Extent of resection affects prognosis for patients with glioblastoma in non-eloquent regions.

Glioblastoma (GBM) is a malignant cerebral neoplasm carrying poor prognosis. The importance of extent of resection (EoR) in GBM patient outcomes has been argued in the literature. Previous studies included tumors in eloquent regions of the brain. This confounds the role of EoR by including patients with intrinsically worse outcomes but will be over-represented in the reduced EoR category. In a homogenous group of patients in whom GTR was considered achievable, we investigated the effect of increasing EoR on survival. A retrospective review of 51 patients was undertaken. Quantitative, volumetric analysis of pre-operative and post-operative magnetic resonance image was compared with corresponding clinical details. The primary outcome measured was post-operative overall survival. Median overall survival was 18.3 months for GTR patients compared to 11.6 months for non-GTR (p = 0.025). Median pre-operative contrast-enhancing tumor volume for GTR patients was 54.7 cm3 and 24.9 cm3 for non-GTR. Post-operative median residual tumor volume was 1.1 cm3 in the non-GTR cohort. In multivariate analyses, GTR (HR [95% CI] = 0.973 [0.954-0.994], p = 0.00559) and increasing EoR (HR [95% CI] = 0.964 [0.944-0.985], p = 0.000665) remained predictors of survival. Centile dichotomization of EoR revealed 74% (HR [95% CI] = 0.351 [0.128-0.958], p = 0.0409) as the lowest threshold conferring statistically significant survival benefit. Where technically feasible, both GTR and EoR remained as independent prognostic factors for survival. GTR remains the gold standard for surgical treatment of GBM in patients, 74% being the minimum EoR required to confer survival benefit.

Quantitative Clinical Imaging Methods for Monitoring Intratumoral Evolution.

Solid tumors are multiscale, open, complex, dynamic systems: complex because they have many interacting components, dynamic because both the components and their interactions can change with time, and open because the tumor freely communicates with surrounding and even distant host tissue. Thus, it is not surprising that striking intratumoral variations are commonly observed in clinical imaging such as MRI and CT and that several recent studies found striking regional variations in the molecular properties of cancer cells from the same tumor. Interestingly, this spatial heterogeneity in molecular properties of tumor cells is typically ascribed to branching clonal evolution due to accumulating mutations while macroscopic variations observed in, for example, clinical MRI scans are usually viewed as functions of blood flow. The clinical significance of spatial heterogeneity has not been fully determined but there is a general consensus that the varying intratumoral landscape along with patient factors such as age, morbidity and lifestyle, contributes significantly to the often unpredictable response of individual patients within a disease cohort treated with the same standard-of-care therapy.Here we investigate the potential link between macroscopic tumor heterogeneity observed by clinical imaging and spatial variations in the observed molecular properties of cancer cells. We build on techniques developed in landscape ecology to link regional variations in the distribution of species with local environmental conditions that define their habitat. That is, we view each region of the tumor as a local ecosystem consisting of environmental conditions such as access to nutrients, oxygen, and means of waste clearance related to blood flow and the local population of tumor cells that both adapt to these conditions and, to some extent, change them through, for example, production of angiogenic factors. Furthermore, interactions among neighboring habitats can produce broader regional dynamics so that the internal diversity of tumors is the net result of complex multiscale somatic Darwinian interactions.Methods in landscape ecology harness Darwinian dynamics to link the environmental properties of a given region to the local populations which are assumed to represent maximally fit phenotypes within those conditions. Consider a common task of a landscape ecologist: defining the spatial distribution of species in a large region, e.g., in a satellite image. Clearly the most accurate approach requires a meter by meter survey of the multiple square kilometers in the region of interest. However, this is both impractical and potentially destructive. Instead, landscape ecology breaks the task into component parts relying on the Darwinian interdependence of environmental properties and fitness of specific species' phenotypic and genotypic properties. First, the satellite map is carefully analyzed to define the number and distribution of habitats. Then the species distribution in a representative sampling of each habitat is empirically determined. Ultimately, this permits sufficient bridging of spatial scales to accurately predict spatial distribution of plant and animal species within large regions.Currently, identifying intratumoral subpopulations requires detailed histological and molecular studies that are expensive and time consuming. Furthermore, this method is subject to sampling bias, is invasive for vital organs such as the brain, and inherently destructive precluding repeated assessments for monitoring post-treatment response and proteogenomic evolution. In contrast, modern cross-sectional imaging can interrogate the entire tumor noninvasively, allowing repeated analysis without disrupting the region of interest. In particular, magnetic resonance imaging (MRI) provides exceptional spatial resolution and generates signals that are unique to the molecular constituents of tissue. Here we propose that MRI scans may be the equivalent of satellite images in landscape ecology and, with appropriate application of Darwinian first principles and sophisticated image analytic methods, can be used to estimate regional variations in the molecular properties of cancer cells.We have initially examined this technique in glioblastoma, a malignant brain neoplasm which is morphologically complex and notorious for a fast progression from diagnosis to recurrence and death, making a suitable subject of noninvasive, rapidly repeated assessment of intratumoral evolution. Quantitative imaging analysis of routine clinical MRIs from glioblastoma has identified macroscopic morphologic characteristics which correlate with proteogenomics and prognosis. The key to the accurate detection and forecasting of intratumoral evolution using quantitative imaging analysis is likely to be in the understanding of the synergistic interactions between observable intratumoral subregions and the resulting tumor behavior.

Microsatellite instability status in gastric cancer: a reappraisal of its clinical significance and relationship with mucin phenotypes.

BACKGROUND: Gastric cancers with microsatellite instabilities (MSI) have been reported to be associated with favorable prognosis. However, the significance of the effect of MSI on the clinicopathological features, as well as its association with mucin phenotype, remains unclear. METHODS: MSI status was assessed in 414 cases of gastric cancer using polymerase chain reaction analysis of five microsatellite loci, as recommended by National Cancer Institution criteria. The expression of mucins (MUC5AC, MUC6, MUC2, and CD10) was assessed. RESULTS: Out of 414 total cases of gastric cancer, 380 (91.7%), 11 (2.7%), and 23 (5.6%) were microsatellite stable (MSS), low-level MSI (MSI-L), and high-level MSI (MSI-H), respectively. Compared to MSS/MSI-L, MSI-H gastric cancers were associated with older age (p=0.010), tumor size (p=0.014), excavated gross (p=0.042), intestinal type (p=0.028), aggressive behaviors (increase of T stage [p=0.009]), perineural invasion [p=0.022], and lymphovascular emboli [p=0.027]). MSI-H gastric cancers were associated with tumor necrosis (p=0.041), tumor-infiltrating lymphocytes (≥2/high power field, p<0.001), expanding growth patterns (p=0.038), gastric predominant mucin phenotypes (p=0.028), and MUC6 expression (p=0.016). Tumor necrosis (≥10% of mass, p=0.031), tumor-infiltrating lymphocytes (p<0.001), intestinal type (p=0.014), and gastric mucin phenotypes (p=0.020) could represent independent features associated with MSI-H gastric cancers. MSI-H intestinal type gastric cancers had a tendency for poor prognosis in univariate analysis (p=0.054) but no association in Cox multivariate analysis (p=0.197). CONCLUSIONS: Our data suggest that MSI-H gastric cancers exhibit distinct aggressive biologic behaviors and a gastric mucin phenotype. This contradicts previous reports that describe MSI-H gastric cancer as being associated with favorable prognosis.

Primary leiomyosarcoma of gallbladder.

Malignant mesenchymalneoplasms of the gallbladder are extremely rare with only 105 cases of primary gallbladder sarcoma having been described. It has a very aggressive behavior and is usually diagnosed at advanced stages. Therefore, curative surgical management may not be possible. We performed a radical cholecystectomy (S4b + S5 segmentectomy), omentectomy and small bowel resection in a 54-year-old patient with locally invasive leiomyosarcoma of the gallbladder. Further studies are needed to confirm the benefit of aggressive treatment for patients with leiomyosarcoma of the gallbladder.

Primary squamous cell carcinoma of the liver initially presenting with pseudoachalasia.

Pseudoachalasia secondary to primary squamous cell carcinoma (SCC) of the liver is extremely rare and has not been reported until now. Here, we report a unique case of primary SCC of the liver initially presenting with progressive dysphagia along with short periods of significant weight loss. A 58-year-old man initially presented with progressive dysphagia along with significant weight loss over brief periods of time. The radiographic and manometric findings were consistent with achalasia. Subsequent esophagogastroduodenoscopy revealed a moderately dilated esophagus without evidence of neoplasm or organic obstruction. However, firm resistance was encountered while traversing the esophagogastric junction (EGJ), although no mucosal lesion was identified. Due to the clinical suspicion of the presence of a malignant tumor, endoscopic ultrasonography (EUS) and computed tomography scans of the chest and abdomen were obtained. A huge hepatic mass with irregular margins extending to the EGJ was found. EUS-guided fine-needle aspiration was performed, and the mass was diagnosed as a primary SCC of the liver by immunohistochemical staining.