p31comet-Induced Cell Death Is Mediated by Binding and Inactivation of Mad2

Fully-automated detection of small bowel carcinoid tumors in CT scans using deep learning

BACKGROUND

Small bowel carcinoid tumor is a rare neoplasm and increasing in incidence. Patients with small bowel carcinoid tumors often experience long delays in diagnosis due to the vague symptoms, slow growth of tumors, and lack of clinician awareness. Computed tomography (CT) is the most common imaging study for diagnosis of small bowel carcinoid tumor. It is often used with positron emission tomography (PET) to capture anatomical and functional aspects of carcinoid tumors and thus to increase the sensitivity.

PURPOSE

We compared three different kinds of methods for the automatic detection of small bowel carcinoid tumors on CT scans, which is the first to the best of our knowledge.

METHODS

Thirty-three preoperative CT scans of 33 unique patients with surgically-proven carcinoid tumors within the small bowel were collected. Ground-truth segmentation of tumors was drawn on CT scans by referring to available 18 F-DOPA PET scans and the corresponding radiology report. These scans were split into the trainval set (n = 24) and the test positive set (n= 9). Additionally, 22 CT scans of 22 unique patients who had no evidence of the tumor were collected to comprise the test negative set. We compared three different kinds of detection methods, which are detection network, patch-based classification, and segmentation-based methods. We also investigated the usefulness of small bowel segmentation for reduction of false positives (FPs) for each method. Free-response receiver operating characteristic (FROC) curves and receiver operating characteristic (ROC) curves were used for lesion- and patient-level evaluations, respectively. Statistical analyses comparing the FROC and ROC curves were also performed.

RESULTS

The detection network method performed the best among the compared methods. For lesion-level detection, the detection network method, without the small bowel segmentation-based filtering, achieved sensitivity values of (60.8%, 81.1%, 82.4%, 86.5%) at per-scan FP rates of (1, 2, 4 ,8), respectively. The use of the small bowel segmentation did not improve the performance (p = 0.742 $p=0.742$ ). For patient-level detection, again the detection network method, but with the small bowel segmentation-based filtering, achieved the highest AUC of 0.86 with a sensitivity of 78% and specificity of 82% at the Youden point.

CONCLUSIONS

The carcinoid tumors in this patient population were very small and potentially difficult to diagnose. The presented method showed reasonable sensitivity at small numbers of FPs for lesion-level detection. It also achieved a promising AUC for patient-level detection. The method may have clinical application in patients with this rare and difficult to detect disease.

The Mad2-Binding Protein p31comet as a Potential Target for Human Cancer Therapy

The spindle assembly checkpoint (SAC) is a surveillance mechanism that prevents mitotic exit at the metaphase-to-anaphase transition until all chromosomes have established correct bipolar attachment to spindle microtubules. Activation of SAC relies on the assembly of the mitotic checkpoint complex (MCC), which requires conformational change from inactive open Mad2 (OMad2) to the active closed Mad2 (C-Mad2) at unattached kinetochores. The Mad2-binding protein p31^comet plays a key role in controlling timely mitotic exit by promoting SAC silencing, through preventing Mad2 activation and promoting MCC disassembly. Besides, increasing evidences highlight the p31^comet potential as target for cancer therapy. Here, we provide an updated overview of the functional significance of p31^comet in mitotic progression, and discuss the potential of deregulated expression of p31^comet in cancer and in therapeutic strategies.

MAD2-p31comet axis deficiency reduces cell proliferation, migration and sensitivity of microtubule-interfering agents in glioma

Mitotic arrest deficient-like-1 (MAD2, also known as MAD2L1) is thought to be an important spindle assembly checkpoint protein, which ensures accurate chromosome segregation and is closely associated with poor prognosis in many cancer. As a MAD2 binding protein, p31^comet counteracts the function of MAD2 and leads to mitotic checkpoint silence. In this study, we explore the function of MAD2-p31^comet axis in malignant glioma cells. Our results showed that disruption of MAD2-p31^comet axis by MAD2 knockdown or p31^comet overexpression suppressed cell proliferation, survival and migration of glioma, indicating that MAD2-p31^comet axis is required for maintaining glioma cells malignancy. It is noted that MAD2 depletion or p31^comet overexpression reduced the sensitivity of glioma cells to microtubule-interfering agents paclitaxel and vinblastine, providing clinical guidance for application of such drugs. Taken together, our findings suggest that MAD2-p31^comet axis may serve as a potential therapeutic target for glioma.