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The characterization of cancer genomes has provided insight into somatically altered genes across tumors, transformed our understanding of cancer biology, and enabled tailoring of therapeutic strategies. However, the function of most cancer alleles remains mysterious, and many cancer features transcend their genomes. Consequently, tumor genomic characterization does not influence therapy for most patients. Approaches to understand the function and circuitry of cancer genes provide complementary approaches to elucidate both oncogene and non-oncogene dependencies. Emerging work indicates that the diversity of therapeutic targets engendered by non-oncogene dependencies is much larger than the list of recurrently mutated genes. Here we describe a framework for this expanded list of cancer targets, providing novel opportunities for clinical translation.

Background and aim Data on the radiologic evaluation of perianal fistulizing Crohn's disease (PFCD) naïve to anti-tumor necrosis factor therapy are scarce, especially in Asian populations. We assessed the effectiveness of infliximab (IFX) on PFCD and explored predictors of 'deep remission' based on clinical and radiologic assessments. Methods Patients with Crohn's disease and active anal fistulas attending our care center for IFX therapy were prospectively enrolled. Each patient underwent clinical examination according to the Fistula Drainage Assessment Index, endoscopy for assessment of Crohn's Disease Activity Index (CDAI) and Perianal Crohn's Disease Activity Index (PCDAI), magnetic resonance imaging (MRI) to determine Van Assche score and Ng score, and laboratory tests up to 2 weeks prior to the start of and up to 2 weeks after the sixth IFX therapy (Week 32). Results Among 38 patients treated with IFX, 52.6% achieved clinical remission based on the Fistula Drainage Assessment Index and 42.1% achieved deep remission based on Ng score. Van Assche score (from 14.5 ± 4.26 to 7.36 ± 7.53), CDAI (from 170 ± 92 to 71 ± 69) and PCDAI (from 7.45 ± 2.65 to 2.44 ± 3.20) decreased significantly after six IFX treatments. The only predictor of deep remission was simple fistula (P  =   0.004, odds ratio = 3.802, 95% confidence interval: 1.541–9.383). Conclusions IFX has been shown to have appreciable effectiveness in Chinese patients with PFCD. MRI is the gold standard for evaluating PFCD, but Van Assche score has some limitations. [ABSTRACT FROM AUTHOR]

Image registration is of great clinical importance in computer aided diagnosis and surgical planning of liver diseases. Deep learning-based registration methods endow liver computed tomography (CT) image registration with characteristics of real-time and high accuracy. However, existing methods in registering images with large displacement and deformation are faced with the challenge of the texture information variation of the registered image, resulting in subsequent erroneous image processing and clinical diagnosis. To this end, a novel unsupervised registration method based on the texture filtering is proposed in this paper to realize liver CT image registration. Firstly, the texture filtering algorithm based on L0 gradient minimization eliminates the texture information of liver surface in CT images, so that the registration process can only refer to the spatial structure information of two images for registration, thus solving the problem of texture variation. Then, we adopt the cascaded network to register images with large displacement and large deformation, and progressively align the fixed image with the moving one in the spatial structure. In addition, a new registration metric, the histogram correlation coefficient, is proposed to measure the degree of texture variation after registration. Experimental results show that our proposed method achieves high registration accuracy, effectively solves the problem of texture variation in the cascaded network, and improves the registration performance in terms of spatial structure correspondence and anti-folding capability. Therefore, our method helps to improve the performance of medical image registration, and make the registration safely and reliably applied in the computer-aided diagnosis and surgical planning of liver diseases.