TOTEM: a multi-cancer detection and localization approach using circulating tumor DNA methylation markers.

BACKGROUND: Detection of cancer and identification of tumor origin at an early stage improve the survival and prognosis of patients. Herein, we proposed a plasma cfDNA-based approach called TOTEM to detect and trace the cancer signal origin (CSO) through methylation markers. METHODS: We performed enzymatic conversion-based targeted methylation sequencing on plasma cfDNA samples collected from a clinical cohort of 500 healthy controls and 733 cancer patients with seven types of cancer (breast, colorectum, esophagus, stomach, liver, lung, and pancreas) and randomly divided these samples into a training cohort and a testing cohort. An independent validation cohort of 143 healthy controls, 79 liver cancer patients and 100 stomach cancer patients were recruited to validate the generalizability of our approach. RESULTS: A total of 57 multi-cancer diagnostic markers and 873 CSO markers were selected for model development. The binary diagnostic model achieved an area under the curve (AUC) of 0.907, 0.908 and 0.868 in the training, testing and independent validation cohorts, respectively. With a training specificity of 98%, the specificities in the testing and independent validation cohorts were 100% and 98.6%, respectively. Overall sensitivity across all cancer stages was 65.5%, 67.3% and 55.9% in the training, testing and independent validation cohorts, respectively. Early-stage (I and II) sensitivity was 50.3% and 45.7% in the training and testing cohorts, respectively. For cancer patients correctly identified by the binary classifier, the top 1 and top 2 CSO accuracies were 77.7% and 86.5% in the testing cohort (n = 148) and 76.0% and 84.0% in the independent validation cohort (n = 100). Notably, performance was maintained with only 21 diagnostic and 214 CSO markers, achieving a training AUC of 0.865, a testing AUC of 0.866, and an integrated top 2 accuracy of 83.1% in the testing cohort. CONCLUSIONS: TOTEM demonstrates promising potential for accurate multi-cancer detection and localization by profiling plasma methylation markers. The real-world clinical performance of our approach needs to be investigated in a much larger prospective cohort.

dlf1 promotes floral transition by directly activating ZmMADS4 and ZmMADS67 in the maize shoot apex.

The floral transition of the maize (Zea mays ssp. mays) shoot apical meristem determines leaf number and flowering time, which are key traits influencing local adaptation and yield potential. dlf1 (delayed flowering1) encodes a basic leucine zipper protein that interacts with the florigen ZCN8 to mediate floral induction in the shoot apex. However, the mechanism of how dlf1 promotes floral transition remains largely unknown. We demonstrate that dlf1 underlies qLB7-1, a quantitative trait locus controlling leaf number and flowering time that was identified in a BC2 S3 population derived from a cross between maize and its wild ancestor, teosinte (Zea mays ssp. parviglumis). Transcriptome sequencing and chromatin immunoprecipitation sequencing demonstrated that DLF1 binds the core promoter of two AP1/FUL subfamily MADS-box genes, ZmMADS4 and ZmMADS67, to activate their expression. Knocking out ZmMADS4 and ZmMADS67 both increased leaf number and delayed flowering, indicating that they promote the floral transition. Nucleotide diversity analysis revealed that dlf1 and ZmMADS67 were targeted by selection, suggesting that they may have played important roles in maize flowering time adaptation. We show that dlf1 promotes maize floral transition by directly activating ZmMADS4 and ZmMADS67 in the shoot apex, providing novel insights into the mechanism of maize floral transition.

Maize male sterile 33 encodes a putative glycerol-3-phosphate acyltransferase that mediates anther cuticle formation and microspore development.

BACKGROUND: The anther cuticle, which is primarily composed of lipid polymers, is crucial for pollen development and plays important roles in sexual reproduction in higher plants. However, the mechanism underlying the biosynthesis of lipid polymers in maize (Zea mays. L.) remains unclear. RESULTS: Here, we report that the maize male-sterile mutant shrinking anther 1 (sa1), which is allelic to the classic mutant male sterile 33 (ms33), displays defective anther cuticle development and premature microspore degradation. We isolated MS33 via map-based cloning. MS33 encodes a putative glycerol-3-phosphate acyltransferase and is preferentially expressed in tapetal cells during anther development. Gas chromatography-mass spectrometry revealed a substantial reduction in wax and cutin in ms33 anthers compared to wild type. Accordingly, RNA-sequencing analysis showed that many genes involved in wax and cutin biosynthesis are differentially expressed in ms33 compared to wild type. CONCLUSIONS: Our findings suggest that MS33 may contribute to anther cuticle and microspore development by affecting lipid polyester biosynthesis in maize.

Multimodal analysis of cell-free DNA whole-methylome sequencing for cancer detection and localization.

Multimodal epigenetic characterization of cell-free DNA (cfDNA) could improve the performance of blood-based early cancer detection. However, integrative profiling of cfDNA methylome and fragmentome has been technologically challenging. Here, we adapt an enzyme-mediated methylation sequencing method for comprehensive analysis of genome-wide cfDNA methylation, fragmentation, and copy number alteration (CNA) characteristics for enhanced cancer detection. We apply this method to plasma samples of 497 healthy controls and 780 patients of seven cancer types and develop an ensemble classifier by incorporating methylation, fragmentation, and CNA features. In the test cohort, our approach achieves an area under the curve value of 0.966 for overall cancer detection. Detection sensitivity for early-stage patients achieves 73% at 99% specificity. Finally, we demonstrate the feasibility to accurately localize the origin of cancer signals with combined methylation and fragmentation profiling of tissue-specific accessible chromatin regions. Overall, this proof-of-concept study provides a technical platform to utilize multimodal cfDNA features for improved cancer detection.