Gastric cancer (GC) is turning out today to be one of the most important welfare issues for both Asian and European countries. Indeed, while the vast majority of the disease burden is located in China and in Pacific and East Asia, GC in European countries still account for about 100,000 deaths per year. With this review article, we aim to focus the attention on one of the most complex cellular pathways involved in GC proliferation, invasion, migration, and metastasis: the MAP kinases. Such large kinases family is to date constantly studied, since their discovery more than 30 years ago, due to the important role that it plays in the regulation of physiological and pathological processes. Interactions with other cellular proteins as well as miRNAs and lncRNAs may modulate their expression influencing the cellular biological features. Here, we summarize the most important and recent studies involving MAPK in GC. At the same time, we need to underly that, differently from cancers arising from other tissues, where MAPK pathways seems to be a gold target for anticancer therapies, GC seems to be unique in any aspect. Our aim is to review the current knowledge in MAPK pathways alterations leading to GC, including H. pylori MAPK-triggering to derail from gastric normal epithelium to GC and to encourage researches involved in MAPK signal transduction, that seems to definitely sustain GC development.

Background: A gold standard method for malnutrition diagnosis is still lacking in Inflammatory Bowel Disease (IBD). Objective: The aims of this study are to determine the prevalence of malnutrition in IBD patients according with recently published Global Leadership Initiative on Malnutrition (GLIM) criteria, to detect the factors contributing to the onset of malnutrition, and to evaluate the most accurate predictor of malnutrition risk within the available nutritional screening tools. Methods: Fifty-three consecutive adult IBD patients [38 Crohn’s disease (CD) and 15 ulcerative colitis (UC)] had been assessed preoperatively by a multidisciplinary IBD team before undergoing elective surgery. Several malnutrition risk tools were tested, such as NRS-2002, MUST, MST, MIRT, and SaskIBD-NR. The statistical association of independent GLIM variables with baseline characteristics of patients was explored as well as the concordance with the European Society for Clinical Nutrition and Metabolism (ESPEN 2015) and the screening tools. Results: Twenty-two IBD patients (42%) were malnourished according to GLIM criteria, of which 13 were CD (34%) and 9 UC (60%). The etiological criteria of inflammation and reduction of food intake were present in 51% and 19% of our patients, respectively. The prevalence of GLIM phenotypic criteria was 28%, 28% and 34% for BMI, Free Fat Mass Index (FFMI) and unintended weight loss (UWL), respectively. The presence of ileostomy was statistically associated with a higher prevalence of BMI (p = 0.030), FFMI (p = 0.030) and UWL (p = 0.002) values lower than the GLIM criteria cut-offs, while secondary surgery is associated with a decrease in FFMI (p = 0.017) and UWL (p = 0.041). The sensitivity of the tested nutritional screening tools, compared with the GLIM prevalence of malnutrition, was not satisfactory (between 50 and 82%). Conclusions: GLIM has a higher rate of malnutrition detection than ESPEN 2015, as malnutrition in IBD seems linked to inflammation and secondary malabsorption even without a reduction of food intake. The sensitivity of the screening tools is lower than the specificity when compared with GLIM criteria for malnutrition diagnosis.

Tailored treatments for metastatic colorectal cancer (mCRC) have not yet completely evolved due to the variety in response to drugs. Therefore, artificial intelligence has been recently used to develop prognostic and predictive models of treatment response (either activity/efficacy or toxicity) to aid in clinical decision making. In this systematic review, we have examined the ability of learning methods to predict response to chemotherapy alone or combined with targeted therapy in mCRC patients by targeting specific narrative publications in Medline up to April 2022 to identify appropriate original scientific articles. After the literature search, 26 original articles met inclusion and exclusion criteria and were included in the study. Our results show that all investigations conducted on this field have provided generally promising results in predicting the response to therapy or toxic side-effects. By a meta-analytic approach we found that the overall weighted means of the area under the receiver operating characteristic (ROC) curve (AUC) were 0.90, 95% C.I. 0.80–0.95 and 0.83, 95% C.I. 0.74–0.89 in training and validation sets, respectively, indicating a good classification performance in discriminating response vs. non-response. The calculation of overall HR indicates that learning models have strong ability to predict improved survival. Lastly, the delta-radiomics and the 74 gene signatures were able to discriminate response vs. non-response by correctly identifying up to 99% of mCRC patients who were responders and up to 100% of patients who were non-responders. Specifically, when we evaluated the predictive models with tests reaching 80% sensitivity (SE) and 90% specificity (SP), the delta radiomics showed an SE of 99% and an SP of 94% in the training set and an SE of 85% and SP of 92 in the test set, whereas for the 74 gene signatures the SE was 97.6% and the SP 100% in the training set.

Robotic surgery has been developed with the aim of improving surgical quality and overcoming the limitations of conventional laparoscopy in the performance of complex mini-invasive procedures. The present study was designed to compare robotic and laparoscopic distal gastrectomy in the treatment of gastric cancer. Between June 2008 and September 2015, 41 laparoscopic and 30 robotic distal gastrectomies were performed by a single surgeon at the same institution. Clinicopathological characteristics of the patients, surgical performance, postoperative morbidity/mortality and pathologic data were prospectively collected and compared between the laparoscopic and robotic groups by the Chi-square test and the Mann-Whitney test, as indicated. There were no significant differences in patient characteristics between the two groups. Mean tumor size was larger in the laparoscopic than in the robotic patients (5.3 ± 0.5 cm and 3.0 ± 0.4 cm, respectively; P = 0.02). However, tumor stage distribution was similar between the two groups. The mean number of dissected lymph nodes was higher in the robotic than in the laparoscopic patients (39.1 ± 3.7 and 30.5 ± 2.0, respectively; P = 0.02). The mean operative time was 262.6 ± 8.6 min in the laparoscopic group and 312.6 ± 15.7 min in the robotic group (P < 0.001). The incidences of surgery-related and surgery-unrelated complications were similar in the laparoscopic and in the robotic patients. There were no significant differences in short-term clinical outcomes between the two groups. Within the limitation of a small-sized, non-randomized analysis, our study confirms that robotic distal gastrectomy is a feasible and safe surgical procedure. When compared with conventional laparoscopy, robotic surgery shows evident benefits in the performance of lymphadenectomy with a higher number of retrieved and examined lymph nodes.