A renaissance for SRC Yeatman, Timothy J
Nature reviews. Cancer,
06/2004, Volume:
4, Issue:
6
Journal Article
Peer reviewed
The c-SRC non-receptor tyrosine kinase is overexpressed and activated in a large number of human malignancies and has been linked to the development of cancer and progression to distant metastases. ...These observations have led to the recent targeting of c-SRC for the development of anticancer therapeutics, which show promise as a new avenue for cancer treatment. Despite this, however, the precise functions of c-SRC in cancer remain unclear. In addition to increasing cell proliferation, a key role of c-SRC in cancer seems to be to promote invasion and motility, functions that might contribute to tumour progression.
Full text
Available for:
DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Colon cancer has been classically described by clinicopathologic features that permit the prediction of outcome only after surgical resection and staging.
We performed an unsupervised analysis of ...microarray data from 326 colon cancers to identify the first principal component (PC1) of the most variable set of genes. PC1 deciphered two primary, intrinsic molecular subtypes of colon cancer that predicted disease progression and recurrence.
Here we report that the most dominant pattern of intrinsic gene expression in colon cancer (PC1) was tightly correlated (Pearson R = 0.92, P < 10(-135)) with the EMT signature-- both in gene identity and directionality. In a global micro-RNA screen, we further identified the most anti-correlated microRNA with PC1 as MiR200, known to regulate EMT.
These data demonstrate that the biology underpinning the native, molecular classification of human colon cancer--previously thought to be highly heterogeneous-- was clarified through the lens of comprehensive transcriptome analysis.
Full text
Available for:
IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
The epithelial-mesenchymal transition (EMT) is a key developmental program that is often activated during cancer progression and may promote resistance to therapy. An analysis of patients (n = 71) ...profiled with both gene expression and a global microRNA assessment (∼ 415 miRs) identified miR-147 as highly anti-correlated with an EMT gene expression signature score and postulated to reverse EMT (MET).
miR-147 was transfected into colon cancer cells (HCT116, SW480) as well as lung cancer cells (A-549). The cells were assessed for morphological changes, and evaluated for effects on invasion, motility, and the expression of key EMT markers. Resistance to chemotherapy was evaluated by treating cells with gefitinib, an EGFR inhibitor. The downstream genes regulated by miR-147 were assayed using the Affymetrix GeneChip U133 Plus2.0 platform. miR-147 was identified to: 1. cause MET primarily by increasing the expression of CDH1 and decreasing that of ZEB1; 2. inhibit the invasion and motility of cells; 3. cause G1 arrest by up-regulating p27 and down-regulating cyclin D1. miR-147 also dramatically reversed the native drug resistance of the colon cancer cell line HCT116 to gefitinib. miR-147 significantly repressed Akt phosphorylation, and knockdown of Akt with siRNA induced MET. The morphologic effects of miR-147 on cells appear to be attenuated by TGF-B1, promoting a plastic and reversible transition between MET and EMT.
miR-147 induced cancer cells to undergo MET and induced cell cycle arrest, suggesting a potential tumor suppressor role. miR-147 strikingly increased the sensitivity to EGFR inhibitor, gefitinib in cell with native resistance. We conclude that miR-147 might have therapeutic potential given its ability to inhibit proliferation, induce MET, as well as reverse drug sensitivity.
Full text
Available for:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Colorectal cancer (CRC) is a highly heterogeneous disease, for which prognosis has been relegated to clinicopathologic staging for decades. There is a need to stratify subpopulations of CRC on a ...molecular basis to better predict outcome and assign therapies. Here we report targeted exome-sequencing of 1,321 cancer-related genes on 468 tumour specimens, which identified a subset of 17 genes that best classify CRC, with APC playing a central role in predicting overall survival. APC may assume 0, 1 or 2 truncating mutations, each with a striking differential impact on survival. Tumours lacking any APC mutation carry a worse prognosis than single APC mutation tumours; however, two APC mutation tumours with mutant KRAS and TP53 confer the poorest survival among all the subgroups examined. Our study demonstrates a prognostic role for APC and suggests that sequencing of APC may have clinical utility in the routine staging and potential therapeutic assignment for CRC.
Abstract
Background
Epithelial-to-mesenchymal transition (EMT) is a process linked to metastasis and drug resistance with non-coding RNAs (ncRNAs) playing pivotal roles. We previously showed that ...miR-100 and miR-125b, embedded within the third intron of the ncRNA host gene
MIR100HG
, confer resistance to cetuximab, an anti-epidermal growth factor receptor (EGFR) monoclonal antibody, in colorectal cancer (CRC). However, whether the MIR100HG transcript itself has a role in cetuximab resistance or EMT is unknown.
Methods
The correlation between MIR100HG and EMT was analyzed by curating public CRC data repositories. The biological roles of MIR100HG in EMT, metastasis and cetuximab resistance in CRC were determined both in vitro and in vivo. The expression patterns of MIR100HG, hnRNPA2B1 and TCF7L2 in CRC specimens from patients who progressed on cetuximab and patients with metastatic disease were analyzed by RNAscope and immunohistochemical staining.
Results
The expression of MIR100HG was strongly correlated with EMT markers and acted as a positive regulator of EMT. MIR100HG sustained cetuximab resistance and facilitated invasion and metastasis in CRC cells both in vitro and in vivo. hnRNPA2B1 was identified as a binding partner of MIR100HG. Mechanistically, MIR100HG maintained mRNA stability of TCF7L2, a major transcriptional coactivator of the Wnt/β-catenin signaling, by interacting with hnRNPA2B1. hnRNPA2B1 recognized the N6-methyladenosine (m
6
A) site of TCF7L2 mRNA in the presence of MIR100HG. TCF7L2, in turn, activated MIR100HG transcription, forming a feed forward regulatory loop. The MIR100HG/hnRNPA2B1/TCF7L2 axis was augmented in specimens from CRC patients who either developed local or distant metastasis or had disease progression that was associated with cetuximab resistance.
Conclusions
MIR100HG and hnRNPA2B1 interact to control the transcriptional activity of Wnt signaling in CRC via regulation of TCF7L2 mRNA stability. Our findings identified MIR100HG as a potent EMT inducer in CRC that may contribute to cetuximab resistance and metastasis by activation of a MIR100HG/hnRNPA2B1/TCF7L2 feedback loop.
Full text
Available for:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
De novo and acquired resistance, which are largely attributed to genetic alterations, are barriers to effective anti-epidermal-growth-factor-receptor (EGFR) therapy. To generate cetuximab-resistant ...cells, we exposed cetuximab-sensitive colorectal cancer cells to cetuximab in three-dimensional culture. Using whole-exome sequencing and transcriptional profiling, we found that the long non-coding RNA MIR100HG and two embedded microRNAs, miR-100 and miR-125b, were overexpressed in the absence of known genetic events linked to cetuximab resistance. MIR100HG, miR-100 and miR-125b overexpression was also observed in cetuximab-resistant colorectal cancer and head and neck squamous cell cancer cell lines and in tumors from colorectal cancer patients that progressed on cetuximab. miR-100 and miR-125b coordinately repressed five Wnt/β-catenin negative regulators, resulting in increased Wnt signaling, and Wnt inhibition in cetuximab-resistant cells restored cetuximab responsiveness. Our results describe a double-negative feedback loop between MIR100HG and the transcription factor GATA6, whereby GATA6 represses MIR100HG, but this repression is relieved by miR-125b targeting of GATA6. These findings identify a clinically actionable, epigenetic cause of cetuximab resistance.
Full text
Available for:
IJS, NUK, SBMB, UL, UM, UPUK
Development of a radiosensitivity predictive assay is a central goal of radiation oncology. We reasoned a gene expression model could be developed to predict intrinsic radiosensitivity and treatment ...response in patients.
Radiosensitivity (determined by survival fraction at 2 Gy) was modeled as a function of gene expression, tissue of origin, ras status (mut/wt), and p53 status (mut/wt) in 48 human cancer cell lines. Ten genes were identified and used to build a rank-based linear regression algorithm to predict an intrinsic radiosensitivity index (RSI, high index = radioresistance). This model was applied to three independent cohorts treated with concurrent chemoradiation: head-and-neck cancer (HNC, n = 92); rectal cancer (n = 14); and esophageal cancer (n = 12).
Predicted RSI was significantly different in responders (R) vs. nonresponders (NR) in the rectal (RSI R vs. NR 0.32 vs. 0.46, p = 0.03), esophageal (RSI R vs. NR 0.37 vs. 0.50, p = 0.05) and combined rectal/esophageal (RSI R vs. NR 0.34 vs. 0.48, p = 0.001511) cohorts. Using a threshold RSI of 0.46, the model has a sensitivity of 80%, specificity of 82%, and positive predictive value of 86%. Finally, we evaluated the model as a prognostic marker in HNC. There was an improved 2-year locoregional control (LRC) in the predicted radiosensitive group (2-year LRC 86% vs. 61%, p = 0.05).
We validate a robust multigene expression model of intrinsic tumor radiosensitivity in three independent cohorts totaling 118 patients. To our knowledge, this is the first time that a systems biology-based radiosensitivity model is validated in multiple independent clinical datasets.
Full text
Available for:
GEOZS, IJS, NUK, OILJ, UL, UM, UPUK
Purpose: Colorectal cancer prognosis is currently predicted from pathologic staging, providing limited discrimination for Dukes stage
B and C disease. Additional markers for outcome are required to ...help guide therapy selection for individual patients.
Experimental Design: A multisite single-platform microarray study was done on 553 colorectal cancers. Gene expression changes were identified
between stage A and D tumors (three training sets) and assessed as a prognosis signature in stage B and C tumors (independent
test and external validation sets).
Results: One hundred twenty-eight genes showed reproducible expression changes between three sets of stage A and D cancers. Using
consistent genes, stage B and C cancers clustered into two groups resembling early-stage and metastatic tumors. A Prediction
Analysis of Microarray algorithm was developed to classify individual intermediate-stage cancers into stage A–like/good prognosis
or stage D–like/poor prognosis types. For stage B patients, the treatment adjusted hazard ratio for 6-year recurrence in individuals
with stage D–like cancers was 10.3 (95% confidence interval, 1.3-80.0; P = 0.011). For stage C patients, the adjusted hazard ratio was 2.9 (95% confidence interval, 1.1-7.6; P = 0.016). Similar results were obtained for an external set of stage B and C patients. The prognosis signature was enriched
for downregulated immune response genes and upregulated cell signaling and extracellular matrix genes. Accordingly, sparse
tumor infiltration with mononuclear chronic inflammatory cells was associated with poor outcome in independent patients.
Conclusions: Metastasis-associated gene expression changes can be used to refine traditional outcome prediction, providing a rational
approach for tailoring treatments to subsets of patients. (Clin Cancer Res 2009;15(24):7642–51)
Background & aims Staging inadequately predicts metastatic risk in patients with colon cancer. We used a gene expression profile derived from invasive, murine colon cancer cells that were highly ...metastatic in an immunocompetent mouse model to identify patients with colon cancer at risk of recurrence. Methods This phase 1, exploratory biomarker study used 55 patients with colorectal cancer from Vanderbilt Medical Center (VMC) as the training dataset and 177 patients from the Moffitt Cancer Center as the independent dataset. The metastasis-associated gene expression profile developed from the mouse model was refined with comparative functional genomics in the VMC gene expression profiles to identify a 34-gene classifier associated with high risk of metastasis and death from colon cancer. A metastasis score derived from the biologically based classifier was tested in the Moffitt dataset. Results A high score was significantly associated with increased risk of metastasis and death from colon cancer across all pathologic stages and specifically in stage II and stage III patients. The metastasis score was shown to independently predict risk of cancer recurrence and death in univariate and multivariate models. For example, among stage III patients, a high score translated to increased relative risk of cancer recurrence (hazard ratio, 4.7; 95% confidence interval, 1.566–14.05). Furthermore, the metastasis score identified patients with stage III disease whose 5-year recurrence-free survival was >88% and for whom adjuvant chemotherapy did not increase survival time. Conclusion A gene expression profile identified from an experimental model of colon cancer metastasis predicted cancer recurrence and death, independently of conventional measures, in patients with colon cancer.
In the Circulating Cell-free Genome Atlas (NCT02889978) substudy 1, we evaluate several approaches for a circulating cell-free DNA (cfDNA)-based multi-cancer early detection (MCED) test by defining ...clinical limit of detection (LOD) based on circulating tumor allele fraction (cTAF), enabling performance comparisons. Among 10 machine-learning classifiers trained on the same samples and independently validated, when evaluated at 98% specificity, those using whole-genome (WG) methylation, single nucleotide variants with paired white blood cell background removal, and combined scores from classifiers evaluated in this study show the highest cancer signal detection sensitivities. Compared with clinical stage and tumor type, cTAF is a more significant predictor of classifier performance and may more closely reflect tumor biology. Clinical LODs mirror relative sensitivities for all approaches. The WG methylation feature best predicts cancer signal origin. WG methylation is the most promising technology for MCED and informs development of a targeted methylation MCED test.
Display omitted
•Clinical LOD is a useful benchmark to assess cfDNA-based test performance•cTAF accounts for cfDNA cancer signal variation across cancer types and stages•cfDNA methylation was the most promising genomic feature for cancer signal detection•The results informed the development of a cfDNA-based multi-cancer early detection test
Jamshidi et al. compare several approaches for circulating cell-free DNA (cfDNA)-based multi-cancer early detection (MCED) tests. A whole-genome methylation-based approach has the best performance among those evaluated. In addition, they define a metric—clinical limit of detection (LOD)—based on tumor fraction to enable future comparison of cfDNA-based tests.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
PDF
