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PubMed2026

STK11 Mutations and Deletions Define an Aggressive Molecular Subgroup of Cervical Adenocarcinoma.

Cervical adenocarcinoma accounts for 15%-20% of cervical cancers and is associated with poorer survival and reduced response to screening and immunotherapy compared with squamous cell carcinoma (SCC). The genomic drivers underlying this molecular subgroup remain incompletely characterized. Whole-exome sequencing was performed on 302 invasive cervical cancers from Guatemala and Venezuela. Structural variation analysis was conducted using SNP-array and whole-genome sequencing data. Findings were replicated in more than 4600 additional cervical cancer samples from TCGA, AACR Project GENIE, MSKCC, and Caris datasets. TP53 mutations were more frequent in adenocarcinoma than SCC, particularly in HPV-negative tumors. STK11 alterations, including mutations and focal deletions, were significantly enriched in HPV-positive adenocarcinomas compared with SCC and affected 23% of adenocarcinomas overall. Whole-genome analyses identified recurrent focal deletions, inversions, chromosomal rearrangements, and breakage-fusion-bridge events involving chromosome 19p and STK11 that were not detected by exome sequencing alone. STK11 alterations were associated with younger age at diagnosis, poorer overall survival, and inferior outcomes following immune checkpoint inhibitor (ICI) therapy. STK11 alterations significantly co-occurred with YAP1 amplification but were largely mutually exclusive with PIK3CA mutation. Cervical adenocarcinomas also demonstrated significantly lower CD274 (PD-L1) expression than SCC. STK11 alterations define a distinct molecular subgroup of cervical adenocarcinoma characterized by structural disruption of chromosome 19p, younger age at onset, and poorer clinical outcomes. These findings have implications for molecular classification and future targeted therapeutic approaches in cervical cancer.

Humans↗
PubMed2026

HeteroGeNETics: Neuroendocrine tumor genetics reflect their heterogeneous complex diversity.

Neuroendocrine neoplasms (NENs) comprise a diverse group of malignancies arising across multiple anatomical sites and displaying remarkable biological and clinical heterogeneity. While advances in sequencing have identified recurrent genetic alterations in several NEN subtypes, these tumors remain largely characterized by a relatively low mutational burden and lack of dominant oncogenic drivers. Consequently, emerging evidence suggests that the molecular basis of neuroendocrine tumorigenesis extends beyond individual mutations and involves broader processes such as chromatin remodeling, telomere maintenance, epigenetic dysregulation and cellular plasticity. This review aims to summarize the current molecular landscape of pulmonary, gastro-enteropancreatic and thymic NENs, focusing on the biological pathways and cellular programs disrupted by recurrent genetic alterations unrelated to syndromes. We discuss how multi-omic studies have refined molecular classification and revealed common principles underlying neuroendocrine tumor development. Collectively, recent literature supports a shift from mutation-centered models toward a more integrated understanding of the complex biology and evolution of NENs.

genomics↗
PubMed2026

SCLC TumorMiner: A genomics platform for small cell lung cancer precision oncology.

Small cell lung cancer (SCLC) is among the most aggressive malignancies. Unlike many other cancers, it is not represented in The Cancer Genome Atlas, and available datasets are fragmented across institutions, disease stages, and treatment settings. RNA sequencing provides a powerful and cost-effective approach, but the high dimensionality of transcriptomic data and the heterogeneity of patient cohorts pose significant challenges. To address such challenges, we developed SCLC TumorMiner (https://discover.nci.nih.gov/SclcTumorMinerCDB/), which includes 50 tumor samples from relapsed patients at the National Cancer Institute (NCI) and 154 samples from untreated patients at the University of Cologne and Tongji University. SCLC TumorMiner enables molecular classification, genomic pathway analyses, risk stratification, identification of predictive cell-surface biomarkers such as DLL3 or TROP2, and drug-response biomarkers such as SLFN11. SCLC TumorMiner illustrates profound differences between untreated and relapsed patient samples. Additionally, "MyPatient", one of SCLC TumorMiner's modules, is presented as a medical assistant application prototype.

SCLC↗
PubMed2026

Proteomic and metabolomic profiling reveals dysregulation of immune states, mucin-type glycosylation and steroid metabolism in extramammary Paget's disease.

BACKGROUND: Extramammary Paget's disease is a rare cutaneous adenocarcinoma characterized by mucin-rich Paget cells and chronic inflammation, yet its molecular basis remains unclear. OBJECTIVE: To systematically characterize the proteomic and metabolomic landscape of EMPD, uncover immune heterogeneity, and identify molecular pathways underlying tumor progression and microenvironment remodeling. METHODS: We performed integrated proteomic and metabolomic analyses on 92 male tumor patients and 30 healthy controls, identifying 10,217 proteins and 1466 metabolites. RESULTS: Extramammary Paget's disease lesions exhibited broad activation of inflammatory pathways. Immune profiling further uncovered substantial inflammatory heterogeneity, delineating immune-cold and immune-hot subtypes, with the latter associated with stronger invasive potential. Aberrant mucin-type glycosylation was also prominent, featuring Tn-modified MUC1 and MUC5AC accompanied by elevated GALNT7, GALNT6, GALNT4, and ST6GAL1, which correlated with inflammatory intensity. Metabolomic data demonstrated elevated levels of testosterone, dehydroepiandrosterone, and related intermediates in tumor tissues, indicating an androgen-enriched metabolic profile in extramammary Paget's disease. CONCLUSION: These findings reveal immune, glycoproteomic, and metabolomic pathways in extramammary Paget's disease pathogenesis and provide novel insights for molecular classification and therapeutic targeting.

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↗
PubMed2026

The KEAP1-NFE2L2/NRF2 Axis in Non-Small Cell Lung Cancer Radioresistance: Redox Homeostasis and Emerging DNA Damage Response Mechanisms.

Radioresistance and local recurrence remain major barriers to effective radiotherapy in non-small cell lung cancer (NSCLC). Loss-of-function KEAP1 alterations or activating NFE2L2 alterations can stabilize NRF2, but do not alone establish sustained transcriptional activity or functional dependency. This focused narrative review evaluates clinical radiotherapy studies and mechanistically informative preclinical studies linking the KEAP1-NFE2L2/NRF2 axis to NSCLC radioresistance. We prioritized clinical studies reporting radiotherapy-specific outcomes and preclinical studies coupling NRF2-related molecular status or perturbation with radiation-response endpoints; contextual studies informed metabolic, DNA damage response (DDR), immune and normal-lung effects. Evidence most consistently supports NRF2-mediated redox protection through glutathione-dependent defense, cellular reducing capacity and antioxidant enzymes, limiting radiation-induced reactive oxygen species (ROS) accumulation and oxidative injury. Limited studies further suggest that NRF2 may affect DNA-damage signaling, checkpoint control and repair. The detailed RPA32-TOPBP1-ATR-CHK1 model is therefore considered proposed rather than established in NRF2-active NSCLC. Retrospective clinical studies associate pathogenic KEAP1/NFE2L2 alterations with impaired local control in some radiotherapy-treated cohorts, but do not justify treating genomic status, protein abundance, transcriptional activity and functional dependency as equivalent measures or demonstrate treatment-predictive value. NRF2-mediated normal-lung protection also constrains systemic inhibition. Prospective studies integrating molecular classification, radiation-response endpoints, local control and normal-tissue toxicity are required before biomarker-guided radiosensitization can be considered.

DNA damage response↗
PubMed2026

Mapping the de-implementation of traditional diagnostic tests in pediatric acute lymphoblastic leukemia.

INTRODUCTION: Advances in cancer diagnostics raise questions about when and how to de-implement traditional approaches; however, these processes remain poorly described. At St. Jude Children's Research Hospital (SJCRH), routine conventional cytogenetics for pediatric acute lymphoblastic leukemia (ALL) diagnosis was de-implemented in 2018 following adoption of clinical genomics. This study aimed to map this process to inform future diagnostic de-implementation initiatives. METHODS: Interviews were conducted with SJCRH staff involved or impacted by cytogenetics de-implementation. Data were analyzed using thematic and rapid qualitative analysis informed by the Consolidated Framework for Implementation Research. Member-checking was used to verify and refine process maps, which were subsequently reviewed by an external expert panel, representing diverse settings, through focus group discussions. RESULTS: Thirteen SJCRH clinicians participated. De-implementation was described as successful, with no negative impact on patient outcomes. Decision-making began with internal correlation studies that demonstrated superior diagnostic performance of clinical genomics. De-implementation was viewed as a natural evolution that improved molecular classification, resource allocation, and workflow efficiency. Perceived risks included loss of cytogenetics competency, delayed turnaround time, and career insecurity, all addressed institutionally. Lessons learned highlighted the importance of deliberate discussion about logic and evidence supporting de-implementation. Fifteen external experts offered suggestions to improve process map generalizability, highlighting institutional- and system-level considerations. CONCLUSION: De-implementation of cytogenetics in ALL in favor of clinical genomics was successful at SJCRH. This study offers an example of diagnostic de-implementation in cancer care and proposes a structured approach to guide future efforts. De-implementation should be considered alongside introduction of novel diagnostic approaches.

cancer diagnostics↗
PubMed2025

Recent Advances in nccRCC Classification and Therapeutic Approaches.

Non-clear cell renal cell carcinoma (nccRCC) constitutes a biologically diverse category of renal malignancies. The 2022 WHO classification framework has significantly evolved to incorporate molecularly defined entities alongside traditional histologic subtypes, reflecting the growing recognition of distinct pathogenic drivers. Current therapeutic paradigms for advanced disease remain suboptimal, with treatment strategies often extrapolated from clear cell renal cell carcinoma (ccRCC). In this review, we highlight transformative multi-omics approaches to address nccRCC's profound heterogeneity, which enables molecular stratification beyond conventional pathology, identifying novel subtypes characterized by unique immune microenvironment features, metabolic profiles, and genomic instability patterns. This molecular reclassification provides a foundational framework for precision oncology, facilitating patient selection for targeted therapies and immunomodulatory strategies. Advancements in multi-omics subtyping represent a pivotal shift toward biologically guided clinical management and underscore the imperative for biomarker-driven therapeutic development in nccRCC.

Humans↗
PubMed2025

A functional assay to classify RB1 variants of uncertain significance.

PURPOSE: The RB1 gene encodes the retinoblastoma protein (pRB) playing a major role in cell cycle control, particularly by its interaction with E2F transcription factors. Familial forms of retinoblastoma are caused by germline pathogenic variants in the RB1 gene predisposing to retinoblastoma and other tumors. By analyzing the RB1 gene in patients with retinoblastoma, we found that missense variants often remain variants of uncertain significance (VUS). METHODS: To classify RB1 VUS, we developed a functional assay evaluating their impact on the ability of pRB to inhibit the activity of the E2F1 promoter, with a luciferase reporter gene. A set of 14 pathogenic/likely pathogenic and benign/likely benign RB1 variants was used for validation. RESULTS: We tested 16 VUS detected in patients with retinoblastoma and found that 9 VUS reduced the ability of pRB to inhibit E2F1 promoter. Among them, the (RB1) c.2263T>G p.(Phe755Val) variant showed a reduced level of pRB on Western blot, suggesting a defect in pRB stability. By applying the criterion PS3_moderate of the American College of Medical Genetics and Genomics/Association for Molecular Pathology classification to this functional assay, 5 of the 9 VUS with functional impact could be classified as likely pathogenic. CONCLUSION: This functional assay can improve the molecular diagnosis of retinoblastoma predisposition by a better determination of pathogenic/likely pathogenic RB1 variants.

Humans↗
PubMed2025

CSGL: chemical synthesis graph learning for molecule representation.

MOTIVATION: Molecule representation learning (MRL) translates molecules into a real vector space, serving as input to downstream tasks in biology, chemistry, and computer science. This article introduces a chemical synthesis graph learning (CSGL) framework, which enhances MRL by considering both the atomic structures of molecules and their roles in chemical reactions through a hierarchical graph representation. Specifically, molecules are first modeled based on their molecular graphs, which capture atomic-level structural information. They are then further refined using a chemical synthesis graph, where nodes represent reactant and product molecule sets, and edges encode chemical transformations between reactants and products (e.g. changes in molecular structures). CSGL optimizes molecular embeddings of reactant and product nodes in a fashion that ensures the embeddings conform to a chemical balance constraint. RESULTS: Experimental results show that our method CSGL achieves strong performance on a variety of tasks, including product prediction, reaction classification, and molecular property prediction. AVAILABILITY AND IMPLEMENTATION: https://github.com/li-2023/CSGL.

Machine Learning↗
PubMed2026

Integrated expression profiling of trophoblast cell-surface antigen 2 (TROP2), folate receptor alpha (FRα), and human epidermal growth factor receptor 2 (HER2) in endometrial Cancer across molecular classes, genomic alterations, and histologic subtypes.

OBJECTIVE: Antibody-drug conjugates (ADCs) are expanding treatment options in endometrial carcinoma, but the distribution of actionable surface targets across histologic, molecular, and genomic subgroups remains incompletely defined. METHODS: This single-institution retrospective tissue microarray (TMA) study included 312 endometrial carcinomas: 158 endometrioid and 154 serous tumors. Trophoblast cell-surface antigen 2 (TROP2) was quantified by histochemical score (H-score); human epidermal growth factor receptor 2 (HER2) was assessed using endometrial carcinoma-specific and gastric/DESTINY-PanTumor02 criteria; and folate receptor alpha (FRα) positivity was defined as ≥75% viable tumor cells with ≥2+ membranous staining. Molecular class was assigned using a hierarchical DNA polymerase epsilon (POLE)-mutant, microsatellite instability/mismatch repair-deficient (MSI/MMRd), p53-abnormal, and no specific molecular profile (NSMP) classifier. Tumor mutational burden (TMB) and recurrent genomic alterations were analyzed in relation to biomarker expression. RESULTS: TROP2 was broadly expressed, with median H-scores of 280 in endometrioid and 200 in serous carcinomas. HER2 gastric-score 2+/3+ expression and FRα positivity were enriched in serous versus endometrioid carcinoma (22.5% vs 8.9% and 20.1% vs 4.4%), restricted to FIGO grade 3 tumors, and concentrated in p53-abnormal disease. FRα positivity was absent in POLE-mutant and MSI/MMRd tumors. HER2 2+/3+ expression correlated with erb-b2 receptor tyrosine kinase 2 (ERBB2) alterations, whereas FRα-positive tumors were enriched for TP53 alterations and showed lower frequencies of ARID1A and PTEN alterations. Triple-negative TROP2/HER2/FRα tumors were uncommon (6/308, 1.9%). CONCLUSIONS: TROP2 is broadly expressed in endometrial carcinoma, whereas HER2 and FRα define a more restricted high-grade, serous/serous-like, p53-abnormal compartment, supporting biomarker-informed ADC development.

Humans↗
PubMed2025

Phosphoproteomics delineates hepatocellular carcinoma subtypes and pinpoints therapeutic targets.

BACKGROUND AND AIMS: Only a minority of patients could benefit from systemic therapy owing to the high heterogeneity of HCC. Therefore, a deeper understanding of the pathogenesis of HCC is essential for precision therapy. Genomic and proteomic studies of HCC have enhanced our understanding of HCC. However, the phosphoproteomic characterization of HCC remains poorly understood. APPROACH AND RESULTS: We conducted an in-depth analysis of a clinical cohort of HCC using high-coverage phosphoproteomic. Effective therapeutic targets were validated using liver cancer cell lines and HCC patient-derived xenograft mouse models that correspond to the phosphoproteomic subtypes of HCC. Phosphoproteomic analysis classified HCC into 3 subtypes, A, B, and C, with increasing malignancy and correlation with clinical features, including patient prognosis, tumor staging, serum alpha-fetoprotein levels, tumor thrombus, and tumor size. Phosphoproteomic subtyping deeply reflected the biological characteristics and clinical features of patients with HCC​​​​​​. The profiles of HCC-dysregulated kinase activities inferred from the different phosphoproteomic subtypes consistently identify increased kinase activity related to cell proliferation. Subtype-C HCC patients showed the most significant dysregulation, indicating a potential therapeutic target. The corresponding drug, bosutinib, demonstrated efficacy in inhibiting the growth of subtype C tumors in liver cancer cell lines and HCC patient-derived xenograft mouse models representative of the phosphoproteomic HCC subtypes. CONCLUSIONS: Our study provides a comprehensive exploration of the phosphoproteomic landscape of HCC, establishing new subtypes that match clinical features and identifying potential therapeutic targets for the most malignant C subtype.

Carcinoma, Hepatocellular↗
PubMed1975

R factors: plasmids conferring resistance to antibacterial agents.

Antibiotic sensitivity and resistance are often under the control of the bacterial chromosome. Frequently, however, an organism may exhibit resistance to one or several antibiotics as a dominant character determined by genes located on a plasmid, a relatively small, circular DNA molecule which replicates, with some degree of autonomy, in the bacterial cytoplasm. Such plasmids, termed drug-resistance (R) factors, generally also specify the formation of sex pili, filamentous appendages on the cell surface. These promote bacterial conjugation, and hence permit the transfer of a copy of the plasmid from the resistant organism to one which may previously have been drug-sensitive. Each ex-conjugant is then capable of acting as a plasmid donor during subsequent pairings, so that R factors are commonly responsible for the epidemic spread of multiple drug-resistance throughout an entire bacterial population. This can present serious problems in antibiotic therapy, particularly as plasmids are often transmissible between organisms of different species, and even different genera. The molecular nature, classification and behaviour of R factors is discussed.

Bacteria↗
PubMed1977

Historical outline of attempts to classify skin diseases.

Over the years physicians have attempted to classify skin diseases. Plenck and Willan were the first to outline clearly the basic components of skin diseases and to devise classifications based on living gross pathologic features. With the development of molecular biology, etiologic classification--a system unrelated to that of clinical appearance--was begun. Most current textbooks present combinations of these two systems and those based on location or on other concepts.

Austria↗
PubMed1979

Classification of drugs by discriminant analysis using fragment molecular connectivity values.

An investigation was made into the use of linear and quadratic discriminant analysis, along with K nearest-neighbor analysis, in the classification of a set of 51 compounds which were divided into five therapeutic categories. By superimposing each compound on a pattern structure, as first proposed by Cammarata, eight positions were assigned on the molecule. Each position was coded with the numerical value of a descriptor index. Relative molar refraction, which was the index used by Cammarata, was compared with a number of molecular connective indices. For each of the indices studied, it was found that only four of the eight positions contributed significantly to between-class differences. It was also found that first-order molecular connectivity, calculated as the sum of the contributions of each of the bonds joining a given position, resulted in consistently fewer misclassifications as compared with the other indices. Using first-order molecular connectivity, validation procedures were performed on the original set of compounds, on random samples drawn from this set, and on a set of ten compounds not included in the analysis. The results obtained were highly data dependent, but they, nevertheless, suggest that molecular connectivity indices should prove useful in structural classification procedures.

Analysis of Variance↗
PubMed1976

[Notes about molecular weights of aroma compounds].

Classification of 2000 food aroma compounds as to their molecular weight shows an accumulation in the range of 135 to 155, and an upper limit of 310. Molecular masses of substances with high aroma effectiveness are below 200. As aroma compounds are composed only of the elements C, H, O, N and S, even numbers of molecular masses predominate among these substances. A periodicity with an interval of 7 units of molecular mass observed seems to be caused by the presence of complete homologuous series of compounds within the range of low molecular masses.

Flavoring Agents↗
PubMed2026

Integration of multi-omics data uncovers novel germline susceptibility candidates in early-onset colorectal cancer.

Colorectal cancer (CRC) is increasingly diagnosed in individuals under 50 years of age, yet the underlying genetic predisposition remains largely unexplained, particularly in mismatch repair (MMR)-proficient cases. This study aimed to identify novel hereditary CRC susceptibility genes by integrating germline and tumour whole-exome sequencing (WES) with transcriptomic profiling across a cohort of early-onset CRC (EOCRC) patients. Tumours were categorised using Consensus Molecular Subtypes (CMS) classification and analysed for mutational signature and burden. We used a novel 'All vs One' multi-omic integration approach to identify loss-of-function rare germline variants with concordant gene expression alterations in tumour tissue. Five candidate genes (ADCY4, NOXO1, CDHR2, ARHGAP10, EEF2K) were prioritised based on this approach and potential biological relevance in CRC. These findings highlight the molecular heterogeneity of EOCRC and demonstrate the utility of multi-omic approaches in refining germline variant interpretation. Integrating tumour transcriptomics enhances gene discovery efforts and supports a more comprehensive understanding of CRC heritability in younger individuals.

Humans↗