Journal of Pathology Clinical Research最新文献

Everolimus is widely used in patients with advanced ER-positive, HER2-negative breast cancer. We looked at alterations in the PIK3CA/AKT/mTOR pathway in a multicenter cohort as potential biomarkers of efficacy. Patients with advanced ER-positive, HER2-negative breast cancer treated with everolimus and endocrine therapy between 2012 and 2014 in two cancer centers were included. Targeted sequencing examined mutations in PIK3CA, ESR1, and AKT1 genes. An immunochemical analysis was conducted to evaluate expression of PTEN, INPP4B, STK11, p4EBP1, and pS6. We analyzed 71 patients (44 primary tumors; 27 metastatic tissues). Median age was 63 years [58–69]. All patients had heavily pretreated advanced disease. A mutation in the PIK3CA pathway was observed in 32 samples (PIK3CA exons 10 and 21 and AKT1 exon 4 in 15.5%, 24.0%, and 5.6% of samples), and in ESR1 in 5 samples (7.0%), respectively. Most samples showed cytoplasmic expression of the PIK3CA pathway proteins. Progression-free survival was longer in patients with a pS6 or p4EBP1 histoscore ≥ median value (6.6 versus 3.7 months, p = 0.037), and in patients with a PTEN histoscore ≤ median value (7.1 versus 5.3 months, p = 0.02). Overall survival was longer in patients with pS6 ≥ 3rd quartile (27.6 versus 19.3 months, p = 0.038) and in patients with any mutation in the PIK3CA/AKT/mTOR pathway (27.6 versus 19.3 months, p = 0.011). The prognosis of patients treated with everolimus for advanced ER-positive, HER2-negative breast cancer appears primarily driven by molecular features associated with the activation of the PIK3CA/AKT/mTOR pathway.

Upper tract urothelial carcinoma (UTUC) is a rare and aggressive, yet understudied, urothelial carcinoma (UC). The more frequent UC of the bladder comprises several molecular subtypes, associated with different targeted therapies and overlapping with protein-based subtypes. However, if and how these findings extend to UTUC remains unclear. Artificial intelligence-based approaches could help elucidate UTUC's biology and extend access to targeted treatments to a wider patient audience. Here, UTUC protein-based subtypes were identified, and a deep-learning (DL) workflow was developed to predict them directly from routine histopathological H&E slides. Protein-based subtypes in a retrospective cohort of 163 invasive tumors were assigned by hierarchical clustering of the immunohistochemical expression of three luminal (FOXA1, GATA3, and CK20) and three basal (CD44, CK5, and CK14) markers. Cluster analysis identified distinctive luminal (N = 80) and basal (N = 42) subtypes. The luminal subtype mostly included pushing, papillary tumors, whereas the basal subtype diffusely infiltrating, non-papillary tumors. DL model building relied on a transfer-learning approach by fine-tuning a pre-trained ResNet50. Classification performance was measured via three-fold repeated cross-validation. A mean area under the receiver operating characteristic curve of 0.83 (95% CI: 0.67–0.99), 0.8 (95% CI: 0.62–0.99), and 0.81 (95% CI: 0.65–0.96) was reached in the three repetitions. High-confidence DL-based predicted subtypes showed significant associations (p < 0.001) with morphological features, i.e. tumor type, histological subtypes, and infiltration type. Furthermore, a significant association was found with programmed cell death ligand 1 (PD-L1) combined positive score (p < 0.001) and FGFR3 mutational status (p = 0.002), with high-confidence basal predictions containing a higher proportion of PD-L1 positive samples and high-confidence luminal predictions a higher proportion of FGFR3-mutated samples. Testing of the DL model on an independent cohort highlighted the importance to accommodate histological subtypes. Taken together, our DL workflow can predict protein-based UTUC subtypes, associated with the presence of targetable alterations, directly from H&E slides.

Breast cancers involving mutations in homologous recombination (HR) genes, most commonly BRCA1 and BRCA2 (BRCA1/2), respond well to PARP inhibitors and platinum-based chemotherapy. However, except for these specific HR genes, it is not clear which other mutations contribute to homologous recombination defects (HRD). Here, we performed next-generation sequencing of tumor tissues and matched blood samples from 119 breast cancer patients using the OncoScreen Plus panel. Genomic mutation characteristics and HRD scores were analyzed. In the HR genes, we found that BRCA1/2 and PLAB2 mutations were related to HRD. HRD was also detected in a subset of patients without germline or somatic mutations in BRCA1/2, PLAB2, or other HR-related genes. Notably, LRP1B, NOTCH3, GATA2, and CARD11 (abbreviated as LNGC) mutations were associated with high HRD scores in breast cancer patients. Furthermore, functional experiments demonstrated that silencing CARD11 and GATA2 impairs HR repair efficiency and enhances the sensitivity of tumor cells to olaparib treatment. In summary, in the absence of mutations in the HR genes, the sensitivity of tumor cells to PARP inhibitors and platinum-based chemotherapy may be enhanced in a subset of breast cancer patients with LNGC somatic mutations.

An increasing number of manuscripts related to digital and computational pathology are being submitted to The Journal of Pathology: Clinical Research as part of the continuous evolution from digital imaging and algorithm-based digital pathology to computational pathology and artificial intelligence. However, despite these technological advances, tissue analysis still relies heavily on pathologists' annotations. There are three crucial elements to the pathologist's role during annotation tasks: granularity, time constraints, and responsibility for the interpretation of computational results. Granularity involves detailed annotations, including case level, regional, and cellular features; and integration of attributions from different sources. Time constraints due to pathologist shortages have led to the development of techniques to expedite annotation tasks from cell-level attributions up to so-called unsupervised learning. The impact of pathologists may seem diminished, but their role is crucial in providing ground truth and connecting pathological knowledge generation with computational advancements. Measures to display results back to pathologists and reflections about correctly applied diagnostic criteria are mandatory to maintain fidelity during human–machine interactions. Collaboration and iterative processes, such as human-in-the-loop machine learning are key for continuous improvement, ensuring the pathologist's involvement in evaluating computational results and closing the loop for clinical applicability. The journal is interested particularly in the clinical diagnostic application of computational pathology and invites submissions that address the issues raised in this editorial.

We performed comprehensive analyses of somatic copy number alterations (SCNAs) and gene expression profiles of gastric intramucosal neoplasia (IMN) using array-based methods in 97 intestinal-type IMNs, including 39 low-grade dysplasias (LGDs), 37 high-grade dysplasias (HGDs), and 26 intramucosal carcinomas (IMCs) with stromal invasion of the lamina propria to identify the molecular mechanism of IMN. In addition, we examined gene mutations using gene panel analyses. We used cluster analyses for exclusion of arbitrariness to identify SCNA patterns and expression profiles. IMNs were classified into two distinct subgroups (subgroups 1 and 2) based on SCNA patterns. Subgroup 1 showed a genomic stable pattern due to the low frequency of SCNAs, whereas subgroup 2 exhibited a chromosomal instability pattern due to the high frequencies of SCNAs and TP53 mutations. Interestingly, although the frequencies of LGD and HGD were significantly higher in subgroup 1 than in subgroup 2, IMC was commonly found in both types. Although the expression profiles of specific mRNAs could be used to categorise subgroups 1 and 2, no clinicopathological findings correlated with either subgroup. We examined signalling pathways specific to subgroups 1 and 2 to identify the association of each subgroup with signalling pathways based on gene ontology tree visualisation: subgroups 1 and 2 were associated with haem metabolism and chromosomal instability, respectively. These findings reveal a comprehensive genomic landscape that highlights the molecular complexity of IMNs and provide a road map to facilitate our understanding of gastric IMNs.

Clear cell renal cell carcinoma (ccRCC) is one of the most common subtypes of renal cancer, with 30% of patients presenting with systemic disease at diagnosis. This aggressiveness is a consequence of the activation of epithelial–mesenchymal transition (EMT) caused by many different inducers or regulators, signaling cascades, epigenetic regulation, and the tumor environment. Alterations in EMT-related genes and transcription factors are associated with poor prognosis in ccRCC. EMT-related factors suppress E-cadherin expression and are associated with tumor progression, local invasion, and metastasis. The aim of this study was to investigate the expression levels and prognostic significance of macrophage migration inhibitory factor (MIF), β-catenin, and E-cadherin in ccRCC patients. We examined these proteins immunohistochemically in tumor areas and adjacent normal tissues resected from patients with ccRCC. Analysis of the cancer genome atlas (TCGA) cohort was performed to verify our results. Kaplan–Meier analysis showed that median overall survival (OS) was significantly shorter in patients with tumors exhibiting high MIFⁿ and MIF^m-c levels compared to those with low MIFⁿ and MIF^m-c levels (p = 0.03 and p = 0.007, respectively). In the TCGA cohort, there was a significant correlation between MIF expression and OS (p < 0.0001). In conclusion, this study provides further evidence for the biological and prognostic value of MIF in the context of EMT as a potential early prognostic marker for advanced-stage ccRCC.

Up to 30% of colorectal cancers (CRCs) develop from sessile serrated lesions (SSLs). Within the serrated neoplasia pathway, at least two principally distinct oncogenetic routes exist generating microsatellite-stable and microsatellite-instable CRCs, respectively. Aberrant DNA methylation (DNAm) is found early in the serrated pathway and might play a role in both oncogenetic routes. We studied a cohort of 23 SSLs with a small focus (<10 mm) of dysplasia or cancer, 10 of which were MLH1 deficient and 13 MLH1 proficient. By comparing, for each SSL, the methylation status of (1) the region of dysplasia or cancer (SSL-D), (2) the nondysplastic SSL (SSL), and (3) adjacent normal mucosa, differentially methylated probes (DMPs) and regions (DMRs) were assessed both genome-wide as well as in a tumor-suppressor gene-focused approach. By comparing DNAm of MLH1-deficient SSL-Ds with their corresponding SSLs, we identified five DMRs, including those annotating for PRDM2 and, not unexpectedly, MLH1. PRDM2 gene promotor methylation was associated with MLH1 expression status, as it was largely hypermethylated in MLH1-deficient SSL-Ds and hypomethylated in MLH1-proficient SSL-Ds. Significantly increased DNAm levels of PRDM2 and MLH1, in particular at ‘critical’ MLH1 probe sites, were to some extent already visible in SSLs as compared to normal mucosa (p = 0.02, p = 0.01, p < 0.0001, respectively). No DMRs, nor DMPs, were identified for SSLs destined to evolve into MLH1-proficient SSL-Ds. Our data indicate that, within both arms of the serrated CRC pathway, the majority of the epigenetic alterations are introduced early during SSL formation. Promoter hypermethylation of PRDM2 and MLH1 on the other hand specifically initiates in SSLs destined to transform into MLH1-deficient CRCs suggesting that the fate of SSLs may not necessarily result from a stochastic process but possibly is already imprinted and predisposed.

Brain metastases are secondary brain tumours characterised by their aggressive nature and poor prognosis. Breast cancer is one of the most common primary tumours in women to spread to the brain. A lack of biomarkers predicting likely spread to the brain and limited therapeutic interventions represents major areas of clinical unmet need. We investigated N-myc downregulated gene-1 (NDRG1) as a clinically relevant biomarker in breast cancer brain metastasis patients. NDRG1 expression was investigated using immunohistochemistry on tissue microarrays of two clinical cohorts: (i) brain metastatic breast cancers (n = 48) and brain metastases (n = 64; including a subset of 39 patient-matched breast and brain metastasis cases) and (ii) unselected primary breast cancers (n = 336). NDRG1 was highly expressed in breast-to-brain metastases, as well as in high-grade primary breast cancers. High NDRG1 expression and also an absence of expression were associated with worse survival outcomes in both breast cancer and breast cancer brain metastasis patients. This establishes NDRG1 as a ‘Goldilocks’ protein, where too much or too little has a negative effect on survival. We pose that this accounts for its previous categorisation as both tumour suppressor and oncoprotein. Additionally, a shift in NDRG1 localisation with a gain of nuclear expression was seen at the brain metastasis stage. Significant survival benefit in cases expressing cytoplasmic NDRG1 was observed, whereas NDRG1 localisation in the nucleus showed a clear association with poorer survival. In vitro analyses revealed that hypoxic stress significantly elevated NDRG1 expression and resulted in its nuclear localisation. Our findings suggest NDRG1 expression and subcellular localisation are clinically relevant biomarkers for poor prognosis in breast cancer and breast cancer brain metastasis.

The GUSTO clinical trial (Gene expression subtypes of Urothelial carcinoma: Stratified Treatment and Oncological outcomes) uses molecular subtypes to guide neoadjuvant therapies in participants with muscle-invasive bladder cancer (MIBC). Before commencing the GUSTO trial, we needed to determine the reliability of a commercial subtyping platform (Decipher Bladder; Veracyte) when performed in an external trial laboratory as this has not been done previously. Here, we report our pre-trial verification of the TCGA molecular subtyping model using gene expression profiling. Formalin-fixed paraffin-embedded tissue blocks of MIBC were used for gene expression subtyping by gene expression microarrays. Intra- and inter-laboratory technical reproducibilities, together with quality control of laboratory and bioinformatics processes, were assessed. Eighteen samples underwent analysis. RNA of sufficient quality and quantity was successfully extracted from all samples. All subtypes were represented in the cohort. Each sample was subtyped twice in our laboratory and once in a separate reference laboratory. No clinically significant discordance in subtype occurred between intra- or inter-laboratory replicates. Examination of sample histopathology showed variability of morphological appearances within and between subtypes. Overall, these results show that molecular subtyping by gene expression profiling is reproducible, robust and suitable for use in the GUSTO clinical trial.

Most invasive lobular breast carcinomas (ILBCs) are luminal-type carcinomas with an HER2-negative phenotype (ERBB2 or HER2 un-amplified) and CDH1 mutations. Rare variants include ERBB2-amplified subtypes associated with an unfavorable prognosis and less response to anti-HER2 targeted therapies. We analyzed the clinicopathological and molecular features of ERBB2-amplified ILBC and compared these characteristics with ERBB2-unamplified ILBC. A total of 253 patients with ILBC were analyzed. Paraffin-embedded formalin-fixed tumor samples from 250 of these patients were added to a tissue microarray. Protein expression of prognostic, stem cell and breast-specific markers was tested by immunohistochemistry (IHC). Hybrid capture-based comprehensive genomic profiling (CGP) was performed for 10 ILBCs that were either fluorescent in situ hybridization (FISH) or IHC positive for HER2 amplification/overexpression and 10 ILBCs that were either FISH or IHC negative. Results were compared with a CGP database of 44,293 invasive breast carcinomas. The CGP definition of ERBB2 amplification was five copies or greater. A total of 17 of 255 ILBC (5%) were ERBB2 amplified. ERBB2-amplified ILBC had higher tumor stage (p < 0.0001), more frequent positive nodal status (p = 0.00022), more distant metastases (p = 0.012), and higher histological grade (p < 0.0001), and were more often hormone receptor negative (p < 0.001) and more often SOX10 positive (p = 0.005). ERBB2 short variant sequence mutations were more often detected in ERBB2-unamplified tumors (6/10, p = 0.027), whereas CDH1 mutations/copy loss were frequently present in both subgroups (9/10 and 7/10, respectively). Amplification of pathogenic genes were more common in HER2-positive ILBC (p = 0.0009). CDK12 gene amplification (≥6 copies) was detected in 7 of 10 ERBB2-amplified ILBC (p = 0.018). There were no CDK12 gene amplifications reported in 44,293 invasive breast carcinomas in the FMI Insights CGP database. ERBB2-amplified ILBC is a distinct molecular subgroup with frequent coamplification of CDK12, whereas ERBB2 sequence mutations occur only in ERBB2-unamplified ILBC. CDK12/ERBB2 co-amplification may explain the poor prognosis and therapy resistance of ERBB2-amplified ILBC.