PubMed Health⌕ Search

SEARCH · PubMed Health

Results for “Neoplasm Grading”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2Linked to original sources
PubMed2025

Genomic profiling of aggressive pathologic features in lung adenocarcinoma.

INTRODUCTION: Pathologic features involving LVI (lympho-vascular invasion), PNI (perineural invasion), STAS (spread through air spaces), and Grade 3 pattern (from the International Association for the Study of Lung Cancer grading system) are related to having an aggressive phenotype and linked to poor prognosis. However, few studies have conducted in-depth analyses of these features simultaneously with genomic profiling. METHODS: A total of 1559 sequencing of adenocarcinoma samples were included in the common driver mutations analysis, 1306 samples were brought into genomic mapping analysis. OncoSG's East Asian ancestry dataset was implemented for Tumor-Node-Metastasis-Biomarker (TNMB) classification and prognostic assessment. RESULTS: EGFR was more significantly prevalent in LVI negativity (P&#xa0;=&#xa0;0.021), STAS negativity (P&#xa0;=&#xa0;0.002), and moderate grade (P&#xa0;<&#xa0;0.001). ALK was significantly interrelated with LVI (P&#xa0;=&#xa0;0.028), STAS (P&#xa0;<&#xa0;0.001), and poor grade (P&#xa0;<&#xa0;0.001); ROS1 and STAS positivity (P&#xa0;=&#xa0;0.031), poor grade (P&#xa0;=&#xa0;0.016) were significantly related. KRAS (P&#xa0;=&#xa0;0.003) and BRAF-V600E (P&#xa0;=&#xa0;0.002) were only significantly intertwined with poor grade. Apart from common driver mutations, TP53, CHEK2, KEAP1, PTEN, RB1, NF1 were significantly enriched in LVI samples (P&#xa0;<&#xa0;0.05). TP53, PTEN, CTNNB1, HGF, NF1 were more prominent in STAS (P&#xa0;<&#xa0;0.01). TP53, LRP1B, NF1 were significantly more prevalent in Grade 3 pattern (P&#xa0;<&#xa0;0.001). The mixture of STK11, PTEN, and TOP2A generated by exclusive mutations may be a potential predictor of TNMB categorization towards survival. The HR of stage II compared I of TNMB was 2.28 (95&#xa0;% CI 1.36-3.86, P&#xa0;<&#xa0;0.001), while stage III compared II was 1.95 (95&#xa0;% CI 1.04-3.21, P&#xa0;=&#xa0;0.031). CONCLUSIONS: This analysis demonstrated the correlation of pathologic features with common driver mutations, key mutations and canonical oncogenic signaling pathways. The data highlighted the similarities and differences among these features horizontally, and provide new insights in TNMB classification and prognostic assessment.

Humans↗
PubMed2026

Artificial intelligence in kidney cancer: a review of clinical applications across the disease spectrum.

PURPOSE OF REVIEW: This review examines recent advances (2024-2025) in the application of artificial intelligence (AI) to kidney cancer diagnosis, prognosis, and treatment planning. It categorizes studies across 13 clinical scenarios to assess where AI offers the most clinical utility. RECENT FINDINGS: AI models have demonstrated strong performance in a range of tasks including tumor grading, subtype classification, survival prediction, and risk stratification. Integration of radiomics, genomics, and histopathology has enabled personalized, noninvasive, and timely decision-making. The highest-performing models used CT-based radiomics, particularly for predicting progression-free and recurrence-free survival. However, performance varies across tasks and tumor subtypes, with lower accuracy in detecting oncocytomas or benign vs. malignant differentiation. AI applications in metastatic and nonresected cases remain underexplored, and ultrasound remains a largely under researched modality. While some models improve diagnostic accuracy and workflow efficiency, broader validation across diverse populations is still needed. SUMMARY: AI is transforming kidney cancer care across multiple clinical stages. Although promising, real-world implementation demands ongoing validation and postdeployment monitoring to prevent performance degradation due to distributional drift. AI's integration with multimodal data offers substantial potential to improve outcomes and reduce overtreatment.

Humans↗
PubMed2024

Comparative genomic landscape of lower-grade glioma and glioblastoma.

Biomarkers for classifying and grading gliomas have been extensively explored, whereas populations in public databases were mostly Western/European. Based on public databases cannot accurately represent Chinese population. To identify molecular characteristics associated with clinical outcomes of lower-grade glioma (LGG) and glioblastoma (GBM) in the Chinese population, we performed whole-exome sequencing (WES) in 16 LGG and 35 GBM tumor tissues. TP53 (36/51), TERT (31/51), ATRX (16/51), EFGLAM (14/51), and IDH1 (13/51) were the most common genes harboring mutations. IDH1 mutation (c.G395A; p.R132H) was significantly enriched in LGG, whereas PCDHGA10 mutation (c.A265G; p.I89V) in GBM. IDH1-wildtype and PCDHGA10 mutation were significantly related to poor prognosis. IDH1 is an important biomarker in gliomas, whereas PCDHGA10 mutation has not been reported to correlate with gliomas. Different copy number variations (CNVs) and oncogenic signaling pathways were identified between LGG and GBM. Differential genomic landscapes between LGG and GBM were revealed in the Chinese population, and PCDHGA10, for the first time, was identified as the prognostic factor of gliomas. Our results might provide a basis for molecular classification and identification of diagnostic biomarkers and even potential therapeutic targets for gliomas.

Humans↗
PubMed2025

The Proteomic Landscape of CTNNB1 Mutated Low-Grade Early-Stage Endometrial Carcinomas.

Endometrial carcinoma is the most frequent gynecologic malignancy in western countries. In recent years, mutations in CTNNB1 have been associated with worse prognosis in low-risk carcinomas. However, there is a lack of understanding of the proteomic implications of CTNNB1 mutations in this type of tumor. In this study, we performed shotgun proteomics using Formalin-Fixed Paraffin-Embedded (FFPE) tissue samples of CTNNB1 mutated and wild-type low-risk endometrial carcinomas. A publicly available proteomic and transcriptomic database was used to validate results. Differential protein expression and Gene Set Enrichment Analysis revealed dysregulation of pathways associated with cell keratinization, immune response modulation, and intracellular calcium regulation. CTNNB1 mutated tumors showed immune dysregulation at multiple levels including cytokine secretion, cell adhesion, and lymphocyte activation. These results were supported by tissue multiplex immunofluorescence analysis, demonstrating reduced CD8 tumor-infiltrating lymphocytes and different immune spatial interaction patterns. Intracellular calcium dysfunction was associated with key transcript dysregulation. We found an increased expression of CAMK2A and ROR2, suggesting a potential role for non-canonical Wnt pathway activation in CTNNB1 mutated tumors.

Humans↗
PubMed2026

A Novel BRCA1 Pathogenic Variant in Tunisian Patient With High Grade Ovarian Cancer: Favorable Therapeutic Response to Olaparib.

BACKGROUND: Ovarian cancer is one of the leading causes of death from gynecological cancer worldwide. Genetic mutations in genes involved in key cellular functions such as BRCA1/2 play a central role in tumorigenesis and have major implications for targeted therapeutic strategies, especially the use of poly (ADP-ribose) polymerase (PARP) inhibitors. CASE: Herein, we described a case of a 50-year-old woman diagnosed with severe anemia secondary to heavy menometrorrhagia. Initial gynecological evaluation, including transvaginal ultrasound, was unremarkable, and endometrial biopsy was not indicated. Imaging revealed no ovarian abnormalities; however, exploratory laparotomy identified a peritoneal nodule, leading to further investigation. Targeted NGS was performed on somatic and germline DNA samples and showed a frame shift deletion of 10&#x2009;bp (c.1256_1265del: p.R419Ter) in the BRCA1 gene. This variant, identified only in tumor tissues, is novel and classified as pathogenic in ClinVar and ACMG databases. Additional somatic alterations were detected in TP53 and MSH6, while germline testing revealed only a variant of uncertain significance in BARD1. After first-line chemotherapy, the patient benefited from olaparib and achieved a progression-free survival of 23&#x2009;months with good tolerance and no evidence of disease recurrence. CONCLUSION: This finding highlights the importance of integrating tumor-based genomic profiling with germline testing to identify actionable mutations and guide precision oncology. The identification of a novel somatic BRCA1 mutation expands the mutational spectrum of HGSOC and underscores the need to include underrepresented populations, such as those from North Africa, in genomic studies.

Humans↗
PubMed2025

Genomic and Transcriptomic Profiling of Radiation-Resistant, Locally Recurrent Prostate Cancer.

PURPOSE: The biology of locally radiorecurrent prostate cancer (LRR-PCa) is poorly understood. METHODS AND MATERIALS: We sought to explore the genomic and transcriptomic landscape of LRR-PCa with targeted DNA sequencing and RNA expression analysis from 41 biopsy-proven LRR-PCa tumors from 36 unique patients who had a recurrence at a median interval of 84 months (IQR, 70-124 months). Genomic alteration frequencies and transcriptomic data were compared between the LRR-PCa cohort and treatment-na&#xef;ve patients from the Cancer Genome Atlas (genomic; n = 496) and Gleason grade-at-recurrence-matched patients from the Decipher Genomics Resource for Intelligent Discovery (transcriptomic; n = 22,320). RESULTS: Twenty-five patients (69%) had pathologic upgrading at recurrence (17% vs 64% with Gleason grade 4-5 disease; P < .001). The LRR-PCa cohort demonstrated significantly greater single-nucleotide variations in 29 genes known to be associated with prostate cancer, including several associated with increased aggressiveness and DNA repair: FAT1 (58.5% vs 1.0%), RAD51B (36.6% vs 0.4%), POLQ (34.1% vs 1.4%), KMT2C (34.1% vs 4.9%), BRCA2 (29.3% vs 1.8%), ATRX (26.8% vs 0.8%), and BRCA1 (24.4% vs 0.4%) (Pvalues < .001 for all). The LRR-PCa cohort had a significantly higher Decipher score (median, 0.80 vs 0.66; P = .05) and demonstrated significantly greater basal subtype based on PAM50 (56% vs 20%; P < .001) and lower androgen receptor activity (61% for LRR vs 9%; P < .001). CONCLUSIONS: Overall, these results suggest that LRR-PCa has a distinct genomic and transcriptomic landscape from de novo prostate cancer. Specifically, LRR-PCa has an enrichment in SNVs in genes associated with tumor aggressiveness and/or DNA repair, has higher Decipher scores, a more basal subtype, and has transcriptomic evidence of lower androgen receptor activity and loss of tumor suppressor genes.

Humans↗
PubMed2026

Spatial Omics in High-Grade Gliomas: Mapping Immune-Tumor Niches for Precision Therapy.

High-grade gliomas (HGGs), particularly glioblastoma (GBM), remain among the most lethal human cancers despite decades of molecular profiling and therapeutic innovation. A primary reason for treatment failure is that HGG biology is spatial: malignant cell states, immune suppression, metabolic stress, and therapeutic resistance are organized into distinct anatomical and functional niches. Spatial omics technologies now enable high-dimensional mapping of gene expression, protein signaling, immune architecture, and metabolic activity within intact tumor tissue. These approaches reveal how proneural and mesenchymal transcriptional states coexist yet localize to distinct regions, alongside hypoxic, invasive, and stem-enriched niches. Spatial analyses show that key clinical determinants, including O6-methylguanine-DNA methyltransferase (MGMT)-associated temozolomide resistance, radiotherapy tolerance in hypoxic regions, and immunotherapy failure driven by myeloid-dominated immune exclusion, are influenced not only by molecular programs but also by cellular location. Beyond biological insight, spatial omics is reshaping clinical paradigms by enabling region-specific patient stratification, early assessment of treatment response, and identification of therapy-resistant reservoirs that seed recurrence. Prior bulk and single-cell studies defined HGG cell states and pathways but often treated resistance as tumor-wide. This review presents a spatially explicit framework that synthesizes spatial transcriptomic and immune-profiling studies to identify tumor-immune niches and spatial bottlenecks that drive therapeutic failure and recurrence.

Humans↗
PubMed2026

A longitudinal single-cell and spatial multiomic atlas of pediatric high-grade glioma.

Pediatric high-grade glioma (pHGG) is an incurable central nervous system malignancy that is a leading cause of pediatric cancer death. While pHGG shares many similarities with adult glioma, it comprises distinct disease entities. In this study, we longitudinally profile a molecularly diverse cohort of 16 pHGG patients through single-nucleus RNA and ATAC sequencing, whole-genome sequencing, and CODEX spatial proteomics to capture the evolution of neoplastic and microenvironmental features during disease progression and treatment. We define a set of core pHGG neoplastic cell states and observe differential tumor-myeloid interactions between malignant cell phenotypes. We find that essential neuromodulators and the interferon response are upregulated post-therapy, implicating them as malignant cell-intrinsic targets. We observe an increase in oligodendrocytes upon progression and that they coordinate spatial motifs with proneural tumor cells. This multiomic atlas of longitudinal pHGG captures features of therapy response and provides a scalable reference for the study of pediatric brain tumors.

Humans↗
PubMed2026

Cabozantinib for advanced grade 3 neuroendocrine tumors: subgroup analysis of the phase 3 CABINET trial (Alliance A021602).

Well-differentiated grade 3 neuroendocrine tumors (NETs) have recently been described as a distinct category, and randomized data regarding efficacy of therapy for these patients are scarce. In the phase 3 CABINET trial, cabozantinib improved PFS compared with placebo in patients with advanced, previously treated, progressive extra-pancreatic NETs (epNETs) and pancreatic NETs (pNETs) of all grades. Here, we evaluate if these results remain consistent in a subgroup of patients with well-differentiated G3 NETs. Patients with locally advanced or metastatic epNETs or pNETs were randomized 2:1 in independent cohorts to receive cabozantinib 60 mg daily vs placebo. We analyzed outcomes of the subset of patients with G3 NETs (Ki-67 > 20%), combining patients in the pNET and epNET cohorts due to small sample sizes. Twenty-four patients had G3 NETs, 16 randomized to cabozantinib and 8 to placebo. Primary sites included pancreas (n = 12), GI tract (n = 7), unknown primary sites (n = 3), and lung/thymus (n = 2). Median PFS for patients with G3 NETs treated with cabozantinib was 7.9 vs 3 months with placebo (HR = 0.15, 95% CI: 0.04-0.57, 1-sided log-rank P = 0.0034). The confirmed overall radiographic response rate was 25% (4/16) with cabozantinib vs 0% (0/8) with placebo. Safety outcomes were consistent with published data for the trial as a whole. Subset analysis of the CABINET trial showed improved PFS associated with cabozantinib vs placebo for G3 NETs of pancreatic and extra-pancreatic origin. Despite limited numbers, these results suggest that cabozantinib can be an effective option for patients with advanced G3 NETs. ClinicalTrials.gov Identifier: NCT03375320.

Humans↗
PubMed2025

A Subset of Serous Tubal Intraepithelial Carcinoma (STIC)-Like Lesions and Concurrent High-Grade Endometrial Carcinoma Are Genomically Related Entities.

In patients with high-grade endometrial carcinoma (HG-EC), concurrent isolated serous tubal intraepithelial carcinoma (STIC) or STIC-like lesions (STIC-LLs) in the fallopian tube(s) may be found. We sought to determine whether concurrently diagnosed HG-ECs and STIC-LLs are genetically related. Six HG-ECs, including serous carcinomas (n = 4) and carcinosarcomas with serous epithelial component (n = 2), with cooccurring STIC-LLs were identified and subjected to microdissection, DNA extraction, and panel sequencing targeting 468 cancer-related genes or, if DNA quantities were limited, to Sanger sequencing. WT1 and p53 protein expression was assessed by immunohistochemistry. We found that 3 HG-ECs and concurrent STIC-LLs shared pathogenic mutations, such as TP53 hotspot, NF2, FBXW7, and PIK3CA mutations. Immunohistochemical analysis revealed that the HG-EC of case 5 lacked WT1 expression and had aberrant p53 expression, although the matched STIC-LL displayed diffuse WT1 expression. Of the remaining 3 cases that did not show evidence of genetic relatedness based on the targeted sequencing panel, 1 STIC-LL harbored a clonal TP53 missense mutation, whereas the matched HG-EC had a distinct clonal TP53 hotspot mutation, a clonal FBXW7 hotspot mutation, and ERBB2 amplification. At the protein level, the p53 expression patterns of the HG-ECs and STIC-LLs were concordant in these 3 cases. Here, we demonstrate that cooccurring HG-ECs and STIC-LLs are genetically related in a subset of cases.

Humans↗
PubMed2026

Radiomics-based gradient boosting model on contrast-enhanced MRI for non-invasive prediction of epidermal growth factor receptor expression and therapeutic response to EGFR-targeted antibody-drug conjugates in high-grade glioma organoid models.

BACKGROUND: Epidermal growth factor (EGF) and its receptor EGF(EGFR) play crucial roles in glioblastoma (GBM) prognosis. However, non-invasive assessment of their expression remains challenging. This study aimed to determine whether radiomics features extracted from contrast-enhanced MRI could predict EGFR expression in high-grade gliomas (HGG) and to explore their associations with immune infiltration and therapeutic response of EGFR-Targeted antibody drug conjugates(EGFR-ADCs). METHODS: We extracted radiomic features from contrast-enhanced MRI of 298 GBM patients from The Cancer Imaging Archive (TCIA) and matched them with RNA-seq data from The Cancer Genome Atlas (TCGA). Feature selection was performed using minimum redundancy maximum relevance (mRMR) and recursive feature elimination (RFE). Machine learning models were built to predict EGF/EGFR expression. Radiogenomic associations were validated by immune infiltration analysis. Patient-Derived Tumor-Like Cell Clusters (PTC) were used to compare the antitumor efficacy of EGFR- ADCs and temozolomide. RESULTS: Elevated EGF/EGFR expression correlated with poor prognosis and increased infiltration of M2 macrophages, regulatory T cells, and CD4&#x207a; memory T cells. Pathway analysis demonstrated significant enrichment of the mechanistic target of rapamycin (mTOR) and Mitogen-Activated Protein Kinase (MAPK) signaling cascades. Radiomics-based prediction models achieved robust performance (AUC&#x2009;>&#x2009;0.85) in stratifying EGFR expression status. In EGFR-positive tumor tissues, EGFR-ADCs exerted antitumor efficacy similar to that of temozolomide. CONCLUSIONS: EGF/EGFR expression is associated with immunosuppressive microenvironments and adverse outcomes in HGG. Radiomics may provide a non-invasive approach for estimating EGFR expression, although model performance requires external validation and EGFR-ADCs showed partial inhibitory activity within the tested range, though potency remains to be defined.These findings suggest a framework into radiogenomic stratification and targeted therapy in GBM.

Radiomics↗
PubMed2026

Matrix Mechanics Governs Mechano-Metabolic Adaptation across Cancer Grades in Bladder Spheroids.

Extracellular matrix (ECM) mechanics is pivotal regulators of tumor progression, yet how viscoelasticity and matrix architecture converge to shape metabolic and invasive adaptation remains insufficiently defined. We postulate that mechanical stimuli from the ECM induce coordinated changes in adhesive and metabolic pathways, and that the nature of this independent mechano-metabolic pathway is conserved across benign, low-invasive, and high-invasive bladder cancer phenotypes. Therefore, we engineered collagen-hyaluronan hydrogels with tunable stiffness to recapitulate soft and rigid tumor microenvironments and profiled bladder cancer spheroids representing benign, low-invasive, and highly invasive states. Integrating hydraulic force spectroscopy, rheology, and molecular phenotyping, we show that matrix stiffening differentially reprograms spheroid architecture, motility, and adhesion- and metabolism-related gene expression. Spheroid behavior emerged from the interplay between intrinsic mechanical properties, matrix rheology, and molecular adaptation. HCV29 spheroids formed rigid, compact structures, relying on cell-matrix adhesion rather than metabolic or proteolytic remodeling. HT1376 spheroids activated glycolysis (HK2) and MMP-2-dependent ECM remodeling in soft matrices, but remained largely nonmigratory, indicating decoupling of invasive priming from motility. T24 spheroids were soft, deformable, and highly migratory in compliant matrices, integrating metabolic reprogramming, adhesion remodeling (E-/N-cadherin, SDC4), and radial collagen fiber alignment to drive invasion. Notably, canonical FAK/AKT/mTOR signaling was absent across all spheroids, while pS6 ribosomal protein and ILK indicated noncanonical, SDC4/integrin-ILK-dependent mechanotransduction supporting cytoskeletal dynamics, metabolism, and ECM remodeling. Collagen organization further differed across spheroid types, with dense, radially aligned fibers in HT1376, intermediate architecture in HCV29, and loose, disorganized networks in T24, closely matching their distinct migratory behaviors and cell-ECM interactions. These findings reveal stage-specific mechanometabolic strategies in bladder cancer, demonstrating how ECM mechanics and architecture jointly guide invasion, metabolic adaptation, and local immune modulation, including the regulation of immune cell infiltration and tumor immune evasion.

Humans↗
PubMed2026

Profiling tumor immune microenvironment of epithelial ovarian carcinoma.

BACKGROUND: Epithelial ovarian carcinoma (EOC) comprises five main histological subtypes: high-grade serous (HGSOC), low-grade serous (LGSOC), clear cell (CCOC), mucinous (MOC), and endometrioid (ENOC). Each histotype harbors specific genomic alterations and clinical outcome. Few studies systematically compared the tumor immune microenvironment across the five subtypes. METHODS: We performed 7-plex (CD45, CD8, CD68, CD163, FoxP3, CD20, and cytokeratin) sequential immunohistochemistry on a clinically annotated tissue microarray including 139 EOC representing the five subtypes and 26 borderline tumors (serous and mucinous). Digital pathology was used to quantify immune cell abundance, their spatial distribution (stroma vs tumor core), and correlation with survival. RESULTS: Immune cells were dominated by macrophages and more abundant in the stroma than tumor core across the five subtypes, consistent with immune excluded pattern. Compared to HGSOC, CCOC displayed the highest infiltration by CD45+ leukocytes and CD68+ macrophages, particularly M2-like CD163+ cells, suggesting a macrophage-rich, immunosuppressive phenotype. LGSOC exhibited the highest infiltration by intraepithelial FoxP3+ regulatory T cells. Comparison of borderline tumors with invasive carcinoma (LGOSC and MOC) revealed that malignant progression is accompanied by loss of CD8+ T cells, enrichment in regulatory T cells and increase of CD163+/CD68+ ratio, consistent with immune evasion during tumorigenesis. There was a trend toward better survival in HGSOC highly infiltrated by lymphocytes, either intraepithelial (CD8+ and FoxP3+) or stromal (FoxP3+ and CD20+). CONCLUSIONS: EOC is characterized by histotype-specific immune milieux defined by macrophage dominance, epithelial immune exclusion and dynamic immune remodeling during progression from borderline tumors to invasive carcinomas.

Humans↗
PubMed2026

Homologous recombination-deficient high-grade serous ovarian cancers exhibit distinct morphological features.

OBJECTIVE: Access to homologous recombination testing remains limited in many centers. We aim to correlate the morphology and immunophenotype of high-grade serous ovarian carcinoma with homologous recombination statuses. METHODS: A retrospective analysis of a high-grade serous ovarian carcinoma tumors with known homologous recombination status. A pathological review of morphology was performed for each tumor, along with immunohistochemical profiling. Tumor morphology was classified as (1) solid, pseudo-endometrioid, or transitional (2) micropapillary or nested. RESULTS: Overall, 81 tumors were included. The median age was 62 (interquartile range; 52-71). Of those, 27 (33.3%) tumors were BRCA1mut, 19 (23.5%) were BRCA2mut, 15 (18.5%) tumors had no BRCA1 or BRCA2 mutations but exhibited a genomic instability score &#x2265;42 and were classified as BRCA1/2-wild-type with homologous recombinant deficient. The remainder 20 (24.7%) cases were homologous recombinant proficient. The proportion of tumors with solid transitional-like morphology was higher in BRCA1 (12/21, 57%) and BRCA2 (12/18, 67%) compared to the tumors with homologous recombinant proficient (3/17, 18%), p =.019. When stratified by genomic instability score, tumors with low score (genomic instability score <26) exhibited 0% solid transitional-like morphology versus 43% solid transitional-like morphology in high-score (genomic instability score >26), p =.03. PAX8 diffuse expression was detected in 71% of BRCA1, 65% of BRCA2, 92% of BRCA-wild-type homologous recombinant deficient tumors, and 100% of homologous recombinant proficient tumors, p =.071. The proportion of diffuse expression was higher in homologous recombinant proficient (100%) versus BRCA2 (65%) (Bonferroni-adjusted pairwise comparisons). CONCLUSIONS: Homologous recombinant deficient tumors are associated with the solid transitional-like morphology, with the BRCA1/2-mutated homologous recombinant deficient cases showing the strongest correlation. Genomic instability score alone may not fully capture the spectrum of homologous recombinant deficient-related phenotypes. The variation in solid transitional-like morphology features among BRCA1- or BRCA2-mutated, BRCA1/2- wild-type with homologous recombinant deficient, and homologous recombinant proficient cases may reflect the diverse biological spectrum of different homologous recombination alterations.

Humans↗
PubMed1978

Adenocarcinoma of the retinal pigment epithelium.

A 57-year-old woman complaining of decreased vision for six months had a mass expanding the choroid inferonasally in the right eye. Clinical examination, ultrasonography, and fluorescein angiography were consistent with a malignant melanoma. The eye was enucleated and pathologic studies showed an adenocarcinoma of the retinal pigment epithelium (RPE). Malignant tumors of the RPE may simulate exactly choroidal melanomas clinically, but apparently have a much better prognosis, in that very few cases have been documented to produce metastatic disease. The vast majority of cases studied histopathologically, in which a diagnosis of adenocarcinoma of the RPE has been made, are low-grade malignant neoplasms with the absence of invasion beyond the choroid or lamina cribrosa at the time of enucleation.

Adenocarcinoma↗
PubMed1978

Proliferative serous tumors of the ovary. Histologic features and prognosis.

In reviewing all proliferative serous tumors of the ovary seen at Barnes Hospital from 1950 to 1974, we quantitated histologic characteristics and defined criteria for diagnosis in 55 borderline tumors, 13 well-differentiated cystadenocarcinomas, and 15 cystadenomas with unusual proliferative areas. This last type with focal proliferation behaved in a benign fashion and should be considered a variant of a simple cystadenoma. Stromal invasion was the only histologic feature which consistently distinguished carcinomas from the borderline tumors. The presence in some borderline tumors of severe cellular atypia, marked epithelial disorganization, frequent mitoses, and cribriform glands in the stroma neither signified carcinoma nor indicated poor prognosis. No patient with a Stage I borderline lesion died of tumor. Although the mortality of patients with Stage IIb or Stage III borderline tumors is high, tumor-related deaths rarely occurred before 5 years, and three patients lived more than 10 years. Borderline serous tumors are low-grade malignant neoplasms which differ from overt carcinomas in the excellent prognosis of Stage I lesions and in long survival even with widespread abdominal disease.

Cystadenocarcinoma↗
PubMed2026

Graph neural network-based risk stratification of prostate cancer using gene expression and SHAP interpretability.

Accurate risk stratification is essential for guiding treatment decisions and preventing over treatment of prostate cancer, which remains one of the most prevalent cancers among adult men. While the Gleason score, obtained from prostate biopsies, is routinely used to assess tumor aggressiveness, the biopsy procedure carries risks such as pain, infection, and, in some cases, serious complications such as sepsis. In this study, we proposed an artificial intelligence-based framework that integrates mRNA expression profiles with functional interaction networks to classify prostate cancer patients into low-, medium-, and high-risk groups defined by Gleason scores. The pipeline comprised five steps: (1) data collection from The Cancer Genome Atlas (TCGA), (2) preprocessing of gene expression data, (3) two-stage feature selection to identify informative biomarkers, (4) risk classification using a dual-branch graph neural network (GNN) that combines gene-gene interaction graphs with sample-level expression features, and (5) model interpretation using SHAP to quantify feature contributions. Differentially expressed genes were identified in the High (ASPN, GMNN, PEBP4, C2, KNCK17), Medium (C2, IGSF1, ASPN, CDKN3, AMH), and Low (TNMD, VWA5B2, ST6GALNAC5, CYP3A5, PHGR1) risk groups, underscoring the molecular heterogeneity of disease progression. On an independent held-out test set, the model achieved AUCs of 0.86, 0.88, and 0.95 for the low-, medium-, and high-risk groups, respectively, with an overall accuracy of 80%. These results suggest that combining GNN-based modeling with explainable AI can capture both global and local molecular patterns relevant to tumor aggressiveness. However, as the model was developed and evaluated solely on the TCGA cohort, the findings should be regarded as exploratory, and external validation will be required to establish generalizability. Within these limitations, the proposed framework highlights the potential of molecular profiling and graph-based deep learning to support more precise, potentially less invasive, risk assessment and individualized treatment planning in prostate cancer.

Prostatic Neoplasms↗