Journal of Pathology Clinical Research最新文献

The spatial structure of various cell types in the tumour microenvironment (TME) can provide valuable insights into disease progression. However, identifying the spatial organization of diverse cell types that significantly correlates with patient prognosis remains challenging. In this study, enabled by deep learning-based cell segmentation and recognition, we developed a computational pipeline to systematically quantify the spatial distribution features of tumour cells, stromal cells, and lymphocytes in haematoxylin and eosin (H&E)-stained pathological images of hepatocellular carcinoma (HCC). We identified six cellular spatial features that consistently and significantly correlated with the overall survival of patients in two independent HCC patient cohorts, The Cancer Genome Atlas Program cohort and the Beijing Hospital cohort. Each threshold for patient stratification was the same for both cohorts, and the six features independently served as prognostic indicators when individually analysed alongside clinical variables. Furthermore, the combination of features such as the mean value of cellular diversity around stromal cells (StrDiv-M), the median distance between all cells (CellDis-MED), and the median value of variation coefficient of the distance around stromal cells and their neighbours (CvStrDis-MED) could further stratify the patient prognosis. In addition, incorporating cell spatial features with another clinical feature, microvascular invasion improved prognostic stratification efficacy for patients from both cohorts. In conclusion, by quantifying the cellular spatial organization features in the HCC TME, we discovered novel biomarkers for evaluating tumour prognosis. These findings could promote mechanistic studies of the cellular spatial organization within the HCC TME and potentially guide future clinical treatment.

External Quality Assessment (EQA) schemes are an important quality assurance tool and aim to ensure consistency among histopathologists. In this study, we use Shannon entropy as a novel metric to evaluate linguistic variability in the UK Liver Pathology EQA scheme. Analysing free-text responses by participants over a decade, we aimed to quantify language trends in morphological assessments and clinicopathological diagnoses. Accounting for an increasing word count and when pathologists joined the scheme, our findings reveal a significant increase in entropy of morphological assessments over time, indicating growing linguistic diversity that may reflect the increasing complexity of liver pathology. Entropy of clinicopathological diagnoses over the same period did not provide clear evidence for convergent diagnostic language. High entropy corresponded to cases that elicited more diverse responses and could be considered more challenging, highlighting the utility of this method to identify potential areas for targeted education. We demonstrate entropy as a novel tool to analyse pathologist language and enhance quality assurance in the evolving pathology landscape.

The intertumoral and intratumoral heterogeneity of colorectal adenocarcinoma (CRC) at the morphologic level is poorly understood. Previously, we identified morphological patterns associated with CRC molecular subtypes and their distinct molecular motifs. Here we aimed to evaluate the heterogeneity of these patterns across CRC. Three pathologists evaluated dominant, secondary, and tertiary morphology on four sections from four different FFPE blocks per tumor in a pilot set of 22 CRCs. An AI-based image analysis tool was trained on these tumors to evaluate the morphologic heterogeneity on an extended set of 161 stage I–IV primary CRCs (n = 644 H&E sections). We found that most tumors had two or three different dominant morphotypes and the complex tubular (CT) morphotype was the most common. The CT morphotype showed no combinatorial preferences. Desmoplastic (DE) morphotype was rarely dominant and rarely combined with other dominant morphotypes. Mucinous (MU) morphotype was mostly combined with solid/trabecular (TB) and papillary (PP) morphotypes. Most tumors showed medium or high heterogeneity, but no associations were found between heterogeneity and clinical parameters. A higher proportion of DE morphotype was associated with higher T-stage, N-stage, distant metastases, AJCC stage, and shorter overall survival (OS) and relapse-free survival (RFS). A higher proportion of MU morphotype was associated with higher grade, right side, and microsatellite instability (MSI). PP morphotype was associated with earlier T- and N-stage, absence of metastases, and improved OS and RFS. CT was linked to left side, lower grade, and better survival in stage I–III patients. MSI tumors showed higher proportions of MU and TB, and lower CT and PP morphotypes. These findings suggest that morphological shifts accompany tumor progression and highlight the need for extensive sampling and AI-based analysis. In conclusion, we observed unexpectedly high intratumoral morphological heterogeneity of CRC and found that it is not heterogeneity per se, but the proportions of morphologies that are associated with clinical outcomes.

Although the characteristics at the invasive tumour front in colorectal cancer (CRC) are simple to assess, they are not included in routine pathology reports because they lack reproducibility and standardisation. In this study, we aimed to validate alternative scoring methods at the invasive tumour front in a large cohort of stage I–III CRC. The retrospective analysis was performed on haematoxylin and eosin–stained sections from 538 patients. At the invasive tumour front, tumour characteristics were scored using three alternative methods: the Karamitopoulou method, which evaluates the percentage of infiltrative tumour; the Taskin method, a five-point grading scale; and the tumour growth pattern (TGP) method, which classifies patterns as pushing, intermediate, or infiltrative. For interobserver assessment, the Karamitopoulou and TGP methods showed good agreement while the Taskin method presented fair agreement. High scores with the Karamitopoulou and Taskin methods correlated significantly with adverse prognostic factors, particularly advanced T stage (p < 0.001), N stage (p < 0.001), and the presence of peritoneal involvement (p < 0.001). The survival rate of the TGP method demonstrated that patients with an infiltrative growth pattern had significantly worse CRC survival compared to those with pushing and intermediate growth patterns (p < 0.001) and the TGP method retained its independence as a prognostic factor in multivariable Cox regression analysis only for colon cancer-specific survival (p < 0.001). The TGP scoring method is an independent prognostic factor only for colon cancer with simple and inexpensive assessment, underlining its practicality in routine reporting. Additionally, this method could be included as an additional histopathological risk indicator with the potential to guide therapeutic decision making.

Solid pseudopapillary neoplasm (SPN) of the pancreas is a rare, low-grade malignant tumor, representing 0.9–2.7% of all exocrine pancreatic tumors. SPN patients generally have a favorable prognosis with a 5-year survival rate exceeding 95% following complete surgical resection. Accurate diagnosis is crucial to avoid unnecessary treatments. Currently, SPN diagnosis relies on imaging techniques such as CT and MRI, along with immunohistochemical analysis of biopsy and resection samples. The main challenge in diagnosis is the potential inability to accurately identify recurrent or metastatic SPN, as well as ‘malignant’ SPN, due to the lack of specific biomarkers. Advances in high-throughput omics technologies, including genomics, transcriptomics, proteomics and metabolomics, have opened new avenues for identifying novel biomarkers for SPN. Additional, liquid biopsy techniques have enabled more comprehensive analysis of biosamples such as pancreatic cyst fluid, offering promising prospects for preoperative diagnosis. This review highlights recent research on SPN diagnosis, focusing on immunohistochemical markers, tissue sampling methods and the potential of omics approaches. It also discusses the challenges and opportunities in improving diagnostic accuracy, particularly for high-grade and metastatic SPNs.

Novel treatment options for metastatic renal cell carcinomas (RCC) include specific MET inhibitors, GAS6/AXL inhibitors, and SRC inhibitors. The interplay between c-MET, SRC, AXL expression, and their gene mutation patterns in different renal carcinoma subtypes is unclear. To improve the understanding of these signaling pathways, we analyzed c-MET, AXL, and SRC expression in 590 clear cell RCC (ccRCC) and 127 papillary RCC (pRCC) by immunohistochemistry and integrated sequencing data to investigate the frequency of MET, AXL, and SRC gene mutations, their expression levels, and the presence of splice variants. In TCGA and in Foundation Medicine, Inc. (FMI) datasets, AXL and SRC gene alterations were extremely rare (<2%) or absent in ccRCC (n = 531 and 2,781, respectively) and pRCC (n = 290 and 566, respectively). On the other hand, MET mutations or amplifications were found in 9.7% (TCGA) and 10.2% (FMI) of pRCC. We show that strong SRC staining intensity by immunohistochemistry is associated with high tumor stage, high grade, and shorter survival in ccRCC (p < 0.001 each). AXL expression correlates with high stage and grade in ccRCC (p < 0.001 each). Both SRC and AXL expression were independent prognostic parameters in multivariate analysis (p < 0.05). MET expression is associated with longer survival in pRCC (p < 0.05). Our TCGA data analysis aligns with SRC immunohistochemistry findings on tumor stage and shorter survival in ccRCC. TCGA expression data showed a moderate positive correlation between AXL and c-MET in pRCC. In addition, we identified alternative splicing events reported for AXL in pRCC, and MET and SRC in ccRCC, across various alternative splicing databases. In conclusion, we identified high SRC expression as a biomarker for poor prognosis of ccRCC. Our data demonstrate c-MET, AXL, and SRC signaling pathway interactions independent of c-MET, AXL, and SRC mutations in ccRCC.

Netrin-1 and B-cell maturation antigen (BCMA) are currently being evaluated as therapeutic targets in oncology. However, studies investigating their expression in mature human lymphoid malignancies are sparse. This study aimed to investigate the expression of BCMA and Netrin-1 in a large cohort of lymphomas to determine their potential role as biomarkers or therapeutic targets. BCMA and Netrin-1 expression was investigated comprehensively using immunohistochemistry in a cohort that included 261 B-cell lymphomas, 45 T-cell lymphomas, and 55 classical Hodgkin lymphomas. Netrin-1 displayed a cytoplasmic staining pattern in plasmablastic lymphomas (27/28, 96%) and classical Hodgkin lymphomas (8/55, 15%). BCMA displayed cytoplasmic staining in most plasmablastic lymphomas (17/20, 85%). Among mature B-cell lymphomas, Netrin-1 and BCMA displayed sensitive (96% and 85%, respectively) and specific (100% and 95%, respectively) staining in plasmablastic lymphomas. These results suggest that these proteins may help pathologists in complex diagnoses and reinforce the interest in developing clinical trials assessing Netrin-1 or BCMA-targeted therapies in plasmablastic lymphoma and classical Hodgkin lymphomas, for which our therapeutic arsenal is weak.

Ductal adenocarcinoma of the prostate (DA) is relatively rare and highly co-existent with prostate adenocarcinoma (AC). This study aimed to investigate the distinctive genomic profiles of patients with DA compared to those without. Blood samples were obtained from 144 patients (36 with DA and 108 without DA) who were diagnosed from 2017 to 2023 at West China Hospital. We performed cell-free DNA sequencing to investigate the genomic differences between patients with DA [DA(+)] and those without [DA(−)], and explored the potential associations between their mutational status and prognosis. Pathogenic and likely pathogenic alterations were included for analysis. We identified that AR pathway [16/36 (44.4%) versus 24/108 (22.2%), p = 0.017] and WNT pathway [6/36 (16.7%) versus 5/108 (4.6%), p = 0.029] mutations were significantly enriched in DA(+) compared to DA(−) patients. Mutation of FOXA1, as a key component of the AR pathway, demonstrated markedly higher prevalence in the DA(+) over the DA(−) cohort [25% (9/36) versus 4.6% (5/108), p = 0.0012]. The DNA damage repair mutation rate and the homologous recombination repair deficiency scores appeared to be comparable between the DA(+) and DA(−) patients. In the metastatic population, DA was characterized by a higher speckle-type POZ protein (SPOP) mutation rate. TP53 mutation was associated with a deteriorating prognosis for both DA(+) and DA(−) patients in terms of castration-free survival. In conclusion, our findings provide further genomic insights into prostate cancer with ductal morphology and are instructive for the diagnosis and treatment of DA.

Schlafen 11 (SLFN11), a regulator of cell fate following DNA injury, sensitizes tumor cells to DNA-damaging agents. Patients with SLFN11-positive tumors may benefit from DNA-damaging chemotherapies. SLFN11 has been studied in different types of cancer including colorectal carcinomas. However, colorectal carcinomas with diffuse positivity (expression in ≥80% of tumor cells) have not been meticulously characterized. SLFN11 immunostaining of tumor microarrays (TMAs) with 3,300 primary CRCs identified 65 (~2.0%) tumors with focal staining (<10% of tumor nuclei positive), 83 (~2.5%) with patchy (≥10% and <80%) and 51 (~1.5%) with diffuse (≥80%) SLFN11 positivity. The latter was confirmed on full sections from donor blocks in 31 (~1%) cases, which were further studied including evaluation of additional immunohistochemical markers, genotyping with targeted DNA sequencing, and assessment of microsatellite instability. SLFN11-positive carcinomas were mostly (21/31, 68%) right-sided tumors with a female predominance (21/31, 68%) and median age of 67 years. Eighteen of 31 (58%) contained areas of mucinous differentiation. Deficiency of mismatch repair proteins was detected in 65% (20/31) of SLFN11-positive carcinomas. Moreover, MLH1 (n = 2), MSH2, MSH6, and PMS2 germline mutations were identified in 25% (5/20) of patients with mismatch repair deficient tumors. BRAF p.V600E mutation was found in 45% (9/20) of mismatch repair deficient, but only 1 of 11 proficient tumors. Colorectal carcinomas with diffuse SLFN11 positivity were often mismatch repair deficient tumors with their typical clinical, morphological, and molecular characteristics.

This work aimed to evaluate both the usefulness and user acceptance of five gradient-based explainable artificial intelligence (XAI) methods in the use case of a prostate carcinoma clinical decision support system environment. In addition, we aimed to determine whether XAI helps to increase the acceptance of artificial intelligence (AI) and recommend a particular method for this use case. The evaluation was conducted on a tool developed in-house with different visualization approaches to the AI-generated Gleason grade and the corresponding XAI explanations on top of the original slide. The study was a heuristic evaluation of five XAI methods. The participants were 15 pathologists from the University Hospital of Augsburg with a wide range of experience in Gleason grading and AI. The evaluation consisted of a user information form, short questionnaires on each XAI method, a ranking of the methods, and a general questionnaire to evaluate the performance and usefulness of the AI. There were significant differences between the ratings of the methods, with Grad-CAM++ performing best. Both AI decision support and XAI explanations were seen as helpful by the majority of participants. In conclusion, our pilot study suggests that the evaluated XAI methods can indeed improve the usefulness and acceptance of AI. The results obtained are a good indicator, but further studies involving larger sample sizes are warranted to draw more definitive conclusions.