Pathobiology最新文献

Introduction: Soft tissue sarcomas (STSs) are a group of rare malignancies with limited treatment options and a persistent lack of effective therapies. Despite the heterogeneous nature of STS, the canonical WNT/β-catenin signalling pathway has been associated with sarcomagenesis and also with the initiation and progression of other cancers.

Methods: Eight patient-derived primary cultures representing different STS histological subtypes were characterized by immunohisto(cyto)chemistry, WNT/β-catenin activation and next-generation sequencing.

Results: Elevated levels of active phospho-β-catenin and its nuclear localization were found in all STS primary cultures, with heterogeneous downstream WNT signalling activation. Genomic analysis of matched STS tumours identified pathogenic or likely pathogenic genetic variants in crucial signalling pathways, including WNT, DNA damage repair, and PI3K/AKT/mTOR-MAPK pathways. Interestingly, 50% of STS tumours studied carried genetic variants in PIK3CA and PTEN genes with potential clinical significance, listed as predictive biomarkers of response to specific drugs (FDA level 3).

Conclusions: This study provides valuable insights into WNT signalling vulnerabilities in STS, offering a foundation for the development of targeted therapeutic strategies and the identification of potential biomarkers for personalized treatment approaches in this challenging group of malignancies.

Introduction: Glioblastoma, the most common primary malignant brain tumor in adults, accounts for approximately 50% of primary malignant brain tumors. Extracranial metastases are extremely rare, affecting <0.5% of patients. This article describes 2 cases where next-generation sequencing and DNA methylation profiling confirmed extracranial metastases of glioblastoma, IDH-WT.

Case presentation: The first case involves a 77-year-old man who developed lung and liver mass within months of diagnosis. While both biopsies revealed undifferentiated malignant tumor, identical genetic mutations on the lung biopsy and DNA methylation profiling on the liver biopsy confirmed glioblastoma metastases. The second case details a 75-year-old woman diagnosed with glioblastoma, IDH-WT who presented diffuse bone infiltration. Bone marrow aspirate and bone marrow biopsy associated with NGS and methylation profiling confirmed glioblastoma metastasis. Both patients succumbed within 8 months.

Conclusion: These cases underscore the importance of molecular diagnostics in identifying glioblastoma metastases and guiding treatment, particularly in rare presentations involving extracranial spread.

Introduction: The tumor microenvironment of sarcomas has not been studied in detail; in particular, little is known about cancer-associated fibroblasts (CAFs). Sarcoma cells are difficult to distinguish from CAFs, either histomorphologically or immunohistochemically.

Methods: We scored the expression of individual CAF markers (fibroblast-activating protein [FAP], CD10, and podoplanin) in the intratumoral and marginal areas of 133 sarcomas. We also examined the association between these markers, as well as the number of CD163-positive macrophages (i.e., tumor-associated macrophages), and clinical outcome.

Results: In all cases, the log-rank test revealed that those with high marker scores and macrophage counts (except for marginal CD10+ CAFs) showed significantly worse disease-free survival (DFS). Grade 2/3 cases with high CAF scores (excluding the marginal FAP and CD10 scores) showed significantly worse DFS, whereas those with high intratumoral FAP/CD10 and marginal podoplanin scores showed significantly worse metastasis-free survival (MFS), and those with high intratumoral CD10 score showed significantly worse local recurrence-free survival (LFS). Multivariate analysis identified intratumoral CD10/podoplanin scores and marginal FAP/podoplanin scores as independent prognostic factors for DFS, intratumoral FAP/CD10 and marginal FAP/podoplanin/CD163-positive macrophage scores as independent prognostic factors for MFS, and the intratumoral podoplanin score as an independent prognostic factor for LFS. There was a weak-to-moderate correlation between each score and CD163-positive macrophage counts.

Conclusion: Patients with high CAF marker expression in the intratumoral and marginal areas have a poorer outcome.

Introduction: The tumor microenvironment of sarcomas has not been studied in detail; in particular, little is known about cancer-associated fibroblasts (CAFs). Sarcoma cells are difficult to distinguish from CAFs, either histomorphologically or immunohistochemically.

Methods: We scored the expression of individual CAF markers (fibroblast-activating protein [FAP], CD10, and podoplanin) in the intratumoral and marginal areas of 133 sarcomas. We also examined the association between these markers, as well as the number of CD163-positive macrophages (i.e., tumor-associated macrophages), and clinical outcome.

Results: In all cases, the log-rank test revealed that those with high marker scores and macrophage counts (except for marginal CD10+ CAFs) showed significantly worse disease-free survival (DFS). Grade 2/3 cases with high CAF scores (excluding the marginal FAP and CD10 scores) showed significantly worse DFS, whereas those with high intratumoral FAP/CD10 and marginal podoplanin scores showed significantly worse metastasis-free survival (MFS), and those with high intratumoral CD10 score show

Introduction: This study aimed to evaluate the prognostic significance of programmed cell death (PD)-1/PD-ligand 1 (PD-L1), PD-ligand 2 (PD-L2), and fibroblast growth factor receptor 3 (FGFR3) expression in bladder cancer (BC).

Methods: A retrospective study was conducted on BC patients who underwent transurethral resection between 2005 and 2014. Of the initial 136 patients, 31 were excluded for not meeting the inclusion criteria, leaving 105 cases for the final analysis. The mRNA levels of PD-1/PD-L1/PD-L2 and FGFR3 were assessed using quantitative reverse transcription PCR and NanoString technology.

Results: High expression of PD-1 and its ligands (PD-L1/PD-L2) showed a strong correlation with each other and was associated with poor clinical outcomes, including higher tumor stage, grade, and cancer-specific mortality (p < 0.001). Conversely, high FGFR3 expression was associated with improved survival and more favorable clinicopathological features. Interestingly, an inverse relationship was observed between FGFR3 and PD-1 (p = 0.032) and PD-L1 (p = 0.016) expression. High mRNA expression profiles of PD-1, PD-L1, PD-L2, and low FGFR3 expression were associated with worse cancer-specific survival (p < 0.001). Multivariate analysis revealed that advanced stage, low FGFR3 expression, and high PD-L2 expression are independent predictors of poor prognosis in BC patients.

Conclusion: Our findings suggest that elevated levels of PD-1, PD-L1, and PD-L2, combined with reduced FGFR3 expression, may assist in identifying patients with poor outcomes and highlight their potential as prognostic biomarkers in BC.

Introduction: Human papillomavirus circulating tumor DNA (HPV ctDNA) is a promising biomarker for monitoring cervical cancer. HPV ctDNA level at baseline (before treatment) reflects tumor burden. However, reported HPV ctDNA detection rates at baseline have shown variations across studies, suggesting the existence of other potential contributing factors. This study aimed to identify additional factors that might influence HPV ctDNA detection at baseline, focusing on histology type and HPV genotypes (high-risk genotypes HPV16 and HPV18).

Methods: We retrospectively analyzed blood samples at baseline prior to treatment from 92 patients diagnosed with HPV16- or HPV18-associated cervical cancer (FIGO IA2-IIIC2) between 2013 and 2020. HPV ctDNA was evaluated using digital droplet PCR.

Results: HPV ctDNA was detected at baseline in 41.3% of cases. Locally advanced cervical cancers had a higher (p = 0.028) detection rate at baseline than early stage cervical cancers. HPV ctDNA positivity was significantly (p = 0.048) higher for HPV18 (60%) than for HPV16 (34.3%). Adenocarcinoma/adenosquamous carcinoma had a higher HPV ctDNA detection rate at baseline (54.2%) than squamous cell carcinoma (36.8%) but not significantly (p = 0.212) higher.

Conclusion: This study found the impact of histology and HPV genotype on HPV ctDNA at baseline in cervical cancer. HPV18 and adenocarcinoma were associated with a higher baseline HPV ctDNA detection rate. These results suggest the need for different HPV ctDNA approaches for analyzing tumor burden. This finding may also serve as a useful reference for posttreatment surveillance studies.

Introduction: Gastric adenocarcinoma with enteroblastic differentiation (GAED) is a rare entity with worse prognosis compared to conventional gastric adenocarcinomas. Its histological characteristics are fetal gut-like architecture and tumor cells with cytoplasmic clearing, as well as positive immunohistochemical reaction to at least one of the enteroblastic markers. Hereby, we present a case of GAED with neuroendocrine marker positivity, with whole-exome sequencing (WES), and an updated literature review.

Case presentation: A 68-year-old woman presented at the general practitioner with abdominal pain. Abdominal ultrasound described gastric wall thickening raising suspicion of gastric cancer; thus, gastroscopy was performed, and biopsy samples were taken, which confirmed malignancy. Neoadjuvant systemic chemotherapy was initiated, and total gastrectomy was performed. Microscopically, pleomorphic polygonal cells were visible with clear cytoplasm and high-grade cellular atypia. Alcian blue and PAS stains demonstrated positivity for acidic and neutral mucins. P53 IHC was negative, indicative of null-phenotype, while Syntaxin-1 and Chromogranin showed focal positivity. SALL4 and Glypican 3 were positive; however, AFP displayed only minimal, uncertain positivity. The Ki67 labeling index was 70%. Due to the morphological and immunohistochemical characteristics, the tumor was concluded as GAED with neuroendocrine marker positivity. WES was carried out revealing 4 pathogenic, including TP53, KLHL7, RAPSN, and ACTA1, and 3 likely pathogenic mutations, encompassing PNKP, HNF1A, and ADNP.

Discussion: GAED is a rare subtype of gastric adenocarcinomas, representing 0.3-5.4% of all cases, and has an unclarified etiology. Our WES results identified new pathogenic and likely pathogenic mutations. From a differential diagnostic point of view, hepatoid adenocarcinoma and the possibility of metastatic origin have to be excluded.

Introduction: Determination of claudin-18.2 expression by immunohistochemistry (IHC) is a prerequisite for targeted treatment of gastric cancers (GCs) with zolbetuximab. Precise assessment of IHC expression categories, however, may be challenging and prone to interobserver variability. Computer-aided diagnosis has a high potential of improving diagnostic accuracy and reproducibility. We established a computer-aided analysis tool for claudin-18.2 positivity scoring.

Methods: Analysis steps included the identification of tumour tissue on haematoxylin-3,3'-diaminobenzidine-stained tissue microarray (TMA) slides, cell segmentation, and membranous staining intensity estimation of claudin-18.2 (clone 43-14A). We analysed 2,248 cores from 417 primary resected GCs with detailed pathological data available.

Results: In 51.6% (1,159/2,248) of TMA cores, no stained tumour cells were detected. Among cases with claudin-18.2 expression, predominantly 1+ and 2+ cells, a minority of 3+ stained cells were found, and 2+ to 3+ staining was unevenly distributed. Utilizing the SPOTLIGHT claudin-18.2 positivity threshold, we identified 12% (187/1,555) positive cores corresponding to 2.5% (9/365) positive cases. Lower staining intensities in tumour centre cores point to intratumoural heterogeneity.

Conclusion: Computer-aided diagnostics helps accurately measure claudin-18.2 expression levels, allowing to precisely determine claudin-18.2 status in GC patients. Previously uncaptured categorization of staining intensities may enhance the understanding of claudin-18.2 threshold for patient stratification.

Introduction: The tumor microenvironment plays a crucial role in the progression and prognosis of colorectal cancer (CRC). Among its components, the tumor-stroma ratio (TSR) and cancer-associated fibroblasts (CAFs) have emerged as significant prognostic markers. However, conventional assessments of TSR and CAF density remain subjective and labor-intensive, limiting their clinical applicability.

Methods: We utilized an artificial intelligence (AI)-based whole slide image analysis platform, Lunit SCOPE IO, to objectively quantify TSR and CAF density in tissue samples from 207 treatment-naïve patients with stage II and III CRC.

Results: Our analysis demonstrated that both TSR (log-rank p < 0.0001) and CAF density (log-rank p = 0.017) were independently associated with disease-free survival (DFS). These AI-derived markers outperformed conventional prognostic factors. Furthermore, integrating TSR and CAF density with existing high-risk criteria enabled reclassification of additional patients as high risk, enhancing DFS prediction and reducing false-negative rates.

Conclusion: AI-powered histopathological quantification of TSR and CAF density improves prognostic accuracy in CRC and offers a promising approach for refining risk stratification. These findings support the integration of AI-based pathology into clinical practice to enhance diagnostic precision and patient management.

Background: Lung cancer is the most common cancer worldwide and is also the leading cause of cancer-related mortality. Its poor prognosis is primarily attributed to unspecific symptoms that result in late diagnosis, and its heterogeneous nature that further complicates treatment. This heterogeneity is largely driven by the diversity in histological subtypes, significantly impacting the clinical course of patients. Therefore, tumour subtyping using haematoxylin and eosin staining and immunohistochemistry is crucial for predicting patients' outcomes, making an accurate diagnosis, and choosing the appropriate treatment approach. Small-cell lung cancer and non-small cell lung cancer are the two major types, and subclassifying non-small cell lung cancer is essential to identify genetic alterations and, consequently, choose an adequate targeted therapy.

Summary: This article reviews all these lung tumour characteristics, specifying histological types and subtypes, and presenting their distinct features. To aid understanding, complementary images from Unilabs illustrate various lung tumour subtypes. Additionally, alternative approaches using artificial intelligence to improve tumour classification are reviewed, along with a discussion of their limitations.

Key messages: Thus, lung tumour classification is crucial for cancer treatment; nonetheless, it can be a subjective process, reliant on the pathologist's interpretation. In the era of artificial intelligence and deep/machine learning, the classification of lung cancer subtypes has the potential to become more efficient, accurate, and consistent. These advancements could lead to faster diagnosis and treatment decisions, ultimately improving patient survival and quality of care. Harnessing AI tools may address the limitations of subjective interpretation, offering a promising avenue for enhancing precision in lung cancer diagnostics.

Introduction: In our research on understanding glioblastoma's resistance mechanisms to immunotherapy, we extensively investigated through an innovative technology that enables the simultaneous assessment of multiple biomarkers. With this approach, we aim to gain deeper insights into the interplay between immunosuppressive cells (ICs) and effector cells (ECs).

Methods: One hundred twenty-six cases of glioblastoma were studied employing tissue microarrays stained with a panel of immune infiltrate validated via multiplex immunofluorescence and quantified by advanced image analysis. All cases were categorized according to an EC/IC ratio and their respective medians. Statistical correlations between cell populations and with survival were calculated.

Results: M2 macrophages were the most abundant ICs, followed by a variable number of ECs and protumoral activated microglia, and a scant quantity of FoxP3 cells. EC showed a statistically significant direct positive correlation with ICs. The patients with tumors exhibiting an EC/IC ratio ≤0.063 displayed a significantly poorer outcome. Furthermore, in the context of incomplete surgical resection, significant differences were evident considering immune scenarios.

Conclusions: By integrating multiplex technology with advanced imaging analysis, we successfully identified 4 distinct immune scenarios in glioblastoma. We observed a favorable immune scenario characterized by a relatively high EC/IC ratio, which is especially evident in the clinical setting of incomplete tumor resection. This promising immune scenario holds significant potential for selecting suitable candidates for immunotherapy in glioblastoma.