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PubMed2024

A methylation risk score for chronic kidney disease: a HyperGEN study.

Chronic kidney disease (CKD) impacts about 1 in 7 adults in the United States, but African Americans (AAs) carry a disproportionately higher burden of disease. Epigenetic modifications, such as DNA methylation at cytosine-phosphate-guanine (CpG) sites, have been linked to kidney function and may have clinical utility in predicting the risk of CKD. Given the dynamic relationship between the epigenome, environment, and disease, AAs may be especially sensitive to environment-driven methylation alterations. Moreover, risk models incorporating CpG methylation have been shown to predict disease across multiple racial groups. In this study, we developed a methylation risk score (MRS) for CKD in cohorts of AAs. We selected nine CpG sites that were previously reported to be associated with estimated glomerular filtration rate (eGFR) in epigenome-wide association studies to construct a MRS in the Hypertension Genetic Epidemiology Network (HyperGEN). In logistic mixed models, the MRS was significantly associated with prevalent CKD and was robust to multiple sensitivity analyses, including CKD risk factors. There was modest replication in validation cohorts. In summary, we demonstrated that an eGFR-based CpG score is an independent predictor of prevalent CKD, suggesting that MRS should be further investigated for clinical utility in evaluating CKD risk and progression.

Humans↗

PubMed2024

Blood-based DNA methylation and exposure risk scores predict PTSD with high accuracy in military and civilian cohorts.

BACKGROUND: Incorporating genomic data into risk prediction has become an increasingly useful approach for rapid identification of individuals most at risk for complex disorders such as PTSD. Our goal was to develop and validate Methylation Risk Scores (MRS) using machine learning to distinguish individuals who have PTSD from those who do not. METHODS: Elastic Net was used to develop three risk score models using a discovery dataset (n = 1226; 314 cases, 912 controls) comprised of 5 diverse cohorts with available blood-derived DNA methylation (DNAm) measured on the Illumina Epic BeadChip. The first risk score, exposure and methylation risk score (eMRS) used cumulative and childhood trauma exposure and DNAm variables; the second, methylation-only risk score (MoRS) was based solely on DNAm data; the third, methylation-only risk scores with adjusted exposure variables (MoRSAE) utilized DNAm data adjusted for the two exposure variables. The potential of these risk scores to predict future PTSD based on pre-deployment data was also assessed. External validation of risk scores was conducted in four independent cohorts. RESULTS: The eMRS model showed the highest accuracy (92%), precision (91%), recall (87%), and f1-score (89%) in classifying PTSD using 3730 features. While still highly accurate, the MoRS (accuracy = 89%) using 3728 features and MoRSAE (accuracy = 84%) using 4150 features showed a decline in classification power. eMRS significantly predicted PTSD in one of the four independent cohorts, the BEAR cohort (beta = 0.6839, p-0.003), but not in the remaining three cohorts. Pre-deployment risk scores from all models (eMRS, beta = 1.92; MoRS, beta = 1.99 and MoRSAE, beta = 1.77) displayed a significant (p < 0.001) predictive power for post-deployment PTSD. CONCLUSION: Results, especially those from the eMRS, reinforce earlier findings that methylation and trauma are interconnected and can be leveraged to increase the correct classification of those with vs. without PTSD. Moreover, our models can potentially be a valuable tool in predicting the future risk of developing PTSD. As more data become available, including additional molecular, environmental, and psychosocial factors in these scores may enhance their accuracy in predicting the condition and, relatedly, improve their performance in independent cohorts.

DNA methylation↗

PubMed2024

Blood-based DNA methylation and exposure risk scores predict PTSD with high accuracy in military and civilian cohorts.

BACKGROUND: Incorporating genomic data into risk prediction has become an increasingly popular approach for rapid identification of individuals most at risk for complex disorders such as PTSD. Our goal was to develop and validate Methylation Risk Scores (MRS) using machine learning to distinguish individuals who have PTSD from those who do not. METHODS: Elastic Net was used to develop three risk score models using a discovery dataset (n = 1226; 314 cases, 912 controls) comprised of 5 diverse cohorts with available blood-derived DNA methylation (DNAm) measured on the Illumina Epic BeadChip. The first risk score, exposure and methylation risk score (eMRS) used cumulative and childhood trauma exposure and DNAm variables; the second, methylation-only risk score (MoRS) was based solely on DNAm data; the third, methylation-only risk scores with adjusted exposure variables (MoRSAE) utilized DNAm data adjusted for the two exposure variables. The potential of these risk scores to predict future PTSD based on pre-deployment data was also assessed. External validation of risk scores was conducted in four independent cohorts. RESULTS: The eMRS model showed the highest accuracy (92%), precision (91%), recall (87%), and f1-score (89%) in classifying PTSD using 3730 features. While still highly accurate, the MoRS (accuracy = 89%) using 3728 features and MoRSAE (accuracy = 84%) using 4150 features showed a decline in classification power. eMRS significantly predicted PTSD in one of the four independent cohorts, the BEAR cohort (beta = 0.6839, p=0.006), but not in the remaining three cohorts. Pre-deployment risk scores from all models (eMRS, beta = 1.92; MoRS, beta = 1.99 and MoRSAE, beta = 1.77) displayed a significant (p < 0.001) predictive power for post-deployment PTSD. CONCLUSION: The inclusion of exposure variables adds to the predictive power of MRS. Classification-based MRS may be useful in predicting risk of future PTSD in populations with anticipated trauma exposure. As more data become available, including additional molecular, environmental, and psychosocial factors in these scores may enhance their accuracy in predicting PTSD and, relatedly, improve their performance in independent cohorts.

Humans↗

PubMed2025

Novel approaches and applications in identifying DNA methylation markers of cardio-kidney-metabolic disease.

Cardio-kidney-metabolic (CKM) diseases represent a major public health challenge, accounting for a large proportion of global burden of morbidity and mortality. These conditions share risk factors, including genetic predisposition, environmental exposures, and lifestyle influences, which collectively drive disease development and progression. Epigenetic modifications, particularly DNA methylation (DNAm), serve as key mediators and biomarkers between these risk factors and disease phenotypes by regulating gene expression without altering the DNA sequence. Epigenome-wide association studies have identified DNAm markers associated with CKM diseases and related phenotypes, highlighting both shared pathways and disease-specific epigenetic signatures in inflammation, metabolic dysfunction, and aging-related processes. Longitudinal studies further demonstrate the dynamic nature of DNAm changes over time, offering insights into disease trajectories. Additionally, methylation risk scores integrating multiple epigenetic markers show promise in improving disease prediction and risk stratification beyond traditional clinical factors. To synthesize the current evidence, we conducted a targeted literature search in PubMed for English-language, peer-reviewed articles published between 2014 and the present. Future research leveraging large, well-phenotyped cohorts, advanced statistical methods, and innovative study designs will be critical for uncovering novel biomarkers, refining risk prediction models, and developing targeted epigenetic therapies to mitigate the global burden.

Humans↗

PubMed2026

A pragmatic adaptation of the RANO clinical risk score for IDH-Wildtype glioblastoma in the absence of MGMT promoter methylation testing.

BACKGROUND: The novel RANO risk score provides prognostic stratification for patients with IDH-wildtype glioblastoma(GBM) and includes age, Karnofsky Performance Scale(KPS), RANO resection class(RRC), and MGMT promoter methylation(MGMTm). However, MGMTm testing is unavailable in many countries. We aimed to explore the prognostic performance of a RANO-adapted clinical score excluding MGMTm. METHODS: We applied the same scoring system established by original RANO score, excluding MGMTm. Three risk classes were defined as numerical scores derived through tertiles. The primary endpoint was overall survival(OS), and the secondary exploratory endpoint was progression-free survival(PFS). RESULTS: One-hundred twenty patients were included. Three risk classes were identified:low-risk(0-1 points,n:47, 39.2%), intermediate-risk(2-3 points,n:27, 22.5%), and high-risk(≥4 points,n:46, 38.3%). The median OS was 35.5 months(95% CI:21.1-49.9) for the low-risk group, 16 months(95% CI:9.9-22.1) for the intermediate-risk group, and 5 months(95% CI:3.6-6.3) for the high-risk group(p < 0.001). Similarly, the median PFS was 16.3 months(95% CI:12.3-20.3) for the low-risk group, 9.9 months(95% CI:7.2-12.6) for the intermediate-risk group, and 4.1 months(95% CI:3.5-4.7) for the high-risk group(p < 0.001). CONCLUSION: This simplified RANO-adapted score demonstrated promising prognostic stratification using basic clinical parameters. As a pragmatic adaptation study, external validation is required before clinical application, particularly in settings where MGMTm testing is unavailable.

Humans↗

PubMed2024

Association analysis between an epigenetic alcohol risk score and blood pressure.

BACKGROUND: Epigenome-wide association studies have identified multiple DNA methylation sites (CpGs) associated with alcohol consumption, an important lifestyle risk factor for cardiovascular diseases. This study aimed to test the hypothesis that an alcohol consumption epigenetic risk score (ERS) is associated with blood pressure (BP) traits. RESULTS: We implemented an ERS based on a previously reported epigenetic signature of 144 alcohol-associated CpGs in meta-analysis of participants of European ancestry. We found a one-unit increment of ERS was associated with eleven drinks of alcohol consumed per day, on average, across several cohorts (p < 0.0001). We examined the association of the ERS with systolic blood pressure (SBP), diastolic blood pressure (DBP), and hypertension (HTN) in 3,898 Framingham Heart Study (FHS) participants. Cross-sectional analyses in FHS revealed that a one-unit increment of the ERS was associated with 1.93 mm Hg higher SBP (p = 4.64E-07), 0.68 mm Hg higher DBP (p = 0.006), and an odds ratio of 1.78 for HTN (p < 2E-16). Meta-analysis of the cross-sectional association of the ERS with BP traits in eight independent external cohorts (n = 11,544) showed similar relationships with BP levels, i.e., a one-unit increase in ERS was associated with 0.74 mm Hg (p = 0.002) higher SBP and 0.50 mm Hg (p = 0.0006) higher DBP, but not with HTN. Longitudinal analyses in FHS (n = 3260) and five independent external cohorts (n = 4021) showed that the baseline ERS was not associated with a change in BP over time or with incident HTN. CONCLUSIONS: Our findings demonstrate that the ERS has potential clinical utility in assessing lifestyle factors related to cardiovascular risk, especially when self-reported behavioral data (e.g., alcohol consumption) are unreliable or unavailable.

Humans↗

PubMed2026

Potential mitochondria-associated pathogenic genes in sepsis: a multi-omics Mendelian randomization study.

BACKGROUND: Mitochondrial dysfunction has been implicated in the pathophysiology of sepsis. However, human genetic evidence linking mitochondria-related genes to sepsis susceptibility remains limited. This study aimed to identify mitochondria-related genes associated with sepsis risk using a multi-omics Mendelian randomization framework. METHODS: Summary-data-based Mendelian randomization (SMR) was applied using sepsis genome-wide association study (GWAS) summary statistics from the UK Biobank and FinnGen databases. Expression, methylation, single-cell, and protein quantitative trait loci (QTLs) were used as genetic instruments. Colocalization analyses were conducted to evaluate whether SMR associations were driven by shared genetic variants. Expression of prioritized candidate genes was further examined in clinical septic samples, and correlations with disease severity (SOFA scores) were assessed. RESULTS: SMR analysis prioritized 13 mitochondria-related genes associated with sepsis risk. Immune cell-specific eQTL analysis suggested that genetically predicted SURF1 expression in memory B cells and naïve T cells was associated with sepsis risk. Differential expression of 12 candidate genes was confirmed in septic patients by qPCR, and PPOX expression showed a negative correlation with SOFA scores. Integration of mQTL and eQTL data supported a regulatory relationship between methylation at cg06661924 and AK4 expression. Increased genetically predicted AK4 expression was associated with higher sepsis risk (OR = 1.21, 95% CI 1.02-1.42). Protein-level analysis identified DUT as a potential sepsis-associated candidate, with consistent evidence across streptococcal and pneumococcal septicemia subtypes. Subtype analyses also suggested heterogeneous genetic signals across different sepsis subtypes. CONCLUSION: This study prioritized several mitochondria-related genes associated with sepsis susceptibility based on human genetic evidence. These findings provide candidate targets for further mechanistic and translational investigation.

Humans↗

PubMed2026

Age-associated epigenomic heterogeneity in papillary tumors of the pineal region: a multicenter YoungNOA investigation.

BACKGROUND: Papillary tumors of the pineal region (PTPR) are rare CNS neoplasms with adult and pediatric presentations, but whether age defines distinct molecular biology is unclear. METHODS: We assembled a multicenter retrospective cohort of 86 histologically confirmed PTPR with genome-wide DNA methylation data, comprising 62 adult and 24 pediatric tumors. Molecular subgroup, array platform, sex, and tumor purity were incorporated into multivariable models. Analyses included DNA methylation class assignment, differential methylation, copy-number variation (CNV), epigenetic mitotic-clock scores, methylation-based tumor microenvironment deconvolution, and descriptive survival evaluation. RESULTS: Adult and pediatric tumors mapped within the established PTPR-A and PTPR-B methylation framework rather than forming age-defined methylation classes. Pediatric tumors were enriched for PTPR-B (22 of 24 tumors [91.7%]) compared with adult tumors (39 of 62 [62.9%]). After adjustment for methylation-based subgroup as well as technical and biological covariates, 2,923 CpG probes were associated with age at a false discovery rate (FDR) threshold below 0.05, and 530 also met the prespecified effect-size threshold. Global methylation summaries were similar between age groups. CNV patterns were dominated by molecular subgroup; adjusted genomic CNV load was not independently associated with pediatric age. In contrast, epiTOC2 intrinsic rate score and the methylation signature represented by the first principal component (PC1) showed age-associated effects independent of molecular subgroup. Methylation-based deconvolution suggested a limited microenvironmental signal, with neutrophil fraction showing the most consistent adjusted association. CONCLUSIONS: Adult and pediatric PTPR share the established PTPR-A/PTPR-B framework. Pediatric tumors, particularly within PTPR-B, showed age-associated DNA methylation differences and higher epigenetic mitotic-clock (epiTOC2) scores in this retrospective cohort. These tissue-level associations do not establish clinical risk or treatment implications and require prospective clinical annotation and orthogonal validation.

Humans↗

PubMed2026

Methylation-Associated Differentiation Features Define Biological and Prognostic Heterogeneity in CMS4 Colorectal Cancer.

Consensus molecular subtype 4 (CMS4) colorectal cancer (CRC) is associated with an aggressive clinical course and poor survival, yet the biological basis of heterogeneity within this subtype remains incompletely understood. DNA methylation is an epigenetic mechanism involved in transcriptional regulation, cellular differentiation, and colorectal tumorigenesis. Here, we integrated single-cell RNA sequencing (scRNA-seq), bulk data, and promoter DNA methylation data to characterize CMS4-associated cancer cell states and methylation-related features. Using the scAB algorithm, we integrated scRNA-seq with bulk CMS4 data and identified CMS4-related cells distributed across multiple patients. Single-cell analyses of cell-cell communication and transcriptional regulation revealed a CMS4-related cancer cell population characterized by macrophage migration inhibitory factor (MIF)-centered intercellular communication, enhanced caudal type homeobox 1 (CDX1) and Kruppel-like factor 5 (KLF5) regulon activity, and gene modules enriched in differentiation-related pathways. CytoTRACE analysis further stratified CMS4 cancer cells into poorly and well-differentiated states, yielding 802 differentially expressed genes (DEGs). Linking these differentiation-associated DEGs with bulk expression and promoter methylation data identified 218 methylation-associated DEGs showing significant inverse methylation expression correlations, suggesting a link between differentiation-related heterogeneity and promoter methylation. Univariable Cox regression followed by LASSO regression further prioritized eight genes for construction of the methylation and differentiation-related prognostic model (MeDiff-PM). MeDiff-PM consistently stratified overall survival in the TCGA CMS4 cohort and two independent validation cohorts, with cutoff-independent continuous Cox analyses further supporting its prognostic association across cohorts. And MeDiff-PM remained prognostically significant after adjustment for available clinical variables. High MeDiff-PM risk scores were associated with activation of P53, WNT, and ubiquitin-mediated proteolysis pathways and with consistent predicted drug response differences for compounds across three CMS4 cohorts. While individual in silico knockout analysis suggested links between MeDiff-PM genes and metallothionein-related and immune-associated transcriptional responses. Collectively, these findings indicate that methylation-associated differentiation features represent a molecular dimension of intra-CMS4 heterogeneity and provide a biologically informed framework for prognostic stratification within CMS4 CRC.

Humans↗

PubMed2026

Methylation profiling in CNS tumor diagnostics: a single-centre real-world experience from Central Europe.

Genome-wide DNA methylation profiling has transformed neuro-oncology by providing an objective, machine learning-based taxonomy that mitigates interobserver variability and refines the histo-molecular criteria of the current WHO classification. We evaluate the real-world diagnostic performance and clinical utility of this modality in a prospective, consecutively accrued three-year cohort of 291 central nervous system (CNS) tumors across a mixed adult-pediatric population. Successful profiling was completed in 95.9% of cases. Using the Epignostix classifier, a high-confidence diagnostic match (calibrated score [CS] ≥ 0.84) was achieved in 70.3% of analyzable samples, while 26.5% returned lower-confidence scores (≥ 0.3 to < 0.84) and only 3.2% remained completely unclassifiable (CS < 0.3). When integrated into a comprehensive diagnostic framework, methylation profiling provided clinically useful results in 81.1% of cases, establishing diagnoses in 70 cases submitted for molecular subclassification and resolving diagnostic uncertainty or prompting major revisions in 149 histologically challenging tumors. Within truly ambiguous lesions, integration of methylome data dictated tumor grade modifications in 38.8% of cases (upgrading in 29.4% and downgrading in 9.4%), shifting patient risk stratification. Crucially, over half (52.7%) of the lower-confidence cases yielded meaningful clinical integration when supported by histomorphology and ancillary genetic or immunohistochemical markers, demonstrating that rigid score cutoffs should not dictate assay failure. Discrepant or misleading classifications occurred in 1.9%. Updating bioinformatic pipelines from version 11b4 to 12.8 rescued multiple ambiguous entries, increasing overall clinical utility to 84.1%. These findings demonstrate that integrating computational epigenomics with classical neuropathology enhances diagnostic precision, while highlighting the ongoing need for careful clinical-pathological correlation.

Central nervous system tumors↗

PubMed2003

Lack of HIN-1 methylation in BRCA1-linked and "BRCA1-like" breast tumors.

We recently identified a candidate tumor suppressor gene, HIN-1, that is silenced due to methylation in the majority of sporadic breast carcinomas and is localized to 5q33-qter, an area frequently lost in BRCA1 tumors and thought to harbor a BRCA1 modifier gene. To establish whether germ-line mutations in HIN-1 may influence breast cancer risk, we sequenced the HIN-1 coding region in 10 familial breast cancer patients with positive logarithm of the odds scores of at least one of the markers flanking HIN-1. We also sequenced the HIN-1 coding region in 15 BRCA1 and 35 sporadic breast tumors to determine whether HIN-1 is the target of the frequent 5q loss in BRCA1 tumors. No sequence alterations were found in any of the cases analyzed. However, analysis of HIN-1 promoter methylation status revealed that in striking contrast to sporadic cases, there is a nearly complete lack of HIN-1 methylation in BRCA1 tumors (P < 0.0001). Sporadic breast tumors with a "BRCA1-like" histopathological phenotype also demonstrated significantly lower frequency of HIN-1 promoter methylation (P = 0.01) compared with other cancer types, and there was also a difference among tumors based on their estrogen receptor and HER2 status (P = 0.006), suggesting that HIN-1 methylation patterns are associated with specific breast cancer subtypes.

Breast Neoplasms↗

PubMed2003

Folate status, genomic DNA hypomethylation, and risk of colorectal adenoma and cancer: a case control study.

BACKGROUND & AIMS: Low folate intake may increase risk for colorectal cancer by inducing DNA hypomethylation. This study reports the influence of folate status, DNA methylation, and polymorphisms of methylenetetrahydrofolate reductase (MTHFR 677C-->T and 1298A-->C), methionine synthase (MS 2756A-->G), and cystathionine-beta-synthase (CBS 844ins68) on risk for developing colorectal neoplasia. METHODS: Thirty-five patients with adenoma, 28 patients with cancer, and 76 controls were recruited for a case control study. Recruitment consent rate was 98%. Blood samples were obtained for determination of blood folates, vitamin B(12), homocysteine, DNA methylation, and genotypes. Tissue biopsy samples were obtained at colonoscopy for determination of DNA methylation in colonic mucosa. Folate status was assessed by constructing a score from estimates of dietary intake and serum and erythrocyte folate. RESULTS: Cancer patients had 26% lower folate status (95% confidence interval [CI]: 6% to 44%, P = 0.01) and 21% lower serum vitamin B(12) concentration (95% CI: -38% to 1%, P = 0.06) compared with controls. [(3)H] methyl incorporation into colonic DNA was 26% higher in patients with adenoma (95% CI: 8% to 56%, P = 0.009) and 30% higher in patients with cancer (95% CI: -3% to 48%, P = 0.08) compared with controls. High folate status was associated with decreased risk for cancer (P = 0.01 for trend). Colonic and leukocyte DNA hypomethylation were associated with increased risk for adenoma (P = 0.02 and P = 0.01 for trend, respectively) and a nonsignificantly increased risk for cancer (P = 0.09 and P = 0.08 for trend, respectively). CONCLUSIONS: Low folate status and DNA hypomethylation are associated with colorectal neoplasia.

Adenoma↗

PubMed1994

Occupational exposure to chlorinated aliphatic hydrocarbons and risk of astrocytic brain cancer.

Chlorinated aliphatic hydrocarbons (CAHs) were evaluated as potential risk factors for astrocytic brain tumors. Job-exposure matrices for six individual CAHs and for the general class of organic solvents were applied to data from a case-control study of brain cancer among white men. The matrices indicated whether the CAHs were likely to have been used in each industry and occupation by decade (1920-1980), and provided estimates of probability and intensity of exposure for "exposed" industries and occupations. Cumulative exposure indices were calculated for each subject. Associations of astrocytic brain cancer were observed with likely exposure to carbon tetrachloride, methylene chloride, tetrachloroethylene, and trichloroethylene, but were strongest for methylene chloride. Exposure to chloroform or methyl chloroform showed little indication of an association with brain cancer. Risk of astrocytic brain tumors increased with probability and average intensity of exposure, and with duration of employment in jobs considered exposed to methylene chloride, but not with a cumulative exposure score. These trends could not be explained by exposures to the other solvents.

Astrocytoma↗

PubMed2005

Paternal age and intelligence: implications for age-related genomic changes in male germ cells.

BACKGROUND: A robust association between advancing paternal age and schizophrenia risk is reported, and genetic changes in the germ cells of older men are presumed to underlie the effect. If that is so, then the pathway may include effects on cognition, as those with premorbid schizophrenia are reported to have lower intelligence. There are also substantial genetic influences on intelligence, so de novo genetic events in male germ cells, which accompany advancing paternal age, may plausibly influence offspring intelligence. OBJECTIVE: An association of paternal age with IQ in healthy adolescents may illuminate the mechanisms that link it to schizophrenia. METHOD: We examined the association of paternal age and IQ scores using the Israeli Army Board data on 44 175 individuals from a richly described birth cohort, along with maternal age and other potential modifiers. RESULTS: A significant inverted U-shaped relationship was observed between paternal age and IQ scores, which was independent from a similar association of IQ scores with maternal age. These relationships were not significantly attenuated by controlling for multiple possible confounding factors, including the other parent's age, parental education, social class, sex and birth order, birth weight and birth complications. Overall, parental age accounted for approximately 2% of the total variance in IQ scores, with later paternal age lowering non-verbal IQ scores more than verbal IQ scores. CONCLUSION: We found independent effects of maternal and paternal age on offspring IQ scores. The paternal age effect may be explained by de novo mutations or abnormal methylation of paternally imprinted genes, whereas maternal age may affect fetal neurodevelopment through age-related alterations in the in-utero environment. The influence of late paternal age to modify non-verbal IQ may be related to the pathways that increase the risk for schizophrenia in the offspring of older fathers.

Cohort Studies↗

PubMed2025

Foundation model based multimodal transformer framework for survival analysis in HER2 stratified breast cancer.

Objective. To improve survival prediction for HER2-positive breast cancer by integrating histopathological, molecular, and clinical data using a multimodal transformer framework.Approach. We propose a multimodal transformer framework for breast cancer survival prediction using HER2 stratified (SurvMBC), a foundation model-enhanced architecture that fuses three data modalities: whole-slide images, clinical narratives, and molecular features. Tumor microenvironment features are extracted using a pathology language and image pre-training (PLIP), clinical narratives are processed with BioBERT, and miRNA expression plus DNA methylation data are embedded using Gen2Vec. These representations are integrated through a cross-modal transformer with attention mechanisms for survival prediction.Main results. The model was evaluated on 1,095 HER2-positive breast cancer patients from The Cancer Genome Atlas. SurvMBC achieved a concordance index (C-index) of 0.857 (95% CI: 0.834, 0.880), a low integrated Brier score, and a strong inverse negative binomial log-likelihood. Risk stratification based on model outputs significantly separated high- and low-risk groups (log-rankp< 0.01) and showed strong associations with tumor stage, grade, and hormone receptor status (allp< 0.05).Significance. SurvMBC demonstrates the effectiveness of multimodal fusion in addressing tumor heterogeneity and improving prognostic accuracy. The attention-based integration enables context-aware learning of survival-relevant features across modalities, supporting individualized risk stratification and risk-adaptive treatment planning for HER2 stratified breast cancer patients.

Breast Neoplasms↗

PubMed2006

Association of smoking, CpG island methylator phenotype, and V600E BRAF mutations in colon cancer.

BACKGROUND: Cigarette smoking has been associated with microsatellite instability in sporadic colon cancer. Most microsatellite-unstable colon cancers have widespread methylation of CpG islands (i.e., the CpG island methylator phenotype [CIMP]), and many of these tumors harbor the V600E BRAF mutation. We investigated whether the association between smoking and all colon cancers could be explained through induction of CIMP and/or BRAF mutations. METHODS: We evaluated 1315 case patients with colon cancer and 2392 control subjects in a population-based study. Demographic information, including smoking history, was obtained in an interview. Microsatellite instability was determined primarily by evaluation of the mononucleotide repeat BAT-26. CIMP was determined by sodium bisulfite modification of DNA followed by methylation-specific polymerase chain reaction amplification of CpG islands in hMLH1, p16, and MINTS1, -2, and -31. Tumors were scored as CIMP high (i.e., > or = 2 CpG islands methylated) or CIMP low (i.e., < 2 CpG islands methylated). BRAF V600E mutations were identified by sequencing. Logistic regression was used to quantify relationships among smoking, CIMP, and BRAF. All statistical tests were two-sided. RESULTS: Heavy smoking (i.e., > 20 cigarettes per day), compared with nonsmoking, was associated with an increased risk of CIMP-high colon cancer (odds ratio [OR] = 2.06, 95% confidence interval [CI] = 1.43 to 2.97) and also with BRAF V600E mutations (OR = 3.16, 95% CI = 1.80 to 5.54). The association between cigarette smoking and the risk of colon cancer was limited to the minority of tumors that were CIMP high and BRAF wild type or CIMP high and BRAF mutated (for heavy smokers, OR = 1.91, 95% CI = 1.23 to 2.97, and OR = 2.85, 95% CI = 1.53 to 5.29, respectively). All relationships above showed a statistically significant relationship to amount smoked (P(trend) < .001 for all, except that relationship with tumors that were CIMP high and BRAF wild type, for which P(trend) = .008) and were independent of microsatellite instability. CONCLUSIONS: Previously identified associations between smoking and colon cancer, whether microsatellite unstable or stable, appear to be explained by the association of smoking with CIMP and BRAF mutations.

Amino Acid Substitution↗

PubMed2005

Promoter hypermethylation as an independent prognostic factor for relapse in patients with prostate cancer following radical prostatectomy.

PURPOSE: To analyze the prognostic significance of six epigenetic biomarkers (APC, Cyclin D2, GSTP1, TIG1, Rassf1A, and RARbeta2 promoter hypermethylation) in a homogeneous group of prostate cancer patients, following radical prostatectomy alone. PATIENTS AND METHODS: Biomarker analyses were done retrospectively on tumors from 74 prostate cancer patients all with a Gleason score of 3 + 4 = 7 and minimum follow-up period of 7 years. Using quantitative methylation-specific PCR, we analyzed six gene promoters in primary prostate tumor tissues. Time to any progression was the primary end point, and development of metastatic disease and/or death from prostate cancer was a secondary point. The association of clinicopathologic and biomolecular risk factors to recurrence was done using the log-rank test and Cox proportional hazards model for multivariate analysis. To identify independent prognostic factors, a stepwise selection method was used. RESULTS: At a median follow-up time of 9 years, 37 patients (50%) had evidence of recurrence: biochemical/prostate-specific antigen relapse, metastases, or death from prostate cancer. In the final multivariate analysis for time to progression (TTP), the significant factors were age > 60 [hazard ratio (HR), 0.4; 95% confidence interval (95% CI), 0.2-0.8; P = 0.01], hypermethylation of GSTP1 (HR, 0.23; 95% CI; 0.09-0.64; P = 0.004), and hypermethylation of APC (HR, 3.0; 95% CI, 1.42-6.32; P = 0.004). In another multivariate analysis, a profile of hypermethylation of APC and cyclin D2 hypermethylation was significant as well: if either any one was hypermethylated (HR, 1.84; 95% CI, 0.92-3.72; P = 0.09) or if both were hypermethylated (HR, 4.3; 95% CI, 1.52-12.33; P = 0.01). CONCLUSIONS: Methylation status of selected genes in the prostate cancer specimen may predict for time to recurrence in Gleason 3 + 4 = 7 patients undergoing prostatectomy. These results should be validated in a larger and unselected cohort.

Adenomatous Polyposis Coli Protein↗

PubMed2006

Supplemental 80% oxygen does not attenuate post-operative nausea and vomiting after breast surgery.

BACKGROUND: Although supplemental oxygen has been shown to be as effective as ondansetron in the prevention of post-operative nausea and vomiting (PONV) in one study in abdominal surgery patients, the antiemetic efficacy of supplemental oxygen is controversial on the basis of studies with other patients. We compared the efficacy of 80% and 30% oxygen in decreasing PONV in breast surgery. Ondansetron was used as an active control. METHODS: Ninety patients were given a standardized sevoflurane anesthetic. They were randomly assigned to three groups: 30% oxygen in nitrogen and saline 2 ml intravenously (i.v.) at the end of surgery (group 30); 80% oxygen in nitrogen and saline 2 ml (group 80); and 30% oxygen in nitrogen and ondansetron 4 mg (group O). Oxygen was administered during surgery and up to 2 h after surgery. RESULTS: The incidence of total response (no retching or vomiting, no nausea) during the first 24 post-operative hours was not different between group 80 (17%) and group 30 (11%) but was higher in group O (43%) than in group 30 (P<0.05). Compared with group O, patients in group 80 experienced more vomiting during the study period 0-24 h (66% vs. 32%; P<0.05) and more nausea during the period 6-24 h (72% vs. 39%; P<0.05). There was no difference between the groups in their risk for PONV, pain scores, opioid consumption, or patient satisfaction. CONCLUSIONS: In this study, supplemental 80% oxygen administration failed to decrease PONV in breast surgery.

Adolescent↗