Recently, carbonic anhydrase (CA) inhibitors have been proposed as a potential new class of antitumor agents. The aim of this study was to evaluate the antitumor activity of three CA inhibitors, namely acetazolamide (AZ) and two newly synthesized aromatic sulfonamides with high affinity for CA IX, 2-(4-sulfamoylphenyl-amino)-4,6-dichloro-1,3,5-triazine (TR1) and 4-[3-(N,N-dimethylaminopropyl)thioreidophenylsulfonylaminoethyl]benzenesulfonamide (GA15), against human tumor cells. The effects of AZ, TR1, and GA15 on cell proliferation and apoptosis were evaluated in CA IX-positive HeLa and 786-O cells and CA IX-negative 786-O/von Hippel-Lindau (VHL) cells. We also investigated whether the potential antitumor activity of these molecules might be mediated by an increase in ceramide production. AZ, TR1, and GA15 could significantly reduce cell proliferation and induce apoptosis in HeLa and 786-O cells. Moreover, all three inhibitors could decrease intracellular pH (pH_i) and increase ceramide production in the same cells. Treatment with the ceramide synthase inhibitor fumonisin B1 prevented the apoptotic effects of the three CA inhibitors. In all experiments, the effects of aromatic sulfonamides were more pronounced than those of AZ. The three inhibitors did not show any antitumor activity in CA IX-negative 786-O/VHL cells and failed to lower pH_i or increase intracellular ceramide levels in the same cells. In conclusion, CA inhibition can decrease cell proliferation and induce apoptosis in human tumor cells. The ability of CA inhibitors to decrease pH_i might trigger cell apoptosis through mediation of ceramide synthesis. Activation of this apoptotic cascade probably is mediated by inhibition of the CA IX isoform.

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.