Analysis of Circulating Tumor DNA in Synchronous Metastatic Colorectal Cancer at Diagnosis Predicts Overall Patient Survival.

Sporadic colorectal cancer (sCRC) initially presents as metastatic tumors in 25-30% of patients. The 5-year overall survival (OS) in patients with metastatic sCRC is 50%, falling to 10% in patients presenting with synchronous metastatic disease (stage IV). In this study, we systematically analyzed the mutations of RAS, PIK3CA and BRAF genes in circulating tumor DNA (ctDNA) and tumoral tissue DNA (ttDNA) from 51 synchronous metastatic colorectal carcinoma (SMCC) patients by real-time PCR, and their relationship with the clinical, biological and histological features of disease at diagnosis. The highest frequency of mutations detected was in the KRAS gene, in tumor biopsies and plasma samples, followed by mutations of the PIK3CA, NRAS and BRAF genes. Overall, plasma systematically contained those genetic abnormalities observed in the tumor biopsy sample from the same subject, the largest discrepancies detected between the tumor biopsy and plasma from the same patient being for mutations in the KRAS and PIK3CA genes, with concordances of genotyping results between ttDNA and ctDNA at diagnosis of 75% and 84%, respectively. Of the 51 SMCC patients in the study, 25 (49%) showed mutations in at least 1 of the 4 genes analyzed in patient plasma. From the prognostic point of view, the presence and number of the most common mutations in the RAS, PIK3CA and BRAF genes in plasma from SMCC patients are independent prognostic factors for OS. Determination of the mutational status of ctDNA in SMCC could be a key tool for the clinical management of patients.

Numerical Bifurcation Analysis of Physiologically Structured Populations: Consumer-Resource, Cannibalistic and Trophic Models.

With the aim of applying numerical methods, we develop a formalism for physiologically structured population models in a new generality that includes consumer-resource, cannibalism and trophic models. The dynamics at the population level are formulated as a system of Volterra functional equations coupled to ODE. For this general class, we develop numerical methods to continue equilibria with respect to a parameter, detect transcritical and saddle-node bifurcations and compute curves in parameter planes along which these bifurcations occur. The methods combine curve continuation, ODE solvers and test functions. Finally, we apply the methods to the above models using existing data for Daphnia magna consuming Algae and for Perca fluviatilis feeding on Daphnia magna. In particular, we validate the methods by deriving expressions for equilibria and bifurcations with respect to which we compute errors, and by comparing the obtained curves with curves that were computed earlier with other methods. We also present new curves to show how the methods can easily be applied to derive new biological insight. Schemes of algorithms are included.

A new approach to monitor water quality in the Menor sea (Spain) using satellite data and machine learning methods.

The Menor sea is a coastal lagoon declared by the European Union as a sensitive area to eutrophication due to human activities. To control the deterioration of its water quality, it is necessary to monitor some parameters such as chlorophyll-a (chl-a), which indicates phytoplankton biomass in the water. In the study area, current efforts focus on in-situ measurements to estimate chl-a by means of a few permanent stations and seasonal oceanographic campaigns, however they are expensive and time consuming. In this work, we proposed a machine learning approach based on Sentinel-2 data to estimate chl-a content on the upper part of the water column. Random forest (rf), support vector machine (svmRadial), Artificial Neural Network (ANN) and Deep Neural Network (DNN) algorithms were utilized under three feature selection scenarios, and several spectral indices were used in combination with Sentinel 2 bands. Rf, svmRadial and DNN performed better when all the available predictors were included in the models (RMSE = 0.82, 0.82 and 1.76 mg/m3 respectively), whereas ANN achieved better results under scenario c (principal components). Our results demonstrate the possibility to estimate chl-a concentration in a cost-effective manner and thereby provide near-real time information to monitor the water quality of the Menor sea, what can be of great interest for local authorities, tourism and fishing industry.

Endoluminal tumor implant of a colorectal cancer in an anal fistula detected by FISH techniques: a case report.

Intraluminal shedding of tumor cells is a rare infrequent sporadic colorectal cancer (sCRC) mechanism of spreading. Less than 30 cases of sCRC metastasis into anal fistula have been reported. Here, we study a 72-year-old male with an adenocarcinoma arising in an anal fistula. Subsequent studies revealed another tumor in the rectum without distant metastatic disease; therefore, a curative-intent abdominoperineal resection was performed. The histologic study showed a moderately differentiated adenocarcinoma in both locations. No perineural or lymphovascular invasion was observed, and all the lymphatic nodes resected were negative for malignancy. Both tumors showed positive CK20 and negative CK7 immunostaining, but KRAS G12D mutation was only detected in the rectal tumor. After those conventional studies, a cytogenetic profile of both tumors was performed by interphase fluorescence in situ hybridization (iFISH) techniques. The FISH study displayed an identical genetic profile in both tumors, loss of the chromosomes 8 and 18q, and no alteration in chromosome 7 and 13q. Based on pathological and genetic findings, we established the same clonal origin of both tumors. Currently, the diagnosis of an intraluminal CRC metastasis relies on histologic and immunohistochemistry findings. We suggest that genetic studies at the individual cell level by FISH techniques may be useful in order to differentiate synchronous from intraluminal metastasis.

Stability of Methylphenidate under Various pH Conditions in the Presence or Absence of Gut Microbiota.

Methylphenidate is one of the most widely used oral treatments for attention-deficit/hyperactivity disorder (ADHD). The drug is mainly absorbed in the small intestine and has low bioavailability. Accordingly, a high interindividual variability in terms of response to the treatment is known among ADHD patients treated with methylphenidate. Nonetheless, very little is known about the factors that influence the drug's absorption and bioavailability. Gut microbiota has been shown to reduce the bioavailability of a wide variety of orally administered drugs. Here, we tested the ability of small intestinal bacteria to metabolize methylphenidate. In silico analysis identified several small intestinal bacteria to harbor homologues of the human carboxylesterase 1 enzyme responsible for the hydrolysis of methylphenidate in the liver into the inactive form, ritalinic acid. Despite our initial results hinting towards possible bacterial hydrolysis of the drug, up to 60% of methylphenidate is spontaneously hydrolyzed in the absence of bacteria and this hydrolysis is pH-dependent. Overall, our results indicate that the stability of methylphenidate is compromised under certain pH conditions in the presence or absence of gut microbiota.

High-Risk Clinicopathological and Genetic Features and Outcomes in Patients Receiving Neoadjuvant Radiochemotherapy for Locally Advanced Rectal Cancer.

Administering preoperative radiochemotherapy (RCT) in stage II-III tumors to locally advanced rectal carcinoma patients has proved to be effective in a high percentage of cases. Despite this, 20-30% of patients show no response or even disease progression. At present, preoperative response is assessed by a combination of imaging and tumor regression on histopathology, but recent studies suggest that various genetic abnormalities may be associated with the sensitivity or resistance of rectal cancer tumor cells to neoadjuvant therapy. In the present study we investigated the relationship between genetic lesions detected by high-density single-nucleotide polymorphisms (SNP) arrays 6.0 and response to neoadjuvant RCT, evaluated according to Dworak criteria in 39 rectal cancer tumors before treatment. The highest frequency of copy-number (CN) losses detected corresponded to chromosomes 18q (n = 27; 69%), 1p (n = 22; 56%), 15q (n = 19; 49%), 8p (n = 18; 48%), 4q (n = 17; 46%), and 22q (n = 17; 46%); in turn, CN gains more frequently involved chromosomes 20p (n = 22; 56%), 8p (n = 20; 51%), and 15q (n = 16; 41%). There was a significant association between alterations in the 1p, 3q, 7q, 12p, 17q, 20p, and 22q chromosomal regions and the degree of response to therapy prior to surgery. However, 4q, 15q11.1, and 15q14 chromosomal region alterations were identified as important by five prediction algorithms, i.e., those with the greatest influence on predicting the tumor response to treatment with preoperative RCT. Multivariate analysis of prognostic factors showed that gains on 15q11.1 and carcinoembryonic antigen (CEA) levels serum at diagnosis were the only independent variables predicting disease-free survival (DFS). Lymph node involvement also showed a prognostic impact on overall survival (OS) in the multivariate analysis. A deep-learning-based algorithm showed a 100% success rate in predicting both DFS and OS at 60 months after diagnosis of the disease. In summary, our results indicate the existence of an association between tumor genetic abnormalities at diagnosis, response to neoadjuvant therapy, and survival of patients with locally advanced rectal cancer. In addition to the clinical and biological characteristics of locally advanced rectal cancer patients, these could be used in the future as therapeutic and prognostic biomarkers, to identify patients sensitive or resistant to preoperative treatment, helping guide therapeutic decision-making. Additional prospective studies in larger series of patients are required to confirm the clinical utility of the newly identified biomarkers.

Microbiota and gut neuropeptides: a dual action of antimicrobial activity and neuroimmune response.

The gut microbiota is comprised of a vast variety of microbes that colonize the gastrointestinal tract and exert crucial roles for the host health. These microorganisms, partially via their breakdown of dietary components, are able to modulate immune response, mood, and behavior, establishing a chemical dialogue in the microbiota-gut-brain interphase. Changes in the gut microbiota composition and functionality are associated with multiple diseases, in which altered levels of gut-associated neuropeptides are also detected. Gut neuropeptides are strong neuroimmune modulators; they mediate the communication between the gut microbiota and the host (including gut-brain axis) and have also recently been found to exert antimicrobial properties. This highlights the importance of understanding the interplay between gut neuropeptides and microbiota and their implications on host health. Here, we will discuss how gut neuropeptides help to maintain a balanced microbiota and we will point at the missing gaps that need to be further investigated in order to elucidate whether these molecules are related to neuropsychiatric disorders, which are often associated with gut dysbiosis and altered gut neuropeptide levels.