Raju Kandimalla

DNA methylation based biomarkers in colorectal cancer: A systematic review.

Since genetic and epigenetic alterations influence the development of colorectal cancer (CRC), huge potential lies in the use of DNA methylation as biomarkers to improve the current diagnosis, screening, prognosis and treatment prediction. Here we performed a systematic review on DNA methylation-based biomarkers published in CRC, and discussed the current state of findings and future challenges. Based on the findings, we then provide a perspective on future studies. Genome-wide studies on DNA methylation revealed novel biomarkers as well as distinct subgroups that exist in CRC. For diagnostic purposes, the most independently validated genes to study further are VIM, SEPT9, ITGA4, OSM4, GATA4 and NDRG4. These hypermethylated biomarkers can even be combined with LINE1 hypomethylation and the performance of markers should be examined in comparison to FIT further to find sensitive combinations. In terms of prognostic markers, myopodin, KISS1, TMEFF2, HLTF, hMLH1, APAF1, BCL2 and p53 are independently validated. Most prognostic markers published lack both a multivariate analysis in comparison to clinical risk factors and the appropriate patient group who will benefit by adjuvant chemotherapy. Methylation of IGFBP3, mir148a and PTEN are found to be predictive markers for 5-FU and EGFR therapy respectively. For therapy prediction, more studies should focus on finding markers for chemotherapeutic drugs as majority of the patients would benefit. Translation of these biomarkers into clinical utility would require large-scale prospective cohorts and randomized clinical trials in future. Based on these findings and consideration we propose an avenue to introduce methylation markers into clinical practice in near future. For future studies, multi-omics profiling on matched tissue and non-invasive cohorts along with matched cohorts of adenoma to carcinoma is indispensable to concurrently stratify CRC and find novel, robust biomarkers. Moreover, future studies should examine the timing and heterogeneity of methylation as well as the difference in methylation levels between epithelial and stromal tissues.

A multidimensional network approach reveals microRNAs as determinants of the mesenchymal colorectal cancer subtype

Colorectal cancer (CRC) is a heterogeneous disease posing a challenge for accurate classification and treatment of this malignancy. There is no common genetic molecular feature that would allow for the identification of patients at risk for developing recurrences and thus selecting patients who would benefit from more stringent therapies still poses a major clinical challenge. Recently, an international multicenter consortium (CRC Subtyping Consortium) was established aiming at the classification of CRC patients in biologically homogeneous CRC subtypes. Four consensus molecular subtypes (CMSs) were identified, of which the mesenchymal CMS4 presented with worse prognosis signifying the importance of identifying these patients. Despite the large number of samples analyzed and their clear association with unifying biological programs and clinical features, single-driver mutations could not be identified and patients are heterogeneous with regard to currently used clinical markers. We therefore set out to define the regulatory mechanisms underlying the distinct gene expression profiles using a network-based approach involving multiple molecular modalities such as gene expression, methylation levels and microRNA (miR) expression. The miR-200 family presented as the most powerful determinant of CMS4-specific gene expression, tuning the majority of genes differentially expressed in the poor prognosis subtype, including genes associated with the epithelial–mesenchymal transition program. Furthermore, our data show that two epigenetic marks, namely the methylation of the two miR-200 promoter regions, can identify tumors belonging to the mesenchymal subtype and is predictive of disease-free survival in CRC patients. Importantly, epigenetic silencing of the miR-200 family is also detected in epithelial CRC cell lines that belong to the mesenchymal CMS. We thus show that determining regulatory networks is a powerful strategy to define drivers of distinct cancer subtypes, which possess the ability to identify subtype affiliation and to shed light on biological behavior.

ΔNp63 drives metastasis in breast cancer cells via PI3K/CD44v6 axis

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.

Methylation of WNT target genes AXIN2 and DKK1 as robust biomarkers for recurrence prediction in stage II colon cancer

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, P<0.0001) analysis in stage II microsatellite stable (MSS) CC patients. This two marker combination showed an AUC of 0.80 (CI: 0.68–0.91, P<0.0001) in the EPICOLON1 validation cohort. Multivariate analysis in the Academic Medical Center (AMC) cohort revealed that both WNT target gene methylation and consensus molecular subtype 4 (CMS4) are significantly associated with poor recurrence-free survival (hazard ratio (HR)methylation: 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, P<0.0001) for recurrence prediction. Notably, we observed that methylation of DKK1 is high in BRAF mutant and CIMP (CpG island methylator phenotype)-positive cancers, whereas AXIN2 methylation appears to be associated with CMS4. Methylation of AXIN2 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.

Consensus molecular subtypes of colorectal cancer are recapitulated in in vitro and in vivo models

Colorectal cancer (CRC) is a highly heterogeneous disease both from a molecular and clinical perspective. Several distinct molecular entities, such as microsatellite instability (MSI), have been defined that make up biologically distinct subgroups with their own clinical course. Recent data indicated that CRC can be best segregated into four groups called consensus molecular subtypes (CMS1–4), each of which has a unique biology and gene expression pattern. In order to develop improved, subtype-specific therapies and to gain insight into the molecular wiring and origin of these subtypes, reliable models are needed. This study was designed to determine the heterogeneity and identify the presence of CMSs in a large panel of CRC cell lines, primary cultures and patient-derived xenografts (PDX). We provide a repository encompassing this heterogeneity and moreover describe that a large part of the models can be robustly assigned to one of the four CMSs, independent of the stromal contribution. We subsequently validate our CMS stratification by functional analysis which for instance shows mesenchymal enrichment in CMS4 and metabolic dysregulation in CMS3. Finally, we observe a clear difference in sensitivity to chemotherapy-induced apoptosis, specifically between CMS2 and CMS4. This relates to the in vivo efficacy of chemotherapy, which delays outgrowth of CMS2, but not CMS4 xenografts. Combined our data indicate that molecular subtypes are faithfully modelled in CRC cell cultures and PDXs, representing tumour cell intrinsic and stable features. This repository provides researchers with a platform to study CRC using the existing heterogeneity.

A MicroRNA Signature Associated With Metastasis of T1 Colorectal Tumors to Lymph Nodes

Most T1 colorectal cancers treated by radical surgery canxa0now 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 ofxa0metastasis, to prevent unnecessary radical surgery. Wexa0collected 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 nodexa0metastases with an AUROC value of 0.77. The 5-microRNA therefore identifies high-risk T1 colorectal cancers with axa0greater degree of accuracy than currently used pathologic features.

Genome-wide discovery and identification of a novel miRNA signature for recurrence prediction in stage II and III colorectal cancer

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

Molecular subtyping of colorectal cancer: Recent progress, new challenges and emerging opportunities

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.

A comprehensive methylation signature identifies lymph node metastasis in esophageal squamous cell carcinoma: Epigenetic panel detects metastasis in ESCC

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.

High mRNA expression of splice variant SYK short correlates with hepatic disease progression in chemonaive lymph node negative colon cancer patients

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.