Journal of Pathology Clinical Research最新文献

The tumour microenvironment (TME) is a key factor in carcinogenesis by affecting tumour growth, invasion, metastasis, and drug resistance. Histopathology and immunohistochemistry provide accessible and reproducible methodologies for TME evaluation, with growing evidence supporting their prognostic and predictive significance in gastrointestinal cancers. This commentary examines four papers published in the Journal of Pathology: Clinical Research that illustrate this methodology across various gastrointestinal cancers. The Tumour Microenvironment Score, Combined Immune Checkpoint Stromal Score, Immune Score for Gastric Cancer, and the multicomponent microenvironment and tumour inflammatory features panel have been developed to assess TME characteristics in colorectal cancer, gastric cancer, and gastroenteropancreatic neuroendocrine neoplasm. The reviewed studies demonstrate that basic morphological characteristics together with the expression of immune checkpoint markers and immune cell markers enable the development of effective clinical tools to enhance risk assessment and treatment planning. These practical, cost-effective, and promising methods need to undergo extensive multicentre testing with established protocols, digital pathology, and molecular information integration.

In breast cancer (BC), the transcription factor GATA3 is linked to estrogen receptor (ER) alpha biology, and its loss is associated with aggressive tumor features. Little is reported about potential roles and implications of GATA3 independent of ER, and possible relationships to the BC tumor microenvironment (TME) have not been much explored. Thus, the discovery of novel biomarkers potentially linked to ER and GATA3 functions and predicting aspects of the TME could significantly improve precision in the management of patient subgroups. We examined GATA3 protein and mRNA expression in a large in-house population-based BC series (n = 837), and in the METABRIC datasets (METABRIC Discovery, n = 997 and METABRIC Validation, n = 995). Associations with primary BC phenotypes, transcriptional programs, TME features, clinical outcomes, and potentially independent roles of GATA3 are reported. We find that low GATA3 expression associates with aggressive features like increased tumor diameter, higher histological grade, triple negative BC, and a basal-like (CK5/6 positive) phenotype. Low GATA3 mRNA expression associated with downregulation of ER-related genes, upregulation of transcriptional signatures reflecting hypoxia, and enrichment of gene sets reflecting tumor cell proliferation, epithelial-mesenchymal transition, and stemness. Low GATA3 protein and mRNA expression both associated with overall reduced BC-specific survival. Notably, low GATA3 expression strongly associated with upregulation of immune checkpoint markers, T-cell activation, and metabolic alterations not previously described in BC. Gene expression patterns underlying GATA3-low tumors, independent of ER status, reflected activation of immunological and metabolic processes. This study suggests that GATA3 might influence the TME independent of ER status. Our results point to metabolic and immunophenotypic alterations in GATA3-low BCs, in particular with T-cell activation and increased expression of immune checkpoints. These findings could be relevant for patient selection in the context of immunotherapies and potential targeting of metabolic pathways.

Anatomical pathology has traditionally relied on the interpretation of histomorphological features under a light microscope by trained pathologists for diagnosis. Technological advancements have enabled the digitisation of tissue slides to produce high-resolution whole slide images, heralding the era of digital pathology (DP). Many laboratories around the world have incorporated DP into their routine workflows owing to the myriad applications it offers in facilitating tumour board discussions, remote reporting, teaching, and research. Most significantly, DP has engendered the field of computational pathology, a novel branch of histopathology incorporating artificial intelligence (AI) models. Computational pathology has been utilised in histomorphological quantification and diagnostic, predictive, and prognostic applications due to its potential to improve diagnostic accuracy, personalise treatment, and streamline workflows. Here, we highlight the work of Meier et al, Shen et al, and Lee et al, published in this journal in recent years, as they apply AI models to predict survival and treatment responses in gastric cancer, breast cancer, and diffuse large B-cell lymphoma, respectively. Collectively, these studies illustrate various approaches to incorporating AI into the DP pipeline and their potential clinical applications. Issues related to diagnostic accuracy, cost, patient confidentiality, and regulatory ethics still need to be addressed within the field. Despite this, the overall sentiment among pathologists is one of cautious optimism.

The tumor immune microenvironment plays a critical role in colorectal cancer (CRC) prognosis. However, most studies assess a limited set of immune markers manually in the tumor region, without considering immune heterogeneity across multiple tissue regions. This study aims to enhance CRC prognostic assessment by developing an automated multi-regional immunohistochemistry (IHC) scoring system for 15 immune markers. Two representative tissue cores were extracted from CRC surgical specimens (n = 154) across four regions: tumor center, invasive margin, paracancerous tissues, and normal tissues. IHC staining was performed for 15 immune markers, and digitized slides were analyzed using computational algorithms to classify tissue types (e.g., glands, tumor, and stroma) and identify stained pixels. Immune infiltration was quantified in different tissue types across regions, and a tumor-to-healthy immune ratio (THIR) score was introduced to compare immune marker expression in tumor versus healthy stroma. Associations between IHC scores and overall survival (OS) and relapse-free survival (RFS) were evaluated. Computational models achieved 95.19% accuracy in tissue classification and 97.90% in staining identification. Analysis of 120 IHC scores (15 markers × 8 tissue types) revealed significant immune heterogeneity, with 56 scores correlating with OS and 54 with RFS. Notably, markers such as Granzyme B and CD4 had higher prognostic relevance at the invasive margin than the tumor center, while markers like S100 and CD20 exhibited opposing prognostic effects across regions. Integrating multiple markers significantly improved prognostic accuracy, with the combined marker score in normal stroma providing the most significant risk stratification (log-rank test, p = 1.56e-7, OS). The THIR score also strongly correlated with patient outcomes. This study advances CRC prognostication through automated multi-regional IHC scoring, highlighting the importance of immune heterogeneity across tissue regions. These findings support integrating region-specific immune profiling into clinical workflows for more personalized and precise patient care.

Breast cancer can be categorised into a number of histological types, based on microscopic appearances. There is some evidence that the different breast cancer histological types are associated with different patient and tumour characteristics, but few previous studies have been large enough to investigate this systematically, especially for rare histological types. National cancer registration data were used to describe trends in the incidence of specific histological types of invasive breast cancer in women diagnosed when aged 18–89 years in England from January 1988 to December 2016, and to investigate associations between breast cancer histological types and patient and tumour characteristics. There were 838,776 women diagnosed with a first primary invasive breast cancer in this 29-year period, including 614,698 (73%) cases of ductal carcinoma NST [no special type (NST)], 90,028 (11%) cases of lobular carcinoma, and more than 16,000 (2%) cases each of tubular and mucinous carcinomas. Rarer histological types included medullary, papillary, metaplastic, and cribriform carcinomas, with >1000 cases of each type. Data quality and completeness improved substantially during the study period. The different histological types of breast cancer showed different patterns in incidence by calendar period of diagnosis, age at diagnosis, and screen-detection status, as well as different associations with tumour characteristics such as grade, stage at diagnosis, and molecular subtype. This large nationwide study provides an overview of the changing incidence of the different histological types of invasive breast cancer in England over almost 30 years. It also gives an opportunity to investigate the characteristics of rare histological types, which smaller studies have been unable to explore. In addition, the results demonstrate the continuing value of histological types defined by microscopic morphology, alongside newer molecular classifications.

Colorectal carcinoma (CRC) is a frequent cause of morbidity and mortality in sub-Saharan Africa. The incidence of early-onset, microsatellite stable (MSS) CRC is on the rise, and the tumour biology of these lesions is poorly categorised. Preliminary data from one centre in Nigeria found differences in the frequencies of mutations in driver genes and altered signalling pathways. We sought to investigate potential alternative driver genes and signalling pathways by whole exome sequencing. Eighty-three cases passed quality control filters and were included in the analysis (77 MSS, 4 microsatellite instability-high, and 2 POLE mutant). APC, TP53, and KRAS were among the most frequently mutated driver genes, although at a lower frequency than expected. BRAF V600E mutations were absent in our cohort. Although there were differences in the frequencies of mutations in the major driver genes, the frequencies of oncogenic pathway alterations were found to be similar. FAT4 (26%) and TET2 (15%) emerged as important mutated driver genes and potential therapeutic targets for further investigation. We have highlighted distinct differences in driver gene mutations in our cohort of young CRC from sub-Saharan Africa and have identified FAT4 and TET2 as potential drivers that are more common and are potential therapeutic targets.

Myeloid sarcoma (MS) is a mass-forming extramedullary manifestation of myeloid blasts, either in relation to an underlying acute myeloid leukemia (AML), another myeloid neoplasm (MN) or as a de novo occurrence. Data on the genetic profile of MS are sparse. In this study, 41 MS of 34 patients, including 7 de novo cases and 24 patients with antecedent or synchronous MN, were analyzed with targeted next-generation sequencing (NGS), RNA-based fusion detection, and gene expression profiling (GEP). In 10 patients, a MS developed after stem cell transplantation for MN. Additionally, 21 available pre-transplant bone marrow biopsies (BMB) from 20 patients and 6 post-transplant BMB from 6 patients were investigated. The most frequently mutated gene was TET2 (41%), followed by NPM1 (38%) and NRAS (35%). Overall, 74% of the cases exhibited mutations affecting the MAPK/ERK pathway. AML-type fusions were detected in seven MS patients, who were younger than those without fusions (median 49 versus 67 years). Nine of 13 patients with a MN and available pre-transplant BMB showed additional mutations restricted to the MS, including an additional NRAS mutation in 3/5 cases with AML. Five of seven of patients with pre-transplant BMB without evidence of a MN revealed clonal hematopoiesis (CH), mostly shared TET2 mutations. Comparative GEP between BM and MS revealed upregulation of the MAPK/ERK pathway in MS and of gene sets relevant for interaction with the microenvironment. In conclusion, MS is characterized by a high incidence of MAPK/ERK pathway mutations and activation, frequent clonal evolution, and association with CH in elderly patients without recurrent AML-type fusions.

In its first decade, The Journal of Pathology: Clinical Research has become a leading source of translational studies advancing molecular diagnostics in cancer, particularly in urologic pathology. This commentary highlights recent contributions that collectively place precision oncology at the forefront of pathology research. One review examines cancer stem cells in renal cell carcinoma, emphasizing the complexity of cellular plasticity and the tumor microenvironment in driving resistance and recurrence. In prostate cancer, epithelial-to-mesenchymal transition (EMT) regulators, including Twist, Slug, and Snail, are identified as synergistic markers of poor prognosis, linked to hypoxia and invasiveness. Another review details the integration of homologous recombination repair gene testing into clinical workflows, supporting targeted treatment strategies with poly (ADP-ribose) polymerase inhibitors. In pediatric oncology, TP53 alterations in Wilms tumor are shown to occur beyond anaplastic cases, expanding their prognostic significance. Advances in molecular subtyping are also demonstrated in bladder cancer, where transcriptomic profiling could enable tailored neoadjuvant therapy. In clear cell renal cell carcinoma, re-evaluation of a prognostic model revealed that while necrosis or sarcomatoid differentiation correlated with poor outcomes, only DNA methylation markers improved prognostic accuracy, underscoring their utility for biopsy-based risk stratification. Finally, digital spatial profiling of sarcomatoid urothelial carcinoma reveals an immunosuppressive microenvironment with CD163-positive cells, implicating them in EMT and aggressive phenotype. Together, these studies highlight the transformative role of integrated molecular diagnostics in guiding individualized therapies and improving outcomes in urologic cancers.

In alignment with the latest WHO classification system, which underscores the integration of molecular alterations in glioma diagnosis and grading, this study investigates the prognostic significance of MYCN amplification in IDH-mutant gliomas, a relationship that remains poorly characterized despite its established association with adverse outcomes in various malignancies. A cohort of 190 patients with IDH-mutant gliomas was analyzed for clinical and pathological characteristics. MYCN amplification status was determined using fluorescence in situ hybridization (FISH) with an MYCN-specific probe. Survival outcomes were assessed via Kaplan–Meier analysis, while independent prognostic factors were identified through multivariable Cox proportional hazards regression models. Tumor morphology was systematically evaluated in cases with MYCN amplification. MYCN amplification was identified in 28 of 190 cases (14.7%), demonstrating a significant correlation with advanced tumor grade and elevated Ki-67 proliferation indices (p < 0.05). Patients harboring MYCN amplification exhibited markedly reduced overall survival compared to non-amplified cases (112.13 ± 6.58 versus 91.14 ± 14.96 months, p = 0.001), with this association being particularly pronounced in lower-grade (WHO grades 2 and 3) IDH-mutant gliomas (122.12 ± 6.81 versus 47.76 ± 6.58 months, p < 0.001). To address limitations in current grading systems, we propose a refined classification approach that upgrades lower-grade IDH-mutant astrocytomas with MYCN amplification to high-grade status. This MYCN-based grading system demonstrated significant prognostic stratification (112.84 ± 10.40 versus 77.65 ± 11.15 months, p < 0.001). Morphological analysis revealed that 50% of MYCN-amplified cases (14/28) exhibited distinct epithelioid features, characterized by abundant eosinophilic cytoplasm and nuclear displacement. In conclusion, MYCN amplification emerges as a critical prognostic indicator in IDH-mutant gliomas, particularly in lower-grade tumors, and is frequently associated with unique epithelioid histological features. These findings highlight the necessity of incorporating MYCN amplification status into grading paradigms for IDH-mutant gliomas to enhance prognostic accuracy and inform clinical decision-making.

PD-L1 expression for the prediction of response to immune-checkpoint blockade remains the most broadly utilised clinically validated biomarker in a range of tumour types. In this study, we aimed to assess, in a prospectively collected matched cohort, the impact of sampling technique and both formalin and alcohol fixation on PD-L1 expression and heterogeneity in non-small cell lung carcinoma (NSCLC). Patients undergoing surgical resection for NSCLC were consented. Surgical specimens were received directly from theatre and sampled fresh to produce two sets of core biopsies, two fine-needle aspirates (FNAs) and two whole-block tissue sections from each specimen. A matched biopsy, FNA, and whole-block were placed into formalin or an alcohol-based fixative (Cytolyt™) prior to PD-L1 immunohistochemistry assessment. A total of 114 specimens from 57 patients were included. All whole-block cases (100%), 92% of core biopsies, and 88% of FNAs were adequate for PD-L1 expression analysis. Fixation had no significant impact on adequacy, but cytology specimens fixed in alcohol showed a significant reduction in PD-L1 expression, with 25% of cases placed into different clinically relevant categories of PD-L1 expression. PD-L1 expression by immunochemistry is an exemplar of the challenges of utilising a heterogeneously expressed protein-based predictive biomarker. Regardless of sampling technique, a good quality biopsy or FNA is likely to give a statistically representative PD-L1 expression, although expression ranges close to clinically relevant cut-offs of 1% and 50% remain a source of potential discordance.