiang,&nbsp;Jiahuan Luo,&nbsp;Jinghua Huang,&nbsp;Xinke Yin,&nbsp;Sha Fu,&nbsp;Jianli Zhao,&nbsp;Kaishun Hu,&nbsp;Jianwei Liao","doi":"10.1002/2056-4538.12367","DOIUrl":"https://doi.org/10.1002/2056-4538.12367","url":null,"abstract":"<p>Breast cancers involving mutations in homologous recombination (HR) genes, most commonly <i>BRCA1</i> and <i>BRCA2</i> (<i>BRCA1/2</i>), respond well to PARP inhibitors and platinum-based chemotherapy. However, except for these specific HR genes, it is not clear which other mutations contribute to homologous recombination defects (HRD). Here, we performed next-generation sequencing of tumor tissues and matched blood samples from 119 breast cancer patients using the OncoScreen Plus panel. Genomic mutation characteristics and HRD scores were analyzed. In the HR genes, we found that <i>BRCA1/2</i> and <i>PLAB2</i> mutations were related to HRD. HRD was also detected in a subset of patients without germline or somatic mutations in <i>BRCA1/2</i>, <i>PLAB2</i>, or other HR-related genes. Notably, <i>LRP1B</i>, <i>NOTCH3</i>, <i>GATA2</i>, and <i>CARD11</i> (abbreviated as LNGC) mutations were associated with high HRD scores in breast cancer patients. Furthermore, functional experiments demonstrated that silencing CARD11 and GATA2 impairs HR repair efficiency and enhances the sensitivity of tumor cells to olaparib treatment. In summary, in the absence of mutations in the HR genes, the sensitivity of tumor cells to PARP inhibitors and platinum-based chemotherapy may be enhanced in a subset of breast cancer patients with LNGC somatic mutations.</p>","PeriodicalId":48612,"journal":{"name":"Journal of Pathology Clinical Research","volume":"10 2","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/2056-4538.12367","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140164232","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Closing the loop – the role of pathologists in digital and computational pathology research","authors":"Tilman T Rau,&nbsp;William Cross,&nbsp;Ricardo R Lastra,&nbsp;Regina C-L Lo,&nbsp;Andres Matoso,&nbsp;C Simon Herrington","doi":"10.1002/2056-4538.12366","DOIUrl":"10.1002/2056-4538.12366","url":null,"abstract":"<p>An increasing number of manuscripts related to digital and computational pathology are being submitted to <i>The Journal of Pathology: Clinical Research</i> as part of the continuous evolution from digital imaging and algorithm-based digital pathology to computational pathology and artificial intelligence. However, despite these technological advances, tissue analysis still relies heavily on pathologists' annotations. There are three crucial elements to the pathologist's role during annotation tasks: granularity, time constraints, and responsibility for the interpretation of computational results. Granularity involves detailed annotations, including case level, regional, and cellular features; and integration of attributions from different sources. Time constraints due to pathologist shortages have led to the development of techniques to expedite annotation tasks from cell-level attributions up to so-called unsupervised learning. The impact of pathologists may seem diminished, but their role is crucial in providing ground truth and connecting pathological knowledge generation with computational advancements. Measures to display results back to pathologists and reflections about correctly applied diagnostic criteria are mandatory to maintain fidelity during human–machine interactions. Collaboration and iterative processes, such as human-in-the-loop machine learning are key for continuous improvement, ensuring the pathologist's involvement in evaluating computational results and closing the loop for clinical applicability. The journal is interested particularly in the clinical diagnostic application of computational pathology and invites submissions that address the issues raised in this editorial.</p>","PeriodicalId":48612,"journal":{"name":"Journal of Pathology Clinical Research","volume":"10 2","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/2056-4538.12366","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140094896","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}