Journal of Clinical Pathology最新文献

Background and aims: Portosinusoidal vascular disease (PSVD) is a broad term encompassing varied histological patterns with changes in portal tracts and sinusoids without cirrhosis. We aimed to assess whether there is any clinical and pathological difference among the various histological categories of PSVD.

Patients and methods: This study included liver biopsy cases classified as PSVD (2020-2022). Clinical and laboratory parameters were obtained from the electronic records. PSVD cases were histologically categorised as obliterative portal venopathy (OPV), OPV with fibrosis (OPV-F), incomplete septal cirrhosis (ISC), nodular regenerative hyperplasia (NRH), mega sinusoids with fibrosis (MSF) and unclassified. Follow-up complications were recorded.

Results: PSVD categories were OPV (45 (26%)), OPV-F (37 (21.4%)), ISC (20 (11.6%)), NRH (19 (11%)), MSF (19 (11%)) and unclassified (33 (19%)). Elevated hepatic venous pressure gradient (HVPG) was noted in OPV-F (10 (IQR: 12-14.7)) and ISC (12 (IQR: 9-14)) mm Hg with higher fibrosis quantity in liver tissue and elevated procollagen III aminoterminal propeptide, which correlated with HVPG. On immunohistochemistry, OPV-F and ISC showed lesser expression of ADAMT13 in liver biopsies (p<0.001). On follow-up, ascites development was more in OPV-F and ISC than in other categories (p=0.001). Higher liver stiffness measurement (LSM) values were recorded in MSF and NRH, compared with other categories, but it did not correlate with fibrosis in liver biopsy.

Conclusions: OPV-F and ISC had higher HVPG, fibrosis, and more ascites development on follow-up than the other categories of PSVD, and all are not the same. In contrast, MSF and NRH have spuriously high LSM.

Aims: The field of molecular pathology has undergone significant advancements in the clinical impact of sarcoma diagnosis, resulting in challenges to nosology of bone and soft tissue tumours. The surge in molecular data has led to the identification of novel fusions and description of new 'entities'. To illustrate this, we have selected five emerging entities with novel fusions: clear cell stromal tumour of the lung with YAP1::TFE3 fusion, GAB1::ABL1 fusion spindle cell neoplasm, NUTM1-rearranged sarcomas, NR1D1-rearranged sarcomas and calcified chondroid mesenchymal neoplasms.

Methods: Literature for the relevant case reports and case series of these five entities were reviewed and clinicopathological data was collected. Additionally, this review includes a table format of recently described fusion-associated mesenchymal neoplasms.

Results: The morphological and immunohistochemical features, along with diagnostic challenges, are discussed for each entity.

Conclusions: Here, we have provided a review of selected emerging mesenchymal neoplasms, which of these neoplasms will meet the threshold to be 'new entities' remains to be determined.

Aims: Genomic sequencing of lymphomas is under-represented in routine clinical testing despite having prognostic and predictive value. Clinical implementation is challenging due to a lack of consensus on reportable targets and a paucity of reference samples. We organised a cross-validation study of a lymphoma-tailored next-generation sequencing panel between two College of American Pathologists (CAP)-accredited clinical laboratories to mitigate these challenges.

Methods: A consensus for the genomic targets was discussed between the two institutes based on recurrence in diffuse large B-cell lymphoma, follicular lymphoma, mantle cell lymphoma, chronic lymphocytic leukaemia and T-cell lymphomas. Using the same genomic targets, each laboratory ordered libraries independently and a cross-validation study was designed to exchange samples (8 cell lines and 22 clinical samples) and their FASTQ files.

Results: The sensitivity of the panel when comparing different library preparation and bioinformatic workflows was between 97% and 99% and specificity was 100% when a 5% limit of detection cut-off was applied. To evaluate how the current standards for variant classification of tumours apply to lymphomas, the Association for Molecular Pathology/American Society of Clinical Oncology/CAP and OncoKB classification systems were applied to the panel. The majority of variants were assigned a possibly actionable class or likely pathogenic due to more limited evidence in the literature.

Conclusions: The cross-validation study highlights the benefits of sample and data exchange for clinical validation and provided a framework for reporting the findings in lymphoid malignancies.

Aims: Mitogen-activated protein kinase (MAPK) pathway alteration is a major oncogenic driver in paediatric low-grade gliomas (LGG) and some adult gliomas, encompassing BRAF (most common) and non-BRAF alterations. The aim was to determine the frequency, molecular spectrum and clinicopathological features of MAPK-altered gliomas in paediatric and adult patients at our neuropathology site in Kuwait.

Methods: We retrospectively searched the data of molecularly sequenced gliomas between 2018 and 2023 for MAPK alterations, revised the pathology in view of the 2021 WHO classification and evaluated the clinicopathological data for possible correlations.

Results: Of 272 gliomas, 40 (15%) harboured a MAPK pathway alteration in 19 paediatric (median 9.6 years; 1.2-17.6) and 21 adult patients (median 37 years; 18.9-89.2), comprising 42% and 9% of paediatric and adult cases, respectively. Pilocytic astrocytoma and glioblastoma were the most frequent diagnoses in children (47%) and adults (43%), respectively. BRAF V600E (n=17, 43%) showed a wide distribution across age groups, locations and pathological diagnoses while KIAA1549::BRAF fusion (n=8, 20%) was spatially and histologically restricted to cerebellar paediatric LGGs. Non-V600E variants and BRAF amplifications accompanied other molecular aberrations in high-grade tumours. Non-BRAF MAPK alterations (n=8) included mutations and gene fusions involving FGFR1, NTRK2, NF1, ROS1 and MYB. Fusions included KANK1::NTRK2, GOPC::ROS1 (both infant hemispheric gliomas), FGFR1::TACC1 (diffuse LGG), MYB::QKI (angiocentric glioma) and BCR::NTRK2 (glioblastoma). Paradoxical H3 K27M/MAPK co-mutations were observed in two LGGs.

Conclusion: The study provided insights into MAPK-altered gliomas in Kuwait highlighting the differences among paediatric and adult patients and providing a framework for planning therapeutic polices.

Microscopic review of tissue sections is of foundational importance in pathology, yet the traditional chemistry-based histology laboratory methods are labour intensive, tissue destructive, poorly scalable to the evolving needs of precision medicine and cause delays in patient diagnosis and treatment. Recent AI-based techniques offer promise in upending histology workflow; one such method developed by PictorLabs can generate near-instantaneous diagnostic images via a machine learning algorithm. Here, we demonstrate the utility of virtual staining in a blinded, wash-out controlled study of 16 cases of lymph node excisional biopsies, including a spectrum of diagnoses from reactive to lymphoma and compare the diagnostic performance of virtual and chemical H&Es across a range of stain quality, image quality, morphometric assessment and diagnostic interpretation parameters as well as proposed follow-up immunostains. Our results show non-inferior performance of virtual H&E stains across all parameters, including an improved stain quality pass rate (92% vs 79% for virtual vs chemical stains, respectively) and an equivalent rate of binary diagnostic concordance (90% vs 92%). More detailed adjudicated reviews of differential diagnoses and proposed IHC panels showed no major discordances. Virtual H&Es appear fit for purpose and non-inferior to chemical H&Es in diagnostic assessment of clinical lymph node samples, in a limited pilot study.

Background: Methylthioadenosine phosphorylase (MTAP) is an essential metabolic enzyme in the purine and methionine salvage pathway. In cancer, MTAP gene copy number loss (MTAP loss) confers a selective dependency on the related protein arginine methyltransferase 5. The impact of MTAP alterations in gastrointestinal (GI) cancers remains unknown although hypothetically druggable. Here, we aim to investigate the prevalence, clinicopathological features and prognosis of MTAP loss GI cancers.

Methods: Cases with MTAP alterations were retrieved from The Cancer Genome Atlas (TCGA) and a real-world cohort of GI cancers profiled by next-generation sequencing. If MTAP alterations other than loss were found, immunohistochemistry was performed. Finally, we set a case-control study to assess MTAP loss prognostic impact.

Results: Findings across the TCGA dataset (N=1363 patients) and our cohort (N=508) were consistent. Gene loss was the most common MTAP alteration (9.4%), mostly co-occurring with CDKN2A/B loss (97.7%). Biliopancreatic and gastro-oesophageal cancers had the highest prevalence of MTAP loss (20.5% and 12.7%, respectively), being mostly microsatellite stable (99.2%). In colorectal cancer, MTAP loss was rare (1.1%), while most MTAP alterations were mutations (5/7, 71.4%); among the latter, only MTAP-CDKN2B truncation led to protein loss, thus potentially actionable. MTAP loss did not confer worse prognosis.

Conclusions: MTAP alterations are found in 5%-10% of GI cancers, most frequently biliopancreatic and gastro-oesophageal. MTAP loss is the most common alteration, identified almost exclusively in MSS, CDKN2A/B loss, upper-GI cancers. Other MTAP alterations were found in colorectal cancer, but unlikely to cause protein loss and drug susceptibility.

Aims: To evaluate the accuracy of Chat Generative Pre-trained Transformer (ChatGPT) powered by GPT-4 in histopathological image detection and classification of colorectal adenomas using the diagnostic consensus provided by pathologists as a reference standard.

Methods: A study was conducted with 100 colorectal polyp photomicrographs, comprising an equal number of adenomas and non-adenomas, classified by two pathologists. These images were analysed by classic GPT-4 for 1 time in October 2023 and custom GPT-4 for 20 times in December 2023. GPT-4's responses were compared against the reference standard through statistical measures to evaluate its proficiency in histopathological diagnosis, with the pathologists further assessing the model's descriptive accuracy.

Results: GPT-4 demonstrated a median sensitivity of 74% and specificity of 36% for adenoma detection. The median accuracy of polyp classification varied, ranging from 16% for non-specific changes to 36% for tubular adenomas. Its diagnostic consistency, indicated by low kappa values ranging from 0.06 to 0.11, suggested only poor to slight agreement. All of the microscopic descriptions corresponded with their diagnoses. GPT-4 also commented about the limitations in its diagnoses (eg, slide diagnosis best done by pathologists, the inadequacy of single-image diagnostic conclusions, the need for clinical data and a higher magnification view).

Conclusions: GPT-4 showed high sensitivity but low specificity in detecting adenomas and varied accuracy for polyp classification. However, its diagnostic consistency was low. This artificial intelligence tool acknowledged its diagnostic limitations, emphasising the need for a pathologist's expertise and additional clinical context.