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PubMed2025

The protective role of γδ T cells in endometrial cancer.

Γδ T cells are non-conventional T cells that are not MHC restricted and have T cell receptors (TCRs) that are stimulated by phosphoantigens, stress-induced proteins, lipids, and other antigens. These cells are prognostic across cancer types in The Cancer Genome Atlas (TCGA) but have not been well studied in endometrial cancer, which has a rising incidence and mortality rate. Endometrial cancer patients have variable responses to checkpoint inhibitors which are related to the molecular subtype of their cancer. As such, there is a pressing need to understand the immune microenvironment in endometrial cancer. This study addresses this gap in knowledge by investigating γδ T cell repertoires and transcriptomes in this disease site. γδ T cell repertoires were obtained for 543 endometrial cancer patients within the TCGA and from 5 endometrial cancer patients in the single cell dataset SRP349751 using TRUST4. GLIPH2 was used to identify TCRs predicted to bind the same antigen. Transcriptomes were investigated in the single cell dataset. DNA Polymerase Epsilon Exonuclease (POLE) and Microsatellite Instability High (MSI-H) endometrial cancer subtypes had the most γδ T cell infiltration. Vδ1 and Vδ3 γδ T cell infiltration was prognostic independent of stage and molecular subtype. GLIPH2 analysis revealed TCRδ motifs for TDK, YTD, and GEL were public across all four molecular subtypes and were present in the single cell data set. Vδ1 γδ T cell transcriptomes were associated with cytotoxicity and recent TCR stimulation. These data support further investigation of immunotherapies targeting γδ T cells in endometrial cancer.

Humans↗

PubMed2026

Transcriptomic profiling across stages of non-muscle-invasive bladder cancer identifies fibroblast activation protein-alpha as a stromal biomarker associated with progression.

BACKGROUND: T1 non-muscle-invasive bladder cancer (NMIBC) represents a biologically aggressive subgroup with substantial heterogeneity in recurrence and progression risk. Current clinicopathological risk stratification tools lack sufficient precision to identify patients at the highest risk of progression to muscle-invasive bladder cancer (MIBC). OBJECTIVE: To characterize transcriptomic differences between T1 and < T1 (Ta/Tis) NMIBC and to explore the association of fibroblast activation protein-α (FAP) gene expression with disease progression. METHODS: Transcriptomic profiling was performed on formalin-fixed paraffin-embedded (FFPE) tumor tissue from 66 patients with primary, treatment-naïve NMIBC and 5 patients with T2 disease (included for exploratory comparisons). Analyses included differential gene expression, gene set enrichment analysis (GSEA), molecular subtyping, immune cell deconvolution, and evaluation of FAP expression in relation to recurrence and progression. External validation of FAP was conducted in three independent NMIBC cohorts. RESULTS: T1 tumors demonstrated a distinct transcriptomic profile compared with < T1 tumors, characterized by enrichment of cell cycle-related and metabolic pathways and a higher prevalence of aggressive molecular subtypes. Despite these molecular differences, no statistically significant differences in recurrence-free, progression-free, cancer-specific, and overall survival were observed, likely reflecting limited event numbers. Among recurrent tumors, early recurrences (≤ 24 months) were associated with epithelial-mesenchymal transition signatures. FAP expression increased with tumor stage (p = 0.0005) and was associated with progression (p = 0.002) and mortality (p = 0.01). Patients with tumors in the highest quartile of FAP expression had worse progression-free survival. This association was consistently observed in three external NMIBC cohorts. CONCLUSIONS: T1 NMIBC exhibits distinct transcriptomic features suggestive of increased biological aggressiveness. Elevated FAP expression is reproducibly associated with progression risk across multiple cohorts, supporting its potential role as a biomarker of aggressive disease. Given the limited number of progression events, these findings should be considered hypothesis-generating and warrant prospective validation before clinical implementation.

Humans↗

PubMed2026

Stage-Independent Real-Time Subtype Classification and Comprehensive Biopsy Profiling of Urothelial Carcinomas by the Lund Taxonomy System.

Bladder cancer is a heterogeneous malignancy with diverse clinical outcomes, and conventional pathological assessment alone is insufficient to capture its underlying biology. Gene expression profiling can stratify tumors into molecular subtypes with prognostic and predictive potential, but the reliability of transcriptomic classification and its clinical utility remains to be established. The translational/observational UROSCANSEQ study (ISRCTN15459149) prospectively evaluates RNA-based Lund Taxonomy (LundTax) molecular subtype classification in a clinical setting. Among 784 consecutive biopsies collected between 2018 and 2022, RNA sequencing was successful for 90% of all biopsies, encompassing 662 bladder cancer patients with a stage distribution of 48% Ta, 27% T1, 24% ≥T2, and 1% CIS. We demonstrate that the LundTax subtype classification algorithm, applied to individual samples, accurately identifies cancer cell phenotypes with characteristic gene and protein expression patterns in a manner robust to RNA quality, data preprocessing strategies, and batch effects, supporting its clinical feasibility across both non-muscle-invasive and muscle-invasive disease. We further extend the LundTax framework by incorporating single-sample molecular risk scores reflecting tumor grade, proliferation, and progression risk, as well as tumor microenvironment signatures. Both risk scores and overall immune and stromal content in biopsies were significantly associated with an increased risk of clinical progression in noninvasive disease. In a separate analysis of the relative cellular composition of the tumor microenvironment, however, only the fraction of natural killer cells remained significant. Together, the expanded LundTax system provides a comprehensive molecular portrait of individual tumor biopsies. By explicitly separating cancer cell-intrinsic phenotypes, prognostic indexes, and microenvironmental signals, the framework minimizes biological confounding and establishes a strong foundation for future studies evaluating clinical outcomes and treatment responses.

Humans↗

PubMed2026

Plasma cell-CD8+ T cell co-enrichment distinguishes immunotherapy-responsive hepatocellular carcinoma subtypes.

BACKGROUND: Hepatocellular carcinoma (HCC) is characterised by significant racial disparities in incidence and outcomes, yet whether these reflect distinct tumour biology or differential distribution of molecular subtypes among immunotherapy patients remains unclear. METHODS: We characterised molecular heterogeneity among 46 patients with HCC of differing background population from the NCI-CLARITY cohort receiving immune checkpoint inhibitor therapy, using transcriptomic and genomic profiling, with validation across multiple independent cohorts. RESULTS: Differential expression analysis comparing African American versus non-African American patients identified 126 genes, of which 55 demonstrated tumour-specific expression across independent validation cohorts with paired tumour-normal samples. Consensus clustering revealed two molecular subtypes with no significant race association, indicating these clusters capture tumour-intrinsic biology rather than ancestry. The genomic landscape showed minimal differences between subtypes. A prognostic signature derived from these expression profiles demonstrated significant risk stratification in the NCI-CLARITY cohort and TCGA-LIHC, but not in Asian cohorts, suggesting population-specific applicability. Immune deconvolution revealed that the two subtypes represent distinct immune microenvironments: one subtype exhibited markedly elevated plasma cell infiltration with strong plasma cell-CD8+T cell correlation suggesting coordinated adaptive immunity, along with elevated tertiary lymphoid structure signatures. The other subtype showed regulatory T cell-macrophage correlation and enrichment for immune-excluded phenotypes. The immune-enriched subtype trended towards higher immunotherapy response rates. CONCLUSIONS: Molecular heterogeneity in HCC reveals distinct tumour-immune ecosystems that transcend racial classification. Tumour immune heterogeneity in HCC reflects distinct molecular patterns, with immune hot tumours characterised by elevated tertiary lymphoid structure signatures and enriched plasma cell and CD8+T cells. These patterns may serve as prognostic biomarkers for immunotherapy patient stratification and demonstrate the value of diverse cohort representation in identifying clinically relevant therapeutic targets.

Gastrointestinal Cancer↗

PubMed2026

Dietary Polyphenol Acteoside-Related Molecular Signatures in Clear Cell Renal Cell Carcinoma: Multi-Omics Profiling and Functional Validation of IMPDH1.

Clear cell renal cell carcinoma (ccRCC) is characterized by substantial metabolic and molecular heterogeneity, but the disease-relevant programs associated with acteoside, a dietary polyphenol, remain poorly understood. We integrated predicted acteoside targets with bulk, single-cell, and spatial transcriptomic data from ccRCC and combined molecular subtyping with cross-cohort machine-learning analysis. Acteoside-related signatures were preferentially enriched in malignant compartments and increased with tumor grade and stage. Consensus clustering identified two molecular subtypes with distinct biological and clinical features. C1 was associated with immune activation, metabolic activity, and more favorable survival, whereas C2 showed greater genomic instability, reduced renal epithelial differentiation, and poorer outcomes. We further benchmarked multiple machine-learning strategies and established a 10-gene prognostic model that retained predictive performance across independent cohorts, with IMPDH1 emerging as the strongest risk-associated feature. Functional experiments confirmed the biological relevance of IMPDH1: its knockdown suppressed ccRCC cell proliferation, DNA synthesis, colony formation, and migration, whereas overexpression produced the opposite effects. Together, these findings indicate that acteoside-related molecular signatures capture clinically relevant heterogeneity in ccRCC and provide a framework for linking dietary-polyphenol-related molecular space with tumor biology. The identification and functional validation of IMPDH1 further highlight its potential importance in ccRCC progression.

IMPDH1↗

PubMed2026

Molecular Signature of Prediabetes With High-Risk of Diabetes Revealed by Deep Plasma Proteome.

AIMS: Prediabetes is biologically heterogeneous, but molecular subtypes linked to diabetes progression remain poorly defined. We aimed to identify plasma proteome-based subtypes of impaired fasting glucose (IFG), characterise their molecular features and assess their association with future diabetes risk. MATERIALS AND METHODS: We quantified 2584 plasma proteins using liquid chromatography-mass spectrometry in 538 IFG participants from a prospective discovery cohort (Nutrition and Health of Aging Population in China, NHAPC). Proteomic subtypes were defined by consensus clustering, linked to longitudinal changes in insulin sensitivity and incident type 2 diabetes mellitus (T2DM), which were further validated in an independent Shanghai Brain Aging Study (SBAS) cohort. RESULTS: Two reproducible IFG molecular subtypes based on plasma proteomics were identified. The high-risk subtype showed higher incident diabetes and a greater 6-year decline in insulin sensitivity and was characterised by enrichment of glycolysis/gluconeogenesis, insulin signalling and neutrophil degranulation, together with a dyslipidemic lipidomic profile indicating co-dysregulation of glucose and lipid homeostasis. The low-risk subtype demonstrated a higher complement cascade and high-density lipoprotein particle remodelling signature. In the high-risk subtype, key proteins and lipids showed stronger associations with longitudinal declines in insulin sensitivity, including PPBP, PGK1 and ALDOA, as well as PE-P 18:0/20:3 and PE-P 18:1/20:3. CONCLUSIONS: Proteome-based molecular subtyping stratifies IFG individuals with similar fasting glucose levels but distinct biology and future diabetes risk, supporting earlier and more targeted prevention.

Humans↗

PubMed2026

Construction and validation of a β-hydroxybutyrylation-related molecular model for predicting prognosis of papillary thyroid carcinoma.

BACKGROUND: Papillary thyroid carcinoma (PTC) usually has a favorable prognosis, yet a subset of patients develops persistent, recurrent, or biologically aggressive disease. The clinical relevance of lysine β-hydroxybutyrylation (Kbhb)-related transcriptional programs in PTC remains unclear. Accordingly, this study aimed to characterize Kbhb-related molecular heterogeneity in PTC, construct a prognostic signature, and explore its association with the tumor microenvironment (TME). METHODS: Transcriptomic and clinical data from PTC samples within The Cancer Genome Atlas Thyroid Carcinoma (TCGA-THCA) cohort were analyzed to identify Kbhb-related differentially expressed genes (DEGs), define molecular subtypes, construct a prognostic signature, and characterize tumor microenvironmental features. Single-cell RNA-sequencing data from PTC were further used to explore the cellular distribution of representative genes. RESULTS: We identified 51 Kbhb-related DEGs in PTC and defined two Kbhb molecular subtypes. The Kbhb_C2 subtype showed shorter progression-free interval (PFI) and a more immune- and stroma-enriched microenvironment. A six-gene prognostic signature comprising TARID, CDSN, PIMREG, KLRC1, SYT13, and NPR3 was then established. High-risk patients had significantly worse PFI in the full, training, and testing cohorts, with 1-, 3-, and 5-year areas under the curve (AUCs) of 0.715, 0.793, and 0.771, respectively, in the full cohort. High-risk tumors also exhibited higher stromal, immune, and ESTIMATE scores, altered immune infiltration, and increased expression of multiple immune checkpoint molecules. Single-cell analysis confirmed distinct cell-type-specific expression patterns of representative genes. CONCLUSIONS: Kbhb-related transcriptional programs define clinically relevant molecular heterogeneity in PTC and are closely associated with prognosis and TME remodeling. The identified six-gene signature provides a biologically interpretable framework for risk stratification in PTC.

Papillary thyroid carcinoma (PTC)↗

PubMed2026

RAG-mediated structural variation and its impact on relapse risk in acute lymphoblastic leukemia.

Relapse during treatment of B-cell acute lymphoblastic leukemia (B-ALL) is a harbinger of poor outcomes. Identifying biomarkers for subsequent relapse risk which are detectable at B-ALL diagnosis remains a priority. Off-target recombination-activating gene (RAG)-mediated structural variants (SVs) generate genomic instability that drives leukemogenesis and may underlie treatment resistance. Leveraging sequencing data in 1,496 pediatric B-ALL patients enriched for relapse status (relapse n=532; non-relapse n=964), we characterized RAG-mediated SVs across B-ALL molecular subtypes and examined their association with patient characteristics and their impact on clinical outcomes. Off-target RAG-mediated SVs were overall frequent, particularly in ETV6::RUNX1, ETV6::RUNX1-like, and Ph-like B-ALL subtypes, while increasing age-at-diagnosis was positively associated with burden of off-target RAG-mediated SVs (P<.001). Off-target RAG-mediated SVs with a recombination signal sequence (RSS) at one breakpoint, a hallmark of off-target RAG activity, were significantly more frequent at diagnosis in patients who subsequently relapsed (P=.001). This association remained significant in multivariable regression analysis (per SV odds ratio [OR]:1.08, 95%CI:1.04-1.12), in minimal residual disease (MRD)-negative patients (OR:1.09, 95%CI:1.04-1.14) and across subtypes. Excluding deletions, MRD-negative ETV6::RUNX1 patients with ≥3 off-target RAG-mediated SVs had a >3-fold risk of relapse (hazard ratio:3.47, 95% CI:1.86-6.49). RAG-mediated SVs were also associated with relapse risk in T-cell ALL patients. Off-target RAG-mediated SV burden at diagnosis is a risk factor of relapse in pediatric ALL across molecular subtypes and independent of MRD status.

Journal Article↗

PubMed2026

Immunological Features of Neuroendocrine Neoplasms and Adrenal Tumors.

Neuroendocrine neoplasms, which occur throughout the human body, as well as adrenocortical carcinoma and pheochromocytoma, which originate in the adrenal gland, are primarily classified as rare malignancies. Immunotherapy, including immune checkpoint inhibitors (ICIs), is generally not incorporated into the standard care protocols for these tumors. The clinical efficacy of ICIs in these tumors has been modest. This may be due to the biological heterogeneity of these tumors. The tumor immune microenvironment profiles are heterogeneous among the molecular subtypes of pheochromocytoma/paraganglioma, suggesting a potential benefit observed in selected subgroups. Poorly differentiated neuroendocrine carcinoma (NEC) exhibits spontaneous activation of adaptive immunity, unlike well-differentiated neuroendocrine tumors. A delta-like ligand 3-directed T-cell-engaging bispecific antibody, tarlatamab, has recently demonstrated prolonged survival in small cell lung cancer, and investigations into its use in extrapulmonary NEC are underway. This review examines the immunological features of representative neuroendocrine and adrenal tumors (neuroendocrine tumor, neuroendocrine carcinoma, adrenocortical carcinoma, and pheochromocytoma/paraganglioma). In the future, elucidating the relationship between specific molecular subtypes and immunophenotypes may facilitate the development of personalized therapies and guide clinical investigations in promising patient subpopulations.

Humans↗

PubMed2026

Meta-Merging the Transcriptomes of Gastric Tumors Redefines the Connections among Molecular and Clinical Subtypes.

INTRODUCTION: The availability of a large number of cancer expression profiles presents an excellent opportunity to re-investigate various biological and clinical questions. While several expression profiles have been established for different cancers, merging them may provide a more powerful platform for extensively extrapolating molecular and clinical features across multiple cohorts. MATERIALS AND METHODS: In this study, five gastric tumor expression profiles from the Gene Expression Omnibus [GEO] and one in-house cohort comprising a total of 1,060 samples were merged. The batch effect was removed using non-parametric ComBat analysis, and the seamless merging of datasets was confirmed through various parameters. RESULTS: Extrapolation of ACRG [Asian Cancer Research Group] and TCGA [The Cancer Genome Atlas] molecular subtypes in the merged cohort of 1,060 gastric tumors revealed nine distinct clusters. Notably, the following patterns were observed: [i] mutual exclusivity between Epithelial to Mesenchymal Transition [EMT] and Microsatellite Instability [MSI] subtypes in 90% of tumors; [ii] overlapping occurrence of EMT and MSI subtypes in the remaining tumors; [iii] overlap between MSI and Epstein-Barr Virus [EBV] subtype tumors; [iv] both commonalities and differences between EMT and Genomically Stable [GS] subtypes; and [v] an association between EBV positivity and PI3K mutation. CONCLUSION: The current study demonstrates that compiling a larger expression profile is valuable for revisiting the molecular features and epidemiology associated with molecular subtypes, thereby aiding in the development of novel diagnostics and targeted therapeutics.

Humans↗

PubMed2025

Pharmacogenomics-based subtype decoded implications for risk stratification and immunotherapy in pancreatic adenocarcinoma.

BACKGROUND: With fatal malignant peculiarities and poor survival rate, outcomes of pancreatic adenocarcinoma (PAAD) were frustrated by non-response and even resistance to therapy due to heterogeneity across clinical patients. Nevertheless, pharmacogenomics has been developed for individualized-treatment and still maintains obscure in PAAD. METHODS: A total of 964 samples from 10 independent multi-center cohorts were enrolled in our study. With drug response data from the profiling of relative inhibition simultaneously in mixtures (PRISM) and genomics of drug sensitivity in cancer (GDSC) databases, we established and validated multidimensionally three pharmacogenomics-classified subtypes using non-negative matrix factorization (NMF) and nearest template prediction (NTP) algorithms, separately. The heterogenous biological characteristics and precision medicine strategies among subtypes were further investigated. RESULTS: Three pharmacogenomics-classified subtypes after stable and reproducible validation, distinguished in six aspects of prognosis, biological peculiarities, immune landscapes, genomic variations, immunotherapy and individualized management strategies. Subtype 2 was close to immunocompetent phenotype and projected to immunotherapy; Subtype 3 held most favorable outcomes and metabolic pathways distinctively, promising to be treated with first-line agents. Subtype 1 with worst prognosis, was anticipated to chromosome instability (CIN) phenotype and resistant to chemotherapeutic agents. In addition, ITGB6 contributed to subtype 1 resistance to 5-fluorouracil, and knockdown of ITGB6 enhanced sensitivity to 5-fluorouracil in in vitro experiments. Ultimately, appropriate clinical stratified treatments were assigned to corresponding subtypes according to pharmacogenomic transcripts. Some limitations were not taken into account, thus needs to be supported by more research. CONCLUSION: A span-new molecular subtype exploited for PAAD uncovered an insight into precise medication on ground of pharmacogenomics, and highly refined multiple clinical management strategies for specific patients.

Humans↗

PubMed2026

Molecular subgroups of human malignant peripheral nerve sheath tumors are conserved in canines.

Malignant peripheral nerve sheath tumors (MPNST) are aggressive sarcomas of Schwann cell lineage with poor prognosis in both humans and dogs. While rare in humans, MPNSTs occur more frequently in dogs and share histomorphological and clinical features. Recent methylome and transcriptome analyses have identified two molecular subgroups of human MPNST with distinct oncogenic signaling pathways and prognostic implications; however, it remains unclear if these subgroups also exist in canines. Given their higher incidence and biological similarities to human disease, canine MPNSTs represent a promising comparative model to investigate molecular subtypes and evaluate novel therapeutic strategies. To characterize canine MPNST and assess molecular parallels with the human subgroups, we applied laser-capture microdissection (LCM) followed by RNAsequencing to analyze tumor tissue from 20 canine MPNST. Principle component and differential gene expression analyses identified two clearly distinct transcriptional clusters corresponding to spindle cell and epithelioid MPNST variants, respectively. Unsupervised cross-species comparison aligned the two canine clusters with the human G1 and G2 subgroups. Accordingly, one cluster was characterized by SHH pathway activation and increased cell cycle activity, while the other showed non-canonical WNT pathway, Schwann cell-like features and marked macrophage infiltration. Immunohistochemistry further demonstrated loss of H3K27me3, p-ERK activation and β-catenin signaling by IHC in a subset of tumors. These findings support the value of canine MPNST as clinically amenable model for structured assessment of novel therapeutic approaches to benefit patients of both species.

Canine cancer model↗

PubMed2026

Immune subtyping of colorectal adenoma identifies a subtype with activated adaptive immunity ahead of progressing to cancer.

BACKGROUND: Colorectal adenomas (CRA) represent precursor lesions with varying risks of malignant transformation. However, molecular subtyping, particularly immune-related classification, remains underexplored in adenomas. This study aims to characterize the immune landscape of CRA through immune subtyping and evaluate its association with cancer progression, gene expression signatures, and functional pathways. METHODS: We conducted a retrospective analysis of transcriptomic data from multiple cohorts of CRA samples. Immune subtypes were identified using non-negative matrix factorization (NMF) based on immune-related genes. Diverse deconvolution algorithms were used to estimate immune cell infiltration. The immune status alteration in premalignant lesion was further consolidated by single-cell transcriptome data. Differential gene expression analysis was performed between subtypes, followed by functional enrichment analyses (Gene Ontology [GO] and Kyoto Encyclopedia of Genes and Genomes [KEGG]). RESULTS: Two distinct immune subtypes were identified: an immune-enriched subtype characterized by high lymphocyte infiltration and elevated expression of immune-related genes, and an immune-deficient subtype with suppressed immune activity. Differential expression analysis revealed significant upregulation of immune response genes (e.g., CD4, CD86, HLA-DRA) in the immune-enriched subtype. GO and KEGG analyses highlighted enrichments in leukocyte transendothelial migration, chemokine signaling, and antigen processing and presentation pathways. Single-cell result revealed an early occurrence of TIGIT activation and exhausted CD8 T cell features in adenoma when compared to normal tissue. CONCLUSION: This study delineates distinct immune subtypes within CRAs. The immune-enriched subtype demonstrates activated adaptive immunity and may reflect a higher potential for immune surveillance, while the immune-deficient subtype exhibits stromal features suggestive of progressive transformation. These findings provide insights into early immune microenvironment alterations and may inform strategies for risk stratification and immunoprevention in colorectal carcinogenesis.

Colorectal adenoma↗

PubMed2026

AI-Driven Multi-Omics Integration of Synthetic Colon Adenocarcinoma for Cluster-Guided PROTAC Candidate Design Targeting KRASG12D.

Colorectal cancer is a leading cause of cancer death, yet its molecular heterogeneity remains poorly translated into individualized treatment. We present a reproducible artificial intelligence (AI) framework that integrates multi-omics benchmarking, sample-level drug prioritization, E3 ubiquitin ligase selection, and shape-anchored Proteolysis Targeting Chimera (PROTAC) design for KRASG12D in colon adenocarcinoma (COAD). A controlled synthetic benchmark comprising 425 tumor and 41 simulated normal profiles, parameterized to match The Cancer Genome Atlas (TCGA) distributions, was used for pipeline verification. Among sixteen methods, the Balanced Latent Integration with Stability Selection (BLISS) model achieved the highest silhouette width (0.86) and competitive agreement (Adjusted Rand Index, ARI, 0.90). The pipeline was validated on real data: a TCGA COAD cohort (186 tumors) with independent Consensus Molecular Subtype (CMS) labels and a CPTAC cohort (104 tumors). Integration modestly recovered CMS (ARI 0.28), and stage, not molecular cluster, drove survival (log-rank p = 0.005 versus 0.81). Sample-level prioritization differed from cluster-level ranking in 82.6% of profiles, below chance (p < 0.0001), without indicating efficacy. Candidate NOVEL00489 showed a good MM-GBSA estimate, matching the reference ASP3082. Compounds are computational candidates requiring experimental validation. This establishes a transparent benchmark for in silico degrader generation in precision oncology.

Humans↗

PubMed2026

[State Changes and Stability Grading of Driver Genes in Non-small Cell Lung Cancer Based on Repeated NGS Testing].

BACKGROUND: Next-generation sequencing (NGS)-based driver gene testing has become a routine component of molecular subtyping and precision therapy for non-small cell lung cancer (NSCLC). Dynamic genomic monitoring facilitates early detection of resistance-related molecular alterations and informs timely therapeutic adjustments. However, standardized criteria for evaluating the stability of serial NGS testing are currently lacking, and the applicability of NGS using formalin-fixed paraffin-embedded (FFPE) specimens for dynamic monitoring remains poorly defined. This study aims to establish a stability grading system for driver gene status alterations based on repeated NGS testing, and to provide evidence-based support for clinical repeat biopsy strategies. METHODS: Data from 1232 patients with NSCLC who underwent two or more NGS tests on FFPE tissue specimens at Beijing Chest Hospital between June 2019 and April 2026 were collected retrospectively. Patients with an interval of ≥4 months between the initial and last tests were included to ensure the representativeness of temporal analysis, resulting in a main analysis cohort of 942 patients. The Kappa consistency test was used to evaluate the state stability of nine core driver genes [epidermal growth factor receptor (EGFR), Kirsten rat sarcoma viral oncogene homolog (KRAS), anaplastic lymphoma kinase (ALK), ROS proto-oncogene 1, receptor tyrosine kinase (ROS1), mesenchymal‑epithelial transition factor (MET), rearranged during transfection (RET), v-raf murine sarcoma viral oncogene homolog B1 (BRAF), erb‑b2 receptor tyrosine kinase 2 (ERBB2), and phosphatidylinositol‑4,5‑bisphosphate 3‑kinase catalytic subunit alpha (PIK3CA)] and to construct a five‑level grading system. Paired variant allele frequency (VAF) differences were compared using the Wilcoxon signed‑rank test. Independent influencing factors for mutation accumulation were identified by binary Logistic regression. RESULTS: The state stability of the nine genes was classified into five levels: EGFR showed high stability (Kappa=0.838), ROS1/ALK/KRAS good stability, BRAF/PIK3CA/RET moderate stability, and ERBB2 low stability, and MET showed high instability. MET exhibited the highest rate of state change (9.3%) with a raw observed agreement of 90.7%. Its Kappa value (0.172) was influenced by the low prevalence (3.7%) compression effect and should therefore be interpreted alongside the observed agreement (90.7%) and the prevalence-adjusted and bias-adjusted Kappa (PABAK). The VAF of PIK3CA increased significantly (P=0.005). T790M positivity increased from 5.8% to 10.8%, and 30 new C797S mutations were detected at the last test (13 with T790M, 17 without). The overall rate of new driver gene variants in the main cohort was 18.0%. Binary Logistic regression showed that a lower number of initial mutated genes was the only independent predictor of new variants [odds ratio (OR)=0.399, P<0.001], while sex and detection interval showed no independent association. CONCLUSIONS: A five level stability grading system for state changes of driver genes in NSCLC based on repeated NGS testing has been established. MET showed the most frequent state changes, which should be interpreted in conjunction with the prevalence effect. The VAF increase of PIK3CA is an observational finding, and its clinical significance requires further prospective validation. A lower initial mutation burden may reflect tumor clonal complexity and was associated with a higher likelihood of subsequent acquisition of new variants. FFPE based NGS is applicable for repeated testing at clinical treatment decision nodes.

Humans↗

PubMed2026

Integrin α3 (ITGA3) expression across breast cancer subtypes: Prognosis and therapeutic relevance.

BACKGROUND: Integrin α3 (ITGA3), which heterodimerizes with integrin β1, has emerged as a potential biomarker and therapeutic target in several epithelial malignancies; however, its clinical relevance in breast cancer remains incompletely characterized. This study evaluated ITGA3 expression across breast cancer molecular subtypes and assessed its prognostic and predictive significance. METHODS: Immunohistochemistry (IHC) was performed on archival breast cancer specimens using tissue microarrays (n = 148) and whole-tissue sections (n = 21). Complete clinicopathologic and outcome data were available for 108 patients, including hormone receptor-positive/human epidermal growth factor receptor 2-negative, HER2-positive, and triple-negative breast cancer (TNBC) subtypes. ITGA3 expression was quantified using H-scores and correlated with clinicopathologic features and survival outcomes. Independent transcriptomic analyses were conducted using the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) and the Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) cohorts to evaluate ITGA3 mRNA expression, co-expressed signaling pathways, and associations with therapeutic response. RESULTS: ITGA3 protein expression was detected in 85.2% of breast cancer specimens and was significantly higher in HR-positive/HER2-negative and HER2-positive tumors compared with TNBC (p < 0.0050). High ITGA3 expression was associated with shorter recurrence-free survival (p < 0.0001). In the METABRIC cohort, tumors with ITGA3 alterations demonstrated significantly worse relapse-free survival (p < 0.0001) and overall survival (p < 0.0500). Transcriptomic analyses revealed that ITGA3 co-expressed with estrogen receptor 1(ESR1), erb-b2 receptor tyrosine kinase 2 (ERBB2), and luminal markers, along with enrichment of estrogen receptor and phosphoinositide 3-kinase-protein kinase B-mechanistic target of rapamycin (PI3K/AKT/mTOR) signaling pathways. ITGA3 expression was not predictive of response to tamoxifen or trastuzumab. CONCLUSION: Elevated ITGA3 expression is associated with breast cancer recurrence and poor clinical outcomes, supporting its potential role as a prognostic biomarker and candidate therapeutic target.

Biomarkers↗

PubMed2026

IDH2 clonal hematopoiesis and IKAROS loss cooperate in a B-ALL subtype after lenalidomide therapy for multiple myeloma.

Lenalidomide, a maintenance treatment in multiple myeloma first-line therapy, increases the risk of secondary malignancies, including B-cell precursor acute lymphoblastic leukemia (B-ALL). We present a comprehensive molecular characterization of 57 patients with lenalidomide-associated B-ALL (LenB-ALL), revealing 3 mutational subgroups: (1) TP53mt (30%); (2) IDH2mt (p.R140Q) (23%); and (3) other, including NRAS/KRASmt. Remarkably, IDH2 R140Q mutations were highly enriched in LenB-ALL compared with those in primary B-ALL (P< .001). Furthermore, IKZF1 intragenic deletions, often subclonal and likely RAG recombinase-mediated, were observed in 54% (7/13) of IDH2mt patients with LenB-ALL. IDH2 mutations were not restricted to the leukemic clone: they persisted during measurable residual disease-negative remission and were identified in lymphoid as well as myeloid cell populations using fluorescence-activated cell sorting and single-cell RNA sequencing. This indicates a preleukemic origin of the IDH2 mutation within the context of clonal hematopoiesis. Transcriptomic and DNA methylation analyses revealed a distinct gene expression profile and a DNA hypermethylation phenotype in IDH2mt LenB-ALL, including IDH2mt-specific as well as lenalidomide-associated features. We propose that lenalidomide promotes the expansion of IDH2-mutated clonal hematopoiesis and, via IKAROS downregulation, induces a maturation arrest at the B-cell precursor stage. Subsequent genetic or epigenetic alterations render leukemogenesis independent of ongoing lenalidomide exposure. All these data define IDH2mt B-ALL as a distinct molecular subtype that is markedly overrepresented after lenalidomide treatment and highlight clonal hematopoiesis as a key contributing factor in the development of LenB-ALL.

Humans↗

PubMed2025

UALCAN Mobile, an app for cancer proteogenomic data analysis.

Cancer is a complex disease affecting various organs and is a major cause of death worldwide. During cancer initiation, disease progression, and tumor metastasis, various genomic and proteomic alterations are observed. Recent technological advances have led to the generation of large amounts of molecular data, including genomics and transcriptomics. These large-scale datasets can be utilized to analyze and identify sub-class-specific cancer biomarkers and targets. However, there is a need for the development of user-friendly tools for large-scale data analysis, disseminating the analyzed data in a visualizable format to cancer researchers with no programming skills. We developed UALCAN, a comprehensive platform that allows users to integrate disparate data to better understand the genes, proteins, and pathways perturbed in cancer and make discoveries of potential biomarkers and targets. In the current study, we describe the development of the UALCAN Mobile application (app) that will provide cancer transcriptomic data obtained from The Cancer Genome Atlas (TCGA) project to evaluate protein-coding gene expression based on various stratifications, including stage, grade, race, gender, and molecular-subtypes across over 30 types of cancers. In addition, the UALCAN mobile provides data analysis options for epigenetic changes due to DNA promoter methylation and Clinical Proteomic Tumor Analysis Consortium (CPTAC) cancer proteomic data. The app provides access to large cancer molecular datasets on the go. To find changes in the expression of causative genes and proteins and to identify biomarkers and therapeutic targets, UALCAN mobile app will be extremely valuable. The "UALCAN Mobile" app is free to use and can be downloaded from both the iOS/Apple and the Android Play Store and has been downloaded over 100 times in each of iOS and android app stores.

app↗