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Purpose: We performed an integrated analysis of molecular classification systems proposed by The Cancer Genome Atlas (TCGA), the Asian Cancer Research Group (ACRG) and the Tumour Microenvironment Score (TME) to identify which classification scheme(s) are most promising to pursue in subsequent translational investigations., Experimental Design: Supervised machine learning classifiers were created using 10-fold nested cross-validation for TCGA, ACRG and TME subtypes and applied to 2,202 gastric cancer patients from 11 separate publicly available datasets. Overall survival was assessed with a multivariable Cox proportional hazards model. A propensity score matched analysis was performed to evaluate the subgroup effect of adjuvant chemotherapy on molecular subtypes. A public external cohort comprised of metastatic gastric cancer treated with immunotherapy was used to externally validate the molecular subtypes., Results: Classification models for TCGA, ACRG and TME achieved an accuracy ± standard deviation of 89.5% ± 0.04, 84.7% ± 0.04 and 89.3% ± 0.02, respectively. We identified the TME score as the only significantly prognostic classification system (HR 0.54 [95% CI 0.39, 0.74], global Wald test p<0.001). In our subgroup analysis, patients who received adjuvant chemotherapy achieved greater survival with increasing TME score (HR 0.47 [95% CI 0.29, 0.74], interaction p<0.05). The combination of TME High and microsatellite instability (MSI) scores significantly outperformed MSI as a univariable predictor of immunotherapy response., Conclusions: We conclude that the Tumour Microenvironment Score is a predominate driver of prognosis as well as chemotherapy and immunotherapy-related outcomes in gastric cancer. This paper provides a foundation for additional analyses and translational work.

Background: Cross-platform normalization seeks to minimize technological bias between microarray and RNAseq whole-transcriptome data. Incorporating multiple gene expression platforms permits external validation of experimental findings, and augments training sets for machine learning models. Here, we compare the performance of Feature Specific Quantile Normalization (FSQN) to a previously used but unvalidated and uncharacterized method we label as Feature Specific Mean Variance Normalization (FSMVN). We evaluate the performance of these methods for bidirectional normalization in the context of nested feature selection., Results: FSQN and FSMVN provided clinically equivalent bidirectional model performance with and without feature selection for colon CMS and breast PAM50 classification. Using principal component analysis, we determine that these methods eliminate batch effects related to technological platforms. Without feature selection, no statistical difference was identified between the performance of FSQN and FSMVN of cross-platform data compared to within-platform distributions. Under optimal feature selection conditions, balanced accuracy was FSQN and FSMVN were statistically equivalent to the within-platform distribution performance in multivariable linear regression analysis. FSQN and FSMVN also provided similar performance to within-platform distributions as the number of selected genes used to create models decreases., Conclusions: In the context of generating supervised machine learning classifiers for molecular subtypes, FSQN and FSMVN are equally effective. Under optimal modeling conditions, FSQN and FSMVN provide equivalent model accuracy performance on cross-platform normalization data compared to within-platform data. Using cross-platform data should still be approached with caution as subtle performance differences may exist depending on the classification problem, training, and testing distributions., (© 2024. The Author(s).)

Recent advances in our understanding of gastric cancer biology have prompted a shift towards more personalized therapy. However, results are based on population-based survival analyses, which evaluate the average survival effects of entire treatment groups or single prognostic variables. This study uses a personalized survival modelling approach called individual survival distributions (ISDs) with the multi-task logistic regression (MTLR) model to provide novel insight into personalized survival in gastric adenocarcinoma. We performed a pooled analysis using 1043 patients from a previously characterized database annotated with molecular subtypes from the Cancer Genome Atlas, Asian Cancer Research Group, and tumour microenvironment (TME) score. The MTLR model achieved a 5-fold cross-validated concordance index of 72.1 ± 3.3%. This model found that the TME score and chemotherapy had similar survival effects over the entire study time. The TME score provided the greatest survival benefit beyond a 5-year follow-up. Stage III and Stage IV disease contributed the greatest negative effect on survival. The MTLR model weights were significantly correlated with the Cox model coefficients (Pearson coefficient = 0.86, p < 0.0001). We illustrate how ISDs can accurately predict the survival time for each patient, which is especially relevant in cases of molecular subtype heterogeneity. This study provides evidence that the TME score is principally associated with long-term survival in gastric adenocarcinoma. Additional external validation and investigation into the clinical utility of this ISD model in gastric cancer is an area of future research.

An inadequate supply of fresh tissue is a major limitation of three-dimensional patient-derived gastric organoid research. We propose that tissue procurement for organoid culture could be increased by developing a cold storage shipment protocol for fresh surgical tissues. Sixty stomach specimens from C57BL/6J mice were resected, of which forty-five were stored in Hank's Balanced Salt (HBSS), University of Wisconsin (UW), or Histidine-Tryptophan-Ketoglutarate (HTK) solutions for subsequent organoid culture. Stomachs were dissociated and processed into gastric organoids as fresh tissue or after transport at 4 °C for 24 or 48 h. All gastric organoid cultures were established and maintained for 10 passages. Cold storage for 24 or 48 h did not significantly affect organoid viability. Although cold storage was associated with decreased organoid growth rate, there were no differences in viability, cytotoxic dose response, or LGR5 and TROY stem cell gene expression compared to organoids prepared from fresh tissue. As a proof of concept, six human gastric cancer organoids were established after 24 or 48 h of storage. Patient-derived gastric organoids from mouse and human gastric tissue can be established after 48 h of cold ischemia. Our method, which only requires ice packs, standard shipping containers, and HBSS is feasible and reliable. This method does not affect the reliability of downstream dose-response assays and maintains organoid viability for at least 10 passages. The shipment of fresh tissue for organoid procurement could serve to enhance multicenter collaboration and achieve more elaborate or controlled organoid experimentation.

Background: Local recurrence after breast conserving surgery is reported in 5-10% of cases. This study aims to determine if preoperative MRI is associated with reduced IBTR rates in the longer term and evaluate IBTR rates of a high risk (TN and Her-2 positive) subgroup in those receiving MRI or not., Methods: Between 1999 and 2005, patients with invasive breast cancer undergoing BCS and radiation were identified. Primary endpoint was IBTR rate., Results: The cohort consisted of 470 cases: 27% underwent MRI and 73% did not. Median follow-up was 97 months. Overall 10-year IBTR rate was 3.6%. There was no significant difference in IBTR rate at 10 years between those receiving MRI or not (1.6% vs. 4.2% (P = 0.37). The TN and Her-2 positive combined subgroup had a higher IBTR rate than all others (9.8% vs. 1.7%, P = 0.001). In the group without MRI, the IBTR rate of the high risk group was 11.8% compared to 1.8% in the remainder (P = 0.002)., Conclusion: With 10-year follow-up, there was no significant difference in IBTR rate whether preoperative MRI is performed versus not. The high risk population showed an increased IBTR rate, this was more marked in those who did not receive MRI., (© 2017 Wiley Periodicals, Inc.)

Background: Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy with poor prognosis in part due to the lack of early detection and screening methods. Metabolomics provides a means for noninvasive screening of tumor-associated perturbations in cellular metabolism., Methods: Urine samples of PDAC patients (n = 32), healthy age and gender-matched controls (n = 32), and patients with benign pancreatic conditions (n = 25) were examined using (1)H-NMR spectroscopy. Targeted profiling of spectra permitted quantification of 66 metabolites. Unsupervised (principal component analysis, PCA) and supervised (orthogonal partial-least squares discriminant analysis, OPLS-DA) multivariate pattern recognition techniques were applied to discriminate between sample spectra using SIMCA-P(+) (version 12, Umetrics, Sweden)., Results: Clear distinction between PDAC and controls was noted when using OPLS-DA. Significant differences in metabolite concentrations between cancers and controls (p < 0.001) were noted. Model parameters for both goodness of fit, and predictive capability were high (R (2) = 0.85; Q (2) = 0.59, respectively). Internal validation methods were used to confirm model validity. Sensitivity and specificity of the multivariate OPLS-DA model were summarized using a receiver operating characteristics (ROC) curve, with an area under the curve (AUROC) = 0.988, indicating strong predictive power. Preliminary analysis revealed an AUROC = 0.958 for the model of benign pancreatic disease compared with PDAC, and suggest that the cancer-associated metabolomic signature dissipates following RO resection., Conclusions: Urinary metabolomics detected distinct differences in the metabolic profiles of pancreatic cancer compared with healthy controls and benign pancreatic disease. These preliminary results suggest that metabolomic approaches may facilitate discovery of novel pancreatic cancer biomarkers.

Background: Esophageal adenocarcinoma (EAC) often presents at a late, incurable stage, and mortality has increased substantially, due to an increase in incidence of EAC arising out of Barrett's esophagus. When diagnosed early, however, the combination of surgery and adjuvant therapies is associated with high cure rates. Metabolomics provides a means for non- invasive screening of early tumor-associated perturbations in cellular metabolism., Methods: Urine samples from patients with esophageal carcinoma (n = 44), Barrett's esophagus (n = 31), and healthy controls (n = 75) were examined using (1)H-NMR spectroscopy. Targeted profiling of spectra using Chenomx software permitted quantification of 66 distinct metabolites. Unsupervised (principal component analysis) and supervised (orthogonal partial least-squares discriminant analysis OPLS-DA) multivariate pattern recognition techniques were applied to discriminate between samples using SIMCA-P(+) software. Model specificity was also confirmed through comparison with a pancreatic cancer cohort (n = 32)., Results: Clear distinctions between esophageal cancer, Barrett's esophagus and healthy controls were noted when OPLS-DA was applied. Model validity was confirmed using two established methods of internal validation, cross-validation and response permutation. Sensitivity and specificity of the multivariate OPLS-DA models were summarized using a receiver operating characteristic curve analysis and revealed excellent predictive power (area under the curve = 0.9810 and 0.9627 for esophageal cancer and Barrett's esophagus, respectively). The metabolite expression profiles of esophageal cancer and pancreatic cancer were also clearly distinguishable with an area under the receiver operating characteristics curve (AUROC) = 0.8954., Conclusions: Urinary metabolomics identified discrete metabolic signatures that clearly distinguished both Barrett's esophagus and esophageal cancer from controls. The metabolite expression profile of esophageal cancer was also discrete from its precursor lesion, Barrett's esophagus. The cancer-specific nature of this profile was confirmed through comparison with pancreatic cancer. These preliminary results suggest that urinary metabolomics may have a future potential role in non-invasive screening in these conditions.

Metabolomics, the newest of the "omics" sciences, has brought much excitement to the field of oncology as a potential new translational tool capable of bringing the molecular world of cancer care to the bedside. While still early in its development, metabolomics could alter the scope and role of surgery in the multidisciplinary treatment of cancer. This review examines potential roles of metabolomics in areas of early cancer detection, personalized therapeutics and tumorigenesis., (Copyright © 2010 Wiley-Liss, Inc.)

Background: It remains uncertain whether routine preoperative breast magnetic resonance imaging (MRI) will lead to improved local outcomes after breast-conserving surgery (BCS) and radiation (RT) for invasive carcinoma. The purpose of this study was to determine whether MRI in the planning of the first lumpectomy reduces ipsilateral breast tumor recurrence (IBTR)., Methods: Using a prospective database, 472 initial lumpectomies from 463 women between 1999 and 2005 were examined. All patients had invasive cancer excised to negative margins on BCS, received RT, and were followed. IBTR rates were calculated by Kaplan-Meier method. Univariate and multivariate analyses were performed to investigate the association between MRI for initial lumpectomies and IBTR outcomes., Results: MRI was performed before 127 (27%) lumpectomies, while 345 (73%) patients did not have a preoperative breast MRI. At median follow-up of 54 months (range 4.8-111.6 months), there was no significant difference in actuarial 8-year IBTR rates between women with preoperative MRI evaluation and women without MRI (1.8% versus 2.5%, respectively; P=0.67). After adjusting for adjuvant therapies, patient, and tumor characteristics, there continued to be no increased risk of IBTR [hazard ratio (HR) 1.7; P=0.60]. MRI visualization of tumors prior to lumpectomy did not influence the achievement of negative margins and was not associated with lower rates of re-excision (MRI: 11.8% versus no-MRI: 13.3%; P=0.50)., Conclusion: MRI evaluation of invasive carcinoma in the planning of initial lumpectomies was not associated with improved local outcomes after BCS with RT in this cohort of patients.

Background: Lumpectomy followed by radiation is standard treatment for early breast cancer. Recently, the use of partial breast intraoperative radiation (IORT) has been developed, and patients selected for IORT should not have positive margins. This study's purpose was to identify factors predicting negative margins after lumpectomy., Methods: Patient age, preoperative investigations, surgery, final pathology, and margin status were examined using a prospective database between 1999 and 2005. Univariate and multivariate logistic regression analysis were performed to identify patient and tumor factors predicting an increased rate of negative margins. The results were used to generate a patient selection algorithm., Results: The rate of positive margins at first resection was 17% in 730 lumpectomies (708 patients). Multivariate analysis revealed that older age (P = .0006), smaller tumor size (P < .0025), type of surgery (OR = 3.4 for ultrasound vs mammogram-guided wire localization, P = .003), and having a core needle biopsy (CNB) with preoperative cancer diagnosis (P < .0001) were predictive for having a negative margin. Patients older than age 50 with a preoperative CNB showing invasive cancer less that 3 cm that can be localized under ultrasound had a negative margin rate of 98% (n = 178). These patients would be ideal for consideration of IORT., Conclusions: Negative margin rates after lumpectomy are predicted by age, tumor size, preoperative investigations, and localization technique. These variables can be used to select patients for IORT with a 2.2% chance of positive margins.

Background: For patients with anal canal cancer who fail combined modality treatment (CMT), salvage surgery (SS) offers the potential for long term survival. The literature regarding SS is limited by small patient numbers and/or heterogeneous treatment protocols. We report on a large series of patients initially treated with chemoradiation at a major referral center., Methods: We identified 60 patients with persistent or recurrent anal cancer who had undergone SS; 20 were excluded. Overall and disease-free survival (OS, DFS) curves were constructed using the Kaplan Meier method. Univariate analysis was done using the Log-Rank test, and multivariable analysis using Cox proportional hazards., Results: The 40 patients (29 women, 11 men, median age 57) underwent curative intent resection. The initial procedure was multivisceral resection (n = 24), abdominoperineal resection alone (n = 14) or local excision (n = 2). Postoperative mortality was 5%. Postoperative complications were seen in 72%. Median follow-up was 18 months overall and 36 months in survivors. Median OS was 41 months; OS and disease free survival at 5 years were 39% and 30%, respectively. Recurrence was present in 21 patients at time of analysis. Failure was locoregional in 86% (18 of 21) and distant in 48% (10 of 21). Independent predictors of poor OS were male gender, Charlson Comorbidity Score and tumor size. Independent predictors of poor disease free survival were positive margins and lymphovascular invasion., Conclusion: SS for anal canal cancer was associated with significant morbidity. Long-term survival was achieved in 39% of patients. Comorbidities should guide patient selection, and R0 resection should be the goal.

Lack of a small animal model of the human hepatitis C virus (HCV) has impeded development of antiviral therapies against this epidemic infection. By transplanting normal human hepatocytes into SCID mice carrying a plasminogen activator transgene (Alb-uPA), we generated mice with chimeric human livers. Homozygosity of Alb-uPA was associated with significantly higher levels of human hepatocyte engraftment, and these mice developed prolonged HCV infections with high viral titers after inoculation with infected human serum. Initial increases in total viral load were up to 1950-fold, with replication confirmed by detection of negative-strand viral RNA in transplanted livers. HCV viral proteins were localized to human hepatocyte nodules, and infection was serially passaged through three generations of mice confirming both synthesis and release of infectious viral particles. These chimeric mice represent the first murine model suitable for studying the human hepatitis C virus in vivo.