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BACKGROUND/AIM N6-Methyladenosine (m6A), the most abundant internal modification of RNA, plays a critical role in cancer development. However, the clinical implications of m6A in hepatocellular carcinoma (HCC) remain unclear. MATERIALS AND METHODS We analyzed 177 HCC and paired noncancerous liver tissues from patients who underwent hepatectomy according to global m6A quantification and expression of m6A demethylases fat mass and obesity-associated protein (FTO) and alpha-ketoglutarate-dependent dioxygenase alkB homolog 5 (ALKBH5). RESULTS The global m6A quantification revealed no significant difference between HCC and non-cancerous tissue. The expression of m6A demethylases FTO and ALKBH5, was significantly lower in HCC than in non-cancerous tissues (both p

BACKGROUND: While emerging evidence indicates that N(6)-methyladenosine (m(6)A) regulators play crucial roles in cancer progression, their clinical significance in gastric cancer (GC) has thus far not been elucidated. METHODS: We investigated the expression of the m(6)A regulator genes and their prognostic potential in a large clinical cohort of 173 GC patients using qRT-PCR assays. In addition, we undertook a series of in-vitro and in-vivo functional studies to investigate the oncogenic role of FTO. RESULTS: GC patients with low expression of METTL3, METTL14, ALKBH5, WTAP and YTHDF1 demonstrated significantly poor OS, while patients with high FTO expression exhibited markedly worse OS. Furthermore, the cumulative risk-score derived from these gene panel also significantly associated with poor OS, with a corresponding hazard ratio of 5.47 (95% CI: 3.18–9.41, p

PURPOSE The development and use of predictive biomarkers to guide treatment decisions are paramount not only for improving survival in patients with metastatic colorectal cancer (mCRC), but also for sparing them from unnecessary toxicity and reducing the economic burden of expensive treatments. We conducted a systematic review of published studies and evaluated the predictive biomarker landscape in the mCRC setting from a molecular and clinical viewpoint. METHODS Studies analyzing predictive biomarkers for approved therapies in patients with mCRC were identified systematically using electronic databases. Preclinical studies and those providing no relevant information were excluded. RESULTS A total of 173 studies comprising 148 biomarkers were selected for final analysis. Of all the biomarkers analyzed, 1.4% (two of 148) were explored in a prospective manner, whereas 98.6% (146 of 148) were evaluated in retrospective studies. Of the latter group, 78.8% (115 of 146) were not tested in subsequent phases, 9.6% (14 of 146) were tested in other retrospective cohorts, 8.9% (13 of 146) were retrospectively tested in at least one or more randomized cohorts, and only 2.7% (four of 146) were prospectively tested in a clinical trial. Finally, only 1.4% (two of 148) were validated sufficiently and are recognized as biomarkers for guiding treatment decision making in patients with mCRC. These markers were RAS mutational status for anti-EGFR antibodies and microsatellite instability status for anti–programmed cell death-1 drugs. CONCLUSION Despite notable efforts to identify predictive biomarkers for various therapies used in the mCRC setting, because of a lack of data beyond retrospective studies and successful biomarker-driven approaches, only two molecular biomarkers have thus far found their translation into the clinic, highlighting the imperative need for implementing novel strategies and additional research in this clinically important field.

OBJECTIVE: This study aimed to do a genomewide transcriptomic profiling to develop a miRNA-based signature for the identification of peritoneal metastasis (PM) in patients with gastric cancer (GC). SUMMARY BACKGROUND DATA: Even though PM in patients with GC has long been recognized to associate with poor survival, currently there is lack of availability of molecular biomarkers for its robust diagnosis. METHODS: We performed a systematic biomarker discovery by analyzing miRNA expression profiles in primary tumors from GC patients with and without PM, and subsequently validated the expression of candidate miRNA biomarkers in three independent clinical cohorts of 354 patients with advanced GC. RESULTS: Five miRNAs (miR-30a-5p, -134-5p, -337-3p, -659-3p, and -3917) were identified during the initial discovery phase; three of which (miR-30a-5p, -659-3p, and -3917) were significantly overexpressed in the primary tumors from PM-positive patients in the testing cohort (p=0.002, 0.04 and 0.007 respectively), and distinguished patients with vs. without peritoneal metastasis with the value of area under the curve (AUC) of 0.82. Furthermore, high expression of these miRNAs also associated with poor prognosis (HR=2.18, p=0.04). The efficacy of the combination miRNA-signature was subsequently validated in an independent validation cohort (AUC=0.74). Finally, our miRNA signature when combined together with the macroscopic Borrmann’s type score offered a much superior diagnostic in all three cohorts (AUC=0.87, 0.76, 0.79, respectively), and led us to establish a risk-prediction nomogram for the diagnosis of PM in GC patients. CONCLUSIONS: We have established a miRNA-based signature that have a potential to identify peritoneal metastasis in GC patients.

Purpose: Emerging evidence indicates that gut microbiome plays a crucial role in the cancer pathogenesis. Although Fusobacterium nucleatum (F. nucleatum) is associated with poor prognosis in multiple cancers, its clinical significance in predicting response to chemotherapy in patients with esophageal squamous cell carcinoma (ESCC) remains unclear. Experimental Design: The F. nucleatum levels were quantified by qPCR assays in tumor tissues from 551 patients with ESCC from two independent cohorts, including 101 patients who received neoadjuvant chemotherapy prior to curative resection. Associations between F. nucleatum burden and recurrence-free survival (RFS), as well with chemotherapeutic response were evaluated using response evaluation criteria in solid tumors (RECISTs), primary tumor metabolic response defined by maximum standardized uptake value (SUVmax) changes in positron emission tomography-CT (PET/CT), and pathologic tumor regression grade (TRG). Results: High burden of F. nucleatum in patients with ESCC associated with poor RFS in both training [log-rank P = 0.02; HR = 1.61; P = 0.03] and validation cohorts (log-rank P = 0.003; HR = 1.96; P = 0.004). Importantly, patients with ESCC with high levels of F. nucleatum displayed poor chemotherapeutic response for all three evaluation methods: RECIST (P = 0.04), SUVmax change in PET/CT (P = 0.0004), and TRG (P = 0.003). Conclusions: We conclude that high levels of intratumoral F. nucleatum have a prognostic significance for predicting poor RFS in patients with ESCC. More importantly, our data indicates that higher F. nucleatum burden correlates with poor response to neoadjuvant chemotherapy, suggesting the possibility that an antibiotic intervention against this bacterium may significantly improve therapeutic response in patients with ESCC.

Colorectal cancer (CRC) is one of the leading causes of cancer-related deaths worldwide. Similar to many other malignancies, CRC is a heterogeneous disease, making it a clinical challenge for optimization of treatment modalities in reducing the morbidity and mortality associated with this disease. A more precise understanding of the biological properties that distinguish patients with colorectal tumors, especially in terms of their clinical features, is a key requirement towards a more robust, targeted-drug design, and implementation of individualized therapies. In the recent decades, extensive studies have reported distinct CRC subtypes, with a mutation-centered view of tumor heterogeneity. However, more recently, the paradigm has shifted towards transcriptome-based classifications, represented by six independent CRC taxonomies. In 2015, the colorectal cancer subtyping consortium reported the identification of four consensus molecular subtypes (CMSs), providing thus far the most robust classification system for CRC. In this review, we summarize the historical timeline of CRC classification approaches; discuss their salient features and potential limitations that may require further refinement in near future. In other words, in spite of the recent encouraging progress, several major challenges prevent translation of molecular knowledge gleaned from CMSs into the clinic. Herein, we summarize some of these potential challenges and discuss exciting new opportunities currently emerging in related fields. We believe, close collaborations between basic researchers, bioinformaticians and clinicians are imperative for addressing these challenges, and eventually paving the path for CRC subtyping into routine clinical practice as we usher into the era of personalized medicine.

Purpose: DNA methylation alterations have emerged as front-runners in cell-free DNA (cfDNA) biomarker development. However, much effort to date has focused on single cancers. In this context, gastrointestinal (GI) cancers constitute the second leading cause of cancer-related deaths worldwide; yet there is no blood-based assay for the early detection and population screening of GI cancers. Experimental Design: Herein, we performed a genome-wide DNA methylation analysis of multiple GI cancers to develop a pan-GI diagnostic assay. By analyzing DNA methylation data from 1,781 tumor and adjacent normal tissues, we first identified differentially methylated regions (DMR) between individual GI cancers and adjacent normal, as well as across GI cancers. We next prioritized a list of 67,832 tissue DMRs by incorporating all significant DMRs across various GI cancers to design a custom, targeted bisulfite sequencing platform. We subsequently validated these tissue-specific DMRs in 300 cfDNA specimens and applied machine learning algorithms to develop three distinct categories of DMR panels Results: We identified three distinct DMR panels: (i) cancer-specific biomarker panels with AUC values of 0.98 (colorectal cancer), 0.98 (hepatocellular carcinoma), 0.94 (esophageal squamous cell carcinoma), 0.90 (gastric cancer), 0.90 (esophageal adenocarcinoma), and 0.85 (pancreatic ductal adenocarcinoma); (ii) a pan-GI panel that detected all GI cancers with an AUC of 0.88; and (iii) a multi-cancer (tissue of origin) prediction panel, EpiPanGI Dx, with a prediction accuracy of 0.85–0.95 for most GI cancers. Conclusions: Using a novel biomarker discovery approach, we provide the first evidence for a cfDNA methylation assay that offers robust diagnostic accuracy for GI cancers.

Simple Summary Colon cancer is one of the leading causes of cancer-related death worldwide. Therefore, the development of new therapeutic strategies is of the utmost importance. Previously, we identified a subset of colon cancers that are characterised by DNA methylation and have a poor prognosis. In this study, we therefore treated ten colon cancer patients with a demethylating agent, decitabine, to investigate if reversal of methylation is feasible and can be used as a novel therapy. Unfortunately, this study revealed that while decitabine treatment is effective in vitro, it only marginally decreased global methylation in patients and had no effect on the specific regions of DNA methylation in the tumours. Future studies should therefore focus on optimisation of treatment schedules in patients with highly methylated tumours. Abstract DNA hypermethylation is common in colon cancer. Previously, we have shown that methylation of WNT target genes predicts poor prognosis in stage II colon cancer. The primary objective of this study was to assess whether pre-operative treatment with decitabine can decrease methylation and increase the expression of WNT target genes APCDD1, AXIN2 and DKK1 in colon cancer patients. A clinical study was conducted, investigating these potential effects of decitabine in colon cancer patients (DECO). Patients were treated two times with 25 mg/m2 decitabine before surgery. Methylation and expression of LINE1 and WNT target genes (primary outcome) and expression of endogenous retroviral genes (secondary outcome) were analysed in pre- and post-treatment tumour samples using pyrosequencing and rt-PCR. Ten patients were treated with decitabine and eighteen patients were used as controls. Decitabine treatment only marginally decreased LINE1 methylation. More importantly, no differences in methylation or expression of WNT target or endogenous retroviral genes were observed. Due to the lack of an effect on primary and secondary outcomes, the study was prematurely closed. In conclusion, pre-operative treatment with decitabine is safe, but with the current dosing, the primary objective, increased WNT target gene expression, cannot be achieved.

Purpose:Due to the lack of effective screening approaches and early detection biomarkers, ovarian cancer has the highest mortality rates among gynecologic cancers. Herein, we undertook a systematic biomarker discovery and validation approach to identify microRNA (miRNA) biomarkers for the early detection of ovarian cancer.Experimental Design:During the discovery phase, we performed small RNA sequencing in stage I high-grade serous ovarian cancer (n = 31), which was subsequently validated in multiple, independent data sets (TCGA, n = 543; GSE65819, n = 87). Subsequently, we performed multivariate logistic regression-based training in a serum data set (GSE106817, n = 640), followed by its independent validation in three retrospective data sets (GSE31568, n = 85; GSE113486, n = 140; Czech Republic cohort, n = 192) and one prospective serum cohort (n = 95). In addition, we evaluated the specificity of OCaMIR, by comparing its performance in several other cancers (GSE31568 cohort, n = 369).Results:The OCaMIR demonstrated a robust diagnostic accuracy in the stage I high-grade serous ovarian cancer patients in the discovery cohort (AUC = 0.99), which was consistently reproducible in both stage I (AUC = 0.96) and all stage patients (AUC = 0.89) in the TCGA cohort. Logistic regression-based training and validation of OCaMIR achieved AUC values of 0.89 (GSE106817), 0.85 (GSE31568), 0.86 (GSE113486), and 0.82 (Czech Republic cohort) in the retrospective serum validation cohorts, as well as prospective validation cohort (AUC = 0.92). More importantly, OCaMIR demonstrated a significantly superior diagnostic performance compared with CA125 levels, even in stage I patients, and was more cost-effective, highlighting its potential role for screening and early detection of ovarian cancer.Conclusions:Small RNA sequencing identified a robust noninvasive miRNA signature for early-stage serous ovarian cancer detection.

Aim To develop a decision model for the population-level evaluation of strategies to improve the selection of stage II colon cancer (CC) patients who benefit from adjuvant chemotherapy. Methods A Markov cohort model with a one-month cycle length and a lifelong time horizon was developed. Five health states were included; diagnosis, 90-day mortality, death other causes, recurrence and CC death. Data from the Netherlands Cancer Registry were used to parameterize the model. Transition probabilities were estimated using parametric survival models including relevant clinical and pathological covariates. Subsequently, biomarker status was implemented using external data. Treatment effect was incorporated using pooled trial data. Model development, data sources used, parameter estimation, and internal and external validation are described in detail. To illustrate the use of the model, three example strategies were evaluated in which allocation of treatment was based on (A) 100% adherence to the Dutch guidelines, (B) observed adherence to guideline recommendations and (C) a biomarker-driven strategy. Results Overall, the model showed good internal and external validity. Age, tumor growth, tumor sidedness, evaluated lymph nodes, and biomarker status were included as covariates. For the example strategies, the model predicted 83, 87 and 77 CC deaths after 5 years in a cohort of 1000 patients for strategies A, B and C, respectively. Conclusion This model can be used to evaluate strategies for the allocation of adjuvant chemotherapy in stage II CC patients. In future studies, the model will be used to estimate population-level long-term health gain and cost-effectiveness of biomarker-based selection strategies.

Risk stratification in Stage II and III colorectal cancer (CRC) patients is critical, as it allows patient selection for adjuvant chemotherapy. In view of the inadequacy of current clinicopathological features for risk-stratification, we undertook a systematic and comprehensive biomarker discovery effort to develop a risk-assessment signature in CRC patients. The biomarker discovery phase examined 853 CRC patients, and identified a gene signature for predicting recurrence-free survival (RFS). This signature was validated in a meta-analysis of 1212 patients from nine independent datasets, and its performance was compared against established prognostic signatures and consensus molecular subtypes (CMS). In addition, a risk-prediction model was trained (n = 142), and subsequently validated in an independent clinical cohort (n = 286). As a result, this mesenchymal-associated transcriptomic signature (MATS) identified high-risk CRC patients with poor RFS in the discovery (hazard ratio [HR]: 1.79), and nine validation cohorts (HR: 1.86). In multivariate analysis, MATS was the most significant predictor of RFS compared to established prognostic signatures and CMS subtypes. Intriguingly, MATS robustly identified CMS4-subtype in multiple CRC cohorts (AUC = 0.92-0.99). In the two clinical cohorts, MATS stratified low and high-risk groups with a 5-year RFS in the training (HR: 4.11) and validation cohorts (HR: 2.55), as well as predicted response to adjuvant therapy in Stage II and III CRC patients. We report a novel prognostic and predictive biomarker signature in CRC, which is superior to currently used approaches and have the potential for clinical translation in near future.

OBJECTIVE The aim of the study was to perform mRNA-miRNA regulatory network analyses to identify a miRNA panel for molecular subtype identification and stratification of high-risk patients with pancreatic ductal adenocarcinoma (PDAC). BACKGROUND Recent transcriptional profiling effort in PDAC has led to the identification of molecular subtypes that associate with poor survival; however, their clinical significance for risk stratification in patients with PDAC has been challenging. METHODS By performing a systematic analysis in The Cancer Genome Atlas and International Cancer Genome Consortium cohorts, we discovered a panel of miRNAs that associated with squamous and other poor molecular subtypes in PDAC. Subsequently, we used logistic regression analysis to develop models for risk stratification and Cox proportional hazard analysis to determine survival prediction probability of this signature in multiple cohorts of 433 patients with PDAC, including a tissue cohort (n = 199) and a preoperative serum cohort (n = 51). RESULTS We identified a panel of 9 miRNAs that were significantly upregulated (miR-205-5p and -934) or downregulated (miR-192-5p, 194-5p, 194-3p, 215-5p, 375-3p, 552-3p, and 1251-5p) in PDAC molecular subtypes with poor survival [squamous, area under the receiver operating characteristic curve (AUC) = 0.90; basal, AUC = 0.89; and quasimesenchymal, AUC = 0.83]. The validation of this miRNA panel in a tissue clinical cohort was a significant predictor of overall survival (hazard ratio = 2.48, P < 0.0001), and this predictive accuracy improved further in a risk nomogram which included key clinicopathological factors. Finally, we were able to successfully translate this miRNA predictive signature into a liquid biopsy-based assay in preoperative serum specimens from PDAC patients (hazard ratio: 2.85, P = 0.02). CONCLUSION We report a novel miRNA risk-stratification signature that can be used as a noninvasive assay for the identification of high-risk patients and potential disease monitoring in patients with PDAC.

Treatment modalities in esophageal squamous cell carcinoma (ESCC) depend largely on lymph node metastasis (LNM) status. With suboptimal detection sensitivity of existing imaging techniques, we propose a methylation signature which identifies patients with LNM with greater accuracy. This would allow precise stratification of high-risk patients requiring more aggressive treatment from low-risk ESCC patients who can forego radical surgery. An unbiased genome-wide methylation signature for LNM detection was established from an initial in silico discovery phase. The signature was tested in independent clinical cohorts comprising of 249 ESCC patients. The prognostic potential of the methylation signature was compared to clinical variables including LNM status. A 10-probe LNM associated signature (LNAS) was developed using stringent bioinformatics analyses. The area under the curve values for LNAS risk scores were 0.81 and 0.88 in the training and validation cohorts respectively, in association with lymphatic vessel invasion and tumor stage. High LNAS risk-score was also associated with worse overall survival [HR (95% CI) 3 (1.8-4.8), p < 0.0001 training and 3.9 (1.5-10.2), p = 0.001 validation cohort]. In conclusion, our novel methylation signature is a powerful biomarker that identifies LNM status robustly and is also associated with worse prognosis in ESCC patients.

PURPOSE: Patients with nonmuscle invasive bladder cancer are followed with frequent cystoscopies. In this study FGFR3, TERT and OTX1 were investigated as a diagnostic urinary marker combination during followup of patients with primary nonmuscle invasive bladder cancer.MATERIALS AND METHODS: In this international, multicenter, prospective study 977 patients with nonmuscle invasive bladder cancer were included. A total of 2,496 urine samples were collected prior to cystoscopy during regular visits. Sensitivity was estimated to detect concomitant recurrences. Kaplan-Meier curves were used to estimate the development of future recurrences after urinalysis and a negative cystoscopy.RESULTS: Sensitivity of the assay combination for recurrence detection was 57% in patients with primary low grade, nonmuscle invasive bladder cancer. However, sensitivity was 83% for recurrences that were pT1 or muscle invasive bladder cancer. Of the cases 2% progressed to muscle invasive bladder cancer. Sensitivity for recurrence detection in patients with primary high grade disease was 72% and 7% of them had progression to muscle invasive bladder cancer. When no concomitant tumor was found by cystoscopy, positive urine samples were more frequently followed by a recurrence over time compared to a negative urine sample (58% vs 36%, p CONCLUSIONS: Recurrences in patients with primary nonmuscle invasive bladder cancer can be detected by a combination of urine assays. This study supports the value of urinalysis as an alternative diagnostic tool in patients presenting with low grade tumors and as a means to identify high stage tumors earlier.

Purpose: Pancreatic ductal adenocarcinoma (PDAC) is a lethal disease with dismal survival rates. Tumor microenvironment (TME), comprising of immune cells and cancer-associated fibroblasts, plays a key role in driving poor prognosis and resistance to chemotherapy. Herein, we aimed to identify a TME-associated, risk-stratification gene biomarker signature in PDAC. Experimental Design: The initial biomarker discovery was performed in The Cancer Genome Atlas (TCGA, n = 163) transcriptomic data. This was followed by independent validation of the gene signature in the International Cancer Genome Consortium (ICGC, n = 95), E-MTAB-6134 (n = 288), and GSE71729 (n = 123) datasets for predicting overall survival (OS), and for its ability to detect poor molecular subtypes. Clinical validation and nomogram establishment was undertaken by performing multivariate Cox regression analysis. Results: Our biomarker discovery effort identified a 15-gene immune, stromal, and proliferation (ISP) gene signature that significantly associated with poor OS [HR, 3.90; 95% confidence interval (CI), 2.36–6.41; P < 0.0001]. This signature also robustly predicted survival in three independent validation cohorts ICGC [HR, 2.63 (1.56–4.41); P < 0.0001], E-MTAB-6134 [HR, 1.53 (1.14–2.04); P = 0.004], and GSE71729 [HR, 2.33 (1.49–3.63); P < 0.0001]. Interestingly, the ISP signature also permitted identification of poor molecular PDAC subtypes with excellent accuracy in all four cohorts; TCGA (AUC = 0.94), ICGC (AUC = 0.91), E-MTAB-6134 (AUC = 0.80), and GSE71729 (AUC = 0.83). The ISP-derived high-risk patients exhibited significantly poor OS in a clinical validation cohort [n = 119; HR, 2.62 (1.50–4.56); P = 0.0004]. A nomogram was established which included the ISP, CA19-9, and T- and N-stage for eventual clinical translation. Conclusions: We report a novel gene signature for risk-stratification and robust identification of patients with PDAC with poor molecular subtypes.

Purpose: In view of high cancer-specificity, DNA methylation alterations have emerged as front-runners in biomarker development, especially as cell-free DNA (cf-DNA) biomarkers for early detection of cancer. However, much effort to date has focused on developing cancer type-specific biomarkers, but have not explored the possibility of developing a pan-cancer diagnostic assay. In this context, gastrointestinal (GI) cancers, including colorectal (CRC), esophageal squamous cell and adenocarcinoma (ESCC and EAC), gastric (GC), liver (HCC) and pancreatic ductal adenocarcinoma (PDAC) constitute the second leading cause of cancer-related deaths worldwide; yet there is no blood-based assay for the early detection and population screening of GI cancers. Here we undertook a genomewide DNA methylation analysis for multiple GI cancers, followed by development of a novel cf-DNA methylation biomarker panels for the early detection of GI cancers (EpiPanGI Dx). Experimental design: By analyzing the DNA methylation data from 1940 tumor and adjacent normal tissues from TCGA and GSE72872 datasets, we first identified the differentially methylated regions (DMRs) between individual GI cancers and adjacent normal tissues, as well as across all GI cancers. We next prioritized a list of DMRs encompassing a 25.6 Mb genomic region by incorporating all identified DMRs across various GI cancers to design a custom SeqCap Epi, targeted bisulfite sequencing platform, optimized for analysis of low-abundance cf-DNA derived from plasma specimens. Using this approach, we sequenced 300 plasma specimens from all GI cancers, as well as age-matched healthy controls, with a 40X coverage. Finally, using machine learning algorithms, we identified unique DMR panels for the detection of various GI cancers. Results: Methylation profiling data from various GI tissues led to the identification of 67,832 DMRs with an adjusted p Conclusions: Utilizing a novel biomarker discovery approach, we provide first evidence for cell-free DNA methylation biomarkers that offer a robust diagnostic accuracy for the identification of specific cancer types, and demonstrate their potential clinical application as a Pan-cancer panel for the early detection of all gastrointestinal cancers. Citation Format: Raju Kandimalla, Jianfeng Xu, Alexander Link, Takatoshi Matsuyama, Kensuke Yamamura, Iqbal Parker, Hiroyuki Uetake, Eva Hernandez-Illan, Juanjo Lozano, Erkut Borazanci, Susan Tsai, Douglas Evans, Stephen J. Meltzer, Hideo Baba, Randall Brand, Daniel Von Hoff, Francesc Balaguer, Wei Li, Ajay Goel. EpiPanGI-Dx: A cell-free DNA methylation fingerprint for the early detection of gastrointestinal cancers [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 1084.

Most T1 colorectal cancers treated by radical surgery can now be cured by endoscopic submucosal dissection. Although 70%-80% of T1 colorectal cancers are classified as high risk,16% of these patients actually have lymph node metastases. Biomarkers are needed to identify patients with T1 cancers with the highest risk of metastasis, to prevent unnecessary radical surgery. We collected data from The Cancer Genome Atlas and identified 5 microRNAs (MIR32, MIR181B, MIR193B, MIR195, and MIR411) with significant changes in expression in T1 and T2 colorectal cancers with vs without lymph node metastases. Levels of the 5 microRNAs identified patients with lymph node invasion by T1 or T2 cancers with an area under the receiver operating characteristic curve (AUROC) value of 0.84. We validated these findings in 2 cohorts of patients with T1 cancers, using findings from histology as the reference. The 5-microRNA signature identified T1 cancers with lymph node invasion in cohort 1 with an AUROC value of 0.83, and in cohort 2 with an AUROC value of 0.74. When we analyzed biopsy samples from untreated patients, the 5-microRNA signature identified cancers with lymph node metastases with an AUROC value of 0.77. The 5-microRNA therefore identifies high-risk T1 colorectal cancers with a greater degree of accuracy than currently used pathologic features.

Purpose: The current tumor–node–metastasis (TNM) staging system is inadequate at identifying patients with high-risk colorectal cancer. Using a systematic and comprehensive biomarker discovery and validation approach, we aimed to identify an miRNA recurrence classifier (MRC) that can improve upon the current TNM staging as well as is superior to currently offered molecular assays. Experimental Design: Three independent genome-wide miRNA expression profiling datasets were used for biomarker discovery (N = 158) and in silico validation (N = 109 and N = 40) to identify an miRNA signature for predicting tumor recurrence in patients with colorectal cancer. Subsequently, this signature was analytically trained and validated in retrospectively collected independent patient cohorts of fresh-frozen (N = 127, cohort 1) and formalin-fixed paraffin-embedded (FFPE; N = 165, cohort 2 and N = 139, cohort 3) specimens. Results: We identified an 8-miRNA signature that significantly predicted recurrence-free interval (RFI) in the discovery (P = 0.002) and two independent publicly available datasets (P = 0.00006 and P = 0.002). The RT-PCR–based validation in independent clinical cohorts revealed that MRC-derived high-risk patients succumb to significantly poor RFI in patients with stage II and III colorectal cancer [cohort 1: hazard ratio (HR), 3.44 (1.56–7.45), P = 0.001; cohort 2: HR, 6.15 (3.33–11.35), P = 0.001; and cohort 3: HR, 4.23 (2.26–7.92), P = 0.0003]. In multivariate analyses, MRC emerged as an independent predictor of tumor recurrence and achieved superior predictive accuracy over the currently available molecular assays. The RT-PCR–based MRC risk score = (−0.1218 × miR-744) + (−3.7142 × miR-429) + (−2.2051 × miR-362) + (3.0564 × miR-200b) + (2.4997 × miR-191) + (−0.0065 × miR-30c2) + (2.2224 × miR-30b) + (−1.1162 × miR-33a). Conclusions: This novel MRC is superior to currently used clinicopathologic features, as well as National Comprehensive Cancer Network (NCCN) criteria, and works regardless of adjuvant chemotherapy status in identifying patients with high-risk stage II and III colorectal cancer. This can be readily deployed in clinical practice with FFPE specimens for decision-making pending further model testing and validation. Clin Cancer Res; 24(16); 3867–77. ©2018 AACR. See related commentary by Rodriguez et al., p. 3787

Purpose: Pancreatic ductal adenocarcinoma (PDAC) remains the fourth leading cause of cancer-related deaths in the United States, with an overall 5-year survival rates of ~8%. The currently used clinicopathological factors (e.g. tumor size and grade, lymph node etc.) for determining patient prognosis are suboptimal. The only FDA-approved molecular non-invasive prognostic biomarker for PDAC patients is CA-19-9, which suffers from inadequate sensitivity and specificity. Nonetheless, the clinical use of CA-19-9, along with the growing evidence that altered glycosylation plays an important role in PDAC pathogenesis, provided us with a rationale to explore the clinical significance of glycan-related genes as potential prognostic biomarkers in PDAC. Experimental design: We performed a comprehensive biomarker discovery (TCGA cohort, n=182), and validation (ICGC, n=80; GSE62452, n=65) to identify a glycan gene signature for predicting overall survival (OS) in PDAC patients. Subsequently, this gene signature was validated in two, independent, clinical cohorts (test cohort, n=103; validation cohort, n=227). The performance of this signature was further evaluated by univariate and multivariate CoxPH analyses. Lastly, using a logistic-regression model, we explored the feasibility of our glycan signature in identifying various molecular subtypes of PDAC. Results: A comprehensive analysis of 411 glycan genes using Cox-LASSO regression modelling led to the identification of a 12-glycan gene signature, which robustly predicted overall survival (OS) of PDAC patients in the discovery (AUC=0.78), and two validation cohorts (ICGC, AUC=0.72; and GSE62452, AUC=0.70). Subsequent qRT-PCR validation in two in-house clinical cohorts revealed that a 9-gene signature was a robust predictor of OS (Test Cohort, HR: 1.81, 95% CI, 1.22-2.69, p=0.003; Validation Cohort, HR: 2.72, 95% CI, 2.00-3.69, p Conclusion: Our systematic biomarker discovery and validation efforts led to the identification and establishment of a 9-gene glycan signature that robustly predicts survival in PDAC patients, and can accurately identify poor PDAC subtypes - highlighting its potential clinical significance for the personalized management of PDAC patients. Citation Format: Priyanka Sharma, Raju Kandimalla, Jasjit K. Banwait, Masayuki Sho, Yasuhiro Kodera, Ajay Goel. A glycan gene signature that robustly predicts prognosis in patients with pancreatic ductal adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4883.

Purpose: Colorectal cancer (CRC) is the third most commonly diagnosed cancer in the United States. Current TNM (Tumor, Node, and Metastasis) classification approach is suboptimal in determining the prognosis of CRC patients. While there is a general consensus that stage II and III CRC patients with microsatellite instability (MSI) exhibit better outcomes, there is a lack of availability of biomarkers that can predict prognosis in microsatellite stable (MSS) patients. Given the emerging evidence that mitochondrial (mt) genomic instability is one of the hallmark features of cancer progression, herein, we systematically explored and established a novel mt-gene panel as a prognostic signature in CRC. Experimental design: Three genome wide mRNA expression profiling datasets were analyzed for the biomarker discovery (GSE33113, n=65) and validation (GSE14333, n=196; TCGA, n=62) of a mt-gene expression signature that predicts recurrence in stage II/III MSS CRC patients. Subsequently, a 14-gene signature was established, and independently tested (n=257) and validated (n=212) in two clinical cohorts, using qRT-PCR assays. The uni- and multi-variate Cox proportional hazard (CoxPH) regression analyses were performed to evaluate the performance of the mt-gene signature individually, and in combination with various clinicopathological factors (e.g. TNM staging, lymphatic invasion, and tumor infiltration) for predicting recurrence free survival (RFS). Results: The expression analysis of 568 mt-genes in CRC patients with and without recurrence, resulted in the identification of 32 significantly dysregulated genes (p Conclusions: We have identified a novel, 14-gene signature as an independent predictor of tumor recurrence; which in combination with TNM-stage and lymphatic invasion, offers an easy-to-translate and facile assay for the personalized risk-assessment in stage II/III MSS-CRC patients. Citation Format: SOUVIK GHATAK, Raju Kandimalla, Jasjit K. Banwait, Hiroyuki Uetake, Francesc Balaguer, Luis Bujanda, Ajay Goel. Transcriptomic profiling identifies a novel mitochondrial gene expression signature that predicts recurrence in microsatellite stable stage II and III colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4907.

Purpose: DNA methylation is associated with bladder cancer and these modifications could serve as useful biomarkers. FGFR3 mutations are present in 60% to 70% of non–muscle invasive bladder cancer (NMIBC). Low-grade bladder cancer recurs in more than 50% of patients. The aim of this study is to determine the sensitivity and specificity of a urine assay for the diagnosis of recurrences in patients with a previous primary NMIBC G1/G2 by using cystoscopy as the reference standard. Experimental Design: We selected eight CpG islands (CGI) methylated in bladder cancer from our earlier genome-wide study. Sensitivity of the CGIs for recurrences detection was investigated on a test set of 101 preTUR urines. Specificity was determined on 70 urines from healthy males aged more than 50 years. A 3-plex assay for the best combination was developed and validated on an independent set of 95 preTUR, recurrence free, and nonmalignant urines (n = 130). Results: The 3-plex assay identified recurrent bladder cancer in voided urine with a sensitivity of 74% in the validation set. In combination with the FGFR3 mutation assay, a sensitivity of 79% was reached (specificity of 77%). Sensitivity of FGFR3 and cytology was 52% and 57%, respectively. Conclusion: The combination of methylation and FGFR3 assays efficiently detects recurrent bladder cancer without the need for stratification of patients regarding methylation/mutation status of the primary tumor. We conclude that the sensitivity of this combination is in the same range as cystoscopy and paves the way for a subsequent study that investigates a modified surveillance protocol consisting of the urine test followed by cystoscopy only when the urine test is positive. DNA methylation is associated with bladder cancer and these modifications could serve as useful biomarkers. FGFR3 mutations are present in 60% to 70% of non-muscle invasive bladder cancer (NMIBC). Low-grade bladder cancer recurs in more than 50% of patients. The aim of this study is to determine the sensitivity and specificity of a urine assay for the diagnosis of recurrences in patients with a previous primary NMIBC G1/G2 by using cystoscopy as the reference standard.

Stage II colon cancer (CC) still remains a clinical challenge with patient stratification for adjuvant therapy (AT) largely relying on clinical parameters. Prognostic biomarkers are urgently needed for better stratification. Previously, we have shown that WNT target genes AXIN2, DKK1, APCDD1, ASCL2 and LGR5 are silenced by DNA methylation and could serve as prognostic markers in stage II CC patients using methylation-specific PCR. Here, we have extended our discovery cohort AMC90-AJCC-II (N=65) and methylation was analyzed by quantitative pyrosequencing. Subsequently, we validated the results in an independent EPICOLON1 CC cohort (N=79). Methylation of WNT target genes is negatively correlated to mRNA expression. A combination of AXIN2 and DKK1 methylation significantly predicted recurrences in univariate (area under the curve (AUC)=0.83, confidence interval (CI): 0.72–0.94, PPmethylation: 3.84, 95% CI: 1.14–12.43; HRCMS4: 3.73, 95% CI: 1.22–11.48). CMS4 subtype tumors with WNT target methylation showed worse prognosis. Combining WNT target gene methylation and CMS4 subtype lead to an AUC of 0.89 (0.791–0.982, PAXIN2 and DKK1 were found to be robust markers for recurrence prediction in stage II MSS CC patients. Further validation of these findings in a randomized and prospective manner could pave a way to identify poor prognosis patients of stage II CC for AT.

Background DNA methylation markers could serve as useful biomarkers, both as markers for progression and for urine-based diagnostic assays. Objective Identify bladder cancer (BCa)–specific methylated DNA sequences for predicting pTa-specific progression and detecting BCa in voided urine. Design, setting, and participants Genome-wide methylation analysis was performed on 44 bladder tumours using the Agilent 244K Human CpG Island Microarray (Agilent Technologies, Santa Clara, CA, USA). Validation was done using a custom Illumina 384-plex assay (Illumina, San Diego, CA, USA) in a retrospective group of 77 independent tumours. Markers for progression were identified in pTa ( n =24) tumours and validated retrospectively in an independent series of 41 pTa tumours by the SNaPshot method (Applied Biosystems, Foster City, CA, USA). Measurements The percentage of methylation in tumour and urine samples was used to identify markers for detection and related to the end point of progression to muscle-invasive disease with Kaplan-Meier models and multivariate analysis. Results and limitations In the validation set, methylation of the T-box 2 ( TBX2), T-box 3 (TBX3), GATA binding protein 2 (GATA2), and Zic family member 4 (ZIC4) genes was associated with progression to muscle-invasive disease in pTa tumours ( p =0.003). Methylation of TBX2 alone showed a sensitivity of 100%, a specificity of 80%, a positive predictive value of 78%, and a negative predictive value of 100%, with an area under the curve of 0.96 ( p TBX3 and GATA2 are independent predictors of progression when compared to clinicopathologic variables ( p =0.04 and p =0.03, respectively). The predictive accuracy improved by 23% by adding methylation of TBX2, TBX3, and GATA2 to the European Organisation for Research and Treatment of Cancer risk scores. We further identified and validated 110 CpG islands (CGIs) that are differentially methylated between tumour cells and control urine. The limitation of this study is the small number of patients analysed for testing and validating the prognostic markers. Conclusions We have identified four methylation markers that predict progression in pTa tumours, thereby allowing stratification of patients for personalised follow-up. In addition, we identified CGIs that will enable detection of bladder tumours in voided urine.

Purpose: Clinical decision making for adjuvant chemotherapy, which includes selection of appropriate patients and optimal treatment regimen, remains the most pressing challenge in the management of stage II and III colorectal cancer (CRC) patients. In this study, we attempted to address this issue by developing a clinically actionable mesenchymal-associated transcriptomic signature (MATS) that can accurately predict prognosis and identify CRC patients who could realistically benefit from adjuvant chemotherapy. Experimental Design: To develop a mesenchymal-associated transcriptomic signature, we first performed gene expression profiling in 152 laser capture microdissected CRC tissues, followed by validation of this signature in 1365 CRC patients from various publicly available cohorts (GSE41258, GSE39582, GSE33113, GSE17536 and TCGA). Subsequently, this signature was trained (N=142) and validated (N=286) in two independent clinical cohorts of stage II and III CRC patients, in which Cox's regression analysis was performed to evaluate the recurrence predictive power of this signature. Furthermore, we investigated the clinical significance of MATS in its ability to identify patients who can benefit from fluoropyrimidine-based adjuvant chemotherapy. Results: Through a comprehensive genome-wide expression analysis, we have identified an eight-gene mesenchymal-associated transcriptomic signature that can significantly predict recurrence-free survival (RFS) and identify a mesenchymal CRC subtype with high accuracy. To evaluate its translational potential, we further trained and validated this signature in two independent CRC cohorts consisting of 428 stage II and III CRC patients. Interestingly, MATS successfully stratified patients into low- and high-risk groups with 5-year RFS rates ranging from 87% and 54% in the training cohort [HR: 4.11 (CI: 2.72-15.43)] and 82% and 56% in the validation cohort [HR: 2.66 (CI: 1.66-3.98)], respectively. While the 48 patients with MATS low-risk stage III CRC showed a substantial improvement in survival, the 77 patients with MATS high-risk stage III CRC did not benefit from the fluoropyrimidine-based adjuvant chemotherapy. Furthermore, in multivariate analysis, MATS was significantly associated with RFS along with T-stage and lymphovascular invasion in both training as well as validation cohorts with HRs of 3.80 (CI: 1.85-7.82, p=0.0003) and 2.09 (CI: 1.28-3.42, p=0.003), respectively. Conclusions: Our novel MATS could robustly identify RFS, and this classifier was superior to various clinicopathologic risk factors used in the clinic for risk stratification in CRC patients. In addition, MATS could also predict which stage III CRC patients might benefit from fluoropyrimidine-based adjuvant chemotherapy, which is a significant step forward in the clinical management of these patients. Citation Format: Takatoshi Matsuyama, Raju Kandimalla, Xuan Wang, Toshiaki Ishikawa, Naoki Takahashi, Yasuhide Yamada, Masamichi Yasuno, Yusuke Kinugasa, Hiroyuki Uetake, Ajay Goel. A mesenchymal-associated transcriptomic signature has a prognostic and predictive potential in stage II and III colorectal cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2651.

P63 is a transcription factor belonging to the family of p53, essential for the development and differentiation of epithelia. In recent years, it has become clear that altered expression of the different isoforms of this gene can play an important role in carcinogenesis. The p63 gene encodes for two main isoforms known as TA and ΔN p63 with different functions. The role of these different isoforms in sustaining tumor progression and metastatic spreading however has not entirely been clarified. Here we show that breast cancer initiating cells express ΔNp63 isoform that supports a more mesenchymal phenotype associated with a higher tumorigenic and metastatic potential. On the contrary, the majority of cells within the tumor appears to express predominantly TAp63 isoform. While ΔNp63 exerts its effects by regulating a PI3K/CD44v6 pathway, TAp63 modulates this pathway in an opposite fashion. As a result, tumorigenicity and invasive capacity of breast cancer cells is a balance of the two isoforms. Finally, we found that tumor microenvironmental cytokines significantly contribute to the establishment of breast cancer cell phenotype by positively regulating ΔNp63 and CD44v6 expression.

Contains fulltext : 177761.pdf (Publisher’s version ) (Open Access) OBJECTIVE: Overall and splice specific expression of Spleen Tyrosine Kinase (SYK) has been posed as a marker predicting both poor and favorable outcome in various epithelial malignancies. However, its role in colorectal cancer is largely unknown. The aim of this study was to explore the prognostic role of SYK in three cohorts of colon cancer patients. METHODS: Total messenger RNA (mRNA) expression of SYK, SYK(T), and mRNA expression of its two splice variants SYK short (S) and SYK long (L) were measured using quantitative reverse transcriptase (RT-qPCR) in 240 primary colon cancer patients (n = 160 patients with chemonaive lymph node negative [LNN] and n = 80 patients with adjuvant treated lymph node positive [LNP] colon cancer) and related to microsatellite instability (MSI), known colorectal cancer mutations, and disease-free (DFS), hepatic metastasis-free (HFS) and overall survival (OS). Two independent cohorts of patients with respectively 48 and 118 chemonaive LNN colon cancer were used for validation. RESULTS: Expression of SYK and its splice variants was significantly lower in tumors with MSI, and in KRAS wild type, BRAF mutant and PTEN mutant tumors. In a multivariate Cox regression analysis, as a continuous variable, increasing SYK(S) mRNA expression was associated with worse HFS (Hazard Ratio[HR] = 1.83; 95% Confidence Interval[CI] = 1.08-3.12; p = 0.026) in the LNN group, indicating a prognostic role for SYK(S) mRNA in patients with chemonaive LNN colon cancer. However, only a non-significant trend between SYK(S) and HFS in one of the two validation cohorts was observed (HR = 4.68; 95%CI = 0.75-29.15; p = 0.098). CONCLUSION: In our cohort, we discovered SYK(S) as a significant prognostic marker for HFS for patients with untreated LNN colon cancer. This association could however not be confirmed in two independent smaller cohorts, suggesting that further extensive validation is needed to confirm the prognostic value of SYK(S) expression in chemonaive LNN colon cancer.

Cancers of the urinary bladder (BC) present as muscle-invasive (MIBC) or non-muscle invasive (NMIBC). Major problems with NMIBC are that 70% of the tumors will recur and 10-20% will eventually progress to MIBC. Therefore the patients are monitored by cystoscopy every 3-6 months after transurethral resection of the tumor in order to spot potential recurrences. DNA methylation has been shown to contribute to the pathogenesis cancer and may serve as useful biomarker. Recent studies showed promising urine methylation biomarkers for BC, but none of these were specifically tested for detection of recurrent BCs which are often smaller and hence more difficult to detect than primary tumors. Therefore we aimed to develop an assay specific for the diagnosis of recurrent bladder tumors in voided urine. From our earlier genome-wide study, we selected 8 candidate CGIs (CpG islands) methylated in BC to screen for the detection of recurrent bladder tumors in voided urine. We first screened these 8 CGIs on an independent set of 50 FFPE bladder tumors and 70 urines from age matched individuals without any history of BC as controls using BS-SNaPshot (Bisulfite specific single nucleotide primer extension assay). Subsequently, the 8 CGIs were investigated in a test set of 100 preTUR (before Trans Urethral Resection) urines associated with a concomitant recurrent tumor. We analyzed the sensitivity, specificity, AUC (area under the curve), PPV and NPV of all the individual markers and five best combinations. We then validated this on a separate cohort of 100 preTUR urines samples. Single marker OTX1 identified recurrent bladder tumors in voided urine with a sensitivity of 71% at a specificity of 90% with an AUC of 0.85 (CI: 0.80-0.91, P Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 4023. doi:1538-7445.AM2012-4023