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Background Breast cancer is one of the most common cancers worldwide with the highest incidence among females in 2020 [1]. The application of breast ultrasound benefits the diagnosis of breast cancer at the early stage, but also leads to over-diagnosis. Patients with breast nodules detected by ultrasound at BI-RADS 4a or higher are usually advised to have a fine needle biopsy or surgery, although the PPVs of BI-RADS 4a and 4b categories are low (6% and 25%, respectively) [2]. Methods In this study, AnchorIRIS™ assay was used for analyzing the methylated status of cfDNA. Target enrichment was performed using an AnchorDx breast cancer-specific methylation panel consisting of 129,794 methylated markers. One hundred and twelve pairs of breast tissue and plasma samples (Malignant: Benign= 56: 56) and 40 leukocyte samples (Malignant: Benign = 20: 20) were used to identify reliable breast cancer-specific methylation markers with low noise background. Finally, a methylation model trained on 307 plasma samples (train set: test set = 214: 93) was selected for differentiating benign from malignant nodules, which was validated by two independent sets (Validation-1: Malignant: Benign = 42:46; Validation-2: Malignant: Benign = 62: 46).Results This methylation model exhibited a powerful performance on differentiating benign from malignant nodules with an AUC of 0.837 (95% CI: 0.757-0.918) in the test set, and maintained a stable predictive power with AUCs of 0.820 and 0.801 in two independent validation sets, respectively. In addition, this methylation model can reflect the difference in methylation signals between metastatic and non-metastatic cancers three years in advance. In contrast to ultrasound, the prediction rate of breast cancer is more accurate across the different age groups using the methylation model, especially for younger women less than 40 years old. Under the ultrasound BI-RADS 4 category, the accuracy (ACC) of the methylation model (IndVal-1, 73.02%; IndVal-2, 78.31%) is on average 22% higher than ultrasound (IndVal-1, 55.56%; IndVal-2, 51.81%). In both of the independent validation sets, the overall accuracy (78.7%) and specificity (SP) (58.7%) at the sensitivities above 95% of the combined model is greater than applying either ultrasound (ACC: 65%; SP: 26.1%) or the methylation model (ACC: 70.6%; SP: 52.2%) alone. Conclusion This methylation model has great potential for the diagnosis of early-stage breast cancer. It improves the diagnostic accuracy of the indeterminate breast nodules, which may assist in decreasing the unnecessary biopsies or surgeries of patients with benign lesions. The methylation model also has the potential in predicting metastatic and non-metastatic breast cancers that is valuable for patient surveillance and risk prediction. References: [1]. Siegel RL, Miller KD, Jemal A: Cancer statistics, 2020. CA Cancer J Clin 70:7-30, 2020 [2]. Spinelli Varella MA, Teixeira da Cruz J, Rauber A, et al: Role of BI-RADS Ultrasound Subcategories 4A to 4C in Predicting Breast Cancer. Clin Breast Cancer 18:e507-e511, 2018 Citation Format: Xianyu Zhang, Zhujia Ye, Yanling Yin, Liuhong Zeng, Jun Wang, Shan Lei, Marina Bibikova, Zhiwei Chen, Jian-Bing Fan, Da Pang. Improving the Performance of Early Breast Cancer Diagnosis by a Model Combining Breast Ultrasound with Methylation Markers in Non-Invasive Circulating Tumor DNA [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P1-05-11.

Background Recurrence represents a well-known poor prognostic factor for colorectal cancer (CRC) patients. This study aimed to establish an effective prognostic prediction model based on noninvasive circulating tumor DNA methylation markers for CRC patients receiving radical surgery. Results Two methylation markers (cg11186405 and cg17296166) were identified by Cox regression and receiver operating characteristics, which could classify CRC patients into high recurrence risk and low recurrence risk group. The 3-year disease-free survival was significantly different between CRC patients with low and high recurrence risk [Training set: hazard ratio (HR) 28.776, 95% confidence interval (CI) 3.594–230.400; P = 0.002; Validation set: HR 7.796, 95% CI 1.425–42.660, P = 0.018]. The nomogram based on the above two methylation markers and TNM stage was established which demonstrated robust prognostic prediction potential, as evidenced by the decision curve analysis result. Conclusions A cell-free DNA methylation model consisting of two DNA methylation markers is a promising method for prognostic prediction in CRC patients.

BackgroundLung cancer is the leading cause of cancer-related mortality. The alteration of DNA methylation plays a major role in the development of lung cancer. Methylation biomarkers become a possible method for lung cancer diagnosis.ResultsWe identified eleven lung cancer-specific methylation markers (CDO1, GSHR, HOXA11, HOXB4-1, HOXB4-2, HOXB4-3, HOXB4-4, LHX9, MIR196A1,PTGER4-1,andPTGER4-2), which could differentiate benign and malignant pulmonary nodules. The methylation levels of these markers are significantly higher in malignant tissues. In bronchoalveolar lavage fluid (BALF) samples, the methylation signals maintain the same differential trend as in tissues. An optimal 5-marker model for pulmonary nodule diagnosis (malignant vs. benign) was developed from all possible combinations of the eleven markers. In the test set (57 tissue and 71 BALF samples), the area under curve (AUC) value achieves 0.93, and the overall sensitivity is 82% at the specificity of 91%. In an independent validation set (111 BALF samples), the AUC is 0.82 with a specificity of 82% and a sensitivity of 70%.ConclusionsThis model can differentiate pulmonary adenocarcinoma and squamous carcinoma from benign diseases, especially for infection, inflammation, and tuberculosis. The model’s performance is not affected by gender, age, smoking history, or the solid components of nodules.

Switchgrass plants were grown in a Sandwich tube system to induce gradual drought stress by withholding watering. After 29 days, the leaf photosynthetic rate decreased significantly, compared to the control plants which were watered regularly. The drought-treated plants recovered to the same leaf water content after three days of re-watering. The root tip (1cm basal fragment, designated as RT1 hereafter) and the elongation/maturation zone (the next upper 1 cm tissue, designated as RT2 hereafter) tissues were collected at the 29th day of drought stress treatment, (named SDT for severe drought treated), after one (D1W) and three days (D3W) of re-watering. The tandem mass tags mass spectrometry-based quantitative proteomics analysis was performed to identify the proteomes, and drought-induced differentially accumulated proteins (DAPs). From RT1 tissues, 6156, 7687, and 7699 proteins were quantified, and 296, 535, and 384 DAPs were identified in the SDT, D1W, and D3W samples, respectively. From RT2 tissues, 7382, 7255, and 6883 proteins were quantified, and 393, 587, and 321 proteins DAPs were identified in the SDT, D1W, and D3W samples. Between RT1 and RT2 tissues, very few DAPs overlapped at SDT, but the number of such proteins increased during the recovery phase. A large number of hydrophilic proteins and stress-responsive proteins were induced during SDT and remained at a higher level during the recovery stages. A large number of DAPs in RT1 tissues maintained the same expression pattern throughout drought treatment and the recovery phases. The DAPs in RT1 tissues were classified in cell proliferation, mitotic cell division, and chromatin modification, and those in RT2 were placed in cell wall remodeling and cell expansion processes. This study provided information pertaining to root zone-specific proteome changes during drought and recover phases, which will allow us to select proteins (genes) as better defined targets for developing drought tolerant plants. The mass spectrometry proteomics data are available via ProteomeXchange with identifier PXD017441.

Switchgrass (Panicum virgatum L.) is a perennial fodder grass and well known as a model renewable bioenergy crop. The plant's high production of biomass for biofuel supply is due to its fast-growing and wide adaptation properties. Very little studies and data are available about microRNAs (miRNAs) in this important biofuel crop. This situation demands to focus and identify new miRNAs and also to study their expressional analysis. In current research, a combination of computational and expressional approaches is applied to profile and characterize miRNAs in switchgrass and analyze some of them under drought stress. A total of 158 new miRNAs belonging to 83 families are identified and characterized from switchgrass expressed sequence tags (ESTs) and genomic survey sequences (GSS). In addition, five pre-miRNA clusters as well as four sense and antisense pre-miRNAs are also predicted from these newly identified miRNAs. Furthermore, 39 miRNAs were randomly selected and subjected to quantitative real-time RT-PCR expressional studies in root, leaf and stem of switchgrass under drought stress. A set of 13, 20 and 25 miRNAs are found as drought responding miRNAs in root, stem and leaf respectively. A total of 894 putative targets are also predicted for 158 switchgrass' miRNAs. These targets play roles in metabolism, transcription factor, signaling pathways, growth & development, stress-related, transport protein and other vital processes. Such findings in switchgrass improved the baseline data of miRNAs and their targets. This data can be utilized to fine-tune this important bioenergy crop under biotic and abiotic stresses. Furthermore, it can also be used for the improvement of biofuel properties of the plant.

Introduction: Early detection is critical to improving cancer patient survival and quality of life. Cell-free DNA (cfDNA) methylation profiling is a promising diagnostic approach for early detection of cancer, even before symptoms appear. We previously reported a non-invasive and cost-effective methylation test, Aurora, which is able to detect three major cancer types with high specificity and sensitivity especially at early stages (I/II), including lung cancer (LC), breast cancer (BC), colorectal cancer (CRC). We have improved this test to include two additional major cancer types, gastric cancer (GC) and esophageal cancer (EC). Taking together, these five cancer types represent 56% of new cancer cases and 60% of cancer-related deaths in China. Methods: We developed a novel high-throughput targeted methylation profiling platform, Aurora 2.0 (an improved version of Aurora 1.0, as presented in AACR 2020), to efficiently enrich and capture cancer-specific DNA methylation markers in plasma, prior to analysis via next-generation sequencing on a MiSeqDx system. About 100 cases each for GC and EC patients (mostly at Stage I/II), together with ~200 healthy controls, have been analyzed by using Aurora 2.0 and used for model development and validation. Results and Discussion: cfDNA methylation profiles have been obtained from 409 plasma samples, comprising 206 healthy controls, 98 GC and 105 EC patients. Logistic regression model has been developed with the Area Under Curve (AUC) of 94.0% and 93.5% for GC and EC, respectively. Overall, the performance (AUC) of Aurora 2.0 for LC/BC/CRC/GC/EC are 97.3%, 96.2%, 92%, 94% and 93.5%, respectively. An independent cohort (~2,000 plasma samples, five cancer types including lung, breast, colorectal, gastric and esophageal cancers with healthy controls) study is undergoing to further validate this test prospectively. The superior performance and cost-effectiveness (~$100) of the test could make early cancer screening of multiple major cancers in symptom-free and average-risk populations more achievable. Citation Format: Linhao Xu, Jun Wang, Weifeng Ma, Xin Liu, Ting Yang, Sihui Li, Qian Hu, Jinsheng Tao, Zhujia Ye, Zhiwei Chen, Jian-Bing Fan. A high performance blood test for multiple cancer early screening [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2610.

10561 Background: Early detection at the localized stage is pivotal for the successful treatment of various cancer types. Although several cancers already have routine screening approaches, the comprehensive utilities are impeded for various reasons, e.g., low accuracy, high cost, limited availability of required facilities, especially in the developing countries. Therefore, an accurate, cost-effective, and non-invasive test for multiple major cancer screening is in high demand. We previously reported a cfDNA methylation test, which can detect five major cancer types with high specificity and sensitivity, especially at the early stage (stage I). These five major cancers, including lung cancer (LC), breast cancer (BC), colorectal cancer (CRC), gastric cancer (GC), and esophageal cancer (EC), account for 56% of new cancer cases and 60% of cancer-related deaths yearly in China. Here, we report the result in an independent cohort as a further validation of this multi-cancer screening test. Methods: The high-throughput targeted methylation profiling platform, Aurora, was used to analyze the plasma samples from an independent retrospective cohort containing 505 healthy controls and ̃200 cases for each cancer type. A locked model based on our previous pilot study (reported in AACR 2020 and 2021) was applied to this data set to assess the overall performance. Results: The Area Under Curves (AUC) of the classifier for LC, BC, CRC, GC and EC are 97.3%, 96.2%, 92.0%, 94.0% and 93.5%, respectively. At a fixed specificity of 99%, the sensitivities for LC, BC, CRC, GC and EC are 84%, 75%, 82%, 85% and 78%, respectively. Conclusions: A methylation blood test for five major cancer screening has been validated in a large retrospective cohort. Its high sensitivity for each cancer type, especially at the early stage (stage I), and easy to use suggests it can be implemented in real clinical world. A large prospective clinical trial is undergoing to further validate this test in asymptomatic populations.

Summary Drought is one of the major abiotic stresses that directly implicate plant growth and crop productivity. Although many genes in response to drought stress have been identified, genetic improvement to drought resistance especially in food crops is showing relatively slow progress worldwide. Here, we reported the isolation of abscisic acid, stress and ripening (ASR) genes from upland rice variety, IRAT109 (Oryza sativa L. ssp. japonica), and demonstrated that overexpression of OsASR5 enhanced osmotic tolerance in Escherichia coli and drought tolerance in Arabidopsis and rice by regulating leaf water status under drought stress conditions. Moreover, overexpression of OsASR5 in rice increased endogenous ABA level and showed hypersensitive to exogenous ABA treatment at both germination and postgermination stages. The production of H2O2, a second messenger for the induction of stomatal closure in response to ABA, was activated in overexpression plants under drought stress conditions, consequently, increased stomatal closure and decreased stomatal conductance. In contrast, the loss‐of‐function mutant, osasr5, showed sensitivity to drought stress with lower relative water content under drought stress conditions. Further studies demonstrated that OsASR5 functioned as chaperone‐like protein and interacted with stress‐related HSP40 and 2OG‐Fe (II) oxygenase domain containing proteins in yeast and plants. Taken together, we suggest that OsASR5 plays multiple roles in response to drought stress by regulating ABA biosynthesis, promoting stomatal closure, as well as acting as chaperone‐like protein that possibly prevents drought stress‐related proteins from inactivation.

Introduction: Early cancer detection remains a critical challenge to improve patients' survival rate and clinical outcomes. Alterations in DNA methylation play a key role in tumor initiation, development, progression and metastasis. Cell-free DNA (cfDNA) methylation analysis on liquid biopsies (e.g., blood and urine) holds a great promise for early detection of cancers even without symptoms. In this context, we are developing a non-invasive, cost-effective test that can detect several major cancer types, including lung (LnC), breast (BrC), colorectal (CRC), gastric (GC), esophageal (EC) and liver (LvC) cancers with high specificity (Sp) and sensitivity (Sn). These six cancer types represent two third of the newly diagnosed cancer patients and 72% of cancer deaths every year in China. Methods: In order to identify highly effective DNA methylation markers for early detection, we have conducted genome-wide methylation profiling on more than 2,000 benign and malignant tissue samples, including large number of early stage (Stage I/II) tumors and pre-cancerous lesions from lung, breast, colorectum, liver, stomach and esophagus. We then developed a high performance assay, Aurora, to capture cancer-specific DNA methylation signatures in plasma. Specifically, cfDNA was extracted from each of the plasma samples, bisulfite-converted, and analyzed by NGS on Illumina MiSeq system. Results and Discussion: To date, methylation profiles of plasma samples derived from, 1) 58 normal and 106 malignant pulmonary nodule patients, 2) 31 normal and 85 malignant CRC patients, and 3) 81 normal and 78 malignant breast nodule patients, were analyzed. Overall performances (Area Under Curve, AUC) of the Aurora test are 90%, 98% and 92% for LnC, BrC and CRC, respectively. Further clinical validation and evaluation are being conducted in larger independent cohorts of these three types of cancers as well as additional cohorts for the other cancers (GC, EC and LvC). The superior performance and low cost (~$100) make the Aurora test very promising for simultaneous screening of multiple major cancers in symptom-free, average risk populations. Citation Format: Linhao Xu, Jun Wang, Ting Yang, Jinsheng Tao, Xin Liu, Zhujia Ye, Dezhi Zhao, Zeyu Jiang, Zhiwei Chen, Jian-Bing Fan. Toward the development of a $100 screening test for 6 major cancer types [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4601.

In this paper, we report on aluminum (Al)-induced root proteomic changes in switchgrass. After growth in a hydroponic culture system supplemented with 400 μM of Al, plants began to show signs of physiological stress such as a reduction in photosynthetic rate. At this time, the basal 2-cm long root tips were harvested and divided into two segments, each of 1-cm in length, for protein extraction. Al-induced changes in proteomes were identified using tandem mass tags mass spectrometry (TMT-MS)-based quantitative proteomics analysis. A total of 216 proteins (approximately 3.6% of total proteins) showed significant differences between non-Al treated control and treated groups with significant fold change (twice the standard deviation; FDR adjusted p-value < 0.05). The apical root tip tissues expressed more dramatic proteome changes (164 significantly changed proteins; 3.9% of total proteins quantified) compared to the elongation/maturation zones (52 significantly changed proteins, 1.1% of total proteins quantified). Significantly changed proteins from the apical 1-cm root apex tissues were clustered into 25 biological pathways; proteins involved in the cell cycle (rotamase FKBP 1 isoforms, and CDC48 protein) were all at a reduced abundance level compared to the non-treated control group. In the root elongation/maturation zone tissues, the identified proteins were placed into 18 pathways, among which proteins involved in secondary metabolism (lignin biosynthesis) were identified. Several STRING protein interaction networks were developed for these Al-induced significantly changed proteins. This study has identified a large number of Al-responsive proteins, including transcription factors, which will be used for exploring new Al tolerance genes and mechanisms. Data are available via ProteomeXchange with identifiers PXD008882 and PXD009125.

The tomato (Solanum lycopersicum) ripening process from mature green (MG) to turning and then to red stages is accompanied by the occurrences of physiological and biochemical reactions, which ultimately result in the formation of the flavor, color and texture of ripe fruits. The two trivalent metal ions Al3+ and La3+ are known to induce different levels of phytotoxicity in suppressing root growth. This paper aims to understand the impacts of these two metal ions on tomato fruit proteomes. Tomato ‘Micro-Tom’ plants were grown in a hydroponic culture system supplemented with 50 μM aluminum sulfate (Al2 (SO4)3.18H2O) for Al3+ or La2(SO4)3 for La3+. Quantitative proteomics analysis, using isobaric tags for relative and absolute quantitation, were performed for fruits at MG, turning and red stages. Results show that in MG tomatoes, proteins involved in protein biosynthesis, photosynthesis and primary carbohydrate metabolisms were at a significantly lower level in Al-treated compared to La-treated plants. For the turning and red tomatoes, only a few proteins of significant differences between the two metal treatments were identified. Results from this study indicate that compared to La3+, Al3+ had a greater influence on the basic biological activities in green tomatoes, but such an impact became indistinguishable as tomatoes matured into the late ripening stages.

This study aimed to identify the aluminum (Al)-induced proteomes in tomato (Solanum lycopersicum, "Micro-Tom") after long-term exposure to the stress factor. Plants were treated in Magnavaca's solution (pH 4.5) supplemented with 7.5 μM Al(3+) ion activity over a 4 month period beginning at the emergence of flower buds and ending when the lower mature leaves started to turn yellow. Proteomes were identified using a 8-plex isobaric tags for relative and absolute quantification (iTRAQ) labeling strategy followed by a two-dimensional (high- and low-pH) chromatographic separation and final generation of tandem mass spectrometry (MS/MS) spectra of tryptic peptides on an LTQ-Orbitrap Elite mass spectrometer. Principal component analysis revealed that the Al-treatment had induced systemic alterations in the proteomes from roots and leaves but not seed tissues. The significantly changed root proteins were shown to have putative functions in Al(3+) ion uptake and transportation, root development, and a multitude of other cellular processes. Changes in the leaf proteome indicate that the light reaction centers of photosynthetic machinery are the primary targets of Al-induced stress. Embryo and seed-coat tissues derived from Al-treated plants were enriched with stress proteins. The biological processes involving these Al-induced proteins concur with the physiological and morphological changes, such as the disturbance of mineral homeostasis (higher contents of Al, P, and Fe and reduced contents of S, Zn, and Mn in Al-treated compared to nontreated plants) in roots and smaller sizes of roots and the whole plants. More importantly, the identified significant proteins might represent a molecular mechanism for plants to develop toward establishing the Al tolerance and adaptation mechanism over a long period of stress treatment.

Aluminum (Al) toxicity is a major constraint to plant growth and crop yield in acid soils. Tomato cultivars are especially susceptible to excessive Al3+ accumulated in the root zone. In this study, tomato plants were grown in a hydroponic culture system supplemented with 50 µM AlK(SO₄)₂. Seeds harvested from Al-treated plants contained a significantly higher Al content than those grown in the control hydroponic solution. In this study, these Al-enriched tomato seeds (harvested from Al-treated tomato plants) were germinated in 50 µM AlK(SO₄)₂ solution in a homopiperazine-1,4-bis(2-ethanesulfonic acid) buffer (pH 4.0), and the control solution which contained the buffer only. Proteomes of radicles were analyzed quantitatively by mass spectrometry employing isobaric tags for relative and absolute quantitation (iTRAQ®). The proteins identified were assigned to molecular functional groups and cellular metabolic pathways using MapMan. Among the proteins whose abundance levels changed significantly were: a number of transcription factors; proteins regulating gene silencing and programmed cell death; proteins in primary and secondary signaling pathways, including phytohormone signaling and proteins for enhancing tolerance to abiotic and biotic stress. Among the metabolic pathways, enzymes in glycolysis and fermentation and sucrolytic pathways were repressed. Secondary metabolic pathways including the mevalonate pathway and lignin biosynthesis were induced. Biological reactions in mitochondria seem to be induced due to an increase in the abundance level of mitochondrial ribosomes and enzymes in the TCA cycle, electron transport chains and ATP synthesis.

Switchgrass (Panicum virgatum) is a perennial crop producing deep roots and thus highly tolerant to soil water deficit conditions. However, seedling establishment in the field is very susceptible to prolonged and periodic drought stress. In this study, a “sandwich” system simulating a gradual water deletion process was developed. Switchgrass seedlings were subjected to a 20-day gradual drought treatment process when soil water tension was increased to 0.05 MPa (moderate drought stress) and leaf physiological properties had expressed significant alteration. Drought-induced changes in leaf proteomes were identified using the isobaric tags for relative and absolute quantitation (iTRAQ) labeling method followed by nano-scale liquid chromatography mass spectrometry (nano-LC-MS/MS) analysis. Additionally, total leaf proteins were processed using a combinatorial library of peptide ligands to enrich for lower abundance proteins. Both total proteins and those enriched samples were analyzed to increase the coverage of the quantitative proteomics analysis. A total of 7006 leaf proteins were identified, and 257 (4% of the leaf proteome) expressed a significant difference (p < 0.05, fold change 1.7) from the non-treated control to drought-treated conditions. These proteins are involved in the regulation of transcription and translation, cell division, cell wall modification, phyto-hormone metabolism and signaling transduction pathways, and metabolic pathways of carbohydrates, amino acids, and fatty acids. A scheme of abscisic acid (ABA)-biosynthesis and ABA responsive signal transduction pathway was reconstructed using these drought-induced significant proteins, showing systemic regulation at protein level to deploy the respective mechanism. Results from this study, in addition to revealing molecular responses to drought stress, provide a large number of proteins (candidate genes) that can be employed to improve switchgrass seedling growth and establishment under soil drought conditions (Data are available via ProteomeXchange with identifier PXD004675).