Search PubMedSearch

SEARCH · Search PubMed

Results for “tumor mutational concordance”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

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

At least 19 recordsLinked to original sources

Tumor Mutational Concordance and Recurrence Timing in Hepatocellular Carcinoma.

INTRODUCTION: In hepatocellular carcinoma (HCC), intrahepatic recurrence includes true recurrence from clonal relapse and multicentric recurrence from de novo tumorigenesis. Recurrence timing is used to distinguish these types; however, its accuracy remains unclear. This study aimed to classify recurrent tumors based on somatic mutational concordance and assess the validity of recurrence timing. METHODS: Whole-exome sequencing was performed on paired primary and recurrent HCC tumors from 49 patients enrolled in a prospective institutional omics project. Tumors with &#x2265; 10 shared somatic mutations were classified as true recurrence. Clinicopathological features, recurrence timing, driver mutation patterns, and survival outcomes were compared between recurrence types. Mutational concordance was quantified using shared variant counts and the Jaccard similarity index. RESULTS: Of the 49 patients, 22 (44.9%) showed true recurrence and 27 (55.1%) had multicentric recurrence. Multicentric recurrence tumors harbored no shared variants or only a single shared variant with the primary tumor. True recurrence was associated with significantly higher concordance in histological differentiation and Edmondson-Steiner grading and greater retention of CTNNB1, TP53, ARID1A, and KEAP1 mutations. The number of shared variants (median: 115 vs. 0, and p&#xa0;<&#xa0;0.001) and the Jaccard index (median: 0.44 vs. 0.00 and p&#xa0;<&#xa0;0.001) were significantly higher in the true recurrence group. Recurrence timing was inconsistently correlated with mutational concordance, although a 3-year cutoff yielded significant separation. CONCLUSION: Recurrence timing alone insufficiently reflects clonal relationships. Genomic profiling offers a reliable framework for distinguishing between recurrence types and guiding HCC management.

clonal relapse

In silico generation of synthetic cancer genomes using generative AI.

Understanding how genomic alterations drive cancer is key to advancing precision oncology. To detect these alterations, accurate algorithms are used; however, due to privacy concerns, few deeply sequenced cancer genomes can be shared, limiting benchmarking and representing a major obstacle to the improvement of analytic tools. To address this, we developed OncoGAN, a generative AI model combining adversarial networks and variational autoencoders to create realistic synthetic cancer genomes. Trained on large-scale genomic datasets, OncoGAN accurately reproduces somatic mutations, copy number alterations, and structural variants across cancer types while preserving donors' privacy. The synthetic genomes reflect tumor-specific mutational signatures and positional mutation patterns. Using DeepTumour, we validated the synthetic data's fidelity, showing high concordance between generated and predicted tumors. Moreover, augmenting the training data with synthetic genomes improved DeepTumour's accuracy, underscoring OncoGAN's potential to generate shareable datasets with known ground truths for benchmarking and enhancement of cancer genome analysis tools.

Humans

Activating mutations in ESR1 contribute to an immunosuppressive breast tumor microenvironment by dampening cytokine secretion.

Patients with estrogen receptor+ (ER+, ESR1+) breast cancer are most at risk of relapse, where activating mutations in ESR1 promote metastasis and therapeutic resistance. These patients are also disadvantaged in responding to immunotherapies, the mechanisms of which remain to be elucidated. Here, we engineered a transgenic mouse model carrying either Y541S or D542G mutation in ESR1, mirroring the 2 most common mutations seen in patients. ESR1mut tumors do not differ in the total number of immune cells yet display downregulation in immune pathways and decreased immune-modulatory cytokines, including IL-17a and IL-1&#x3b2;. T cells and macrophages have lower IFN-&#x3b3; and antigen presentation, respectively. Mechanistically, ESR1mut negatively regulates immune modulator expression and upregulates Stat5 to dampen cytokine expression. In concordance, validation on ESR1mut patient tumors shows decreased IL-17a and IL-1&#x3b2;. Collectively, our findings reveal that ESR1 mutations contribute to an immunosuppressive tumor microenvironment by dampening cytokine secretion and immune cell activity.

Animals

Integrated morphologic, immunophenotypic, and molecular profiling of advanced upper tract urothelial carcinoma across tumor compartments supports biopsy-based testing.

Upper tract urothelial carcinoma (UTUC) is an aggressive malignancy with limited molecular characterization in advanced disease. FGFR3 alterations are well established in low-grade urothelial carcinoma, but their prevalence, stability, and biological significance in locally advanced and metastatic UTUC remain only partially defined. We performed an integrated morphologic, immunohistochemical, and molecular analysis of 24 locally advanced and/or metastatic UTUC from 20 patients. FGFR3 status was assessed by RT-PCR across multiple tumor compartments, including biopsies, primary tumors, lymph-node metastases, and distant metastatic sites. Immunohistochemistry included CK20, CK5, GATA3, p53, and mismatch repair proteins. Targeted next-generation sequencing (NGS) was used to characterize co-occurring genomic alterations and to assess concordance with p53 immunophenotype. FGFR3 alterations were identified in 50% of patients and in 54.2% of analyzed tumors. FGFR3 status showed high intra-patient stability, with concordance between primary tumors and distant metastases in 90% of cases, whereas concordance with lymph node metastases was lower (50%), suggesting site-specific clonal divergence. Despite advanced stage, 92.3% of FGFR3-altered tumors displayed papillary urothelial carcinoma morphology, and most showed a luminal immunophenotype (61.5% by CK20/CK5 and 69.2% by GATA3/CK5). Targeted NGS revealed additional pathogenic alterations in 75% of patients, most frequently involving RTK/RAS/MAPK signaling (70%), cell-cycle regulation (25%), and PI3K/AKT pathway components (10%). TP53 mutations co-occurred with FGFR3 alterations in 60% of FGFR3-mutated patients and showed 90.4% concordance with p53 immunohistochemistry. Finally, a few cases exhibited complex, multi-site FGFR3 mutational patterns, consistent with intratumoral clonal evolutions. In conclusion, FGFR3 alterations are frequent and remarkably stable in advanced UTUC, even in high-grade and metastatic disease. These findings support the reliability of FGFR3 testing on limited diagnostic material and reinforce its relevance for therapeutic stratification. UTUC emerges as a molecularly dynamic disease in which early oncogenic drivers such as FGFR3 continue to shape tumor biology and therapeutic vulnerability at advanced stages.

Humans

CMAtlas: a comprehensive DNA methylation atlas for exploring epigenetic alterations in 34 human cancer types.

MOTIVATION: Aberrant DNA methylation is a fundamental epigenetic hallmark of cancer. However, existing resources often lack technological diversity and comprehensive cancer coverage. Furthermore, most platforms fail to achieve deep multi-omics integration and tend to ignore cancer-type-specific methylation features, limiting their utility in precision oncology and drug discovery. RESULTS: We developed Cancer Methylation Atlas (CMAtlas), a comprehensive platform integrating 13&#xa0;753 samples across 34 cancer types. By applying technology-tailored pipelines to data from various profiling technologies, we identified 830&#xa0;725 tumor-specific differentially methylated elements (DMEs) and 1&#xa0;480&#xa0;098 differentially methylated regions (DMRs), alongside 1&#xa0;154&#xa0;256 cancer-type-specific DMEs and 329&#xa0;154 DMRs. The platform demonstrates high cross-platform consistency and strong concordance between tumor tissues and cell lines, ensuring the robustness of our findings. All DMEs and DMRs are annotated with multi-omics data (RNA expression, somatic mutations, and chromatin accessibility) and clinical relevance (survival associations and cell-free DNA profiling). We further demonstrate the utility of CMAtlas by identifying prognostic aberrant methylation in colorectal cancer driver genes. AVAILABILITY AND IMPLEMENTATION: CMAtlas is freely accessible at {{https://cmatlas.renlab.cn/}}. The platform offers an intuitive web interface supporting gene-centric and cancer-centric queries, alongside customizable analysis modules designed to facilitate user-specific research needs.

Humans

A machine learning-derived intratumoral heterogeneity-related signature predicts the prognosis for and therapeutic response in patients with skin cutaneous melanoma.

BACKGROUND: Reliable biomarkers for predicting prognosis and therapeutic response in skin cutaneous melanoma (SKCM) remain limited. This study aimed to develop an intratumoral heterogeneity (ITH)-related prognostic signature for SKCM using integrative machine learning. METHODS: RNA sequencing (RNA-seq) data from 472 SKCM patients in The Cancer Genome Atlas (TCGA) and 214 patients in the GSE65904 cohort were analyzed. ITH scores were calculated using the DEPTH2 algorithm. Differentially expressed genes (DEGs) were identified between high- and low-ITH groups [|log2fold change (FC)| &#x2265;1, false discovery rate (FDR) <0.05]. Based on 38 prognostic DEGs identified by univariate Cox regression, we employed an integrative framework of 101 machine learning algorithm combinations to construct prognostic models in the TCGA training cohort. The model with the highest average concordance index (C-index) was validated in the GSE65904 cohort and selected as the prognostic ITH-related signature (PIRS). Associations of the PIRS risk score with tumor mutational burden (TMB), immune cell infiltration, immune checkpoint gene expression, and drug sensitivity were systematically evaluated. Model performance was assessed using receiver operating characteristic (ROC) curves and Cox regression analyses. RESULTS: A 38-gene PIRS was constructed using the plsRcox algorithm. Patients with high PIRS risk scores exhibited significantly poorer overall survival (OS) in both the TCGA and Gene Expression Omnibus (GEO) cohorts. The PIRS was identified as an independent prognostic factor, with area under the curve (AUC) values of 0.779, 0.734, and 0.756 for 1-, 3-, and 5-year survival, respectively. High-risk samples displayed significantly lower TMB (P<0.05), reduced immune and stromal cell infiltration (P<0.001), downregulated immune function, and decreased expression of immune checkpoint genes. Additionally, high- and low-PIRS risk score groups exhibited distinct sensitivity patterns to different classes of targeted agents. CONCLUSIONS: The machine learning-derived PIRS robustly predicts prognosis in SKCM patients. Its clinical application is promising for optimizing patient risk stratification and treatment decisions, though further prospective validation is warranted.

Skin cutaneous melanoma (SKCM)

Gastroenteropancreatic Neuroendocrine Carcinoma (GEP-NEC): An Aggressive Disease Course and Limitations for Personalized Oncology.

Neuroendocrine carcinoma (NEC) is a rare, aggressive malignancy with limited treatment options and poor prognosis. We report a male patient diagnosed with a gastroenteropancreatic (GEP)-NEC with synchronous liver metastasis at the time of surgery who underwent a radical resection attempt. Despite radical-intent surgery followed by adjuvant carboplatin/etoposide, early recurrence developed with progression through multiple subsequent chemotherapy lines. During the treatment process, genetic profiling was&#xa0;performed twice to identify actionable genomic targets, with inclusion in the national IMPRESS study as a last resort. Comprehensive genomic profiling revealed TP53 mutation and RB1 loss but no actionable alterations. A patient-derived organoid (PDO) was successfully established from resected tumor tissue and retained key neuroendocrine and proliferative features, with partial genomic concordance to the primary tumor. Differences between the primary and subsequent PDO in variant allele frequencies suggest clonal selection during culture. Exploratory metabolomic profiling of tryptophan pathway metabolites in patient serum and PDO-culture media indicated tumor-associated metabolic alterations. We present clinical and translational efforts in difficult-to-treat NEC, illustrating both the translational challenges and the potential role of PDOs in advancing personalized treatment strategies for a cancer with very limited treatment options.

Gastroenteropancreatic neuroendocrine carcinoma

In-depth assessment of BRAF, NRAS, KRAS, EGFR, and PIK3CA mutations on cell-free DNA in the blood of melanoma patients receiving immune checkpoint inhibition.

INTRODUCTION: Circulating tumor DNA (ctDNA) holds promise for guiding immune checkpoint inhibitor (ICI) therapy and stratifying responders from non-responders. While tumor-informed ctDNA detection approaches are sensitive and mutation-inclusive, they require tumor tissue, which limits applicability in real-world settings. Conversely, tumor-agnostic methods often have limited genomic coverage. In this study, we evaluated a tumor-agnostic, broad-panel ctDNA assay in patients with advanced melanoma treated with ICI. METHODS: We conducted a prospective analysis of 241 longitudinal samples from 39 patients with unresectable stage III/IV melanoma using a SYSMEX targeted NGS panel covering 1,114 COSMIC mutations. Plasma samples were collected at baseline and during ICI therapy. The assay's sensitivity reached seven mutant molecules, corresponding to a 0.07% mutation allele frequency (MAF). ctDNA profiles were compared with matched tumor tissue and correlated with clinical features and survival. RESULTS: At baseline, ctDNA was detected in 64.5% of patients. Common mutations included BRAFV600E (43.8%) and NRASG12D (36.4%), followed by KRAS, EGFR, and PIK3CA variants. Overall tissue-plasma concordance was 51.6%, with more extended biopsy-plasma intervals associated with discordance (p&#x2009;=&#x2009;0.0105). Notably, 12.2% of cases exhibited partial concordance, characterized by shared mutations and additional plasma-only alterations, underscoring the complementary value of blood-based profiling. Persistent or re-emerging ctDNA positivity post-therapy correlated with shorter progression-free survival (PFS, p&#x2009;=&#x2009;0.003), while ctDNA-negative patients showed significantly improved outcomes. Patients that remained ctDNA-negative had significantly longer progression-free survival (median not reached) compared to those with persistent ctDNA positivity (median 3&#xa0;months) or those converting to positive (median 7.5&#xa0;months; p&#x2009;=&#x2009;0.0073). Early NRAS and KRAS ctDNA levels strongly predicted poor response (p&#x2009;=&#x2009;0.0069 and p&#x2009;=&#x2009;0.028). The prognostic impact extended beyond canonical drivers, as non-hotspot variants also correlated with the outcome. Notably, even low-level ctDNA persistence (5-10 MM/mL) carried adverse prognostic implications (p&#x2009;=&#x2009;0.0054). Concerning a shorter PFS, ctDNA positivity was also associated with elevated S100 levels (p&#x2009;=&#x2009;0.047). Organ-specific mutation enrichment (e.g., KRASG12D in brain, EGFRG719A in lymph nodes) suggested possible metastatic tropism. CONCLUSION: Broad tumor-agnostic ctDNA analysis effectively identified clinically relevant mutations and predicted outcomes in ICI-treated melanoma patients. This approach enables tissue-independent and real-time ctDNA monitoring and may inform patient selection and therapeutic strategies in future interventional trials.

Humans

Prognostic significance of DNA damage response-related markers in esophageal squamous cell carcinoma using machine learning approaches.

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) lacks reliable prognostic biomarkers. Homologous recombination deficiency (HRD) has been implicated in genomic instability across multiple cancers, but its prognostic significance in ESCC remains unexplored. This study aimed to evaluate HRD score as a prognostic biomarker and develop a machine learning-based predictive model for ESCC. METHODS: Transcriptomic and clinical data from 78 ESCC patients were obtained from The Cancer Genome Atlas (TCGA) and randomly split into training (70%) and test (30%) cohorts. Prognostic models were constructed using 112 machine learning algorithm combinations based on DNA damage response (DDR)-related genes. Gene set enrichment analysis (GSEA), somatic mutation profiling, and immune cell infiltration estimation via CIBERSORT were performed to characterize HRD-associated molecular features. RESULTS: High HRD scores were significantly associated with poorer overall survival (P<0.05). Among 112 algorithm combinations, the survival support vector machine (Survival-SVM) model demonstrated optimal performance [training concordance index (C-index): 0.741; test C-index: 0.708], identifying six hub genes: PARP1, MBD4, TELO2, NSMCE3, SMUG1, and BABAM1. A nomogram incorporating risk score (RS) and clinical variables achieved strong predictive accuracy for 1- to 3-year survival [area under the curve (AUC) >0.7]. High-HRD tumors exhibited distinct mutational patterns (TP53 and TTN) and enriched glutathione metabolism and cytochrome P450 pathways. Immune infiltration analysis revealed significant differences in plasma cell and neutrophil infiltration between risk groups (P<0.05), suggesting HRD-associated immune microenvironment remodeling. CONCLUSIONS: We developed a novel HRD-based prognostic model incorporating six DDR-related genes that demonstrates robust predictive performance in ESCC. HRD score is identified as an independent prognostic factor associated with genomic instability, immune microenvironment alterations, and clinical outcomes. These findings provide a theoretical basis for personalized treatment strategies, including potential applications of PARP inhibitors and immunotherapy in ESCC.

Esophageal squamous cell carcinoma (ESCC)

Establishment of a multi-targeted magnetic combined enrichment system for circulating tumor cells in gastric cancer and analysis of their genomic profiles.

Background: This study aims to establish an efficient Circulating tumor cells (CTCs) multi-targeted magnetic combined sorting system for Gastric cancer (GC), while comparing it with tissue and circulating tumor DNA (ctDNA) samples to evaluate its feasibility and consistency for genomic profiling analysis. Method: Establish an efficient CTCs sorting system for GC targeting epithelial cell adhesion molecule, cell surface vimentin, and protein tyrosine kinase 7, and evaluate its physicochemical properties and cell capture efficiency. Assess the feasibility of tumor cell detection through animal experiments. Sixty-eight GC patients underwent CTCs detection. Clinical information was analyzed to evaluate the clinical utility of CTCs in the auxiliary diagnosis of GC. Next-generation sequencing was performed on GC tissue, CTCs, and ctDNA samples to assess the consistency of genetic mutations across different sample types. Results: The constructed CTCs sorting system exhibits excellent physicochemical properties, achieving a capture rate of 94.68%. Animal studies confirm a positive correlation between tumor cells count and tumor volume. The number of CTCs in the blood of GC patients is significantly correlated with tumor size, stage, and metastasis. The CTCs count in GC patients is significantly higher than in healthy individuals and high-risk groups for cancer, with diagnostic sensitivity and specificity of 97.29% and 97.73%, respectively. The mutation detection rate in CTCs samples was significantly higher than that in tissue and ctDNA samples. The concordance rate between CTCs and tissue mutations was 24.32%, while the concordance rate between CTCs and ctDNA mutations was 19.05%. Conclusion: This study successfully established a multi-target combined CTCs multi-targeted magnetic combined sorting system for GC. CTCs detection based on this system can be used for the auxiliary diagnosis of GC patients. Furthermore, compared to GC tissue and ctDNA samples, CTCs detection enables more comprehensive genomic profiling analysis and serves as an important supplement to GC genomic analysis.

Humans

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

Methylation-based droplet digital polymerase chain reaction shows high concordance with chronic lymphocytic leukemia IGHV somatic mutation status.

OBJECTIVE: Somatic hypermutation at immunoglobulin heavy chain variable (IGHV) genes, an established prognostic and predictive biomarker for chronic lymphocytic leukemia (CLL), is assessed by gene sequencing. We developed a single methylation-specific droplet digital polymerase chain reaction (methyl-ddPCR) to predict IGHV status in patients with CLL. METHODS: The CLL methylation array and IGHV data from the International Cancer Genome Consortium (ICGC) were used for biomarker discovery. Top-ranked candidate regions were manually screened for PCR primer and probe binding sites. A single methyl-ddPCR was evaluated on an internal cohort of CLLs with mutated (M), unmutated (U), and inconclusive IGHV results originally determined by next-generation sequencing (NGS). RESULTS: Analysis of ICGC data identified array probe cg23844018 as a candidate for the PCR. The corresponding CpG site showed high methylation levels in U-CLL and lower levels in M-CLL. On the internal cohort, a single optimal cutoff correctly classified 104 of 115 U- and M-CLLs (90.4%; area under the curve&#x2005;=&#x2005;0.96). The PCR data correlated with some prognostic fluorescence in situ hybridization and CLL subset groupings. Limited analysis suggests that the PCR may be able to stratify some patients with CLL who have inconclusive results on IGHV NGS testing. CONCLUSIONS: The methyl-ddPCR showed high concordance with CLL IGHV status in an internal cohort.

Humans

KRAS Expression Complements Genomic Profiling in Identifying Therapeutic Vulnerability in Gastric Cancer.

BACKGROUND: Gastric cancer (GC) remains a major therapeutic challenge. Although alterations in the RAS pathway occur in over 50% of tumors, only a limited proportion are clinically actionable. We investigated whether KRAS expression complements genomic profiling for patient stratification and therapeutic vulnerability in GC. METHODS: Comprehensive genomic profiling was performed in 19 Taiwanese GC patients and compared with TCGA-STAD data (n = 434). KRAS mRNA expression and overall survival were evaluated by meta-analysis of 13 independent cohorts (n = 2,521). Protein-level validation was performed by immunohistochemistry in an independent cohort (n = 121). Functional KRAS dependency and response to combined MEK/SHP2 inhibition were assessed in eight GC cell lines. RESULTS: KRAS amplification was entirely contained within the KRAS-high population, whereas most KRAS-high tumors lacked detectable amplification. High KRAS expression was associated with poorer overall survival (HR 1.23, p = 0.001) and remained an independent prognostic factor after multivariable adjustment (adjusted HR 1.24, p = 0.003). Protein-level analysis showed a concordant trend. KRAS expression correlated strongly with functional dependency (R2 = 0.88, p = 0.005), was enriched in MSI and CIN subtypes, and identified cell lines with enhanced sensitivity to combined MEK/SHP2 inhibition. CONCLUSIONS: KRAS expression complements genomic profiling by identifying biologically relevant KRAS-dependent GCs beyond mutation or amplification alone. Integrating expression-based stratification with genomic profiling may improve patient selection for RAS pathway-directed combination therapies.

Biomarker

Histopathologic, Genomic, and Clinical Characteristics of Primary Cutaneous Melanocytic Tumors With Concomitant NRAS Q61 and IDH1 R132C Mutations.

Cutaneous melanocytic tumors with concomitant NRAS Q61 and IDH1 R132C mutations have been described as intermediate-grade melanocytomas with characteristic biphasic morphology, but the malignant end of this genotype-defined spectrum remains poorly characterized. We assessed histopathologic, immunohistochemical, molecular, and clinical features of 16 primary cutaneous melanocytic tumors harboring both mutations. Following integrated review, 7 tumors were classified as melanocytoma and 9 as melanoma. Melanocytomas showed reproducible biphasic architecture with congenital nevus-like features, a biphasic HMB-45 pattern, low Ki-67, PRAME negativity, retained p16, and minimal copy number variations (CNVs). Melanomas retained partial morphologic overlap in a subset but were distinguished by higher-grade cytology, immunohistochemical features supportive of malignancy, and progression-associated genomic alterations, including TERT promoter mutation (9/9), 9p21/CDKN2A loss (4/7), and higher CNV burden. NRAS and IDH1 variant allele frequencies were strongly concordant (r = 0.83, P < 0.001), supporting their presence in the same dominant clone. Clinically, two patients presented with stage IIIB disease, but no distant metastasis or melanoma-related death occurred during a median melanoma follow-up of 3.9 years (IQR, 2.5-5.1). In exploratory analyses, moderate-to-severe atypia (RR, 6.2; 95% CI, 1.0-38.8; P = .009), Ki-67 &#x2265;10% (RR, 4.4; 95% CI, 1.1-18.4; P = .003), lymphocytic infiltrate (RR, 2.4; 95% CI, 1.1-5.3; P = .03), absence of the typical biphasic pattern (RR, 2.4; 95% CI, 1.1-5.3; P = .03), and complete p16 loss (RR, 2.4; 95% CI, 1.1-5.3; P = .03) were associated with molecular or clinical progression to melanoma, defined as the presence of at least one of the following: TERT promoter mutation, pathogenic CDKN2A mutation, 9p21/CDKN2A loss, &#x2265;3 genome-wide segmental CNVs, or any metastasis. These findings support the existence of NRAS/IDH1 co-mutated melanoma as the malignant counterpart of NRAS/IDH1-mutated melanocytoma within a single genotype-defined spectrum.

IDH1 mutations

Familial occurrence of Wilms' tumor: nephroblastoma in one of monozygous twins and in another sibling.

We report the occurrence of pathologically documented Wilm's tumor in a 24-month-old male twin and just 9 months later in his 12-month-old male sibling. We considered the twins to be monozygotic because of their phenotypic similarities, the probability computed from analysis of blood groups, and the comparison of their dermatoglphics. There were no other persons in the kindred with either tumor or associated malformations, and the parents were not consanguineous. Because of the frequency of Wilm's tumor, the few instances of demonstrated occurrence in siblings seem insufficient to postulate monogenic determination. Concordance in monozygotic twins has simply not been proven. The monozygotic unaffected twin of our first patient has remained without evidence of tumor to 5 years, and, as long as he remains so, he appears to represent an exception to the hypothesis of the mutagenic origin of this childhood tumor.

Blood Group Antigens

Genomic profiling by circulating tumor DNA in patients with hormone receptor-positive/HER2-negative advanced breast cancer: Prevalence of actionable mutations across treatment lines.

INTRODUCTION: Plasma next-generation sequencing (NGS) is endorsed by ESMO as an alternative to tissue testing in advanced hormone receptor-positive, HER2-negative metastatic breast cancer (HR+/HER2- mBC), particularly after progression on endocrine therapy plus CDK4/6 inhibitors. However, prospective real-world data across distinct therapeutic contexts remain limited. PATIENTS AND METHODS: In this prospective observational study conducted within a nationwide cancer network in Brazil, centralized plasma NGS, and tissue NGS when available, was performed in two independent cohorts: prior to initiation of first-line endocrine therapy in the metastatic setting (Cohort 1) and at progression on endocrine therapy plus a CDK4/6 inhibitor (Cohort 2). The primary objective was to evaluate plasma-detected ESR1 mutation prevalence across these therapeutic contexts, and secondarily to assess other actionable drivers detected by plasma or tissue NGS. RESULTS: Among 86 collected plasma samples, 72 (84%) had evaluable NGS results (Cohort 1, n = 37; Cohort 2, n = 35). ESR1 mutations were identified in 18.9% of patients in Cohort 1 and 40.0% in Cohort 2, mostly at low variant allele fractions (<0.5%), corresponding to an absolute prevalence difference of 21.1 percentage points (95% CI, -0.2 to 40.3; P value=0.07). When considering any actionable alteration detected by plasma, including ESR1, PIK3CA, AKT1, PTEN, BRCA1, BRCA2, and ERBB2, prevalences were 43.2% and 68.6%, respectively (P value=0.04). Only four patients had ESR1 mutations identified in tissue, three in metastatic samples. Plasma-tissue concordance was higher for PIK3CA mutations (85.1%). CONCLUSION: Plasma NGS identified clinically meaningful ESR1 mutation rates across both contexts, supporting guideline-endorsed plasma-based genomic profiling in HR+/HER2- mBC.

CDK4/6 inhibitors

A novel glycogene-related signature for prognostic prediction and immune microenvironment assessment in kidney renal clear cell carcinoma.

BACKGROUND: Kidney Renal Clear Cell Carcinoma (KIRC) is a prevalent urinary malignancies worldwide. Glycosylation is a key post-translational modification that is essential in cancer progression. However, its relationship with prognosis, tumour microenvironment (TME), and treatment response in KIRC remains unclear. METHOD: Expression profiles and clinical data were retrieved from The Cancer Genome Atlas and Gene Expression Omnibus databases. Consensus clustering, Cox regression, and LASSO regression analyses were conducted to develop an optimal glycogene-related signature. The prognostic relevance of this molecular signature was rigorously analyzed, along with its connections to tumour microenvironment (TME), tumour mutation burden, immune checkpoint activity, cancer-immunity cycle regulation, immunomodulatory gene expression patterns, and therapeutic response profiles. Validation was performed using real-world clinical specimens, quantitative PCR (qPCR), and immunohistochemistry (IHC), supported by cohort analyses from the Human Protein Atlas (HPA) database. RESULTS: A glycogene-associated prognostic scoring system was established to categorize patients into risk-stratified subgroups. Patients in the high-risk cohort exhibited significantly poorer survival outcomes (p&#x2009;<&#x2009;0.001). By incorporating clinicopathological variables into this framework, we established a predictive nomogram demonstrating strong calibration and a concordance index (C-index) of 0.78. The high-risk subgroup displayed elevated immune infiltration scores (p&#x2009;<&#x2009;0.001), upregulated expression of immune checkpoint-related genes (p&#x2009;<&#x2009;0.05), and an increased frequency of somatic mutations (p&#x2009;=&#x2009;0.043). The risk score positively correlated with cancer-immunity cycle activation and immunotherapy-related signals. The high-risk groups also showed associations with T cell exhaustion, immune-activating genes, chemokines, and receptors. Drug sensitivity analysis revealed that low-risk patients were more sensitive to sorafenib, pazopanib, and erlotinib, whereas high-risk individuals responded better to temsirolimus (p&#x2009;<&#x2009;0.01). qPCR and IHC analyses consistently revealed distinct expression patterns of MX2 and other key genes across the risk groups, further corroborated by the HPA findings. CONCLUSION: This glycogene-based signature provides a robust tool for predicting prognosis, TME characteristics, and therapeutic responses in KIRC, offering potential clinical utility in patient management.

Humans

DNA Methylation-Based Classification of Kidney Neoplasms.

Renal neoplasms are morphologically and molecularly heterogeneous, with their diagnosis often hindered by interobserver variability and overlapping microscopic features. A subset of cases is unclassifiable despite immunohistochemical, mutation, and cytogenetic-based diagnostic workup. Through examination of the genome-wide DNA methylation signatures of over 2000 renal neoplasms, we identified 23 coherent groups that correlate with known neoplasm types and identified novel clinically relevant subtypes of existing neoplasm types. We used machine learning models to develop and validate a classifier trained on DNA methylation profiles of 1284 samples. The classifier was tested on an external data set of 287 renal neoplasms with >90% concordance between expected neoplasm type and high-score DNA methylation-based classification. Discordance between the original histologic label and methylation class led to potential reclassification of some cases. This work demonstrates proof of principle for the feasibility of a DNA methylation classifier as a clinically useful tool to assist in the diagnosis of renal neoplasms.

Humans