Journal of Pathology Clinical Research最新文献

Oesophageal adenocarcinomas may show different histopathological patterns, including excessive acellular mucin pools, signet-ring cells (SRCs), and poorly cohesive cells (PCCs). These components have been suggested to correlate with poor outcomes after neoadjuvant chemoradiotherapy (nCRT), which might influence patient management. However, these factors have not been studied independently of each other with adjustment for tumour differentiation grade (i.e. the presence of well-formed glands), which is a possible confounder. We studied the pre- and post-treatment presence of extracellular mucin, SRCs, and/or PCCs in relation to pathological response and prognosis after nCRT in patients with oesophageal or oesophagogastric junction adenocarcinoma. A total of 325 patients were retrospectively identified from institutional databases of two university hospitals. All patients were scheduled for ChemoRadiotherapy for Oesophageal cancer followed by Surgery Study (CROSS) nCRT and oesophagectomy between 2001 and 2019. Percentages of well-formed glands, extracellular mucin, SRCs, and PCCs were scored in pre-treatment biopsies and post-treatment resection specimens. The association between histopathological factors (≥1 and >10%) and tumour regression grade 3–4 (i.e. >10% residual tumour), overall survival, and disease-free survival (DFS) was evaluated, adjusted for tumour differentiation grade amongst other clinicopathological variables. In pre-treatment biopsies, ≥1% extracellular mucin was present in 66 of 325 patients (20%); ≥1% SRCs in 43 of 325 (13%), and ≥1% PCCs in 126 of 325 (39%). We show that pre-treatment histopathological factors were unrelated to tumour regression grade. Pre-treatment presence of >10% PCCs was associated with lower DFS (hazard ratio [HR] 1.73, 95% CI 1.19–2.53). Patients with post-treatment presence of ≥1% SRCs had higher risk of death (HR 1.81, 95% CI 1.10–2.99). In conclusion, pre-treatment presence of extracellular mucin, SRCs, and/or PCCs is unrelated to pathological response. The presence of these factors should not be an argument to refrain from CROSS. At least 10% PCCs pre-treatment and any SRCs post-treatment, irrespective of the tumour differentiation grade, seem indicative of inferior prognosis, but require further validation in larger cohorts.

Prognostic tools are an essential component of the clinical management of patients with renal cell carcinoma (RCC). Although tumour stage and grade can provide important information, they fail to consider patient- and tumour-specific biology. In this study, we set out to find a novel molecular marker of RCC by using hepatocyte nuclear factor 4A (HNF4A), a transcription factor implicated in RCC progression and malignancy, as a blueprint. Through transcriptomic analyses, we show that the nuclear factor I A (NFIA)-driven transcription network is active in primary RCC and that higher levels of NFIA confer a survival benefit. We validate our findings using immunohistochemical staining and analysis of a 363-patient tissue microarray (TMA), showing for the first time that NFIA can independently predict poor cancer-specific survival in clear cell RCC (ccRCC) patients (hazard ratio = 0.46, 95% CI = 0.24–0.85, p value = 0.014). Furthermore, we confirm the association of HNF4A with higher grades and stages in ccRCC in our TMA cohort. We present novel data that show HNF4A protein expression does not confer favourable prognosis in papillary RCC, confirming our survival analysis with publicly available HNF4A RNA expression data. Further work is required to elucidate the functional role of NFIA in RCC as well as the testing of these markers on patient material from diverse multi-centre cohorts, to establish their value for the prognostication of RCC.

Our objective was to test whether p53 expression status is associated with survival for women diagnosed with the most common ovarian carcinoma histotypes (high-grade serous carcinoma [HGSC], endometrioid carcinoma [EC], and clear cell carcinoma [CCC]) using a large multi-institutional cohort from the Ovarian Tumor Tissue Analysis (OTTA) consortium. p53 expression was assessed on 6,678 cases represented on tissue microarrays from 25 participating OTTA study sites using a previously validated immunohistochemical (IHC) assay as a surrogate for the presence and functional effect of TP53 mutations. Three abnormal expression patterns (overexpression, complete absence, and cytoplasmic) and the normal (wild type) pattern were recorded. Survival analyses were performed by histotype. The frequency of abnormal p53 expression was 93.4% (4,630/4,957) in HGSC compared to 11.9% (116/973) in EC and 11.5% (86/748) in CCC. In HGSC, there were no differences in overall survival across the abnormal p53 expression patterns. However, in EC and CCC, abnormal p53 expression was associated with an increased risk of death for women diagnosed with EC in multivariate analysis compared to normal p53 as the reference (hazard ratio [HR] = 2.18, 95% confidence interval [CI] 1.36–3.47, p = 0.0011) and with CCC (HR = 1.57, 95% CI 1.11–2.22, p = 0.012). Abnormal p53 was also associated with shorter overall survival in The International Federation of Gynecology and Obstetrics stage I/II EC and CCC. Our study provides further evidence that functional groups of TP53 mutations assessed by abnormal surrogate p53 IHC patterns are not associated with survival in HGSC. In contrast, we validate that abnormal p53 IHC is a strong independent prognostic marker for EC and demonstrate for the first time an independent prognostic association of abnormal p53 IHC with overall survival in patients with CCC.

In recent years, the treatment of breast cancer has advanced dramatically and neoadjuvant chemotherapy (NAC) has become a common treatment method, especially for locally advanced breast cancer. However, other than the subtype of breast cancer, no clear factor indicating sensitivity to NAC has been identified. In this study, we attempted to use artificial intelligence (AI) to predict the effect of preoperative chemotherapy from hematoxylin and eosin images of pathological tissue obtained from needle biopsies prior to chemotherapy. Application of AI to pathological images typically uses a single machine-learning model such as support vector machines (SVMs) or deep convolutional neural networks (CNNs). However, cancer tissues are extremely diverse and learning with a realistic number of cases limits the prediction accuracy of a single model. In this study, we propose a novel pipeline system that uses three independent models each focusing on different characteristics of cancer atypia. Our system uses a CNN model to learn structural atypia from image patches and SVM and random forest models to learn nuclear atypia from fine-grained nuclear features extracted by image analysis methods. It was able to predict the NAC response with 95.15% accuracy on a test set of 103 unseen cases. We believe that this AI pipeline system will contribute to the adoption of personalized medicine in NAC therapy for breast cancer.

Gamma-butyrobetaine dioxygenase (BBOX1) is a catalyst for the conversion of gamma-butyrobetaine to l-carnitine, which is detected in normal renal tubules. The purpose of this study was to analyze the prognosis, immune response, and genetic alterations associated with low BBOX1 expression in patients with clear cell renal cell carcinoma (RCC). We analyzed the relative influence of BBOX1 on survival using machine learning and investigated drugs that can inhibit renal cancer cells with low BBOX1 expression. We analyzed clinicopathologic factors, survival rates, immune profiles, and gene sets according to BBOX1 expression in a total of 857 patients with kidney cancer from the Hanyang University Hospital cohort (247 cases) and The Cancer Genome Atlas (610 cases). We employed immunohistochemical staining, gene set enrichment analysis, in silico cytometry, pathway network analyses, in vitro drug screening, and gradient boosting machines. BBOX1 expression in RCC was decreased compared with that in normal tissues. Low BBOX1 expression was associated with poor prognosis, decreased CD8+ T cells, and increased neutrophils. In gene set enrichment analyses, low BBOX1 expression was related to gene sets with oncogenic activity and a weak immune response. In pathway network analysis, BBOX1 was linked to regulation of various T cells and programmed death-ligand 1. In vitro drug screening showed that midostaurin, BAY-61-3606, GSK690693, and linifanib inhibited the growth of RCC cells with low BBOX1 expression. Low BBOX1 expression in patients with RCC is related to short survival time and reduced CD8+ T cells; midostaurin, among other drugs, may have enhanced therapeutic effects in this context.

Cancer progression is influenced by junctional adhesion molecule (JAM) family members. The relationship between JAM family members and different types of cancer was examined using The Cancer Genome Atlas dataset. mRNA levels of the F11R (F11 receptor) in tumours were inversely correlated to the expression of JAM-2 and JAM-3. This relationship was unique to breast cancer (BCa) and was associated with poor prognosis (p = 0.024, hazard ratio = 1.44 [1.05–1.99]). A 50-gene molecular signature (prediction analysis of microarray 50) was used to subtype BCa. F11R mRNA expression significantly increased in human epidermal growth factor receptor 2 (HER2)-enriched (p = 0.0035) and basal-like BCa tumours (p = 0.0005). We evaluated F11R protein levels in two different compositions of BCa subtype patient tissue array cohorts to determine the relationship between BCa subtype and prognosis. Immunohistochemistry staining revealed that a high F11R protein level was associated with poor overall survival (p < 0.001; Taipei Medical University [TMU] cohort, p < 0.001; Kaohsiung Veterans General Hospital [KVGH] cohort) or disease-free survival (p < 0.001 [TMU cohort], p = 0.034 [KVGH cohort]) in patients with BCa. Comparison of F11R levels in different subtypes revealed the association of poor prognosis with high levels of F11R among luminal (p < 0.001 [TMU cohort], p = 0.027 [KVGH cohort]), HER2 positive (p = 0.018 [TMU cohort], p = 0.037 [KVGH cohort]), and triple-negative (p = 0.013 [TMU cohort], p = 0.037 [KVGH cohort]) BCa. F11R-based RNA microarray analysis and Ingenuity Pathway Analysis were successful in profiling the detailed gene ontology of triple-negative BCa cells regulated by F11R. The EP300 transcription factor was highly correlated with F11R in BCa (R = 0.51, p < 0.001). By analysing these F11R-affected molecules with the L1000CDs datasets, we were able to predict some repurposing drugs for potential application in F11R-positive BCa treatment.

Diffuse pleural mesothelioma (PM) is a highly aggressive tumour typically associated with short survival. Recently, the effectiveness of first-line immune checkpoint inhibitors in patients with unresectable PM was reported. CD70–CD27 signalling plays a co-stimulatory role in promoting T cell expansion and differentiation through the nuclear factor κB (NF-κB) pathway. Conversely, the PD-L1 (CD274)–PD-1 (PDCD1) pathway is crucial for the modulation of immune responses in normal conditions. Nevertheless, pathological activation of both the CD70–CD27 and PD-L1–PD-1 pathways by aberrantly expressed CD70 and PD-L1 participates in the immune evasion of tumour cells. In this study, 171 well-characterised PMs including epithelioid (n = 144), biphasic (n = 15), and sarcomatoid (n = 12) histotypes were evaluated immunohistochemically for CD70, PD-L1, and immune cell markers such as CD3, CD4, CD8, CD56, PD-1, FOXP3, CD68, and CD163. Eight percent (14/171) of mesotheliomas simultaneously expressed CD70 and PD-L1 on the tumour cell membrane. PMs co-expressing CD70 and PD-L1 contained significantly higher numbers of CD8+ (p = 0.0016), FOXP3+ (p = 0.00075), and CD163+ (p = 0.0011) immune cells within their microenvironments. Overall survival was significantly decreased in the cohort of patients with PM co-expressing CD70 and PD-L1 (p < 0.0001). In vitro experiments revealed that PD-L1 and CD70 additively enhanced the motility and invasiveness of PM cells. In contrast, PM cell proliferation was suppressed by PD-L1. PD-L1 enhanced mesenchymal phenotypes such as N-cadherin up-regulation. Collectively, these findings suggest that CD70 and PD-L1 both enhance the malignant phenotypes of PM and diminish anti-tumour immune responses. Based on our observations, combination therapy targeting these signalling pathways might be useful in patients with PM.

Intrahepatic cholangiocarcinoma harbours druggable genetic lesions including FGFR2 gene fusions. Reliable and accurate detection of these fusions is becoming a critical component of the molecular work-up, but real-world data on the performance of fluorescence in situ hybridisation (FISH) and targeted RNA-based next-generation sequencing (NGS) are very limited. Bridging this gap, we report results of the first round robin test for FGFR2 fusions in cholangiocarcinoma and contextualise test data with genomic architecture. A cohort of 10 cholangiocarcinoma (4 fusion positive and 6 fusion negative) was tested by the Institute of Pathology, University Hospital Heidelberg, Germany. Data were validated by four academic pathology departments in Germany. Fusion-positive cases comprised FGFR2::BICC1, FGFR2::DBP, FGFR2::TRIM8, and FGFR2::ATE1 fusions. In a second step, a round robin test involving 21 academic and non-academic centres testing with RNA-based NGS approaches was carried out; five participants performed FISH testing in addition. Thirteen of 16 (81%) centres successfully passed the NGS only and 3 of 5 (60%) centres passed the combined NGS + FISH round robin test. Identified obstacles were bioinformatic pipelines not optimised for the detection of FGFR2 fusions and assays not capable of detecting unknown fusion partners. This study shows the benefit of targeted RNA-NGS for the detection of FGFR2 gene fusions. Due to the marked heterogeneity of the genomic architecture of these fusions, fusion partner agnostic (i.e. open) methodological approaches that are capable of identifying yet unknown fusion partners are superior. Furthermore, we highlight pitfalls in subsequent bioinformatic analysis and limitations of FISH-based tests.

CD47 expressed on tumor cells binds to signal regulatory protein alpha on macrophages, initiating inhibition of phagocytosis. We investigated the relationships between tumor expression of CD47 and CD68 macrophage content, subsets of tumor-infiltrating lymphocytes (TILs), and vascular invasion in breast cancer. A population-based series of 282 cases (200 screen detected and 82 interval patients) from the Norwegian Breast Cancer Screening Program was examined. Immunohistochemical staining for CD47 and CD68 was evaluated on tissue microarray (TMA) slides. For CD47 evaluation, a staining index was used. CD68 tumor-associated macrophages were counted and dichotomized. TIL subsets (CD45, CD3, CD4, CD8, and FOXP3) were counted and dichotomized using immunohistochemistry on TMA slides. Vascular invasion (both lymphatic and blood vessel) was determined on whole tissue slides. High CD47 tumor cell expression or high counts of CD68 macrophages were significantly associated with elevated levels of all TIL subsets (p < 0.02), CD163 macrophages (p < 0.001), blood vessel invasion (CD31 positive) (p < 0.01), and high tumor cell Ki67 (p < 0.004). High CD47 expression was associated with ER negativity (p < 0.001), HER2 positive status (p = 0.03), and interval-detected tumors (p = 0.03). Combined high expression of CD47–CD68 was associated with a shorter recurrence-free survival (RFS) by multivariate analysis (hazard ratio [HR]: 2.37, p = 0.018), adjusting for tumor diameter, histologic grade, lymph node status, and molecular subtype. Patients with luminal A tumors showed a shorter RFS for CD47–CD68 high cases by multivariate assessment (HR: 5.73, p = 0.004). This study demonstrates an association of concurrent high CD47 tumor cell expression and high CD68 macrophage counts with various TIL subsets, blood vessel invasion (CD31 positive), other aggressive tumor features, and interval-presenting breast cancer. Our findings suggest a link between CD47, tumor immune response, and blood vessel invasion (CD31 positive). Combined high expression of CD47–CD68 was an independent prognostic factor associated with poor prognosis in all cases, as well as in the luminal A category.