Journal of Pathology Clinical Research最新文献

In addition to the traditional staging system in colorectal cancer (CRC), the Immunoscore® has been proposed to characterize the level of immune infiltration in tumor tissue and as a potential prognostic marker. The aim of this study was to examine and validate associations of an immune cell score analogous to the Immunoscore® with established molecular tumor markers and with CRC patient survival in a routine setting. Patients from a population-based cohort study with available CRC tumor tissue blocks were included in this analysis. CD3+ and CD8+ tumor infiltrating lymphocytes in the tumor center and invasive margin were determined in stained tumor tissue slides. Based on the T-cell density in each region, an  immune cell score closely analogous to the concept of the Immunoscore® was calculated and tumors categorized into IS-low, IS-intermediate, or IS-high. Logistic regression models were used to assess associations between clinicopathological characteristics with the immune cell score, and Cox proportional hazards models to analyze associations with cancer-specific, relapse-free, and overall survival. From 1,535 patients with CRC, 411 (27%) had IS-high tumors. Microsatellite instability (MSI-high) was strongly associated with higher immune cell score levels (p < 0.001). Stage I–III patients with IS-high had better CRC-specific and relapse-free survival compared to patients with IS-low (hazard ratio [HR] = 0.42 [0.27–0.66] and HR = 0.45 [0.31–0.67], respectively). Patients with microsatellite stable (MSS) tumors and IS-high had better survival (HR_CSS = 0.60 [0.42–0.88]) compared to MSS/IS-low patients. In this population-based cohort of CRC patients, the immune cell score was significantly associated with better patient survival. It was a similarly strong prognostic marker in patients with MSI-high tumors and in the larger group of patients with MSS tumors. Additionally, this study showed that it is possible to implement an analogous immune cell score approach and validate the Immunoscore® using open source software in an academic setting. Thus, the Immunoscore® could be useful to improve the traditional staging system in colon and rectal cancer used in clinical practice.

Colon mucosae of ulcerative colitis (UC) and Crohn's disease (CD) display differences in the number and distribution of immune cells that are difficult to assess by eye. Deep learning-based analysis on whole slide images (WSIs) allows extraction of complex quantitative data that can be used to uncover different inflammatory patterns. We aimed to explore the distribution of CD3 and γδ T cells in colon mucosal compartments in histologically inactive and active inflammatory bowel disease. By deep learning-based segmentation and cell detection on WSIs from a well-defined cohort of CD (n = 37), UC (n = 58), and healthy controls (HCs, n = 33), we quantified CD3 and γδ T cells within and beneath the epithelium and in lamina propria in proximal and distal colon mucosa, defined by the Nancy histological index. We found that inactive CD had significantly fewer intraepithelial γδ T cells than inactive UC, but higher total number of CD3 cells in all compartments than UC and HCs. Disease activity was associated with a massive loss of intraepithelial γδ T cells in UC, but not in CD. The total intraepithelial number of CD3 cells remained constant regardless of disease activity in both CD and UC. There were more mucosal CD3 and γδ T cells in proximal versus distal colon. Oral corticosteroids had an impact on γδ T cell numbers, while age, gender, and disease duration did not. Relative abundance of γδ T cells in mucosa and blood did not correlate. This study reveals significant differences in the total number of CD3 and γδ T cells in particularly the epithelial area between CD, UC, and HCs, and demonstrates useful application of deep segmentation to quantify cells in mucosal compartments.

Deep learning models are increasingly being used to interpret whole-slide images (WSIs) in digital pathology and to predict genetic mutations. Currently, it is commonly assumed that tumor regions have most of the predictive power. However, it is reasonable to assume that other tissues from the tumor microenvironment may also provide important predictive information. In this paper, we propose an unsupervised clustering-based multiple-instance deep learning model for the prediction of genetic mutations using WSIs of three cancer types obtained from The Cancer Genome Atlas. Our proposed model facilitates the identification of spatial regions related to specific gene mutations and exclusion of patches that lack predictive information through the use of unsupervised clustering. This results in a more accurate prediction of gene mutations when compared with models using all image patches on WSIs and two recently published algorithms for all three different cancer types evaluated in this study. In addition, our study validates the hypothesis that the prediction of gene mutations solely based on tumor regions on WSI slides may not always provide the best performance. Other tissue types in the tumor microenvironment could provide a better prediction ability than tumor tissues alone. These results highlight the heterogeneity in the tumor microenvironment and the importance of identification of predictive image patches in digital pathology prediction tasks.

Tumor stem cells play a pivotal role in carcinogenesis and metastatic spread in colorectal cancer (CRC). Olfactomedin 4 (OLFM4) is co-expressed with the established stem cell marker leucine-rich repeat-containing G protein-coupled receptor 5 at the bottom of intestinal crypts and has been suggested as a surrogate for cancer stemness and a biomarker in gastrointestinal tumors associated with prognosis. Therefore, it was the aim of the present study to clarify whether OLFM4 is involved in carcinogenesis and metastatic spread in CRC. We used a combined approach of functional assays using forced OLFM4 overexpression in human CRC cell lines, xenograft mice, and an immunohistochemical approach using patient tissues to investigate the impact of OLFM4 on stemness, canonical Wnt signaling, properties of metastasis and differentiation as well as prognosis. OLFM4 expression correlated weakly with tumor grade in one patient cohort (metastasis collection: p = 0.05; pooled analysis of metastasis collection and survival collection: p = 0.19) and paralleled the expression of differentiation markers (FABP2, MUC2, and CK20) (p = 0.002) but did not correlate with stemness-associated markers. Further analyses in CRC cells lines as well as xenograft mice including forced overexpression of OLFM4 revealed that OLFM4 neither altered the expression of markers of stemness nor epithelial–mesenchymal transition, nor did OLFM4 itself drive proliferation, migration, or colony formation, which are all prerequisites of carcinogenesis and tumor progression. In line with this, we found no significant correlation between OLFM4 expression, metastasis, and patient survival. In summary, expression of OLFM4 in human CRC seems to be characteristic of differentiation marker expression in CRC but is not a driver of carcinogenesis nor metastatic spread.

Elastin (ELN) fibers are essential constituents of the tumor microenvironment of gastric cancer (GC). However, few studies have investigated the clinical prognostic significance of ELN in GC. We screened for molecular markers that were highly related to distant metastasis by transcriptome sequencing. The Cancer Genome Atlas (TCGA) and Harbin Medical University (HMU) validation cohorts were used to validate ELN expression and to explore molecular mechanisms. Immunohistochemistry for ELN, vimentin (VIM), and fibroblast activation protein, and elastic fiber-specific staining were used to evaluate the relationship between ELN and prognosis. R studio was used to construct a nomogram prognostic model. In this study, we found that ELN mRNA levels were significantly higher in cancer tissues and were associated with poor prognosis in TCGA and HMU patients. Gene set enrichment analysis showed that ELN was mainly enriched in the epithelial–mesenchymal transition (EMT) pathway. The mRNA expression of ELN was positively correlated with fibroblast molecular markers, especially VIM. For validation, we collected a tissue microarray containing 180 pairs of samples. We found that ELN was positively correlated with VIM expression in cancer tissue but not in paracancerous tissues by immunohistochemistry staining. Univariate and multivariate analyses showed that the expression of ELN and lymph node metastasis rate were independent predictors for overall survival. Moreover, a nomogram model was used to evaluate the risk of death by combining the expression of ELN and lymph node metastasis rate. ELN may play an important role in the progression of GC by regulating EMT and is a useful prognostic indicator in predicting the prognosis of GC.

Neurodegenerative diseases such as Parkinson's disease (PD), Alzheimer's disease (AD), and amyotrophic lateral sclerosis (ALS) are traditionally considered strictly neurological disorders. However, clinical presentation is not restricted to neurological systems, and non-central nervous system (CNS) manifestations, particularly gastrointestinal (GI) symptoms, are common. Our objective was to understand the systemic distribution of pathology in archived non-CNS tissues, taken as part of routine clinical practice during life from people with ALS. We examined tissue from 13 people who went on to develop ALS; including sporadic ALS (n = 12) and C9orf72 hexanucleotide repeat expansion (n = 1). The tissue cohort consisted of 68 formalin-fixed paraffin embedded samples from 21 surgical cases (some patients having more than one case over their lifetimes), from 8 organ systems, which we examined for evidence of phosphorylated TDP-43 (pTDP-43) pathology. We identified pTDP-43 aggregates in multiple cell types of the GI tract, including macrophages and dendritic cells within the lamina propria; as well as ganglion/neuronal and glial cells of the myenteric plexus. Aggregates were also noted within lymph node parenchyma, blood vessel endothelial cells, and chondrocytes. We note that in all cases with non-CNS pTDP-43 pathology, aggregates were present prior to ALS diagnosis and in some instances preceded neurological symptom onset by more than 10 years. These data imply that patients with microscopically unexplained non-CNS symptoms could have occult protein aggregation that could be detected many years prior to neurological involvement.

Fundoscopy is the standard method for diagnosis and follow-up of intraocular retinoblastoma, but it is sometimes insufficient to discern whether tumors are inactivated following treatments. In this work, we hypothesized that the amount of conserved nuclear DNA sequences in the cell-free DNA (cfDNA) fraction of the aqueous humor (AH) might complement fundoscopy for retinoblastoma follow-up. To address our hypothesis, we developed highly sensitive droplet digital polymerase chain reaction (ddPCR) methods to quantify highly conserved DNA sequences of nucleus-encoded genes (GAPDH and B4GALNT1) and of a mitochondrial gene, MT-ATP6. We obtained AH samples during intravitreal treatments. We analyzed 42 AH samples from 25 patients with intraocular retinoblastoma and 11 AH from controls (non-cancer patients). According to clinical criteria, we grouped patients as having progression-free or progressive retinoblastoma. cfDNA concentration in the AH was similar in both retinoblastoma groups. Copy counts for nucleus-derived sequences of GAPDH and B4GALNT1 were significantly higher in the AH from patients with progressive disease, compared to the AH from progression-free patients and control non-cancer patients. The presence of mitochondrial DNA in the AH explained that both retinoblastoma groups had similar cfDNA concentration in AH. The optimal cut-off point for discriminating between progressive and progression-free retinoblastomas was 108 GAPDH copies per reaction. Among patients having serial AH samples analyzed during their intravitreal chemotherapy, GAPDH copies were high and decreased below the cut-off point in those patients responding to chemotherapy. In contrast, one non-responder patient remained with values above the cut-off during follow-up, until enucleation. We conclude that the measurement of conserved nuclear gene sequences in AH allows follow-up of intraocular retinoblastoma during intravitreal treatment. The method is applicable to all patients and could be relevant for those in which fundoscopy evaluation is inconclusive.

The necessity to accurately predict recurrence and clinical outcome in early stage colorectal cancer (CRC) is critical to identify those patients who may benefit from adjuvant chemotherapy. Here, we developed and validated a gene-based risk-score algorithm for patient stratification and personalised treatment in early stage disease based on alterations in the secretion of metastasis-related proteins. A quantitative label-free proteomic analysis of the secretome of highly and poorly metastatic CRC cell lines with different genetic backgrounds revealed 153 differentially secreted proteins (fold-change >5). These changes in the secretome were validated at the transcriptomic level. Starting from 119 up-regulated proteins, a six-gene/protein-based prognostic signature composed of IGFBP3, CD109, LTBP1, PSAP, BMP1, and NPC2 was identified after sequential discovery, training, and validation in four different cohorts. This signature was used to develop a risk-score algorithm, named SEC6, for patient stratification. SEC6 risk-score components showed higher expression in the poor prognosis CRC subtypes: consensus molecular subtype 4 (CMS4), CRIS-B, and stem-like. High expression of the signature was also associated with patients showing dMMR, CIMP⁺ status, and BRAF mutations. In addition, the SEC6 signature was associated with lower overall survival, progression-free interval, and disease-specific survival in stage II and III patients. SEC6-based risk stratification indicated that 5-FU treatment was beneficial for low-risk patients, whereas only aggressive treatments (FOLFOX and FOLFIRI) provided benefits to high-risk patients in stages II and III. In summary, this novel risk-score demonstrates the value of the secretome compartment as a reliable source for the retrieval of biomarkers with high prognostic and chemotherapy-predictive capacity, providing a potential new tool for tailoring decision-making in patient care.

Grading of squamous cell carcinomas (SCCs) based on tumour budding and cell nest size has been termed cellular dissociation grading (CDG) and was suggested as a robust outcome predictor when assessed in biopsies and resections of various extrapulmonary SCCs. In pulmonary SCC (pSCC), this has so far been shown only for resected cancers. As most lung cancers are inoperable, it is of utmost importance to clarify whether the prognostic impact of CDG is retained in the biopsy setting. Two independent pSCC biopsy cohorts from Munich (n = 134, non-resected) and Heidelberg (n = 135, resected) were assessed. Tumour budding and cell nest size measures were assembled into the three-tiered CDG system (G1–G3). Data were correlated with clinicopathological parameters and overall- (OS), disease-specific- (DSS), and disease-free survival (DFS). Interobserver variability and concordance between biopsy and resection specimen were also investigated. CDG was highly congruent between biopsy and resection specimens (κ = 0.77, p < 0.001). In both pSCC cohorts, biopsy-derived CDG strongly impacted on OS, DSS, and DFS (e.g. DFS: p < 0.001). In multivariate survival analyses, CDG remained a stage independent predictor of survival in both cohorts (DFS: p < 0.001 respectively; hazard ratio Munich cohort: CDG-G2: 4.31, CDG-G3; 5.14; Heidelberg cohort: CDG-G2: 5.87, CDG-G3: 9.07). Interobserver agreement for CDG was almost perfect (κ = 0.84, p < 0.001). We conclude that assessment of CDG based on tumour budding and cell nest size is feasible on pSCC biopsies and harbours stage independent prognostic information in resectable as well as non-resectable pSCC. Integration of this grading approach into clinicopathological routine should be considered.

Programmed cell death-1 (PD-1) and its ligand (PD-L1) are significant mediators of immune suppression in the tumor microenvironment. We focused on the immunological impact of PD-1/PD-L1 signaling during tumor progression in colorectal carcinoma (CRC) and its association with resistance to neoadjuvant chemoradiotherapy (NCRT) in locally advanced rectal carcinoma (LAd-RC). Histopathological and immunohistochemical analyses of 100 CRC cases (including 34 RC) without NCRT and 109 NCRT-treated LAd-RC cases were performed. Membranous tumoral PD-L1 expression was identified in 9 of 100 (9%) CRC cases, including 1 of 34 (2.9%) RC cases, but PD-L1 immunopositivity was not associated with any clinicopathological factors, with the exception of deficient mismatch repair (dMMR) status. In contrast, stromal PD-L1+ immune cells, which frequently exhibited coexpression of PD-1 and CD8 markers, were significantly correlated with tumor vessel invasion, nuclear β-catenin+ tumor budding cancer stem cell (CSC)-like features, and unfavorable prognosis. In the LAd-RC cases, stromal CD8+ (but not PD-L1+) immune cell infiltration in pretreatment-biopsied samples was significantly and positively associated with therapeutic efficacy. After NCRT, tumoral PD-L1 expression was observed in only 2 of 83 (2.4%) tumors, independent of dMMR status, whereas high stromal PD-L1+ and tumoral nuclear β-catenin positivity were significantly linked to a poor response to NCRT and high tumor budding features. In addition, high stromal PD-L1 immunoreactivity was significantly associated with poorer overall survival. In conclusion, a combination of stromal PD-L1+ immune cells and nuclear β-catenin+ tumor budding may contribute to tumor progression in CRC and resistance to NCRT in LAd-RC, through formation of niche-like lesions that exhibit immune resistance and CSC properties.