Network machine learning maps phytochemically rich "Hyperfoods" to fight COVID-19.

In this paper, we introduce a network machine learning method to identify potential bioactive anti-COVID-19 molecules in foods based on their capacity to target the SARS-CoV-2-host gene-gene (protein-protein) interactome. Our analyses were performed using a supercomputing DreamLab App platform, harnessing the idle computational power of thousands of smartphones. Machine learning models were initially calibrated by demonstrating that the proposed method can predict anti-COVID-19 candidates among experimental and clinically approved drugs (5658 in total) targeting COVID-19 interactomics with the balanced classification accuracy of 80-85% in 5-fold cross-validated settings. This identified the most promising drug candidates that can be potentially "repurposed" against COVID-19 including common drugs used to combat cardiovascular and metabolic disorders, such as simvastatin, atorvastatin and metformin. A database of 7694 bioactive food-based molecules was run through the calibrated machine learning algorithm, which identified 52 biologically active molecules, from varied chemical classes, including flavonoids, terpenoids, coumarins and indoles predicted to target SARS-CoV-2-host interactome networks. This in turn was used to construct a "food map" with the theoretical anti-COVID-19 potential of each ingredient estimated based on the diversity and relative levels of candidate compounds with antiviral properties. We expect this in silico predicted food map to play an important role in future clinical studies of precision nutrition interventions against COVID-19 and other viral diseases.

Assessing the Impact of Primary Tumour Location on Survival After Resection of Colorectal Liver Metastases: A Propensity Weighted Retrospective Cohort Study.

BACKGROUND: Right-sided colonic tumours appear to have poorer survival after resection of colorectal liver metastases, although this may be confounded by various factors including advanced stage and emergency presentation. METHODS: Medical records of consecutive patients undergoing resection of colorectal liver metastases at a single centre from 2008 to 2015 were retrospectively reviewed. Cases were categorised by primary tumour location (right colon, left colon, rectum). Each primary location was weighted using propensity scores to balance covariates, including staging and mode of presentation. Cox regression was then applied to derive multivariable hazard ratios (HR) of survival after liver resection. Primary outcomes were 10-year overall survival (OS) and 5-year disease-free survival (DFS) after liver resection based on PTL. RESULTS: 414 patients were included in the analysis. Left colonic tumours were significantly associated with higher rates of bilobar liver metastasis (36.2% vs. 20.1% and 30.1%) and larger maximum size of liver metastases compared with rectal and right-sided tumours, respectively. There was no difference in rates of extra-hepatic metastases, recurrence in the liver after resection or RAS, BRAF or p53 mutational status. After propensity weighting and Cox-regression, right-sided tumours were independently associated with significantly reduced 10 year OS (HR 1.56, 95% CI 1.03-2.36, p = 0.04) but not 5 year DFS (HR 1.36, 95% CI 0.89-2.08, p = 0.15). CONCLUSIONS: Compared with left colonic and rectal tumours, right-sided colonic tumours are independently associated with inferior OS after resection of CRLM. This is despite higher rates of bilobar liver metastases and larger metastases with left-sided tumours.

ChemDistiller: an engine for metabolite annotation in mass spectrometry.

Motivation: High-resolution mass spectrometry permits simultaneous detection of thousands of different metabolites in biological samples; however, their automated annotation still presents a challenge due to the limited number of tailored computational solutions freely available to the scientific community. Results: Here, we introduce ChemDistiller, a customizable engine that combines automated large-scale annotation of metabolites using tandem MS data with a compiled database containing tens of millions of compounds with pre-calculated 'fingerprints' and fragmentation patterns. Our tests using publicly and commercially available tandem MS spectra for reference compounds show retrievals rates comparable to or exceeding the ones obtainable by the current state-of-the-art solutions in the field while offering higher throughput, scalability and processing speed. Availability and implementation: Source code freely available for download at https://bitbucket.org/iAnalytica/chemdistillerpython. Supplementary information: Supplementary data are available at Bioinformatics online.

Translational -omics: Future potential and current challenges in precision medicine.

Rapid advances in computational science and biotechnology are paving the way for precision medicine - a vision in next-generation healthcare that promises to provide a care package uniquely tailored to each individual's molecular make-up. Until relatively recently, the focus has been firmly centred around the genome; however, over the past two decades there has been a surge in the study of molecular activity within other biological domains (proteome/transcriptome/metabolome) involved in health and pathogenesis. The term '-omics' is broadly applied to these disciplines and 'translational -omics' refers to clinical utilisation of data derived from these scientific approaches. Translational -omics represents the cornerstone of the precision medicine initiative and offers positively disruptive solutions in global healthcare from a humanitarian, scientific and economic standpoint. However, there are unique challenges anticipated for all stakeholders within the precision medicine community, and addressing these early on in the adoption of precision approaches is critical. Herein, we outline the potential for translational -omics in precision medicine, highlight key roadblocks to successful implementation and propose potential solutions to current and expected problems.

Chemo-informatic strategy for imaging mass spectrometry-based hyperspectral profiling of lipid signatures in colorectal cancer.

Mass spectrometry imaging (MSI) provides the opportunity to investigate tumor biology from an entirely novel biochemical perspective and could lead to the identification of a new pool of cancer biomarkers. Effective clinical translation of histology-driven MSI in systems oncology requires precise colocalization of morphological and biochemical features as well as advanced methods for data treatment and interrogation. Currently proposed MSI workflows are subject to several limitations, including nonoptimized raw data preprocessing, imprecise image coregistration, and limited pattern recognition capabilities. Here we outline a comprehensive strategy for histology-driven MSI, using desorption electrospray ionization that covers (i) optimized data preprocessing for improved information recovery; (ii) precise image coregistration; and (iii) efficient extraction of tissue-specific molecular ion signatures for enhanced biochemical distinction of different tissue types. The proposed workflow has been used to investigate region-specific lipid signatures in colorectal cancer tissue. Unique lipid patterns were observed using this approach according to tissue type, and a tissue recognition system using multivariate molecular ion patterns allowed highly accurate (>98%) identification of pixels according to morphology (cancer, healthy mucosa, smooth muscle, and microvasculature). This strategy offers unique insights into tumor microenvironmental biochemistry and should facilitate compilation of a large-scale tissue morphology-specific MSI spectral database with which to pursue next-generation, fully automated histological approaches.

Rapid diagnosis and staging of colorectal cancer via high-resolution magic angle spinning nuclear magnetic resonance (HR-MAS NMR) spectroscopy of intact tissue biopsies.

OBJECTIVE: To develop novel metabolite-based models for diagnosis and staging in colorectal cancer (CRC) using high-resolution magic angle spinning nuclear magnetic resonance (HR-MAS NMR) spectroscopy. BACKGROUND: Previous studies have demonstrated that cancer cells harbor unique metabolic characteristics relative to healthy counterparts. This study sought to characterize metabolic properties in CRC using HR-MAS NMR spectroscopy. METHODS: Between November 2010 and January 2012, 44 consecutive patients with confirmed CRC were recruited to a prospective observational study. Fresh tissue samples were obtained from center of tumor and 5 cm from tumor margin from surgical resection specimens. Samples were run in duplicate where tissue volume permitted to compensate for anticipated sample heterogeneity. Samples were subjected to HR-MAS NMR spectroscopic profiling and acquired spectral data were imported into SIMCA and MATLAB statistical software packages for unsupervised and supervised multivariate analysis. RESULTS: A total of 171 spectra were acquired (center of tumor, n = 88; 5 cm from tumor margin, n = 83). Cancer tissue contained significantly increased levels of lactate (P < 0.005), taurine (P < 0.005), and isoglutamine (P < 0.005) and decreased levels of lipids/triglycerides (P < 0.005) relative to healthy mucosa (R2Y = 0.94; Q2Y = 0.72; area under the curve, 0.98). Colon cancer samples (n = 49) contained higher levels of acetate (P < 0.005) and arginine (P < 0.005) and lower levels of lactate (P < 0.005) relative to rectal cancer samples (n = 39). In addition unique metabolic profiles were observed for tumors of differing T-stage. CONCLUSIONS: HR-MAS NMR profiling demonstrates cancer-specific metabolic signatures in CRC and reveals metabolic differences between colonic and rectal cancers. In addition, this approach reveals that tumor metabolism undergoes modification during local tumor advancement, offering potential in future staging and therapeutic approaches.

1H HR-MAS NMR spectroscopy of tumor-induced local metabolic "field-effects" enables colorectal cancer staging and prognostication.

Colorectal cancer (CRC) is a major cause of morbidity and mortality in developed countries. Despite operative advances and the widespread adoption of combined-modality treatment, the 5-year survival rarely exceeds 60%. Improving our understanding of the biological processes involved in CRC development and progression will help generate new diagnostic and prognostic approaches. Previous studies have identified altered metabolism as a common feature in carcinogenesis, and quantitative measurement of this altered activity (metabonomics/metabolomics) has the potential to generate novel metabolite-based biomarkers for CRC diagnosis, staging and prognostication. In the present study we applied high-resolution magic angle spinning nuclear magnetic resonance (HR-MAS NMR) spectroscopy to analyze metabolites in intact tumor samples (n = 83) and samples of adjacent mucosa (n = 87) obtained from 26 patients undergoing surgical resection for CRC. Orthogonal partial least-squares discriminant analysis (OPLS-DA) of metabolic profiles identified marked biochemical differences between cancer tissue and adjacent mucosa (R(2) = 0.72; Q(2) = 0.45; AUC = 0.91). Taurine, isoglutamine, choline, lactate, phenylalanine, tyrosine (increased concentrations in tumor tissue) together with lipids and triglycerides (decreased concentrations in tumor tissue) were the most discriminant metabolites between the two groups in the model. In addition, tumor tissue metabolic profiles were able to distinguish between tumors of different T- and N-stages according to TNM classification. Moreover, we found that tumor-adjacent mucosa (10 cm from the tumor margin) harbors unique metabolic field changes that distinguish tumors according to T- and N-stage with higher predictive capability than tumor tissue itself and are accurately predictive of 5-year survival (AUC = 0.88), offering a highly novel means of tumor classification and prognostication in CRC.

A Systematic Review of Surgical Management Strategies in the Treatment of Peritoneal Carcinomatosis of Neuroendocrine Origin.

Cytoreductive surgery (CRS) represents the cornerstone of surgical management for peritoneal carcinomatosis (PC) and involves peritonectomy procedures aimed at complete peritoneal tumour resection. Frequently, CRS is combined with hyperthermic intraperitoneal chemotherapy (HIPEC). The combination of CRS + HIPEC is now considered the standard of care in patients with colorectal and ovarian PC. However, the role of this multi-modality treatment approach in patients with PC of neuroendocrine tumour origin (NET-PC) is less well understood. This systematic review provides a summary of available evidence on management strategies for patients with NET-PC. A systematic literature search was performed using Ovid Medline, EMBASE and Cochrane Library databases to identify studies reporting outcomes for patients with NET-PC undergoing surgical treatment. Eligible studies were assessed for methodological quality and design and evaluated for a method of surgical treatment, method of HIPEC delivery, oncological outcomes, and treatment-related morbidity. Eight studies, including a total of 1240 patients with NET-PC, met predefined inclusion criteria and have been included in this review. In three of the included studies, CRS alone was performed for patients with NET-PC, while five studies reported outcomes with combined treatment using CRS plus HIPEC. All studies were performed at tertiary peritoneal malignancy centres. Only one study directly compared outcomes in patients with NET-PC undergoing CRS plus HIPEC compared with CRS in isolation, with no significant difference in overall survival reported. Carefully selected patients with NET-PC may benefit from aggressive surgical treatment in the form of CRS +/- HIPEC. These procedures are best undertaken at centres with expertise in the management of both neuroendocrine tumours and peritoneal malignancy, as both are conditions that require tertiary-level care. The additional benefit of the HIPEC component in this group of patients remains unclear and warrants further investigation in clinical trials. Overall, the quality of data on this subject is restricted by the low number of studies and the variability in treatment methods employed. A multi-national data registry for patients with NET-PC may offer the opportunity to better define treatment algorithms. Translational research efforts in parallel should focus on developing a better biological understanding of NET-PC, with a view to identifying more effective intraperitoneal cytocidal agents.

Management Strategies and Outcomes for Small Intestinal Neuroendocrine Tumours with Involvement of the Superior Mesenteric Vessels: A Systematic Review.

Small intestinal neuroendocrine tumours (SI-NETs) are the most common small intestinal tumours. A particularly challenging subset of these tumours is those that involve the superior mesenteric artery or vein for which the role and feasibility of surgery are often questioned. This systematic review aimed to identify and evaluate the management strategies used for these complex SI-NETs. The identified studies showed positive outcomes with surgery and multimodality therapy.

Genomic-driven nutritional interventions for radiotherapy-resistant rectal cancer patient.

Radiotherapy response of rectal cancer patients is dependent on a myriad of molecular mechanisms including response to stress, cell death, and cell metabolism. Modulation of lipid metabolism emerges as a unique strategy to improve radiotherapy outcomes due to its accessibility by bioactive molecules within foods. Even though a few radioresponse modulators have been identified using experimental techniques, trying to experimentally identify all potential modulators is intractable. Here we introduce a machine learning (ML) approach to interrogate the space of bioactive molecules within food for potential modulators of radiotherapy response and provide phytochemically-enriched recipes that encapsulate the benefits of discovered radiotherapy modulators. Potential radioresponse modulators were identified using a genomic-driven network ML approach, metric learning and domain knowledge. Then, recipes from the Recipe1M database were optimized to provide ingredient substitutions maximizing the number of predicted modulators whilst preserving the recipe's culinary attributes. This work provides a pipeline for the design of genomic-driven nutritional interventions to improve outcomes of rectal cancer patients undergoing radiotherapy.

Implementation of molecular phenotyping approaches in the personalized surgical patient journey.

OBJECTIVE: The present review describes commonly employed metabolic profiling platforms and discusses the current and likely future application of these technologies in surgery. BACKGROUND: The metabolic adaptations that occur in response to surgical illness and trauma are incompletely understood. Evaluating these will be critical to the development of personalized surgical health solutions. Metabonomics is an advancing field in systems biology, which provides a means of interrogating these metabolic shifts. METHODS: Recent literature regarding metabolic profiling technologies and their applications in surgical practice are discussed. Future strategies are proposed for the incorporation of these and next-generation technologies in the evaluation of all steps in the patient surgical pathway. RESULTS: Metabolite-based profiling has provided valuable insights into the metabolic irregularities that occur in cancer development and progression across a variety of cancer subclasses including colorectal, breast, prostate, and lung cancers. In addition, metabolic modeling has shown considerable promise in other surgical conditions including trauma and sepsis and in the assessment of pharmacotherapeutic efficacy. DISCUSSION: Metabonomics offers a posttranscriptional view of system activity providing functional information downstream of the genome and proteome. Information at this level will provide the surgeon with a novel means of evaluating major socioeconomic problems such as cancer and sepsis. In addition, the rapid nature of emerging next generation profiling platforms provides a viable means of "real-time" perioperative metabolic assessment and optimization.

Increased local recurrence and reduced survival from colorectal cancer following anastomotic leak: systematic review and meta-analysis.

OBJECTIVE: To examine the long-term oncological impact of anastomotic leakage (AL) after restorative surgery for colorectal cancer using meta-analytical methods. Outcomes evaluated were local recurrence, distant recurrence, and survival. BACKGROUND: Recurrence after potentially curative surgery for colorectal cancer remains a significant clinical problem and has a poor prognosis. AL may be a risk factor for disease recurrence, however available studies have been conflicting. A meta-analysis was conducted to investigate the impact of AL on disease recurrence and long-term survival. METHODS: Studies published between 1965 and 2009 evaluating the long-term oncological impact of AL were identified by an electronic literature search. Outcomes evaluated included local recurrence, distant recurrence, and cancer specific survival. Meta-analysis was performed using the DerSimonian-Laird random-effects model to compute odds ratio and 95% confidence intervals. Study heterogeneity was evaluated using Q statistics and I and publication bias assessed with funnel plots and Egger's test. RESULTS: Twenty-one studies comprising 13 prospective nonrandomized studies, 1 prospective randomized, and 7 retrospective studies met the inclusion criteria, yielding a total of 21,902 patients. For rectal anastomoses, the odd ratios (OR) of developing a local recurrence when there was AL was 2.05 (95% CI = 1.51-2.8; P = 0.0001). For studies describing both colon and rectal anastomoses, the OR of local recurrence when there was an AL was 2.9 (95% CI = 1.78-4.71; P < 0.001). The OR of developing a distant recurrence after AL was 1.38 (95% CI = 0.96-1.99; P = 0.083). Long term cancer specific mortality was significantly higher after AL with an OR of 1.75 (95% CI = 1.47-2.1; P = 0.0001). CONCLUSIONS: AL has a negative prognostic impact on local recurrence after restorative resection of rectal cancer. A significant association between colorectal AL and reduced long-term cancer specific survival was also noted. No association between AL and distant recurrence was found.

Short- and long-term outcomes after laparoscopic and open hepatic resection: systematic review and meta-analysis.

BACKGROUND: Laparoscopic liver resection (LLR) is now considered a feasible alternative to open liver resection (OLR) in selected patients. Nevertheless studies comparing LLR and OLR are few and concerns remain about long-term oncological equivalence. The present study compares outcomes with LLR vs. OLR using meta-analytical methods. METHODS: Electronic literature searches were conducted to identify studies comparing LLR and OLR. Short-term outcomes evaluated included operating time, blood loss, length of hospital stay, peri-operative morbidity and resection margin status. Longer-term outcomes included local and distant recurrence, and overall (OS) and disease-free survival (DFS). Meta-analyses were performed using the Mantel-Haenszel method and Cohen's d method, with results expressed as odds ratio (OR) or standardized mean difference (SMD), respectively, with 95% confidence intervals (CI). RESULTS: Twenty-six studies met the inclusion criteria with a population of 1678 patients. LLR resulted in longer operating time, but reduced blood loss, portal clamp time, overall and liver-specific complications, ileus and length of stay. No difference was found between LLR and OLR for oncological outcomes. DISCUSSION: LLR has short-term advantages and seemingly equivalent long-term outcomes and can be considered a feasible alternative to open surgery in experienced hands.

Phytochemically rich dietary components and the risk of colorectal cancer: A systematic review and meta-analysis of observational studies.

BACKGROUND: Personalized nutrition and protective diets and lifestyles represent a key cancer research priority. The association between consumption of specific dietary components and colorectal cancer (CRC) incidence has been evaluated by a number of population-based studies, which have identified certain food items as having protective potential, though the findings have been inconsistent. Herein we present a systematic review and meta-analysis on the potential protective role of five common phytochemically rich dietary components (nuts, cruciferous vegetables, citrus fruits, garlic and tomatoes) in reducing CRC risk. AIM: To investigate the independent impact of increased intake of specific dietary constituents on CRC risk in the general population. METHODS: Medline and Embase were systematically searched, from time of database inception to January 31, 2020, for observational studies reporting CRC incidence relative to intake of one or more of nuts, cruciferous vegetables, citrus fruits, garlic and/or tomatoes in the general population. Data were extracted by two independent reviewers and analyzed in accordance with the Meta-analysis of Observational Studies in Epidemiology (MOOSE) and Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) reporting guidelines and according to predefined inclusion/exclusion criteria. Effect sizes of studies were pooled using a random-effects model. RESULTS: Forty-six studies were identified. CRC risk was significantly reduced in patients with higher vs lower consumption of cruciferous vegetables [odds ratio (OR) = 0.90; 95% confidence interval (CI): 0.85-0.95; P < 0.005], citrus fruits (OR = 0.90; 95%CI: 0.84-0.96; P < 0.005), garlic (OR = 0.83; 95%CI: 0.76-0.91; P < 0.005) and tomatoes (OR = 0.89; 95%CI: 0.84-0.95; P < 0.005). Subgroup analysis showed that this association sustained when looking at case-control studies alone, for all of these four food items, but no significant difference was found in analysis of cohort studies alone. Nut consumption exhibited a similar trend, but overall results were not significant (OR = 0.72; 95%CI: 0.50-1.03; P < 0.07; I 2 = 90.70%). Putative anticarcinogenic mechanisms are proposed using gene-set enrichment analysis of gene/protein perturbations caused by active compounds within each food item. CONCLUSION: Increased cruciferous vegetable, garlic, citrus fruit and tomato consumption are all inversely associated with CRC risk. These findings highlight the potential for developing precision nutrition strategies for CRC prevention.

Application of robotic technologies in lower gastrointestinal tract endoscopy: A systematic review.

BACKGROUND: Conventional optical colonoscopy is considered the gold standard investigation for colorectal tract pathology including colorectal malignancy, polyps and inflammatory bowel disease. Inherent limitations exist with current generation endoscopic technologies, including, but not limited to, patient discomfort, endoscopist fatigue, narrow field of view and missed pathology behind colonic folds. Rapid developments in medical robotics have led to the emergence of a variety of next-generation robotically-augmented technologies that could overcome these limitations. AIM: To provide a comprehensive summary of recent developments in the application of robotics in lower gastrointestinal tract endoscopy. METHODS: A systematic review of the literature was performed from January 1, 2000 to the January 7, 2021 using EMBASE, MEDLINE and Cochrane databases. Studies reporting data on the use of robotic technology in ex vivo or in vivo animal and human experiments were included. In vitro studies (studies using synthetic colon models), studies evaluating non-robotic technology, robotic technology aimed at the upper gastrointestinal tract or paediatric endoscopy were excluded. System ergonomics, safety, visualisation, and diagnostic/therapeutic capabilities were assessed. RESULTS: Initial literature searching identified 814 potentially eligible studies, from which 37 were deemed suitable for inclusion. Included studies were classified according to the actuation modality of the robotic device(s) as electromechanical (EM) (n = 13), pneumatic (n = 11), hydraulic (n = 1), magnetic (n = 10) and hybrid (n = 2) mechanisms. Five devices have been approved by the Food and Drug Administration, however most of the technologies reviewed remain in the early phases of testing and development. Level 1 evidence is lacking at present, but early reports suggest that these technologies may be associated with improved pain and safety. The reviewed devices appear to be ergonomically capable and efficient though to date no reports have convincingly shown diagnostic or therapeutic superiority over conventional colonoscopy. CONCLUSION: Significant progress in robotic colonoscopy has been made over the last couple of decades. Improvements in design together with the integration of semi-autonomous and autonomous systems over the next decade will potentially result in robotic colonoscopy becoming more commonplace.

Impact of primary tumour location on colorectal liver metastases: A systematic review.

BACKGROUND: Colorectal cancer (CRC) is the third most common cause of cancer-related death worldwide. Despite significant advances in screening, surgical management and adjuvant therapies, average 5-year survival seldom exceeds 60% in most developed nations. Metastatic disease represents the primary cause of mortality in patients with CRC, and the liver is the most common location for distant tumour spread. Up to 25% of patients are found to have synchronous liver metastases at the time of diagnosis and a further 30%-40% will develop metachronous disease in the course of follow-up. It has been suggested that primary tumour location [right side versus left side, primary tumour location (PTL)] can influence oncological outcomes in this patient group and that this should be considered in prognostic models and therapeutic decision-making algorithms. This suggestion is not universally accepted and there have been conflicting reports in the literature to date. AIM: To provide a comprehensive summary of the available evidence regarding the impact of PTL on oncological outcomes in patients with colorectal cancer liver metastases (CRCLM). METHODS: MEDLINE, EMBASE and COCHRANE were searched for relevant publications using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses methodology. Data on oncological outcomes was then extracted from full text articles that met the predefined inclusion criteria. RESULTS: A total of 41 studies were identified that met predefined inclusion criteria for this review. In 21 out of 38 studies that provided data on overall survival, a statistically significant improvement in overall survival was reported in patients with left sided primary tumours. These studies included a total of 13897 patients compared with 4306 patients in the studies that did not show a significant difference. Eight studies noted a similar trend towards improved disease-free or progression-free survival. Several authors observed distinct patterns of relapse after treatment of hepatic metastases according to PTL; for example hepatic recurrence after treatment of CRCLM appears to occur more aggressively with right-sided CRC. CONCLUSION: Taken together, the findings of the present review indicate that PTL may have a role as an independent prognostic factor when determining treatment and disease surveillance strategies in CRC. The mechanisms responsible for this variation remain poorly understood, but are likely to relate to molecular, histological and embryological differences, as well as inherent differences in therapeutic sensitivity.

Network Mapping of Molecular Biomarkers Influencing Radiation Response in Rectal Cancer.

Preoperative radiotherapy (RT) plays an important role in the management of locally advanced rectal cancer (RC). Tumor regression after RT shows marked variability, and robust molecular methods are needed to help predict likely response. The aim of this study was to review the current published literature and use Gene Ontology (GO) analysis to define key molecular biomarkers governing radiation response in RC. A systematic review of electronic bibliographic databases (Medline, Embase) was performed for original articles published between 2000 and 2015. Biomarkers were then classified according to biological function and incorporated into a hierarchical GO tree. Both significant and nonsignificant results were included in the analysis. Significance was binarized on the basis of univariate and multivariate statistics. Significance scores were calculated for each biological domain (or node), and a direct acyclic graph was generated for intuitive mapping of biological pathways and markers involved in RC radiation response. Seventy-two individual biomarkers across 74 studies were identified. On highest-order classification, molecular biomarkers falling within the domains of response to stress, cellular metabolism, and pathways inhibiting apoptosis were found to be the most influential in predicting radiosensitivity. Homogenizing biomarker data from original articles using controlled GO terminology demonstrated that cellular mechanisms of response to RT in RC-in particular the metabolic response to RT-may hold promise in developing radiotherapeutic biomarkers to help predict, and in the future modulate, radiation response.

Colorectal Peritoneal Metastases: A Systematic Review of Current and Emerging Trends in Clinical and Translational Research.

Colorectal peritoneal metastases (CPM) are associated with abbreviated survival and significantly impaired quality of life. In patients with CPM, radical multimodality treatment consisting of cytoreductive surgery (CRS) combined with hyperthermic intraperitoneal chemotherapy (HIPEC) has demonstrated oncological superiority over systemic chemotherapy alone. In highly selected patients undergoing CRS + HIPEC, overall survival of over 60% has been reported in some series. These are patients in whom the disease burden is limited and where the diagnosis is made at an early stage in the disease course. Early diagnosis and a deeper understanding of the biological mechanisms that regulate CPM are critical to refining patient selection for radical treatment, personalising therapeutic approaches, enhancing prognostication, and ultimately improving long-term survivorship. In the present study, we outline three broad themes which represent critical future research targets in CPM: (1) enhanced radiological strategies for early detection and staging; (2) identification and validation of translational biomarkers for diagnostic, prognostic, and therapeutic deployment; and (3) development of optimized approaches for surgical cytoreduction as well as more precise strategies for intraperitoneal drug selection and delivery. Herein, we provide a contemporary narrative review of the state of the art in these three areas. A systematic review in accordance with PRISMA guidelines was undertaken on all English language studies published between 2007 and 2017. In vitro and animal model studies were deemed eligible for inclusion in the sections pertaining to biomarkers and therapeutic optimisation, as these areas of research currently remain in the early stages of development. Acquired data were then divided into hierarchical thematic categories (imaging modalities, translational biomarkers (diagnostic/prognostic/therapeutic), and delivery techniques) and subcategories. An interactive sunburst figure is provided for intuitive interrogation of the CPM research landscape.