Journal of Pathology Clinical Research最新文献

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.

Current European/US guidelines recommend that molecular testing in advanced non-small cell lung cancer (aNSCLC) be performed using next-generation sequencing (NGS). However, the global uptake of NGS is limited, largely owing to reimbursement constraints. We compared real-world costs of NGS and single-gene testing (SGT) in nonsquamous aNSCLC. This observational study was conducted across 10 pathology centers in 10 different countries worldwide. Biomarker data collected via structured questionnaires (1 January–31 December 2021) were used to feed micro-costing analyses for three scenarios [‘Starting Point’ (SP; 2021–2022), ‘Current Practice’ (CP; 2023–2024), and ‘Future Horizons’ (FH; 2025–2028)] in both a real-world model, comprising all biomarkers tested by each center, and a standardized model, comprising the same sets of biomarkers across centers. Testing costs (including retesting) encompassed personnel costs, consumables, equipment, and overheads. Overall, 4,491 patients with aNSCLC were evaluated. Mean per-patient costs decreased for NGS relative to SGT over time, with real-world model costs 18% lower for NGS than for SGT in the SP scenario, and 26% lower for NGS than for SGT in the CP scenario. Mean per-biomarker costs also decreased over time for NGS relative to SGT. In the standardized model, the tipping point for the minimum number of biomarkers required for NGS to result in cost savings (per patient) was 10 and 12 in the SP and CP scenarios, respectively. Retesting had a negligible impact on cost analyses, and results were robust to variation in cost parameters. This study provides robust real-world global evidence for cost savings with NGS-based panels over SGT to evaluate predictive biomarkers in nonsquamous aNSCLC when the number of biomarkers to be tested exceeds 10. Widespread adoption of NGS may enable more efficient use of limited healthcare resources.

Pulmonary typical carcinoids (TCs) are uncommon, well-differentiated neuroendocrine tumors of the lung that do not exhibit necrosis and have fewer than two mitoses per 2 mm², as defined by the current World Health Organization classifications. Despite their low-grade status and favorable prognostic impact, the protein expression profile and morphological characteristics associated with tumor progression and metastatic spread remain largely unidentified. Oncocytic and spindle cell histological variants are acknowledged for their role in differential diagnosis, though their clinical significance remains a topic of debate. We centrally reviewed a multicenter series of 297 TCs to identify cases of oncocytic and spindle cell variants. We examined associations with clinicopathological features and immunohistochemical markers (orthopedia homeobox protein, thyroid transcription factor 1, mammalian achaete-scute homologue 1, somatostatin receptor 2A, Ki-67, anti-mitochondria, and S100); these data were further related to disease-free survival (DFS), overall survival, and cancer-specific survival (CSS). Our analysis identified oncocytic TCs (n = 36, 12.1%), spindle cell TCs (n = 55, 18.5%), and ordinary TCs, defined as those without either variant or with variants that were not prominent (n = 206, 69.4%). Interestingly, ordinary tumors were associated with a higher number of tumor-related deaths (p = 0.01) compared to the other histological variants. Additionally, patients with spindle cell morphology had longer CSS compared to those with ordinary morphology (p = 0.04). Parameters such as histological variant, age, tumor stage, and Ki-67 were significantly linked to DFS on multivariable analysis, even after accounting for differences between centers. In conclusion, oncocytic, spindle cell, and ordinary TCs are linked to distinct clinicopathological characteristics and exhibit varying clinical outcomes.

Breast cancer affects millions globally, necessitating precise biomarker testing for effective treatment. HER2 testing is crucial for guiding therapy, particularly with novel antibody-drug conjugates (ADCs) like trastuzumab deruxtecan, which shows promise for breast cancers with low HER2 expression. Current HER2 testing methods, including immunohistochemistry (IHC) and in situ hybridization (ISH), have limitations. IHC, a semi-quantitative assay, is prone to interobserver variability. While ISH provides higher precision than IHC, it remains more resource-intensive in terms of cost and workflow. However, turnaround time is typically faster than that of other advanced molecular methods such as next-generation sequencing. We adapted the clustering-constrained-attention multiple-instance deep learning model to improve IHC testing and reduce dependence on reflex fluorescence ISH (FISH) tests. Using 5,731 HER2 IHC images, including 592 cases with FISH testing, we trained two models: one for predicting HER2 scores from IHC images and another for predicting FISH scores from equivocal cases. The HER2 IHC score prediction model achieved 91% ± 0.01 overall accuracy and a receiver operating characteristic (ROC) area under the curve (AUC) of 0.98 ± 0.01. The FISH score prediction model had an ROC AUC of 0.84 ± 0.07, with sensitivity at 0.37 ± 0.13 and specificity at 0.96 ± 0.03. External validation on cases from 203 institutions showed similar performance. The HER2 IHC model maintained a 91% ± 0.01 accuracy and an ROC AUC of 0.98 ± 0.01, while the FISH model had an ROC AUC of 0.75 ± 0.03, with sensitivity at 0.28 ± 0.04 and specificity at 0.93 ± 0.01. Our model advances HER2 scoring by reducing subjectivity and variability in current scoring methods. Despite lower accuracy and sensitivity in the FISH prediction model, it may be a beneficial option for settings where reflex FISH testing is unavailable or prohibitive. With high specificity, our model can serve as an effective screening tool, enhancing breast cancer diagnosis and treatment selection.

We previously showed that Warburg subtyping (low/moderate/high), based on the expression of six glycolytic proteins and transcriptional regulators [glucose transporter 1 (GLUT1), pyruvate kinase M2 (PKM2), lactate dehydrogenase A (LDHA), monocarboxylate transporter 4 (MCT4), p53, and PTEN], holds independent prognostic value in colorectal cancer (CRC) patients. The present study aimed to investigate whether the expression level of one of the proteins (GLUT1, PKM2, LDHA, MCT4, p53, and PTEN) can act as a proxy for our previously identified six protein-based Warburg subtypes. Protein expression levels for individual Warburg-related proteins were available for 2,251 CRC patients from the Netherlands Cohort Study. Kaplan–Meier curves and Cox regression were used to explore associations between individual Warburg-related proteins and CRC-specific and overall survival. Previously identified associations between Warburg subtypes and CRC-specific and overall survival were adjusted for individual proteins, showing a significant association with survival in the current study. Multivariable-adjusted analyses showed that the expression of GLUT1, LDHA, MCT4, PKM2, or p53 was associated with neither CRC-specific nor overall survival. Decreasing PTEN expression was associated with significantly poorer overall survival (p-trend_categories = 0.026). Additional adjustment for PTEN expression had minimal impact on the previously identified association between Warburg subtypes and survival, and the six protein-based Warburg-high subtype remained a statistically significant predictor of overall survival (hazard ratio 1.15; 95% CI 1.01–1.32). In conclusion, our results emphasise that individual Warburg-related proteins cannot serve as a proxy or surrogate marker for Warburg subtyping, thereby highlighting the importance of combining the expression levels of multiple Warburg-related proteins when examining the prognostic significance of a complex biological pathway such as the Warburg effect.

Papillary thyroid carcinoma (PTC) is one of the most common endocrine malignancies, with varying levels of risk and clinical behavior. A better understanding of the molecular characteristics could improve molecular diagnosis and risk assessment. In this study, we performed whole transcriptomic sequencing on 113 PTC cases, including 70 high-risk and 43 low-risk Chinese patients. Comparative transcriptional profiling analysis revealed two functionally distinct patterns of gene dysregulation between the risk subtypes. Low-risk PTCs showed significant upregulation of immune-related genes and increased immune cell infiltration, whereas high-risk PTCs presented extensive alterations in gene expression and activation of oncogenic signaling pathways. Additionally, we developed a 31-gene transcriptomic signature (PTCrisk) for differentiating high-risk from low-risk PTCs, which was validated across both in-house and external multicenter cohorts. PTCrisk scores were positively correlated with key clinicopathological features, including tumor size, lymph node metastasis, TNM stage, and BRAF mutation status. Overall, our study provides further molecular insights into PTC risk stratification and may contribute to the development of personalized therapeutic strategies for PTC patients.

Intraductal papillary mucinous neoplasm (IPMN) can progress into malignant pancreatic cancer, posing challenges in accurately assessing the risk of malignancy. While the nucleotide-binding oligomerization domain (NOD)-like receptor pyrin domain containing 3 (NLRP3) inflammasome pathway's role in pancreatic ductal adenocarcinoma (PDAC) has been extensively studied, its implications in IPMN remain unexplored. This study aimed to investigate the prognostic significance of NLRP3 inflammasome-related proteins across IPMN subtypes and their associations with tumor characteristics, with a secondary focus on comparing expression patterns in IPMN and PDAC. A cohort of 187 patients (100 IPMN and 87 PDAC) underwent high-dimensional histopathological imaging using the multiplexed immunohistochemical consecutive staining on single slide method and a semi-automated image analysis workflow. Expression levels of NLRP3, apoptosis-associated speck-like protein containing a caspase-recruitment domain (ASC), caspase-1, interleukin-1 beta, interleukin-18 (IL-18), interleukin-1 receptor antagonist, and interleukin-18 binding protein (IL-18BP) were evaluated and compared between IPMN and PDAC samples. The relationships between protein expression and tumor characteristics were examined. Principal component analysis distinguished between intestinal and nonintestinal clusters based on NLRP3-associated proteins. Lower IL-18 expression was linked to the intestinal subtype, while higher caspase-1 was linked to the pancreatobiliary subtype. Elevated caspase-1 and ASC expression were associated with invasiveness in IPMN. No significant correlation was found between the examined proteins and later-stage tumor characteristics in invasive cases. The IL-18/IL-18BP ratio was an independent prognostic factor in invasive IPMN. Our findings highlight the prognostic significance of IL-18 and the IL-18/IL-18BP ratio in invasive IPMNs. These results point to a complex regulation of NLRP3 inflammasome proteins, especially effector cytokines, in pancreatic neoplasms, which are strongly linked to subtype and prognosis.

Sarcomatoid urothelial carcinoma (SUC) is a rare histologic subtype with poor prognosis. While there is known intra-tumoral heterogeneity between individual SUC tumors, the relationship between sarcomatoid and conventional urothelial carcinoma (CUC) within the same patient is poorly understood. The objective of this study was to identify differences between the sarcomatoid and CUC tumor microenvironment components that may drive this aggressive phenotype. Using tissue microarrays from eight patient tumors with mixed CUC and SUC, we examined paired CUC, mixed urothelial carcinoma (UC) regions, and SUC using the Nanostring Digital Spatial Profiling platform. We found SUC and mixed UC had higher levels of stromal cells, predominately macrophages and fibroblasts, when compared with CUC within the same tumor. CD14, CD163, and transforming growth factor-beta levels were significantly higher in SUC than in CUC. Immunohistochemical analysis revealed consistently moderate to strong expression of CD163-positive antigen-presenting cells (APCs) in SUC regions, whereas CD68-positive APC expression was generally absent. Thus, in mixed histology SUC, the SUC component preferentially expressed CD163-positive APCs and fibroblasts compared to the CUC component. As CD163-positive APCs and fibroblasts are known to be tumor-promoting and immune-suppressive, this infiltration may contribute to epithelial to mesenchymal transition and other aggressive properties of SUC.