RESUMO
Colorectal cancer (CRC) stands as a major contributor to cancer-related fatalities within China. There is an urgent need to identify accurate biomarkers for recurrence predicting in CRC. Reduced representation bisulfite sequencing was used to perform a comparative analysis of methylation profiles in tissue samples from 30 recurrence to 30 non-recurrence patients with CRC. Least absolute shrinkage and selection operator method was performed to select the differential methylation regions (DMRs) and built a DNA methylation classifier for predicting recurrence. Based on the identified top DMRs, a methylation classifier was built and consisted of eight hypermethylated DMRs in CRC. The DNA methylation classifier showed high accuracy for predicting recurrence with an area under the receiver operator characteristic curve of 0.825 (95% CI 0.680-0.970). The Kaplan-Meier survival analysis demonstrated that CRC patients with high methylation risk score, evaluated by the DNA methylation classifier, had poorer survival than low risk score (Hazard Ratio 4.349; 95% CI 1.783-10.61, P = 0.002). And only CRC patients with low methylation risk score could acquire benefit from adjuvant therapy. The DNA methylation classifier has been proved as crucial biomarkers for predicting recurrence and exhibited promising prognostic value after curative surgery in patients with CRC.
Assuntos
Biomarcadores Tumorais , Neoplasias Colorretais , Metilação de DNA , Recidiva Local de Neoplasia , Humanos , Neoplasias Colorretais/genética , Neoplasias Colorretais/patologia , Neoplasias Colorretais/mortalidade , Biomarcadores Tumorais/genética , Masculino , Feminino , Prognóstico , Pessoa de Meia-Idade , Recidiva Local de Neoplasia/genética , Idoso , Estimativa de Kaplan-Meier , Regulação Neoplásica da Expressão GênicaRESUMO
BACKGROUND: Thyroid nodule (TN) patients in China are subject to overdiagnosis and overtreatment. The implementation of existing technologies such as thyroid ultrasonography has indeed contributed to the improved diagnostic accuracy of TNs. However, a significant issue persists, where many patients undergo unnecessary biopsies, and patients with malignant thyroid nodules (MTNs) are advised to undergo surgery therapy. METHODS: This study included a total of 293 patients diagnosed with TNs. Differential methylation haplotype blocks (MHBs) in blood leukocytes between MTNs and benign thyroid nodules (BTNs) were detected using reduced representation bisulfite sequencing (RRBS). Subsequently, an artificial intelligence blood leukocyte DNA methylation (BLDM) model was designed to optimize the management and treatment of patients with TNs for more effective outcomes. RESULTS: The DNA methylation profiles of peripheral blood leukocytes exhibited distinctions between MTNs and BTNs. The BLDM model we developed for diagnosing TNs achieved an area under the curve (AUC) of 0.858 in the validation cohort and 0.863 in the independent test cohort. Its specificity reached 90.91% and 88.68% in the validation and independent test cohorts, respectively, outperforming the specificity of ultrasonography (43.64% in the validation cohort and 47.17% in the independent test cohort), albeit with a slightly lower sensitivity (83.33% in the validation cohort and 82.86% in the independent test cohort) compared to ultrasonography (97.62% in the validation cohort and 100.00% in the independent test cohort). The BLDM model could correctly identify 89.83% patients whose nodules were suspected malignant by ultrasonography but finally histological benign. In micronodules, the model displayed higher specificity (93.33% in the validation cohort and 92.00% in the independent test cohort) and accuracy (88.24% in the validation cohort and 87.50% in the independent test cohort) for diagnosing TNs. This performance surpassed the specificity and accuracy observed with ultrasonography. A TN diagnostic and treatment framework that prioritizes patients is provided, with fine-needle aspiration (FNA) biopsy performed only on patients with indications of MTNs in both BLDM and ultrasonography results, thus avoiding unnecessary biopsies. CONCLUSIONS: This is the first study to demonstrate the potential of non-invasive blood leukocytes in diagnosing TNs, thereby making TN diagnosis and treatment more efficient in China.
Assuntos
Neoplasias da Glândula Tireoide , Nódulo da Glândula Tireoide , Humanos , Nódulo da Glândula Tireoide/diagnóstico por imagem , Nódulo da Glândula Tireoide/genética , Estudos Prospectivos , Inteligência Artificial , Ultrassonografia , Neoplasias da Glândula Tireoide/diagnóstico , Neoplasias da Glândula Tireoide/patologia , Neoplasias da Glândula Tireoide/cirurgia , Estudos RetrospectivosRESUMO
CONTEXT: Accurately distinguishing between benign thyroid nodules (BTNs) and papillary thyroid cancers (PTCs) with current conventional methods poses a significant challenge. OBJECTIVE: We identify DNA methylation markers of immune response-related genes for distinguishing BTNs and PTCs. METHODS: In this study, we analyzed a public reduced representative bisulfite sequencing dataset and revealed distinct methylation patterns associated with immune signals in PTCs and BTNs. Based on these findings, we developed a diagnostic classifier named the Methylation-based Immune Response Signature (MeIS), which was composed of 15 DNA methylation markers associated with immune response-related genes. We validated MeIS's performance in 2 independent cohorts: Z.S.'s retrospective cohort (50 PTC and 18 BTN surgery-leftover samples) and Z.S.'s preoperative cohort (31 PTC and 30 BTN fine-needle aspiration samples). RESULTS: The MeIS classifier demonstrated significant clinical promise, achieving areas under the curve of 0.96, 0.98, 0.89, and 0.90 in the training set, validation set, Z.S.'s retrospective cohort, and Z.S.'s preoperative cohort, respectively. For the cytologically indeterminate thyroid nodules, in Z.S.'s retrospective cohort, MeIS exhibited a sensitivity of 91% and a specificity of 82%; in Z.S.'s preoperative cohort, MeIS achieved a sensitivity of 84% and a specificity of 74%. Additionally, combining MeIS and BRAF V600E detection improved the detecting performance of cytologically indeterminate thyroid nodules, yielding sensitivities of 98% and 87%, and specificities of 82% and 74% in Z.S.'s retrospective cohort and Z.S.'s preoperative cohort, respectively. CONCLUSION: The 15 markers we identified can be employed to improve the diagnostic of cytologically indeterminate thyroid nodules.
Assuntos
Metilação de DNA , Câncer Papilífero da Tireoide , Neoplasias da Glândula Tireoide , Nódulo da Glândula Tireoide , Humanos , Nódulo da Glândula Tireoide/genética , Nódulo da Glândula Tireoide/patologia , Nódulo da Glândula Tireoide/diagnóstico , Masculino , Feminino , Estudos Retrospectivos , Pessoa de Meia-Idade , Adulto , Neoplasias da Glândula Tireoide/genética , Neoplasias da Glândula Tireoide/diagnóstico , Neoplasias da Glândula Tireoide/patologia , Neoplasias da Glândula Tireoide/imunologia , Diagnóstico Diferencial , Câncer Papilífero da Tireoide/genética , Câncer Papilífero da Tireoide/diagnóstico , Câncer Papilífero da Tireoide/patologia , Câncer Papilífero da Tireoide/imunologia , Biomarcadores Tumorais/genética , Biópsia por Agulha Fina , IdosoRESUMO
Papillary thyroid carcinoma (PTC) is the most prevalent form of thyroid cancer. Methylation of some genes plays a crucial role in the tendency to malignancy as well as poor prognosis of thyroid cancer, suggesting that methylation features can serve as complementary markers for molecular diagnosis. In this study, we aimed to develop and validate a diagnostic model for PTC based on DNA methylation markers. A total of 142 thyroid nodule tissue samples containing 84 cases of PTC and 58 cases of thyroid adenoma (TA) were collected for reduced representation bisulfite sequencing (RRBS) and subsequent analysis. The diagnostic model was constructed by the logistic regression (LR) method followed by 5-cross validation and based on 94 tissue methylation haplotype block (MHB) markers. The model achieved an area under the receiver operating characteristic curve (AUROC) of 0.974 (95% CI, 0.964-0.981) on 108 training samples and 0.917 (95% CI, 0.864-0.973) on 27 independent testing samples. The diagnostic model scores showed significantly high in males (P = 0.0016), age ≤ 45 years (P = 0.026), high body mass index (BMI) (P = 0.040), lymph node metastasis (P = 0.00052) and larger nodules (P = 0.0017) in the PTC group, and the risk score of this diagnostic model showed significantly high in recurrent PTC group (P = 0.0005). These results suggest that the diagnostic model can be expected to be a powerful tool for PTC diagnosis and there are more potential clinical applications of methylation markers to be excavated.
Assuntos
Carcinoma Papilar , Neoplasias da Glândula Tireoide , Masculino , Humanos , Pessoa de Meia-Idade , Câncer Papilífero da Tireoide/diagnóstico , Câncer Papilífero da Tireoide/genética , Metilação de DNA/genética , Haplótipos , Carcinoma Papilar/diagnóstico , Carcinoma Papilar/genética , Carcinoma Papilar/patologia , Recidiva Local de Neoplasia/genética , Neoplasias da Glândula Tireoide/diagnóstico , Neoplasias da Glândula Tireoide/genética , Neoplasias da Glândula Tireoide/patologiaRESUMO
Although genetic diversity has a cardinal role in domestication, abundant natural allelic variations across the rice genome that cause agronomically important differences between diverse varieties have not been fully explored. Here we implement an approach integrating genome-wide association testing with functional analysis on grain size in a diverse rice population. We report that a major quantitative trait locus, GLW7, encoding the plant-specific transcription factor OsSPL13, positively regulates cell size in the grain hull, resulting in enhanced rice grain length and yield. We determine that a tandem-repeat sequence in the 5' UTR of OsSPL13 alters its expression by affecting transcription and translation and that high expression of OsSPL13 is associated with large grains in tropical japonica rice. Further analysis indicates that the large-grain allele of GLW7 in tropical japonica rice was introgressed from indica varieties under artificial selection. Our study demonstrates that new genes can be effectively identified on the basis of genome-wide association data.