Pathobiology最新文献

Pediatric hematologic malignancies often show genetic features distinct from their adult counterparts, which reflect the differences in their pathogenesis. Advances in the molecular diagnostics including the widespread use of next-generation sequencing technology have revolutionized the diagnostic workup for hematologic disorders and led to the identification of new disease subgroups as well as prognostic information that impacts the clinical treatment. The increasing recognition of the importance of germline predisposition in various hematologic malignancies also shapes the disease models and management. Although germline predisposition variants can occur in patients with myelodysplastic syndrome/neoplasm (MDS) of all ages, the frequency is highest in the pediatric patient population. Therefore, evaluation for germline predisposition in the pediatric group can have significant clinical impact. This review discusses the recent advances in juvenile myelomonocytic leukemia, pediatric acute myeloid leukemia, B-lymphoblastic leukemia/lymphoma, and pediatric MDS. This review also includes a brief discussion of the updated classifications from the International Consensus Classification (ICC) and the 5th edition World Health Organization (WHO) classification regarding these disease entities.

The expanding digitalization of routine diagnostic histological slides holds a potential to apply artificial intelligence (AI) to pathology, including bone marrow (BM) histology. In this perspective, we describe potential tasks in diagnostics that can be supported, investigations that can be guided, and questions that can be answered by the future application of AI on whole-slide images of BM biopsies. These range from characterization of cell lineages and quantification of cells and stromal structures to disease prediction. First glimpses show an exciting potential to detect subtle phenotypic changes with AI that are due to specific genotypes. The discussion is illustrated by examples of current AI research using BM biopsy slides. In addition, we briefly discuss current challenges for implementation of AI-supported diagnostics.

Introduction: The incidence of myelodysplastic syndrome and acute myeloid leukemia is significantly increased in children with Down syndrome (DS). Within the revised 2016 WHO edition, these entities are jointly classified as myeloid leukemia associated with DS (ML-DS). Additionally, infants with DS may develop transient abnormal myelopoiesis (TAM) which is histomorphologically similar to ML-DS. While TAM is self-limiting, it is associated with an increased risk of subsequently developing ML-DS. Differentiating TAM and ML-DS is challenging but clinically critical.

Methods: We performed a retrospective review of ML-DS and TAM cases collected from five large academic institutions in the USA. We assessed clinical, pathological, immunophenotypical, and molecular features to identify differentiating criteria.

Results: Forty cases were identified: 28 ML-DS and 12 TAM. Several features were diagnostically distinct, including younger age in TAM (p < 0.05), as well as presentation with clinically significant anemia and thrombocytopenia in ML-DS (p < 0.001). Dyserythropoiesis was unique to ML-DS, as well as structural cytogenetic abnormalities aside from the constitutional trisomy 21. Immunophenotypic characteristics of TAM and ML-DS were indistinguishable, including the aberrant expression of CD7 and CD56 by the myeloid blasts.

Discussion: The findings of the study confirm marked biological similarities between TAM and ML-DS. At the same time, several significant clinical, morphological, and genetic differences were observed between TAM and ML-DS. The clinical approach and the differential diagnosis between these entities are discussed in detail.

Introduction: Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal types of malignancy, with poor prognosis and rising incidence. IQ motif containing GTPase-activating protein 3 (IQGAP3) is a member of the IQGAPs family of scaffolding proteins that govern multiple cellular activities like cytoskeletal remodeling and cellular signal transduction. This study aimed to analyze the expression and biological function of IQGAP3 in PDAC.

Methods: We analyzed IQGAP3 expression in 81 PDAC samples by immunohistochemistry. RNA interference was used to inhibit IQGAP3 expression in PDAC cell lines.

Results: Immunohistochemical analysis of IQGAP3 showed that 54.3% of PDACs were positive for cytoplasmic expression of IQGAP3, with no expression found in non-neoplastic tissue. Furthermore, IQGAP3 expression was an independent poor prognostic factor in our immunostaining-based studies and analyses of public databases. Our cohort and the Cancer Genome Atlas database indicated that IQGAP3 is co-localized with kinesin family member C1 (KIFC1), which we previously reported as a cancer stem cell-associated protein. IQGAP3 small interfering RNA treatment decreased PDAC cell proliferation and spheroid colony formation via ERK and AKT pathways.

Discussion/conclusion: These results suggest that IQGAP3, a transmembrane protein, is involved in survival and stemness and may be a promising new therapeutic target for PDAC.

Background: Perineural invasion (PNI) is a complex molecular process histologically represented by the presence of tumor cells within the peripheral nerve sheath and defined when infiltration into the 3 nerve sheath layers can be clearly identified. Several molecular pathways have been implicated in cSCC. PNI is a well-recognized risk factor in cutaneous squamous cell carcinoma (cSCC) and its accurate assessment represents a challenging field in pathology daily practice.

Summary: As a highly intricate and dynamic process, PNI involves a contingent on bidirectional signaling interactions between the tumor and various nerve components, such as Schwann cells and neurons. The current staging systems recommend the identification of PNI as a dichotomous variable (presence vs. absence) to identify a subgroup of high-risk patients. However, recent further insights revealed that the evaluation of morphological PNI-related features in cSCC may enhance the prognostic stratification of patients and may optimize the current staging guidelines for recurrence risk assessment and improvement of patient selection for postoperative adjuvant treatments. Furthermore, recent emerging biomarkers could redefine early PNI detection.

Key messages: This review provides updated insights into cSCC with PNI, focusing on molecular and cellular pathogenic processes, and aims to increase knowledge on prognostic relevant PNI-related histological features.

Introduction: Lymph node metastasis is one of the most common ways of tumour metastasis. The presence or absence of lymph node involvement influences the cancer's stage, therapy, and prognosis. The integration of artificial intelligence systems in the histopathological diagnosis of lymph nodes after surgery is urgent.

Methods: Here, we propose a pan-origin lymph node cancer metastasis detection system. The system is trained by over 700 whole-slide images (WSIs) and is composed of two deep learning models to locate the lymph nodes and detect cancers.

Results: It achieved an area under the receiver operating characteristic curve (AUC) of 0.958, with a 95.2% sensitivity and 72.2% specificity, on 1,402 WSIs from 49 organs at the National Cancer Center, China. Moreover, we demonstrated that the system could perform robustly with 1,051 WSIs from 52 organs from another medical centre, with an AUC of 0.925.

Conclusion: Our research represents a step forward in a pan-origin lymph node metastasis detection system, providing accurate pathological guidance by reducing the probability of missed diagnosis in routine clinical practice.

Introduction: Tryptophan metabolism has been shown to be involved in tumor development. Two main tryptophan-degrading enzymes, tryptophan 2,3-dioxygenase (TDO2) and indoleamine 2,3-dioxygenase 1 (IDO1), may potently promote cancer cell survival and distant metastasis in diverse types of cancer, such as lung and breast cancer. IDO1 overexpression is an independent prognosticator in gastric cancer (GC). This work aimed to uncover the expression of TDO2 and its clinicopathologic significance in GC.

Methods: TDO2 expression was evaluated in public data of The Cancer Genome Atlas cohort STAD and in two different GC cohorts. Correlation between TDO2 and immune cell infiltrates as well as PD-L1 tumor staining was investigated. The biofunction of TDO2 was examined with MTT, colony formation, and spheroid formation assays by RNA interference.

Results: TDO2 expression was correlated with both progressive disease and clinical outcome, and its expression was an independent predictor of prognosis in GC. TDO2 expression was correlated with infiltration of immune cells and tumor expression of PD-L1. Inhibition of TDO2 expression suppressed cell proliferation, colony formation, and cell invasion of GC cells. Additionally, suppression of TDO2 expression inhibited spheroid body-formation and viability of GC organoids.

Conclusion: Our data show that TDO2 might be a crucial marker for predicting prognosis and targeted therapy in GC.

Introduction: TP53 is the most frequently mutated gene in lung tumors, but its prognostic role in admixed populations, such as Brazilians, remains unclear. In this study, we aimed to evaluate the frequency and clinicopathological impact of TP53 mutations in non-small cell lung cancer (NSCLC) patients in Brazil.

Methods: We analyzed 446 NSCLC patients from Barretos Cancer Hospital. TP53 mutational status was evaluated through targeted next-generation sequencing (NGS) and the variants were biologically classified as disruptive/nondisruptive and as truncating/nontruncating. We also assessed genetic ancestry using 46 ancestry-informative markers. Analysis of lung adenocarcinomas from the cBioportal dataset was performed. We further examined associations of TP53 mutations with patients' clinicopathological features.

Results: TP53 mutations were detected in 64.3% (n = 287/446) of NSCLC cases, with a prevalence of 60.4% (n = 221/366) in lung adenocarcinomas. TP53 mutations were associated with brain metastasis at diagnosis, tobacco consumption, and higher African ancestry. Disruptive and truncating mutations were associated with a younger age at diagnosis. Additionally, cBioportal dataset revealed that TP53 mutations were associated with younger age and Black skin color. Patients harboring disruptive/truncating TP53 mutations had worse overall survival than nondisruptive/nontruncating and wild-type patients.

Conclusion: TP53 mutations are common in Brazilian lung adenocarcinomas, and their biological characterization as disruptive and truncating mutations is associated with African ancestry and shorter overall survival.