SEEK and you may find cancer earlier: Many cancers can be cured by surgery and/or systemic therapies when detected before they have metastasized. This clinical reality, coupled with the growing appreciation that cancer's rapid genetic evolution limits its response to drugs, have fueled interest in methodologies for earlier detection of the disease. Cohen et al. developed a noninvasive blood test, called CancerSEEK that can detect eight common human cancer types (see the Perspective by Kalinich and Haber). The test assesses eight circulating protein biomarkers and tumor-specific mutations in circulating DNA. In a study of 1000 patients previously diagnosed with cancer and 850 healthy control individuals, CancerSEEK detected cancer with a sensitivity of 69 to 98% (depending on cancer type) and 99% specificity. Science , this issue p. 926 ; see also p. 866

Purpose: Serum–biomarker based screening for pancreatic cancer could greatly improve survival in appropriately targeted high-risk populations. Experimental Design: Eighty-three circulating proteins were analyzed in sera of patients diagnosed with pancreatic ductal adenocarcinoma (PDAC, n = 333), benign pancreatic conditions (n = 144), and healthy control individuals (n = 227). Samples from each group were split randomly into training and blinded validation sets prior to analysis. A Metropolis algorithm with Monte Carlo simulation (MMC) was used to identify discriminatory biomarker panels in the training set. Identified panels were evaluated in the validation set and in patients diagnosed with colon (n = 33), lung (n = 62), and breast (n = 108) cancers. Results: Several robust profiles of protein alterations were present in sera of PDAC patients compared to the Healthy and Benign groups. In the training set (n = 160 PDAC, 74 Benign, 107 Healthy), the panel of CA 19–9, ICAM-1, and OPG discriminated PDAC patients from Healthy controls with a sensitivity/specificity (SN/SP) of 88/90%, while the panel of CA 19–9, CEA, and TIMP-1 discriminated PDAC patients from Benign subjects with an SN/SP of 76/90%. In an independent validation set (n = 173 PDAC, 70 Benign, 120 Healthy), the panel of CA 19–9, ICAM-1 and OPG demonstrated an SN/SP of 78/94% while the panel of CA19–9, CEA, and TIMP-1 demonstrated an SN/SP of 71/89%. The CA19–9, ICAM-1, OPG panel is selective for PDAC and does not recognize breast (SP = 100%), lung (SP = 97%), or colon (SP = 97%) cancer. Conclusions: The PDAC-specific biomarker panels identified in this investigation warrant additional clinical validation to determine their role in screening targeted high-risk populations. Clin Cancer Res; 17(4); 805–16. ©2010 AACR.

Molecular and clinical markers outperform current clinical and imaging criteria for the diagnosis and management of patients with pancreatic cysts.

Ets. METHODS: The expression of MUC5AC in benign pancreatic pathologies, PC precursor lesions, primary PC tissues and metastatic lesions was evaluated by immunohistochemistry. Circulating MUC5AC levels were measured using sandwich ELISA assay developed in-house, and CA19-9 was measured using radioimmunoassay. A combined training set (n=346) was used to evaluate the diagnostic (n=241) and predictive (n=105, total samples 201 from pre- and post-surgical and chemotherapy set) significance of MUC5AC. Results were further validated with a pre-defined cut-off value using independent sets from the Mayo Clinic (n=94) and the University of Pittsburgh Medical Center (n=321). RESULTS: Tissue expression analyses indicated thede novoexpression of MUC5AC in pancreatic intraepithelial precursor lesions 1A (PanIN1A); the expression was maintained through all stages of progression to invasive adenocarcinoma. The median circulating MUC5AC levels in patients with resectable early-stage PC (EPC) (stage 1/2; 67.2 ng/ml, IQR: 23.9–382.1) and unresectable late-stage PC (LPC) (stage 3/4; 389.7 ng/ml, IQR: 87.7–948.6) were significantly higher compared with (P-value ≤0.0001) benign controls (BC) (7.2 ng/ml, IQR: 0.4–26.5) and (P-value ≤0.0001) chronic pancreatitis (CP) controls (8.4 ng/ml, IQR: 1.5–19.2). In the diagnostic training set (n=241), MUC5AC efficiently differentiated EPC from healthy controls (HC) (83%/80% sensitive (SN)/specific (SP)), BC (67%/87% SN/SP), and CP (83%/77% SN/SP). Independent validation sets from the Mayo Clinic and UPMC confirmed the diagnostic potential of MUC5AC to differentiate EPC from BC (68%/73%; 65%/83%) and CP (68%/79%; 65%/72%). Furthermore, MUC5AC and CA19-9 combination significantly improved (p-value < 0.001) the diagnostic accuracy for differentiating resectable cases from controls. CONCLUSIONS: MUC5AC is a valuable diagnostic biomarker, either alone or in combination with CA19-9, to differentiate PC from CP and benign controls....

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.

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy characterized by extensive local invasion and systemic spread. In this study, we employed a three-dimensional organoid model of human pancreatic cancer to characterize the molecular alterations critical for invasion. Time-lapse microscopy was used to observe invasion in organoids from 25 surgically resected human PDAC samples in collagen I. Subsequent lentiviral modification and small-molecule inhibitors were used to investigate the molecular programs underlying invasion in PDAC organoids. When cultured in collagen I, PDAC organoids exhibited two distinct, morphologically defined invasive phenotypes, mesenchymal and collective. Each individual PDAC gave rise to organoids with a predominant phenotype, and PDAC that generated organoids with predominantly mesenchymal invasion showed a worse prognosis. Collective invasion predominated in organoids from cancers with somatic mutations in the driver gene SMAD4 (or its signaling partner TGFBR2). Reexpression of SMAD4 abrogated the collective invasion phenotype in SMAD4-mutant PDAC organoids, indicating that SMAD4 loss is required for collective invasion in PDAC organoids. Surprisingly, invasion in passaged SMAD4-mutant PDAC organoids required exogenous TGFβ, suggesting that invasion in SMAD4-mutant organoids is mediated through noncanonical TGFβ signaling. The Rho-like GTPases RAC1 and CDC42 acted as potential mediators of TGFβ-stimulated invasion in SMAD4-mutant PDAC organoids, as inhibition of these GTPases suppressed collective invasion in our model. These data suggest that PDAC utilizes different invasion programs depending on SMAD4 status, with collective invasion uniquely present in PDAC with SMAD4 loss. Significance: Organoid models of PDAC highlight the importance of SMAD4 loss in invasion, demonstrating that invasion programs in SMAD4-mutant and SMAD4 wild-type tumors are different in both morphology and molecular mechanism.