Cell-free DNA methylation profiles enable early detection of colorectal and gastric cancer.

Colorectal cancer (CRC) and gastric cancer (GC) rank the top five common and lethal cancers worldwide. Early detection can significantly reduce the mortality of CRC and GC. However, current clinical screening methods including invasive endoscopic techniques and noninvasive fecal occult blood test screening tests/fecal immunochemical test have shown low sensitivity or unsatisfactory patient's compliance. Aberrant DNA methylation occurs frequently in tumorigenesis and cell-free DNA (cfDNA) methylation has shown the potential in multi-cancer detection. Herein, we aimed to explore the value of cfDNA methylation in the gastrointestinal cancer detection and develop a noninvasive method for CRC and GC detection. We applied targeted methylation sequencing on a total of 407 plasma samples from patients diagnosed with CRC, GC, and noncancerous gastrointestinal benign diseases (Non-Ca). By analyzing the methylation profiles of 34 CRC, 62 GC and 107 Non-Ca plasma samples in the training set (n=203), we identified 40,110 gastrointestinal cancer-specific markers and 63 tissue of origin (TOO) prediction markers. A new integrated model composed of gastrointestinal cancer detection and TOO prediction for three types of classification of CRC, GC and Non-Ca patients was further developed through logistic regression algorithm and validated in an independent validation set (n=103). The model achieved overall sensitivities of 83% and 81.3% at specificities of 81.5% and 80% for identifying gastrointestinal cancers in the test set and validation set, respectively. The detection sensitivities for GC and CRC were respectively 81.4% and 83.3% in the cohort of the test and validation sets. Among these true positive cancer samples, further TOO prediction showed accuracies of 95.8% and 95.8% for GC patients and accuracies of 86.7% and 93.3% for CRC patients, in test set and validation set, respectively. Collectively, we have identified novel cfDNA methylation biomarkers for CRC and GC detection and shown the promising potential of cfDNA as a noninvasive gastrointestinal cancer detection tool.

Predicting disease-free survival in colorectal cancer by circulating tumor DNA methylation markers.

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.

A novel DNA methylation signature associated with lymph node metastasis status in early gastric cancer.

BACKGROUND: Lymph node metastasis (LNM) is an important factor for both treatment and prognosis of early gastric cancer (EGC). Current methods are insufficient to evaluate LNM in EGC due to suboptimal accuracy. Herein, we aim to identify methylation signatures for LNM of EGC, facilitate precision diagnosis, and guide treatment modalities. METHODS: For marker discovery, genome-wide methylation sequencing was performed in a cohort (marker discovery) using 47 fresh frozen (FF) tissue samples. The identified signatures were subsequently characterized for model development using formalin-fixed paraffin-embedded (FFPE) samples by qPCR assay in a second cohort (model development cohort, n = 302, training set: n = 151, test set: n = 151). The performance of the established model was further validated using FFPE samples in a third cohorts (validation cohort, n = 130) and compared with image-based diagnostics, conventional clinicopathology-based model (conventional model), and current standard workups. RESULTS: Fifty LNM-specific methylation signatures were identified de novo and technically validated. A derived 3-marker methylation model for LNM diagnosis was established that achieved an AUC of 0.87 and 0.88, corresponding to the specificity of 80.9% and 85.7%, sensitivity of 80.6% and 78.1%, and accuracy of 80.8% and 83.8% in the test set of model development cohort and validation cohort, respectively. Notably, this methylation model outperformed computed tomography (CT)-based imaging with a superior AUC (0.88 vs. 0.57, p < 0.0001) and individual clinicopathological features in the validation cohort. The model integrated with clinicopathological features demonstrated further enhanced AUCs of 0.89 in the same cohort. The 3-marker methylation model and integrated model reduced 39.4% and 41.5% overtreatment as compared to standard workups, respectively. CONCLUSIONS: A novel 3-marker methylation model was established and validated that shows diagnostic potential to identify LNM in EGC patients and thus reduce unnecessary gastrectomy in EGC.

A urine-based DNA methylation assay to facilitate early detection and risk stratification of bladder cancer.

BACKGROUND: Current non-invasive tests have limited sensitivities and lack capabilities of pre-operative risk stratification for bladder cancer (BC) diagnosis. We aimed to develop and validate a urine-based DNA methylation assay as a clinically feasible test for improving BC detection and enabling pre-operative risk stratifications. METHODS: A urine-based DNA methylation assay was developed and validated by retrospective single-center studies in patients of suspected BC in Cohort 1 (n = 192) and Cohort 2 (n = 98), respectively. In addition, a prospective single-center study in hematuria patient group (Cohort 3, n = 174) was used as a second validation of the model. RESULTS: The assay with a dual-marker detection model showed 88.1% and 91.2% sensitivities, 89.7% and 85.7% specificities in validation Cohort 2 (patients of suspected BC) and Cohort 3 (patients of hematuria), respectively. Furthermore, this assay showed improved sensitivities over cytology and FISH on detecting low-grade tumor (66.7-77.8% vs. 0.0-22.2%, 0.0-22.2%), Ta tumor (83.3% vs. 22.2-41.2%, 44.4-52.9%) and non-muscle invasive BC (NMIBC) (80.0-89.7% vs. 51.5-52.0%, 59.4-72.0%) in both cohorts. The assay also had higher accuracies (88.9-95.8%) in diagnosing cases with concurrent genitourinary disorders as compared to cytology (55.6-70.8%) and FISH (72.2-77.8%). Meanwhile, the assay with a five-marker stratification model identified high-risk NMIBC and muscle invasive BC with 90.5% sensitivity and 86.8% specificity in Cohort 2. CONCLUSIONS: The urine-based DNA methylation assay represents a highly sensitive and specific approach for BC early-stage detection and risk stratification. It has a potential to be used as a routine test to improve diagnosis and prognosis of BC in clinic.

Urine DNA methylation assay enables early detection and recurrence monitoring for bladder cancer.

BACKGROUNDCurrent methods for the detection and surveillance of bladder cancer (BCa) are often invasive and/or possess suboptimal sensitivity and specificity, especially in early-stage, minimal, and residual tumors.METHODSWe developed an efficient method, termed utMeMA, for the detection of urine tumor DNA methylation at multiple genomic regions by MassARRAY. We identified the BCa-specific methylation markers by combined analyses of cohorts from Sun Yat-sen Memorial Hospital (SYSMH), The Cancer Genome Atlas (TCGA), and the Gene Expression Omnibus (GEO) database. The BCa diagnostic model was built in a retrospective cohort (n = 313) and validated in a multicenter, prospective cohort (n = 175). The performance of this diagnostic assay was analyzed and compared with urine cytology and FISH.RESULTSWe first discovered 26 significant methylation markers of BCa in combined analyses. We built and validated a 2-marker-based diagnostic model that discriminated among patients with BCa with high accuracy (86.7%), sensitivity (90.0%), and specificity (83.1%). Furthermore, the utMeMA-based assay achieved a great improvement in sensitivity over urine cytology and FISH, especially in the detection of early-stage (stage Ta and low-grade tumor, 64.5% vs. 11.8%, 15.8%), minimal (81.0% vs. 14.8%, 37.9%), residual (93.3% vs. 27.3%, 64.3%), and recurrent (89.5% vs. 31.4%, 52.8%) tumors. The urine diagnostic score from this assay was better associated with tumor malignancy and burden.CONCLUSIONUrine tumor DNA methylation assessment for early diagnosis, minimal, residual tumor detection and surveillance in BCa is a rapid, high-throughput, noninvasive, and promising approach, which may reduce the burden of cystoscopy and blind second surgery.FUNDINGThis study was supported by the National Key Research and Development Program of China and the National Natural Science Foundation of China.

Identifying potential DNA methylation markers in early-stage colorectal Cancer.

Colorectal cancer (CRC) is the second leading malignancy worldwide. Accurate screening is pivotal to early CRC detection, yet current screening modality involves invasive colonoscopy while non-invasive FIT tests have limited sensitivity. We applied a DNA methylation assay to identify biomarkers for early-stage CRC detection, risk stratification and precancerous lesion screening at tissue level. A model of biomarkers SFMBT2, ITGA4, THBD and ZNF304 showed 96.1% sensitivity and 87.0% specificity in CRC detection, with 100.0% sensitivity for advanced precancerous lesion and stage I CRC. Performances were further validated with TCGA data set, which showed a consistent AUC of 0.99 and exhibited specificity against other cancer types. KCNJ12, VAV3-AS1 and EVC were further identified for stage stratification (stage 0-I versus stage II-IV), with AUC of 0.87, 83.0% sensitivity and 71.2% specificity. Additionally, dual markers of NEUROD1 and FAM72C showed 83.2% sensitivity and 77.4% specificity in differing non-advanced precancerous lesions from inflammatory bowel diseases.

Resistance to anti-microtubule drug-induced cell death is determined by regulation of BimEL expression.

Anti-microtubule agents are frequently used as anticancer therapeutics. Cell death induced by these agents is considered to be due to sustained mitotic arrest caused by the activation of spindle assembly checkpoint (SAC). However, some cell types are resistant to mitotic cell death. Cells' ability to escape mitotic arrest (mitotic slippage) is thought to be a major mechanism contributing to this resistance. Here, we show that resistance to cell death induced by anti-mitotic agents is not linked to cells' capacity to undergo mitotic slippage as generally believed but is dependent on the state of BimEL regulation during mitosis. While transcriptional repression of BimEL in the mitotic death-resistant cells involves polycomb repressive complex 2 (PRC2)-mediated histone trimethylation, the BimEL protein is destabilized by cullin 1/4A-ßTrCP-dependent degradation involving activation of cullin 1/4A by neddylation. These results imply that pharmacological augmentation of BimEL activity in anti-microtubule drug-resistant tumors may have important therapeutic implications.

Mapping Mitotic Death: Functional Integration of Mitochondria, Spindle Assembly Checkpoint and Apoptosis.

Targeting the mitotic pathways of rapidly proliferating tumor cells has been an effective strategy in traditional cancer therapy. Chemotherapeutics such as taxanes and vinca alkaloids, which disrupt microtubule function, have enjoyed clinical success; however, the accompanying side effects, toxicity and multi drug resistance remain as serious concerns. The emerging classes of inhibitors targeting mitotic kinases and proteasome face their own set of challenges. It is hoped that elucidation of the regulatory interface between mitotic checkpoints, mitochondria and mitotic death will aid the development of more efficacious anti-mitotic agents and improved treatment protocols. The links between the spindle assembly checkpoint (SAC) and mitochondrial dynamics that control the progression of anti-mitotic agent-induced apoptosis have been under investigation for several years and the functional integration of these various signaling networks is now beginning to emerge. In this review, we highlight current research on the regulation of SAC, the death pathway and mitochondria with particular focus on their regulatory interconnections.

Distinct Responses of Cytotoxic Ganoderma lucidum Triterpenoids in Human Carcinoma Cells.

The medicinal mushroom Ganoderma lucidum is well recognized for its effective cancer-preventative and therapeutic properties, while specific components responsible for these anticancer effects are not well studied. Six triterpenoids that are ganolucidic acid E, lucidumol A, ganodermanontriol, 7-oxo-ganoderic acid Z, 15-hydroxy-ganoderic acid S, and ganoderic acid DM were isolated and identified from an extract of the mushroom. All compounds reduced cell growth in three human carcinoma cells (Caco-2, HepG2, and HeLa cells) dose dependently with LC50s from 20.87 to 84.36 µM. Moreover, the six compounds induced apoptosis in HeLa cells with a maximum increase (22%) of sub-G1 accumulations and 43.03% apoptotic cells in terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) assay (15-hydroxy-ganoderic acid S treatment). Apoptosis was further confirmed by annexin-V staining. Four of the compounds also caused apoptosis in Caco-2 cells with maximum 9.5% increase of sub-G1 accumulations (7-oxo-ganoderic acid Z treatment) and maximum 29.84% apoptotic cells in TUNEL assay (ganoderic acid DM treatment). Contrarily, none of the compounds induced apoptosis in HepG2 cells. The different responses of the three cell lines following these treatments indicated that the bioactive properties of these compounds may vary from cells of different sites of origin and are likely acting under diverse regulatory mechanisms.

Extraction optimisation and isolation of triterpenoids from Ganoderma lucidum and their effect on human carcinoma cell growth.

The response surface methodology was used to optimise the extraction conditions of Ganoderma lucidum based on a Box-Behnken design. A quadratic model sufficiently simulated the response of ganoderic acid H with a determination coefficient (R(2)) of 0.98. The optimal condition for extracting triterpenoids was determined to be 100.00% ethanol at 60.22°C for 6.00 h, under which the yield of the reference triterpenoid ganoderic acid H increased from 0.88 to 2.09 mg/g powder. Following extraction, triterpenoid-enriched fraction was further isolated into 23 fractions, and 7 fractions were identified as ganoderic acids A, B, D, G, H and I and ganoderenic acid D. Of the seven triterpenoids, ganoderenic acid D was most cytotoxic with IC50 values of 0.14 ± 0.01, 0.18 ± 0.02 and 0.26 ± 0.03 mg/mL in Hep G2, Hela and Caco-2 cells, respectively. While ganoderic acids A, G and H were relatively non-cytotoxic. The variation of inhibitory effects for these triterpenoids was likely related to their chemical structures.