Reza Mirnezami

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 2 and publication bias assessed with funnel plots and Eggers 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.

Preparing for Precision Medicine

Precision medicine uses clinicopathological indexes and molecular profiling to create diagnostic, prognostic, and therapeutic strategies tailored to the patient. Its success depends on establishing frameworks for regulating, compiling, and interpreting key information.

Intraoperative Tissue Identification Using Rapid Evaporative Ionization Mass Spectrometry

A mass spectrometric approach was developed for intraoperative identification of cancerous tissue, in near–real-time. Diagnosing the Masses One of the best options for curing cancer is surgery. Yet, surgeons can leave cancerous tissue behind by not seeing the “tumor margins”—or edges of the tumor—clearly. If a surgeon isn’t sure whether tissue is normal or cancerous, the tissue is sent to a pathologist for testing. During this time (20 to 30 min), the patient remains under anesthesia, and, quite often, additional samples are required. To ensure that all malignant tissue is removed in the operating room, Balog and colleagues developed a mass spectrometry–based approach that identifies cancer during surgery. After analyzing ex vivo samples of cancerous, healthy, and benign/inflammatory tissue with rapid evaporative ionization mass spectrometry (REIMS), the authors created a database of the nearly 3000 tissue-specific mass spectra. These spectra were unique for each cancer type, with lipids such as phosphatidylcholine and phosphotidylinositol showing different ratios. Using these ratios, Balog et al. were even able to identify the origin of metastatic tumors ex vivo. To adapt this technology for use in vivo, during surgery, the authors created the “intelligent knife” (iKnife), which samples surgical smoke for mass spectrometric analysis. More than 800 spectra were acquired with the iKnife from 81 patients. These spectra, when matched against the previously created database, confirmed the results of normal histology, with low rates of false-positive and false-negative readouts. This first-in-human demonstration shows that the iKnife technology is ready for widespread use in the operating room to improve the accuracy of surgical intervention in cancer. Rapid evaporative ionization mass spectrometry (REIMS) is an emerging technique that allows near–real-time characterization of human tissue in vivo by analysis of the aerosol (“smoke”) released during electrosurgical dissection. The coupling of REIMS technology with electrosurgery for tissue diagnostics is known as the intelligent knife (iKnife). This study aimed to validate the technique by applying it to the analysis of fresh human tissue samples ex vivo and to demonstrate the translation to real-time use in vivo in a surgical environment. A variety of tissue samples from 302 patients were analyzed in the laboratory, resulting in 1624 cancerous and 1309 noncancerous database entries. The technology was then transferred to the operating theater, where the device was coupled to existing electrosurgical equipment to collect data during a total of 81 resections. Mass spectrometric data were analyzed using multivariate statistical methods, including principal components analysis (PCA) and linear discriminant analysis (LDA), and a spectral identification algorithm using a similar approach was implemented. The REIMS approach differentiated accurately between distinct histological and histopathological tissue types, with malignant tissues yielding chemical characteristics specific to their histopathological subtypes. Tissue identification via intraoperative REIMS matched the postoperative histological diagnosis in 100% (all 81) of the cases studied. The mass spectra reflected lipidomic profiles that varied between distinct histological tumor types and also between primary and metastatic tumors. Thus, in addition to real-time diagnostic information, the spectra provided additional information on divergent tumor biochemistry that may have mechanistic importance in cancer.

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 Cohens 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.

Robotic colorectal surgery: hype or new hope? A systematic review of robotics in colorectal surgery

Aim  Robotic colorectal surgery is an emerging field and may offer a solution to some of the difficulties inherent to conventional laparoscopic surgery. The aim of this review is to provide a comprehensive and critical analysis of the available literature on the use of robotic technology in colorectal surgery.

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

Significance Mass spectrometry imaging (MSI) technology represents a highly promising approach in cancer research. Here, we outline current roadblocks in translational MSI and introduce a comprehensive workflow designed to address current methodological limitations. An integrated bioinformatics platform is presented that allows intuitive histology-directed interrogation of MSI datasets. We show that this strategy permits the analysis of multivariate molecular signatures with direct correlation to morphological regions of interest, which can offer new insights into how different tumor microenvironmental populations interact with one another and generate novel region-of-interest specific biomarkers and therapeutic targets. 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.

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.

Cytoreductive surgery in combination with hyperthermic intraperitoneal chemotherapy improves survival in patients with colorectal peritoneal metastases compared with systemic chemotherapy alone.

Background:Colorectal cancer peritoneal metastasis (CPM) confers an exceptionally poor prognosis, and traditional treatment involving systemic chemotherapy (SC) is largely ineffective. Cytoreductive surgery (CRS) combined with hyperthermic intraperitoneal chemotherapy (HIPEC) is increasingly advocated for selected patients with CPM; however, opinions are divided because of the perceived lack of evidence, high morbidity, mortality, and associated costs for this approach. As there is no clear consensus, the aim of this study was to compare outcomes following CRS+HIPEC vs SC alone for CPM using meta-analytical methodology, focusing on survival outcomes. Secondary outcomes assessed included morbidity, mortality, quality of life (QOL), and health economics (HE).Methods:An electronic literature search was conducted to identify studies comparing survival following CRS+HIPEC vs SC for CPM. The odds ratio (OR) was calculated using the Mantel–Haenszel method with corresponding 95% confidence intervals (CI) and P-values. Heterogeneity was examined using the Q-statistic and quantified with I2. The fixed-effect model (FEM) was used in the absence of significant heterogeneity. For included studies, 2- and 5-year survival was compared for CRS+HIPEC vs SC alone.Results:Four studies (three case–control, one RCT) provided comparative survival data for patients undergoing CRS+HIPEC (n=187) vs SC (n=155) for CPM. Pooled analysis demonstrated superior 2-year (OR 2.78; 95% CI 1.72–4.51; P=0.001) and 5-year (OR 4.07; 95% CI 2.17–7.64; P=0.001) survival with CRS+HIPEC compared with SC. Mortality ranged from 0 to 8%. No data were available for the assessment of QOL or HE.Conclusions:Although limited by between-study heterogeneity, the data support the assertion that in carefully selected patients, multimodal treatment of CPM with CRS+HIPEC has a highly positive prognostic impact on medium- and long-term survival compared with SC alone. There is a paucity of comparative data available on morbidity, QOL, and HE.

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.

Chemical mapping of the colorectal cancer microenvironment via MALDI imaging mass spectrometry (MALDI-MSI) reveals novel cancer-associated field effects

Matrix‐assisted laser desorption ionisation imaging mass spectrometry (MALDI‐MSI) is a rapidly advancing technique for intact tissue analysis that allows simultaneous localisation and quantification of biomolecules in different histological regions of interest. This approach can potentially offer novel insights into tumour microenvironmental (TME) biochemistry. In this study we employed MALDI‐MSI to evaluate fresh frozen sections of colorectal cancer (CRC) tissue and adjacent healthy mucosa obtained from 12 consenting patients undergoing surgery for confirmed CRC. Specifically, we sought to address three objectives: (1) To identify biochemical differences between different morphological regions within the CRC TME; (2) To characterise the biochemical differences between cancerous and healthy colorectal tissue using MALDI‐MSI; (3) To determine whether MALDI‐MSI profiling of tumour‐adjacent tissue can identify novel metabolic ‘field effects’ associated with cancer. Our results demonstrate that CRC tissue harbours characteristic phospholipid signatures compared with healthy tissue and additionally, different tissue regions within the CRC TME reveal distinct biochemical profiles. Furthermore we observed biochemical differences between tumour‐adjacent and tumour‐remote healthy mucosa. We have referred to this ‘field effect’, exhibited by the tumour locale, as cancer‐adjacent metaboplasia (CAM) and this finding builds on the established concept of field cancerisation.