Citations

Abstract Background Cardiac magnetic resonance elastography (MRE) allows the non-invasive quantification of myocardial stiffness, but long-interval reproducibility data at 3.0 T single-frequency 140-Hz remain limited. Purpose To evaluate the short- and long-interval reproducibility of 3.0 T cardiac MRE for left ventricular (LV) myocardial stiffness across healthy volunteers and patients with conditions associated with elevated myocardial stiffness. Materials and Methods This prospective single-center study included 69 participants: 60 healthy volunteers and 9 with cardiovascular disease (6 with aortic stenosis and 3 with long-standing hypertension). All participants underwent baseline cardiac MRE (scanner: Signa Premier 3.0 T, GE Healthcare, driver: Resoundant), an immediate short-interval rescan (SIR) within 5 minutes, and a long-interval rescan (LIR) after approximately 1 month. Left ventricular myocardial stiffness and octahedral shear strain signal-to-noise ratio were measured independently by 2 readers. Reproducibility was assessed using Bland-Altman analysis, intraclass correlation coefficients (ICCs), within-subject coefficient of variation, standard error of measurement, and smallest detectable change at the 95% confidence (SDC95) level. Results Baseline LV myocardial stiffness was higher in the disease group than in healthy volunteers, 11.73 ± 1.01 kPa and 7.80 ± 0.70 kPa (mean ± SD; P < .001), respectively. Inter-reader agreement was excellent across all timepoints, with ICCs of 0.970 at baseline (95% CI, 0.953-0.982), 0.966 for SIR (95% CI, 0.945-0.979), and 0.962 for LIR (95% CI, 0.939-0.976). Within-reader scan-rescan reproducibility was also excellent. For Reader 1, stiffness ICC was 0.979 for the SIR (95% CI, 0.966-0.987) and 0.957 for the LIR (95% CI, 0.932-0.973), with SDC95 values of 0.616 kPa (95% CI, 0.528-0.741) and 0.869 kPa (95% CI, 0.744-1.044), respectively. Reader 2 showed excellent reproducibility, with ICCs ≤0.943. Conclusions 3D single-frequency 140-Hz cardiac MRE at 3.0 T provides excellent short- and long-interval reproducibility for LV myocardial stiffness quantification. The SDC95 values may help distinguish true longitudinal stiffness changes from measurement variability.

PURPOSE Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related deaths worldwide. The higher incidence and earlier onset of HCC in sub-Saharan Africa suggest a potential role for a genetic predisposition. This study evaluated the association of TERT -rs2242652-(A), a variant linked to lower HCC risk, with HCC in populations from Ghana, Nigeria, and Cameroon, compared with a population from the United States. METHODS The study included 537 patients with HCC: United States (n = 348), Ghana (n = 79), Nigeria (n = 43), and Cameroon (n = 67). The control group had 2,872 cancer-free individuals: United States (n = 2,399), Ghana (n = 323), Nigeria (n = 85), and Cameroon (n = 65). Whole-exome sequencing was conducted using germline DNA, and data for TERT -rs2242652 were analyzed. Odds ratios (ORs) and 95% CIs were calculated using unconditional logistic regression. Chi-square tests assessed protective allele frequencies. RESULTS In the US cohort, TERT -rs2242652 was significantly associated with lower HCC risk (OR, 0.75 [95% CI, 0.58 to 0.96]; P = .02), with an allele frequency of 18.8% (15.4% in HCC cases v 19.3% in controls). In the combined sub-Saharan African population, no significant association was observed, but there was a trend toward decreased HCC risk (OR, 0.80 [95% CI, 0.53 to 1.22]; P = .29), with an allele frequency of 12.2% (10.6% in HCC cases v 12.9% in controls). Separate analyses of Ghanaian, Nigerian, and Cameroonian populations showed similar nonsignificant trends. The protective allele frequency in the combined African populations was significantly lower than in the US cohort ( P < .0001). CONCLUSION In sub-Saharan African populations, there was a lower frequency of the HCC protective allele TERT -rs2242652 compared with European Americans. These findings underscore the importance of multiethnic genetic studies in understanding population differences in HCC risk and developing prevention strategies.

Abstract Hepatocellular carcinoma (HCC) is a leading cause of cancer mortality globally, with particularly high burdens among people living with HIV (PLWH) in low‐resource settings like Nigeria. Effective early detection remains a major challenge due to limited access to imaging‐based surveillance and the low sensitivity of current biomarkers such as alpha‐fetoprotein (AFP). We conducted an epigenome‐wide association study (EWAS) of circulating cell‐free DNA (ccfDNA) methylation in a Nigerian cohort of HIV‐positive individuals ( n = 245), spanning HCC, cirrhosis (FibroScan ≥12.3 kPa), fibrosis (FibroScan ≥7.6 and <12.3 kPa), and HCC‐free without fibrosis (FibroScan <7.6 kPa) groups. Using random forest modeling, we developed and evaluated a ccfDNA methylation classifier (ccfDNAmRF) for HCC risk prediction. We identified 73 CpG sites significantly associated with HCC (false discovery rate <0.01). The ccfDNAmRF model demonstrated strong discriminatory power, achieving 100% sensitivity and 80%–91% specificity for distinguishing HCC from cirrhosis, fibrosis, and HCC‐free groups (area under the curve [AUC]: 92%–97%). Combining ccfDNA methylation risk scores with AFP further improved classification accuracy (AUC up to 98.5%). Notably, ccfDNA methylation patterns displayed clear dose–response relationships across the disease spectrum, supporting their utility for early‐stage detection and risk stratification. Our findings highlight the promise of ccfDNA methylation biomarkers as a non‐invasive, blood‐based screening tool for improving early identification of HCC cases among PLWH.

PURPOSE Large language models (LLMs) have demonstrated remarkable versatility in oncology applications, such as cancer staging and survival analysis. Despite their potential, ethical concerns such as data privacy breaches, bias in training data, lack of transparency, and risks associated with erroneous outputs pose significant challenges to their adoption in high-stakes oncology settings. Therefore, we aim to explore the ethical challenges associated with LLM-based applications in oncology and evaluate emerging techniques designed to address these issues. METHODS Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses framework, a systematic review was conducted to evaluate publications related to ethical issues of LLMs in oncology across eight academic databases (eg, PubMed, Web of Science, and Embase) between January 1, 2019, and December 31, 2024. RESULTS The search retrieved 4,319 published articles, of which 65 publications were preserved and included in our analysis. We identified six prevalent ethical challenges in oncology, including trust, equity, privacy, transparency, nonmaleficence, and accountability. We then evaluated emerging technical solutions to mitigate ethical challenges and summarized evaluation metrics used to assess these solutions' effectiveness. CONCLUSION This review provides actionable recommendations for responsibly deploying LLMs in oncology, ensuring adherence to ethical guidelines, and fostering improved patient outcomes. By bridging technical and clinical perspectives, this review offers a foundational framework for advancing ethical artificial intelligence applications in oncology and highlights areas for future research.

Abstract Background Physical activity (PA) is an established protective factor for colorectal cancer (CRC), but it is unclear if genetic variants modify this effect. To investigate this possibility, we conducted a genome-wide gene–PA interaction analysis. Methods Using logistic regression and two-step and joint tests, we analyzed interactions between common genetic variants across the genome and PA in relation to CRC risk. Self-reported PA levels were categorized as active (≥ 8.75 MET-h/wk) vs. inactive (< 8.75 MET-h/wk) and as study- and sex-specific quartiles of activity. Results PA had an overall protective effect on CRC (OR [active vs. inactive] = 0.85; 95%CI = 0.81–0.90). The two-step GxE method identified an interaction between rs4779584, an intergenic variant near the GREM1 and SCG5 genes, and PA for CRC risk (p-interaction = 2.6×10 − 8 ). Stratification by genotype at this locus showed a significant reduction in CRC risk by 20% in active vs. inactive participants with the CC genotype (OR = 0.80; 95%CI = 0.75–0.85), but no significant PA–CRC association among CT or TT carriers. When PA was modeled as quartiles, the 1-d.f. GxE test identified that rs56906466, an intergenic variant near the KCNG1 gene, modified the association between PA and CRC (p-interaction = 3.5×10 − 8 ). Stratification at this locus showed that increase in PA (highest vs. lowest quartile) was associated with a lower CRC risk solely among TT carriers (OR = 0.77; 95%CI = 0.72–0.82). Conclusions In summary, we identified two genetic variants that modified the association between PA and CRC risk. One of them, related to GREM1 and SCG5 , suggests that the bone morphogenetic protein (BMP)-related, inflammatory, and/or insulin signaling pathways may be associated with the protective influence of PA on colorectal carcinogenesis.

SummaryDespite the clinical and molecular heterogeneity of follicular lymphoma (FL), there remains a lack of biomarker‐directed therapeutic approaches in routine clinical practice, with the notable exception of the EZH2 inhibitor tazemetostat in EZH2‐mutant FL. Here we examined whether gene mutation status predicts response to clinical mTOR inhibitors (mTORi) in FL, by performing targeted mutational profiling of biopsies from 21 relapsed/refractory FL patients treated with mTORi everolimus or temsirolimus within clinical trials. We observed an enrichment of mutations within the catalytic histone acetyltransferase (HAT) domain of CREBBP in mTORi‐responders, and describe distinct transcriptional characteristics and co‐occurring mutations of FL harbouring these mutations; reinforcing the growing appreciation of CREBBPHAT mutation as a key biological determinant and its promise as a therapeutic biomarker in FL.

Regular, long-term aspirin use may act synergistically with genetic variants, particularly those in mechanistically relevant pathways, to confer a protective effect on colorectal cancer (CRC) risk. We leveraged pooled data from 52 clinical trial, cohort, and case-control studies that included 30,806 CRC cases and 41,861 controls of European ancestry to conduct a genome-wide interaction scan between regular aspirin/nonsteroidal anti-inflammatory drug (NSAID) use and imputed genetic variants. After adjusting for multiple comparisons, we identified statistically significant interactions between regular aspirin/NSAID use and variants in 6q24.1 (top hit rs72833769 ), which has evidence of influencing expression of TBC1D7 (a subunit of the TSC1-TSC2 complex, a key regulator of MTOR activity), and variants in 5p13.1 (top hit rs350047 ), which is associated with expression of PTGER4 (codes a cell surface receptor directly involved in the mode of action of aspirin). Genetic variants with functional impact may modulate the chemopreventive effect of regular aspirin use, and our study identifies putative previously unidentified targets for additional mechanistic interrogation.

Abstract Colorectal cancer risk can be impacted by genetic, environmental, and lifestyle factors, including diet and obesity. Gene-environment interactions (G × E) can provide biological insights into the effects of obesity on colorectal cancer risk. Here, we assessed potential genome-wide G × E interactions between body mass index (BMI) and common SNPs for colorectal cancer risk using data from 36,415 colorectal cancer cases and 48,451 controls from three international colorectal cancer consortia (CCFR, CORECT, and GECCO). The G × E tests included the conventional logistic regression using multiplicative terms (one degree of freedom, 1DF test), the two-step EDGE method, and the joint 3DF test, each of which is powerful for detecting G × E interactions under specific conditions. BMI was associated with higher colorectal cancer risk. The two-step approach revealed a statistically significant G×BMI interaction located within the Formin 1/Gremlin 1 (FMN1/GREM1) gene region (rs58349661). This SNP was also identified by the 3DF test, with a suggestive statistical significance in the 1DF test. Among participants with the CC genotype of rs58349661, overweight and obesity categories were associated with higher colorectal cancer risk, whereas null associations were observed across BMI categories in those with the TT genotype. Using data from three large international consortia, this study discovered a locus in the FMN1/GREM1 gene region that interacts with BMI on the association with colorectal cancer risk. Further studies should examine the potential mechanisms through which this locus modifies the etiologic link between obesity and colorectal cancer. Significance: This gene-environment interaction analysis revealed a genetic locus in FMN1/GREM1 that interacts with body mass index in colorectal cancer risk, suggesting potential implications for precision prevention strategies.

Abstract Background: Tobacco smoking is an established risk factor for colorectal cancer. However, genetically defined population subgroups may have increased susceptibility to smoking-related effects on colorectal cancer. Methods: A genome-wide interaction scan was performed including 33,756 colorectal cancer cases and 44,346 controls from three genetic consortia. Results: Evidence of an interaction was observed between smoking status (ever vs. never smokers) and a locus on 3p12.1 (rs9880919, P = 4.58 × 10−8), with higher associated risk in subjects carrying the GG genotype [OR, 1.25; 95% confidence interval (CI), 1.20–1.30] compared with the other genotypes (OR &lt;1.17 for GA and AA). Among ever smokers, we observed interactions between smoking intensity (increase in 10 cigarettes smoked per day) and two loci on 6p21.33 (rs4151657, P = 1.72 × 10−8) and 8q24.23 (rs7005722, P = 2.88 × 10−8). Subjects carrying the rs4151657 TT genotype showed higher risk (OR, 1.12; 95% CI, 1.09–1.16) compared with the other genotypes (OR &lt;1.06 for TC and CC). Similarly, higher risk was observed among subjects carrying the rs7005722 AA genotype (OR, 1.17; 95% CI, 1.07–1.28) compared with the other genotypes (OR &lt;1.13 for AC and CC). Functional annotation revealed that SNPs in 3p12.1 and 6p21.33 loci were located in regulatory regions, and were associated with expression levels of nearby genes. Genetic models predicting gene expression revealed that smoking parameters were associated with lower colorectal cancer risk with higher expression levels of CADM2 (3p12.1) and ATF6B (6p21.33). Conclusions: Our study identified novel genetic loci that may modulate the risk for colorectal cancer of smoking status and intensity, linked to tumor suppression and immune response. Impact: These findings can guide potential prevention treatments.