Machine learning and radiomics analysis by computed tomography in colorectal liver metastases patients for RAS mutational status prediction.

PURPOSE: To assess the efficacy of machine learning and radiomics analysis by computed tomography (CT) in presurgical setting, to predict RAS mutational status in colorectal liver metastases. METHODS: Patient selection in a retrospective study was carried out from January 2018 to May 2021 considering the following inclusion criteria: patients subjected to surgical resection for liver metastases; proven pathological liver metastases; patients subjected to enhanced CT examination in the presurgical setting with a good quality of images; and RAS assessment as standard reference. A total of 851 radiomics features were extracted using the PyRadiomics Python package from the Slicer 3D image computing platform after slice-by-slice segmentation on CT portal phase by two expert radiologists of each individual liver metastasis performed first independently by the individual reader and then in consensus. Balancing technique was performed, and inter- and intraclass correlation coefficients were calculated to assess the between-observer and within-observer reproducibility of features. Receiver operating characteristics (ROC) analysis with the calculation of area under the ROC curve (AUC), sensitivity (SENS), specificity (SPEC), positive predictive value (PPV), negative predictive value (NPV) and accuracy (ACC) were assessed for each parameter. Linear and non-logistic regression model (LRM and NLRM) and different machine learning-based classifiers were considered. Moreover, features selection was performed before and after a normalized procedure using two different methods (3-sigma and z-score). RESULTS: Seventy-seven liver metastases in 28 patients with a mean age of 60 years (range 40-80 years) were analyzed. The best predictors, at univariate analysis for both normalized procedures, were original_shape_Maximum2DDiameter and wavelet_HLL_glcm_InverseVariance that reached an accuracy of 80%, an AUC ≥ 0.75, a sensitivity ≥ 80% and a specificity ≥ 70% (p value < < 0.01). However, a multivariate analysis significantly increased the accuracy in RAS prediction when a linear regression model (LRM) was used. The best performance was obtained using a LRM combining linearly 12 robust features after a z-score normalization procedure: AUC of 0.953, accuracy 98%, sensitivity 96%, specificity of 100%, PPV 100% and NPV 96% (p value < < 0.01). No statistically significant increase was obtained considering the tested machine learning both without normalization and with normalization methods. CONCLUSIONS: Normalized approach in CT radiomics analysis allows to predict RAS mutational status in colorectal liver metastases patients.

Machine learning-based radiomics analysis in predicting RAS mutational status using magnetic resonance imaging.

PURPOSE: To assess the efficacy of radiomics features, obtained by magnetic resonance imaging (MRI) with hepatospecific contrast agent, in pre-surgical setting, to predict RAS mutational status in liver metastases. METHODS: Patients with MRI in pre-surgical setting were enrolled in a retrospective study. Manual segmentation was made by means 3D Slicer image computing, and 851 radiomics features were extracted as median values using the PyRadiomics Python package. The features were extracted considering the agreement with the Imaging Biomarker Standardization Initiative (IBSI). Balancing was performed through synthesis of samples for the underrepresented classes using the self-adaptive synthetic oversampling (SASYNO) approach. Inter- and intraclass correlation coefficients (ICC) were calculated to assess the between-observer and within-observer reproducibility of all radiomics characteristics. For continuous variables, nonparametric Wilcoxon-Mann-Whitney test was utilized. Benjamini and Hochberg's false discovery rate (FDR) adjustment for multiple testing was used. Receiver operating characteristics (ROC) analysis with the calculation of area under the ROC curve (AUC), sensitivity (SENS), specificity (SPEC), positive predictive value (PPV), negative predictive value (NPV) and accuracy (ACC) were assessed for each parameter. Linear and non-logistic regression model (LRM and NLRM) and different machine learning-based classifiers including decision tree (DT), k-nearest neighbor (KNN) and support vector machine (SVM) were considered. Moreover, features selection were performed before and after a normalized procedure using two different methods (3-sigma and z-score). McNemar test was used to assess differences statistically significant between dichotomic tables. All statistical procedures were done using MATLAB R2021b Statistics and Machine Toolbox (MathWorks, Natick, MA, USA). RESULTS: Seven normalized radiomics features, extracted from arterial phase, 11 normalized radiomics features, from portal phase, 12 normalized radiomics features from hepatobiliary phase and 12 normalized features from T2-W SPACE sequence were robust predictors of RAS mutational status. The multivariate analysis increased significantly the accuracy in RAS prediction when a LRM was used, combining 12 robust normalized features extracted by VIBE hepatobiliary phase reaching an accuracy of 99%, a sensitivity 97%, a specificity of 100%, a PPV of 100% and a NPV of 98%. No statistically significant increase was obtained, considering the tested classifiers DT, KNN and SVM, both without normalization and with normalization methods. CONCLUSIONS: Normalized approach in MRI radiomics analysis allows to predict RAS mutational status.

Panitumumab plus trifluridine/tipiracil as anti-EGFR rechallenge therapy in patients with refractory RAS wild-type metastatic colorectal cancer: Overall survival and subgroup analysis of the randomized phase II VELO trial.

The randomized phase II VELO trial showed that the addition of panitumumab to trifluridine/tipiracil significantly improves progression-free survival (PFS) as compared to trifluridine/tipiracil in third-line therapy in patients with refractory RAS wild-type (WT) metastatic colorectal cancer (mCRC). With longer follow-up, final overall survival results and posttreatment subgroup analysis are presented. Sixty-two patients with refractory RAS WT mCRC were randomly assigned to receive, as third-line therapy, trifluridine/tipiracil alone (arm A) or in combination with panitumumab (arm B). Primary endpoint was PFS; secondary endpoints included overall survival (OS) and overall response rate (ORR). Median OS was 13.1 months (95% CI 9.5-16.7) in arm A compared to 11.6 months (95% CI 6.3-17.0) in arm B (HR: 0.96, 95% CI 0.54-1.71, P = .9). To evaluate the impact of subsequent lines of treatment, subgroup analysis was performed for the 24/30 patients in arm A, that received fourth-line therapy after disease progression. Median PFS was 4.1 months (95% CI 1.44-6.83) for 17 patients treated with anti-EGFR rechallenge as compared to 3.0 months (95% CI 1.61-4.31) for seven patients that received other therapies (HR: 0.29, 95% CI 0.10-0.85, P = .024). Median OS from the start of fourth-line treatment was 13.6 months (95% CI 7.2-20), and 5.1 months (95% CI 1.8-8.3) for patients treated with anti-EGFR rechallenge vs other therapies, respectively (HR: 0.30, 95% CI 0.11-0.81, P = .019). Final results of the VELO trial support the role of anti-EGFR rechallenge in the continuum of care of patients with RAS/BRAF WT mCRC.

Perspectives in Immunotherapy: meeting report from Immunotherapy Bridge (Naples, November 30th-December 1st, 2022).

The discovery and development of novel treatments that harness the patient's immune system and prevent immune escape has dramatically improved outcomes for patients across cancer types. However, not all patients respond to immunotherapy, acquired resistance remains a challenge, and responses are poor in certain tumors which are considered to be immunologically cold. This has led to the need for new immunotherapy-based approaches, including adoptive cell transfer (ACT), therapeutic vaccines, and novel immune checkpoint inhibitors. These new approaches are focused on patients with an inadequate response to current treatments, with emerging evidence of improved responses in various cancers with new immunotherapy agents, often in combinations with existing agents. The use of cell therapies, drivers of immune response, and trends in immunotherapy were the focus of the Immunotherapy Bridge (November 30th-December 1st, 2022), organized by the Fondazione Melanoma Onlus, Naples, Italy, in collaboration with the Society for Immunotherapy of Cancer.

KEYSTEP-008: phase II trial of pembrolizumab-based combination in MSI-H/dMMR metastatic colorectal cancer.

Robust clinical activity has been observed with the immune checkpoint inhibitor pembrolizumab in patients with microsatellite instability-high/mismatch repair-deficient (MSI-H/dMMR) metastatic colorectal cancer (mCRC). However, given the response rate of 45% and a median progression-free survival of 16.5 months with first-line pembrolizumab demonstrated in KEYNOTE-177, there is room for improvement. Targeting a second immune receptor, such as CTLA-4, LAG-3, TIGIT, or ILT-4 may improve efficacy of PD-1 inhibition. Here we describe the design and rationale for the open-label, randomized, phase II KEYSTEP-008 trial, which will evaluate the efficacy and safety of pembrolizumab-based combination therapy compared with pembrolizumab monotherapy in chemotherapy-refractory (cohort A) or previously untreated (cohort B) MSI-H/dMMR mCRC. Clinical Trial Registration: NCT04895722 (ClinicalTrials.gov).

Plain language summary of the TOPAZ-1 study: durvalumab and chemotherapy for advanced biliary tract cancer.

WHAT IS THIS SUMMARY ABOUT?: This is a summary describing the results of a Phase III study called TOPAZ-1. The study looked at treatment with durvalumab (a type of immunotherapy) and chemotherapy to treat participants with advanced biliary tract cancer (BTC). Advanced BTC is usually diagnosed at late stages of disease, when it cannot be cured by surgery. This study included participants with advanced BTC who had not received previous treatment, or had their cancer come back at least 6 months after receiving treatment or surgery that aimed to cure their disease. Participants received treatment with durvalumab and chemotherapy or placebo and chemotherapy. The aim of this study was to find out if treatment with durvalumab and chemotherapy could increase the length of time that participants with advanced BTC lived, compared with placebo and chemotherapy. WHAT WERE THE RESULTS OF THE STUDY?: Participants who took durvalumab and chemotherapy had a 20% lower chance of experiencing death at any point in the study compared with participants who received placebo and chemotherapy. The side effects experienced by participants were similar across treatment groups, and less than 12% of participants in either treatment group had to stop treatment due to treatment-related side effects. WHAT DO THE RESULTS OF THE STUDY MEAN?: Overall, these results support durvalumab and chemotherapy as a new treatment option for people with advanced BTCs. Based on the results of this study, durvalumab is now approved for the treatment of adults with advanced BTCs in combination with chemotherapy by government organizations in Europe, the United States and several other countries.

Radiomics and machine learning analysis by computed tomography and magnetic resonance imaging in colorectal liver metastases prognostic assessment.

OBJECTIVE: The aim of this study was the evaluation radiomics analysis efficacy performed using computed tomography (CT) and magnetic resonance imaging in the prediction of colorectal liver metastases patterns linked to patient prognosis: tumor growth front; grade; tumor budding; mucinous type. Moreover, the prediction of liver recurrence was also evaluated. METHODS: The retrospective study included an internal and validation dataset; the first was composed by 119 liver metastases from 49 patients while the second consisted to 28 patients with single lesion. Radiomic features were extracted using PyRadiomics. Univariate and multivariate approaches including machine learning algorithms were employed. RESULTS: The best predictor to identify tumor growth was the Wavelet_HLH_glcm_MaximumProbability with an accuracy of 84% and to detect recurrence the best predictor was wavelet_HLH_ngtdm_Complexity with an accuracy of 90%, both extracted by T1-weigthed arterial phase sequence. The best predictor to detect tumor budding was the wavelet_LLH_glcm_Imc1 with an accuracy of 88% and to identify mucinous type was wavelet_LLH_glcm_JointEntropy with an accuracy of 92%, both calculated on T2-weigthed sequence. An increase statistically significant of accuracy (90%) was obtained using a linear weighted combination of 15 predictors extracted by T2-weigthed images to detect tumor front growth. An increase statistically significant of accuracy at 93% was obtained using a linear weighted combination of 11 predictors by the T1-weigthed arterial phase sequence to classify tumor budding. An increase statistically significant of accuracy at 97% was obtained using a linear weighted combination of 16 predictors extracted on CT to detect recurrence. An increase statistically significant of accuracy was obtained in the tumor budding identification considering a K-nearest neighbors and the 11 significant features extracted T1-weigthed arterial phase sequence. CONCLUSIONS: The results confirmed the Radiomics capacity to recognize clinical and histopathological prognostic features that should influence the choice of treatments in colorectal liver metastases patients to obtain a more personalized therapy.

Perspectives in Immunotherapy: meeting report from the Immunotherapy Bridge, December 1st-2nd, 2021.

Over the past decade, immunotherapy has become an increasingly fundamental modality in the treatment of cancer. The positive impact of immune checkpoint inhibition, especially anti-programmed death (PD)-1/PD-ligand (L)1 blockade, in patients with different cancers has focused attention on the potential for other immunotherapeutic approaches. These include inhibitors of additional immune checkpoints, adoptive cell transfer (ACT), and therapeutic vaccines. Patients with advanced cancers who previously had limited treatment options available may now benefit from immunotherapies that can offer durable responses and improved survival outcomes. However, despite this, a significant proportion of patients fail to respond to immunotherapy, especially those with less immunoresponsive cancer types, and there remains a need for new treatment strategies.The virtual Immunotherapy Bridge (December 1st-2nd, 2021), organized by the Fondazione Melanoma Onlus, Naples, Italy in collaboration with the Society for Immunotherapy of Cancer addressed several areas of current research in immunotherapy, including lessons learned from cell therapies, drivers of immune response, and trends in immunotherapy across different cancers, and these are summarised here.

New approach to implement cancer patient care: The valutazione percorso rete oncologica campana (ValPeROC)-experience from an Italian oncology network.

OBJECTIVE: The primary goal of the Campania Oncology Network (ROC) was to reduce cancer delay and care fragmentation through the establishment of cancer-specific multidisciplinary oncologic groups (GOMs) and diagnostic and therapeutic assistance paths (PDTAs). METHODS: Five cancer centres of the ROC, with their own cancer specific GOM, were selected. In our analysis, we have focused on four neoplasms: lung, colon, ovarian and prostate cancers. The median time for pre-GOM and GOM Times was calculated for each tumour site. Univariate and multivariate logistic regressions were performed to individuate risk factors for pre-GOM and GOM Time. RESULTS: Significant differences were observed for prostate cancer compared to other patients either for pre-GOM or GOM Times. Significant risks were found for ovarian and prostate cancers in pre-GOM time and for prostate cancer in GOM-Time. CONCLUSIONS: This experience will produce knowledge and data to guide decision-making and to manage more effectively the challenges of fighting cancer in Campania region. The Valutazione Percorso Rete Oncologica Campana (ValPeROC) study evaluates, for the first time, the ROC activity, through the analysis of key performance indices. Pre-GOM and GOM Time represent the quality of the entire regional health system and are useful to define models, which can evaluate the performance of the ROC over time.

Radiomics and machine learning analysis based on magnetic resonance imaging in the assessment of liver mucinous colorectal metastases.

PURPOSE: The purpose of this study is to evaluate the Radiomics and Machine Learning Analysis based on MRI in the assessment of Liver Mucinous Colorectal Metastases.Query METHODS: The cohort of patients included a training set (121 cases) and an external validation set (30 cases) with colorectal liver metastases with pathological proof and MRI study enrolled in this approved study retrospectively. About 851 radiomics features were extracted as median values by means of the PyRadiomics tool on volume on interest segmented manually by two expert radiologists. Univariate analysis, linear regression modelling and pattern recognition methods were used as statistical and classification procedures. RESULTS: The best results at univariate analysis were reached by the wavelet_LLH_glcm_JointEntropy extracted by T2W SPACE sequence with accuracy of 92%. Linear regression model increased the performance obtained respect to the univariate analysis. The best results were obtained by a linear regression model of 15 significant features extracted by the T2W SPACE sequence with accuracy of 94%, a sensitivity of 92% and a specificity of 95%. The best classifier among the tested pattern recognition approaches was k-nearest neighbours (KNN); however, KNN achieved lower precision than the best linear regression model. CONCLUSIONS: Radiomics metrics allow the mucinous subtype lesion characterization, in order to obtain a more personalized approach. We demonstrated that the best performance was obtained by T2-W extracted textural metrics.

Immunotherapy may protect cancer patients from SARS-CoV-2 infection: a single-center retrospective analysis.

Coronavirus disease 2019 (COVID-19) global pandemic has created unique challenges to healthcare systems throughout the world. Ensuring subjects' safety is mandatory especially in oncology, in consideration of cancer patients' particular frailty. We examined the proportion of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) IgM and/or IgG positive subjects in three different groups from Istituto Nazionale Tumori - IRCCS "Fondazione G. Pascale" in Naples (Campania region, Italy): cancer patients treated with Innovative Immunotherapy (Immune Checkpoint Inhibitors, ICIs), cancer patients undergoing standard Chemotherapies (CHTs) and healthcare providers. 9 out of 287 (3.1%) ICIs patients resulted positive, with a significant lower percentage in respect to CHTs patients (39 positive subjects out of 598, 6.5%) (p = 0.04). There was no statistically significant difference between ICIs cohort and healthcare providers, 48 out of 1050 resulting positive (4.6%). Performing a Propensity Score Matching based on gender and tumor stage, the effect of treatment on seropositivity was analyzed through a regression logistic model and the ICIs treatment resulted to be the only protective factor significantly (p = 0.03) associated with positivity (odds ratio-OR: 0.41; 95% confidence interval-CI 0.18-0.91). According to these preliminary data, ICIs would appear to be a protective factor against the onset of COVID-19 infection.

Validation of the standardized index of shape tool to analyze DCE-MRI data in the assessment of neo-adjuvant therapy in locally advanced rectal cancer.

PURPOSE: Standardized index of shape (SIS) tool validation to examine dynamic contrast enhanced-magnetic resonance imaging (DCE-MRI) in preoperative chemo-radiation therapy (pCRT) assessment of locally advanced rectal cancer (LARC) in order to guide the surgeon versus more or less conservative treatment. MATERIALS AND METHODS: A total of 194 patients (January 2008-November 2020), with III-IV locally advanced rectal cancer and subjected to pCRT were included. Three expert radiologists performed DCE-MRI analysis using SIS tool. Degree of absolute agreement among measurements, degree of consistency among measurements, degree of reliability and level of variability were calculated. Patients with a pathological tumour regression grade (TRG) 1 or 2 were classified as major responders (complete responders have TRG 1). RESULTS: Good significant correlation was obtained between SIS measurements (range 0.97-0.99). The degree of absolute agreement ranges from 0.93 to 0.99, the degree of consistency from 0.81 to 0.9 and the reliability from 0.98 to 1.00 (p value < < 0.001). The variability coefficient ranges from 3.5% to 26%. SIS value obtained to discriminate responders by non-responders a sensitivity of 95.9%, a specificity of 84.7% and an accuracy of 91.8% while to detect complete responders, a sensitivity of 99.2%, a specificity of 63.9% and an accuracy of 86.1%. CONCLUSION: SIS tool is suitable to assess pCRT response both to identify major responders and complete responders in order to guide the surgeon versus more or less conservative treatment.

Immunological effects of adjuvants in subsets of antigen presenting cells of cancer patients undergoing chemotherapy.

BACKGROUND: We have previously shown that HCC patients and healthy subjects are equally responsive to a RNAdjuvant®, a novel TLR-7/8/RIG-I agonist based on noncoding RNA developed by CureVac, by an ex vivo evaluation. However, the immunological effect of adjuvants on immune cells from cancer patients undergoing chemotherapy remains to be demonstrated. Different adjuvants currently used in cancer vaccine clinical trials were evaluated in the present study on immune cells from cancer patients before and after chemotherapy in an ex vivo setting. METHODS: PBMCs were obtained from 4 healthy volunteers and 23 patients affected by either colon (OMA) or lung cancer (OT). The effect of CpG, Poly I:C, Imiquimod and RNA-based adjuvant (RNAdjuvant®) was assessed using a multiparametric approach to analyze network dynamics of early immune responses. Evaluation of CD80, CD86 and HLA-DR expression as well as the downstream effect on CD4+ T cell phenotyping was performed by flow cytometry; cytokine and chemokine production was evaluated by Bio-Plex ProTM. RESULTS: Treatment with RNAdjuvant® induced the strongest response in cancer patients in terms of activation of innate and adoptive immunity. Indeed, CD80, CD86 and HLA-DR expression was found upregulated in circulating dendritic cells, which promoted a CD4+ T cell differentiation towards an effector phenotype. RNAdjuvant® was the only one to induce most of the cytokines/chemokines tested with a pronounced Th1 cytokine pattern. According to the different parameters evaluated in the study, no clear cut difference in immune response to adjuvants was observed between healthy subjects and cancer patients. Moreover, in the latter group, the chemotherapy treatment did not consistently correlate to a significant altered response in the different parameters. CONCLUSIONS: The present study is the first analysis of immunological effects induced by adjuvants in cancer patients who undergo chemotherapy, who are enrolled in the currently ongoing cancer vaccine clinical trials. The results show that the RNAdjuvant® is a potent and Th1 driving adjuvant, compared to those tested in the present study. Most importantly, it is demonstrated that chemotherapy does not significantly impair the immune system, implying that cancer patients are likely to respond to a cancer vaccine even after a chemotherapy treatment.

Cetuximab, irinotecan and fluorouracile in fiRst-line treatment of immunologically-selected advanced colorectal cancer patients: the CIFRA study protocol.

BACKGROUND: Combination of chemotherapies (fluoropirimidines, oxaliplatin and irinotecan) with biologic drugs (bevacizumab, panitumumab, cetuximab) have improved clinical responses and survival of metastatic colorectal cancer (mCRC). However, patients' selection thorough the identification of predictive factors still represent a challange. Cetuximab (Erbitux®), a chimeric monoclonal antibody binding to the Epidermal Growth Factor Receptor (EGFR), belongs to the Immunoglobulins (Ig) grade 1 subclass able to elicite both in vitro and in vivo the Antibody-Dependent Cell-mediated Cytotoxicity (ADCC). ADCC is the cytotoxic killing of antibody-coated target cells by immunologic effectors. The effector cells express a receptor for the Fc portion of these antibodies (FcγR); genetic polymorphisms of FcγR modify the binding affinity with the Fc of IgG1. Interestingly, the high-affinity FcγRIIIa V/V is associated with increased ADCC in vitro and in vivo. Thus, ADCC could partially account for cetuximab activity. METHODS/DESIGN: CIFRA is a single arm, open-label, phase II study assessing the activity of cetuximab in combination with irinotecan and fluorouracile in FcγRIIIa V/V patients with KRAS, NRAS, BRAF wild type mCRC. The study is designed with a two-stage Simon model based on a hypothetical higher response rate (+ 10%) of FcγRIIIa V/V patients as compared to previous trials (about 60%) assuming ADCC as one of the possible mechanisms of cetuximab action. The test power is 95%, the alpha value of the I-type error is 5%. With these assumptions the sample for passing the first stage is 14 patients with > 6 responses and the final sample is 34 patients with > 18 responses to draw positive conclusions. Secondary objectives include toxicity, responses' duration, progression-free and overall survival. Furthermore, an associated translational study will assess the patients' cetuximab-mediated ADCC and characterize the tumor microenvironment. DISCUSSION: The CIFRA study will determine whether ADCC contributes to cetuximab activity in mCRC patients selected on an innovative immunological screening. Data from the translational study will support results' interpretation as well as provide new insights in host-tumor interactions and cetuximab activity. TRIAL REGISTRATION: The CIFRA trial (version 0.0, June 21, 2018) has been registered into the NIH-US National Library of Medicine, ClinicalTrials.gov database with the identifier number ( NCT03874062 ).

Diagnostic performance of gadoxetic acid-enhanced liver MRI versus multidetector CT in the assessment of colorectal liver metastases compared to hepatic resection.

BACKGROUND: Imaging is an essential tool in the management of patients with Colorectal cancer (CRC) by helping evaluate number and sites of metastases, determine resectability, assess response to treatment, detect drug toxicities and recurrences. Although multidetector computed tomography (MDCT) is the first tool used for staging and patient's surveillance, magnetic resonance imaging (MRI) is the most reliable imaging modality that allows to assess liver metastases. Our purpose is to compare the diagnostic performance of gadoxetic acid-(Gd-EOB) enhanced liver MRI and contrast-enhanced MDCT in the detection of liver metastasis from colorectal cancer (mCRC). METHODS: One hundred and twenty-eight patients with pathologically proven mCRC (512 liver metastases) underwent Gd-EOB MRI and MDCT imaging. An additional 46 patients without mCRC were included as control subjects. Three radiologists independently graded the presence of liver nodules on a five-point confidence scale. Sensitivity and specificity for the detection of metastases were calculated. Weighted к values were used to evaluate inter-reader agreement of the confidence scale regarding the presence of the lesion. RESULTS: MRI detected 489 liver metastases and MDCT 384. In terms of per-lesion sensitivity in the detection of liver metastasis, all three readers had higher diagnostic sensitivity with Gd-EOB MRI than with MDCT (95.5% vs. 72% reader 1; 90% vs. 72% reader 2; 96% vs. 75% reader 3). Each reader showed a statistical significant difference (p < <.001 at Chi square test). MR imaging showed a higher performance than MDCT in per-patient detection sensitivity (100% vs. 74.2% [p < <.001] reader 1, 98% vs. 73% [p < <.001] reader 2, and 100% vs. 78% [p < <.001] reader 3). In the control group, MRI and MDCT showed similar per-patient specificity (100% vs. 98% [p = 0.31] reader 1, 100% vs. 100% [p = 0.92] reader 2, and 100% vs. 96% [p = 0.047] reader 3). Inter-reader agreement of lesion detection between the three radiologists was moderate to excellent (k range, 0.56-0.86) for Gd-EOB MRI and substantial to excellent for MDCT (k range, 0.75-0.8). CONCLUSION: Gadoxetic acid-enhanced MRI performs significantly better in the detection of mCRC, than MDCT, particularly in patients treated with chemotherapy, in subcapsular lesions, and in peribiliary metastases.

Posterior HOX genes and HOTAIR expression in the proximal and distal colon cancer pathogenesis.

BACKGROUND: Increasing evidences showed that the location of the primary tumor on the right (proximal) or left (distal) side of the colon have a prognostic/predictive value for colon cancer patients. However, the understanding of the molecular mechanisms that contribute to the pathogenesis in different location of colon is still unclear. Probably an important role could be played by genes that control the spatial-temporal development of bodily structures, such as HOX genes. METHODS: The main purpose of this study was to analyze the expression of the paralogous 13 HOX genes and of the HOX regulating lncRNA HOTAIR in distal and proximal CRC cases. We have carried out a Tissue Micro Array with left and right CRC samples associated with all clinical-pathological parameters of patients. The expression of HOX genes was evaluated by immunohistochemistry and the staining of HOTAIR was performed by in situ hybridization using a specifically designed LNA probe. RESULTS: All paralogous 13 HOX genes and HOTAIR are silent in normal tissue and expressed in CRC samples. HOXB13, HOXC13 and HOTAIR showed a statistical association with lymph nodes metastasis (p value = 0.003, p value = 0.05, p value = 0.04). HOXB13, HOXC13 and lncRNA HOTAIR are overexpressed in right CRCs samples (p value < 0 and p value = 0.021). HOTAIR is also strongly correlated with HOXB13 (p value = 0.02) and HOXC13 (p value = 0.042) expression. CONCLUSIONS: Our data highlighted an important role of posterior HOX genes in colorectal cancer carcinogenesis. Specifically, the aberrant expression of the HOXB13, HOXC13 and HOTAIR in proximal colon cancers could add an important dowel in understanding molecular mechanisms related to tumor pathogenesis in this location.

Estimating Survival Probabilities of Advanced Gastric Cancer Patients in the Second-Line Setting: The Gastric Life Nomogram.

OBJECTIVE: We built and externally validated a nomogram for predicting the overall survival (OS) probability of advanced gastric cancer patients receiving second-line treatment. METHODS: The nomogram was developed on a set of 320 Italian patients and validated on two independent sets (295 Italian and 172 Korean patients). Putative prognostic variables were selected using a random forest model and included in the multivariable Cox model. The nomogram's performance was evaluated by calibration plot and C index. RESULTS: ECOG performance status, neutrophils to lymphocytes ratio, and peritoneal involvement were selected and included into the multivariable model. The C index was 0.72 (95% CI 0.68-0.75) in the development set, 0.69 (95% CI 0.65-0.73) in the Italian validation set, but only 0.57 (95% CI 0.52-0.62) in the Korean set. While Italian calibrations were quite good, the Korean one was poor. Regarding 6-month OS predictions, calibration was best in both Caucasian cohorts and worst the in Asian one. CONCLUSIONS: Our nomogram may be a useful tool to predict 3- or 6-month OS in Caucasian gastric cancer patients eligible for second-line therapy. Based on three easy-to-collect variables, the Gastric Life nomogram may help clinicians improve patient selection for second-line treatments and assist in clinical trial enrollment.

A radiologist's point of view in the presurgical and intraoperative setting of colorectal liver metastases.

Multidisciplinary management of patients with metastatic colorectal cancer requires in each phase an adequate choice of the most appropriate imaging modality. The first challenging step is liver lesions detection and characterization, using several imaging modality ultrasound, computed tomography, magnetic resonance and positron emission tomography. The criteria to establish the metastases resectability have been modified. Not only the lesions number and site but also the functional volume remnant after surgery and the quality of the nontumoral liver must be taken into account. Radiologists should identify the liver functional volume remnant and during liver surgical procedures should collaborate with the surgeon to identify all lesions, including those that disappeared after the therapy, using intraoperative ultrasound with or without contrast medium.

Outcomes of Advanced Gastric Cancer Patients Treated with at Least Three Lines of Systemic Chemotherapy.

BACKGROUND: Second-line therapy has consistently demonstrated survival benefit if compared with best supportive care; however, there is limited evidence whether further lines of treatment may improve the prognosis of advanced gastric cancer (AGC) patients. MATERIALS AND METHODS: Starting from a real-world cohort of 868 AGC patients, we retrospectively analyzed baseline parameters, tumor characteristics, and treatment data of those treated with at least three lines. Categorical features were described through cross-tables and chi-square test. We explored the impact of treatment intensity and progression-free survival (PFS) experienced in previous lines on PFS and overall survival in third-line by uni- and multivariate Cox regression models and described by Kaplan-Meier estimator plot with log-rank test. RESULTS: Overall, 300 patients were included in the analysis. The most common site of primary tumor was gastric body; 45.3% of cancers had an intestinal histotype, 14% were human epidermal growth receptor 2 positive. In third-line, 45.7% of patients received a single-agent chemotherapy, 49.7% a combination regimen. Patients who had experienced a first-line PFS ≥6.9 months had a better prognosis compared with those who had achieved a shorter one. Consistently, a second-line PFS ≥3.5 months positively influenced the prognosis. Patients receiving a third-line combination regimen had better outcomes compared with those treated with a single-agent chemotherapy. CONCLUSION: Our real-world study confirms that selected AGC patients may receive third-line treatment. Longer PFS in previous lines or a more intense third-line treatment positively influenced prognosis. Further efforts are warranted to define the best therapeutic sequences, and to identify the optimal candidate for treatment beyond second-line. IMPLICATIONS FOR PRACTICE: The benefit of third-line treatment to advanced gastric cancer patients is controversial. This study depicts a real scenario of the clinical practice in Italy, confirming that a non-negligible proportion of patients receive a third-line therapy. Longer progression-free survival in previous treatment lines or higher third-line treatment intensity positively influenced prognosis. Including a large number of real-world patients, this study provides information on third-line treatment from the daily clinical practice; moreover, its results help in defining the best therapeutic sequence and offer some hints to select the optimal candidate for treatment beyond second-line.

Gemcitabine mono-therapy versus gemcitabine plus targeted therapy in advanced pancreatic cancer: a meta-analysis of randomized phase III trials.

BACKGROUND: Prognosis of advanced pancreatic cancer is dismal and the novel targeted therapies, albeit successfully used to treat many advanced tumors, have shown modest results. We performed a meta-analysis in order to quantify the effect size on survival of adding targeted therapy to single agent gemcitabine. METHODS: Randomized phase III trials comparing gemcitabine mono-therapy versus gemcitabine plus a targeted agent in first-line treatment of advanced pancreatic cancer designed on survival as primary outcome were selected. Search was done through Medline and the registry of the NIH. Keywords used for searching were 'pancreas', 'pancreatic', 'gemcitabine'. Study quality was assessed with MERGE criteria. Findings were depicted in classical Forest plots. Publication bias was evaluated by the construction of funnel plot. RESULTS: Nine studies met the meta-analysis inclusion criteria including 4564 patients. The target therapies were: erlotinib, cetuximab, rigosertib, elpamotide, bevacizumab, aflibercept, axitinib, masitinib and ganitumab. There was no statistically significant heterogeneity among the nine trials (p = 0.77). The hazard ratio (HR) of the pooled analysis was 0.998 (CI 95%: 0.932-1.068). Subgroup meta-analysis was also performed in anti-EGFR and anti-angiogenesis trials: the pooled HR were 0.94 (CI 95%: 0.705-1.175) and 1.055 (CI 95%: 0.913-1.197), respectively. CONCLUSIONS: The present meta-analysis does not show significant improvements in survival for targeted drugs in advanced pancreatic cancer. The possible reason of these results could be linked to the biology of pancreatic cancer as well as to the absence of predictive factors.