Marc A. Attiyeh

Limited heterogeneity of known driver gene mutations among the metastases of individual patients with pancreatic cancer

The extent of heterogeneity among driver gene mutations present in naturally occurring metastases—that is, treatment-naive metastatic disease—is largely unknown. To address this issue, we carried out 60× whole-genome sequencing of 26 metastases from four patients with pancreatic cancer. We found that identical mutations in known driver genes were present in every metastatic lesion for each patient studied. Passenger gene mutations, which do not have known or predicted functional consequences, accounted for all intratumoral heterogeneity. Even with respect to these passenger mutations, our analysis suggests that the genetic similarity among the founding cells of metastases was higher than that expected for any two cells randomly taken from a normal tissue. The uniformity of known driver gene mutations among metastases in the same patient has critical and encouraging implications for the success of future targeted therapies in advanced-stage disease.

Development and Validation of a Multi-Institutional Preoperative Nomogram for Predicting Grade of Dysplasia in Intraductal Papillary Mucinous Neoplasms (IPMNs) of the Pancreas: A Report from The Pancreatic Surgery Consortium.

Objective: Previous nomogram models for patients undergoing resection of intraductal papillary mucinous neoplasms (IPMNs) have been relatively small single-institutional series. Our objective was to improve upon these studies by developing and independently validating a new model using a large multiinstitutional dataset. Summary Background Data: IPMNs represent the most common radiographically identifiable precursor lesions of pancreatic cancer. They are a heterogenous group of neoplasms in which more accurate markers of high-grade dysplasia or early invasive carcinoma could help avoid unnecessary surgery in 1 case and support potentially curative intervention (resection) in another. Methods: Prospectively maintained databases from 3 institutions were queried for patients who had undergone resection of IPMNs between 2005 and 2015. Patients were separated into main duct [main and mixed-type (MD)] and branch duct (BD) types based on preoperative imaging. Logistic regression modeling was used on a training subset to develop 2 independent nomograms (MD and BD) to predict low-risk (low- or intermediate-grade dysplasia) or high-risk (high-grade dysplasia or invasive carcinoma) disease. Model performance was then evaluated using an independent validation set. Results: We identified 1028 patients who underwent resection for IPMNs [MD: n = 454 (44%), BD: n = 574 (56%)] during the 10-year study period. High-risk disease was present in 487 patients (47%). Patients with high-risk disease comprised 71% and 29% of MD and BD groups, respectively (P <0.0001). MD and BD nomograms were developed on the training set [70% of total (n = 720); MD: n = 318, BD: n = 402] and validated on the test set [30% (n = 308); MD: n = 136, BD: n = 172]. The presence of jaundice was almost exclusively associated with high-risk disease (57 of 58 patients, 98%). Cyst size >3.0 cm, solid component/mural nodule, pain symptoms, and weight loss were significantly associated with high-risk disease. C-indices were 0.82 and 0.81 on training and independent validation sets, respectively; Brier scores were 0.173 and 0.175, respectively. Conclusions: For patients with suspected IPMNs, we present an independently validated model for the prediction of high-risk disease.

Melanoma genome evolution across species

BackgroundCancer genomes evolve in both space and time, which contributes to the genetic heterogeneity that underlies tumor progression and drug resistance. In human melanoma, identifying mechanistically important events in tumor evolution is hampered due to the high background mutation rate from ultraviolet (UV) light. Cross-species oncogenomics is a powerful tool for identifying these core events, in which transgenically well-defined animal models of cancer are compared to human cancers to identify key conserved alterations.ResultsWe use a zebrafish model of tumor progression and drug resistance for cross-species genomic analysis in melanoma. Zebrafish transgenic tumors are initiated with just 2 genetic lesions, BRAFV600E and p53-/-, yet take 4–6 months to appear, at which time whole genome sequencing demonstrated >3,000 new mutations. An additional 4-month exposure to the BRAF inhibitor vemurafenib resulted in a highly drug resistant tumor that showed 3 additional new DNA mutations in the genes BUB1B, PINK1, and COL16A1. These genetic changes in drug resistance are accompanied by a massive reorganization of the transcriptome, with differential RNA expression of over 800 genes, centered on alterations in cAMP and PKA signaling. By comparing both the DNA and mRNA changes to a large panel of human melanomas, we find that there is a highly significant enrichment of these alterations in human patients with vemurafenib resistant disease.ConclusionsOur results suggest that targeting of alterations that are conserved between zebrafish and humans may offer new avenues for therapeutic intervention. The approaches described here will be broadly applicable to the diverse array of cancer models available in the zebrafish, which can be used to inform human cancer genomics.

Should Patients With Cystic Lesions of the Pancreas Undergo Long-term Radiographic Surveillance?: Results of 3024 Patients Evaluated at a Single Institution.

Objective: In 2015, the American Gastroenterological Association recommended the discontinuation of radiographic surveillance after 5 years for patients with stable pancreatic cysts. The current study evaluated the yield of continued surveillance of pancreatic cysts up to and after 5 years of follow up. Methods: A prospectively maintained registry of patients evaluated for pancreatic cysts was queried (1995–2016). Patients who initially underwent radiographic surveillance were divided into those with <5 years and ≥5 years of follow up. Analyses for the presence of cyst growth (>5 mm increase in diameter), cross-over to resection, and development of carcinoma were performed. Results: A total of 3024 patients were identified, with 2472 (82%) undergoing initial surveillance. The ≥5 year group (n = 596) experienced a greater frequency of cyst growth (44% vs. 20%; P < 0.0001), a lower rate of cross-over to resection (8% vs 11%; P = 0.02), and a similar frequency of progression to carcinoma (2% vs 3%; P = 0.07) compared with the <5 year group (n = 1876). Within the ≥5 year group, 412 patients (69%) had demonstrated radiographic stability at the 5-year time point. This subgroup, when compared with the <5 year group, experienced similar rates of cyst growth (19% vs. 20%; P= 0.95) and lower rates of cross-over to resection (5% vs 11%; P< 0.0001) and development of carcinoma (1% vs 3%; P= 0.008). The observed rate of developing cancer in the group that was stable at the 5-year time point was 31.3 per 100,000 per year, whereas the expected national age-adjusted incidence rate for this same group was 7.04 per 100,000 per year. Conclusion: Cyst size stability at the 5-year time point did not preclude future growth, cross-over to resection, or carcinoma development. Patients who were stable at 5 years had a nearly 3-fold higher risk of developing cancer compared with the general population and should continue long-term surveillance.

Quantification of CT images for the classification of high- and low-risk pancreatic cysts

Pancreatic cancer is the most lethal cancer with an overall 5-year survival rate of 7%1 due to the late stage at diagnosis and the ineffectiveness of current therapeutic strategies. Given the poor prognosis, early detection at a pre-cancerous stage is the best tool for preventing this disease. Intraductal papillary mucinous neoplasms (IPMN), cystic tumors of the pancreas, represent the only radiographically identifiable precursor lesion of pancreatic cancer and are known to evolve stepwise from low-to-high-grade dysplasia before progressing into an invasive carcinoma. Observation is usually recommended for low-risk (low- and intermediate-grade dysplasia) patients, while high-risk (high-grade dysplasia and invasive carcinoma) patients undergo resection; hence, patient selection is critically important in the management of pancreatic cysts.2 Radiologists use standard criteria such as main pancreatic duct size, cyst size, or presence of a solid enhancing component in the cyst to optimally select patients for surgery.3 However, these findings are subject to a radiologist’s interpretation and have been shown to be inconsistent with regards to the presence of a mural nodule or solid component.4 We propose objective classification of risk groups based on quantitative imaging features extracted from CT scans. We apply new features that represent the solid component (i.e. areas of high intensity) within the cyst and extract standard texture features. An adaptive boost classifier5 achieves the best performance with area under receiver operating characteristic curve (AUC) of 0.73 and accuracy of 77.3% for texture features. The random forest classifier achieves the best performance with AUC of 0.71 and accuracy of 70.8% with the solid component features.

Local recurrences at the anastomotic area are clonally related to the primary tumor in sporadic colorectal carcinoma

Purpose Anastomotic recurrences (AR) occur in 2–10% of colorectal carcinoma cases after resection of primary tumor (PT). Currently, there are no molecular data investigating their genetic profile and multiple theories exist about their pathogenesis. The aim of our study was to compare the genomic profile of AR to that of the patients’ corresponding matched PT and, when available, to a distant metastasis (DM). Experimental Design Thirty-six tumors from 14 patients were genotyped using a capture-based, next-generation assay to define the mutational status of 341 cancer-associated genes. All patients had R0 resection of their PT and AR occurred 1.1−7.0 years following PT resection. A DM or a second AR was analyzed in 8 patients. All tumors were microsatellite stable except in one patient with Lynch syndrome. Results A total of 254 somatic mutations were detected including 138 mutations in the microsatellite stable (MSS) cases. The most commonly mutated genes were APC, KRAS, TP53, PIK3CA, ATM and PIK3R1. In all patients with MSS tumors the AR and PT shared between 50−100% of mutations, including mutations in key driver genes, consistent with these tumors being clonally related. Genetic events private to DM were not detected in AR and phylogenetic analysis showed that ARs were more closely related to PT than DM. In the Lynch syndrome patient the PT and AR showed distinct somatic mutations consistent with independent primaries. Conclusions ARs are clonally related to PT in sporadic colorectal carcinomas and do not appear to represent seeding of the anastomotic site by distant metastases.

An Unusual Genomic Variant of Pancreatic Ductal Adenocarcinoma with an Indolent Clinical Course

We describe an 85-yr-old male of Ashkenazi Jewish descent with biopsy-proven locally advanced pancreatic ductal adenocarcinoma (PDA). The patient underwent a modified course of gemcitabine and stereotactic body radiation therapy and survived for 42 mo with a stable pancreatic head mass and no evidence of metastatic disease before death due to complications from a stroke. Whole-exome sequencing of his tumor revealed a simple genome landscape with no evidence of mutations, copy-number changes, or structural alterations in genes most commonly associated with PDA (i.e., KRAS, CDKN2A, TP53, or SMAD4). An analysis of his germline DNA revealed no pathogenic variants of significance. Whole-exome and whole-genome sequencing identified a somatic mutation of RNF213 and an inversion/deletion of CTNNA2 as the genetic basis of his PDA. Although PDA is classically characterized by a predictable set of mutations, these data suggest that alternate genetic paths to PDA may exist, which can be associated with a more indolent clinical course.

Minimal functional driver gene heterogeneity among untreated metastases

Metastatic drivers same as primary Treatment decisions for cancer patients are increasingly guided by analysis of the gene mutations that drive primary tumor growth. Relatively little is known about driver gene mutations in metastases, which cause most cancer-related deaths. Reiter et al. explored whether the growth of different metastatic lesions within an individual patient is fueled by the same or distinct gene mutations. In a study of 76 untreated metastases from 20 patients with different types of cancer, all metastases within a patient shared the same functional driver gene mutations. Thus, analysis of a single biopsy could help oncologists select the optimal therapy for patients with widespread metastatic disease. Science, this issue p. 1033 The growth of different metastatic lesions within an individual cancer patient is fueled by the same genetic mutations. Metastases are responsible for the majority of cancer-related deaths. Although genomic heterogeneity within primary tumors is associated with relapse, heterogeneity among treatment-naïve metastases has not been comprehensively assessed. We analyzed sequencing data for 76 untreated metastases from 20 patients and inferred cancer phylogenies for breast, colorectal, endometrial, gastric, lung, melanoma, pancreatic, and prostate cancers. We found that within individual patients, a large majority of driver gene mutations are common to all metastases. Further analysis revealed that the driver gene mutations that were not shared by all metastases are unlikely to have functional consequences. A mathematical model of tumor evolution and metastasis formation provides an explanation for the observed driver gene homogeneity. Thus, single biopsies capture most of the functionally important mutations in metastases and therefore provide essential information for therapeutic decision-making.

Precancerous neoplastic cells can move through the pancreatic ductal system

Most adult carcinomas develop from noninvasive precursor lesions, a progression that is supported by genetic analysis. However, the evolutionary and genetic relationships among co-existing lesions are unclear. Here we analysed the somatic variants of pancreatic cancers and precursor lesions sampled from distinct regions of the same pancreas. After inferring evolutionary relationships, we found that the ancestral cell had initiated and clonally expanded to form one or more lesions, and that subsequent driver gene mutations eventually led to invasive pancreatic cancer. We estimate that this multi-step progression generally spans many years. These new data reframe the step-wise progression model of pancreatic cancer by illustrating that independent, high-grade pancreatic precursor lesions observed in a single pancreas often represent a single neoplasm that has colonized the ductal system, accumulating spatial and genetic divergence over time.Comparison of multiple lesions from individual pancreases sheds light on how ancestral clones can spread through the ductal system and give rise to precursor lesions, with acquisition of further mutations leading to pancreatic cancer.

Preoperative risk prediction for intraductal papillary mucinous neoplasms by quantitative CT image analysis

BACKGROUND Intraductal papillary mucinous neoplasms (IPMNs) are radiographically identifiable potential precursor lesions of pancreatic adenocarcinoma. While resection is recommended when main duct dilation is present, management of branch duct IPMN (BD-IPMN) remains controversial. This study sought to evaluate whether preoperative quantitative imaging features of BD-IPMNs could distinguish low-risk disease (low- and intermediate-grade dysplasia) from high-risk disease (high-grade dysplasia and invasive carcinoma). METHODS Patients who underwent resection between 2005 and 2015 with pathologically proven BD-IPMN and a preoperative CT scan were included in the study. Quantitative image features were extracted using texture analysis and a novel quantitative mural nodularity feature developed for the study. Significant features on univariate analysis were combined with clinical variables to build a multivariate prediction model. RESULTS Within the study group of 103 patients, 76 (74%) had low-risk disease and 27 (26%) had high-risk disease. Quantitative imaging features were prognostic of low-vs. high-risk disease. The model based only on clinical variables achieved an AUC of 0.67 and 0.79 with the addition of quantitative imaging features. CONCLUSION Quantitative image analysis of BD-IPMNs is a novel method that may enable risk stratification. External validation may provide a reliable non-invasive prognostic tool for clinicians.