Background

The goal of personalized medicine is to provide patients optimal drug screening and treatment based on individual genomic or proteomic profiles. Reverse-Phase Protein Array (RPPA) technology offers proteomic information of cancer patients which may be directly related to drug sensitivity. For cancer patients with different drug sensitivity, the proteomic profiling reveals important pathophysiologic information which can be used to predict chemotherapy responses.

Results

The goal of this paper is to present a framework for personalized medicine using both RPPA and drug sensitivity (drug resistance or intolerance). In the proposed personalized medicine system, the prediction of drug sensitivity is obtained by a proposed augmented naive Bayesian classifier (ANBC) whose edges between attributes are augmented in the network structure of naive Bayesian classifier. For discriminative structure learning of ANBC, local classification rate (LCR) is used to score augmented edges, and greedy search algorithm is used to find the discriminative structure that maximizes classification rate (CR). Once a classifier is trained by RPPA and drug sensitivity using cancer patient samples, the classifier is able to predict the drug sensitivity given RPPA information from a patient.

Conclusion

In this paper we proposed a framework for personalized medicine where a patient is profiled by RPPA and drug sensitivity is predicted by ANBC and LCR. Experimental results with lung cancer data demonstrate that RPPA can be used to profile patients for drug sensitivity prediction by Bayesian network classifier, and the proposed ANBC for personalized cancer medicine achieves better prediction accuracy than naive Bayes classifier in small sample size data on average and outperforms other the state-of-the-art classifier methods in terms of classification accuracy.

Subcutaneous panniculitis-like T-cell lymphoma (SPTL) is a distinctive lymphoma characterized by an infiltration of subcutaneous tissue by neoplastic cytotoxic T cells. There was no distinction between TCR alpha/beta phenotype and TCR gamma/delta phenotype, and anthracycline-based chemotherapy was usually used for both. Here, we report a patient with recurrent SPTL who achieved a second long-term complete remission by repeated cyclosporine A (CsA) treatment. From 2000 to 2001, the patient received anthracycline-based combination chemotherapy. However, the treatment did not induce long-term remission. In 2002, he received cyclosporine treatment for about 6 months. This resulted in a 5-year remission that ended in relapse in 2008. He received CsA treatment once again and attained a second long-term remission. This case suggests that re-treatment with CsA can be a good option for relapsed SPTL cases and can result in long-term remission.

The giant cell tumor of the salivary gland is very rare, and 20 cases have been reported in the English-language literature. We report an additional case. A 57-year old man had noticed a mass in the right parotid area for several weeks. The diagnosis using aspiration cytology was a giant cell tumor possibly with a carcinomatous component. Superficial parotidectomy was carried out. The resected parotid gland contained a 1.8 cm-sized well-circumscribed brownish tumor. Histologically the tumor consisted of evenly distributed osteoclast-like giant cells, mononuclear cells and two small foci of a carcinomatous component. The osteoclast-like giant cells and mononuclear cells were positive for vimentin and CD68, and the carcinomatous component was positive for cytokeratin and epithelial membrane antigen. There was no metastatic lesion in the cervical lymph nodes. We believe this is the first case in Korea of an osteoclast-like giant cell tumor of the parotid gland.

Purpose

This study was designed to determine the influencing factors and clinical course of pathologically proven cases of radiation-induced brain injury (RIBI).

Materials and Methods

The pathologic records of twelve patients were reviewed; these patients underwent surgery following radiotherapy due to disease progression found by follow-up imaging. However, they were finally diagnosed with RIBI. All patients had been treated with 3-dimensional conventional fractionated radiotherapy and/or radiosurgery for primary or metastatic brain tumors with or without chemotherapy. The histological distribution was as follows: two falx meningioma, six glioblastoma multiform (GBM), two anaplastic oligodendroglioma, one low grade oligodendroglioma, and one small cell lung cancer with brain metastasis.

Results

Radiation necrosis was noted in eight patients and the remaining four were diagnosed with radiation change. Gender (p = 0.061) and biologically equivalent dose (BED)3 (p = 0.084) were the only marginally influencing factors of radiation necrosis. Median time to RIBI was 7.3 months (range, 0.5 to 61 months). Three prolonged survivors with GBM were observed. In the subgroup analysis of high grade gliomas, RIBI that developed <6 months after radiotherapy was associated with inferior overall survival rates compared to cases of RIBI that occurred ≥6 months (p = 0.085).

Conclusion

Our study demonstrated that RIBI could occur in early periods after conventional fractionated brain radiotherapy within normal tolerable dose ranges. Studies with a larger number of patients are required to identify the strong influencing factors for RIBI development.

Background

Biological networks offer us a new way to investigate the interactions among different components and address the biological system as a whole. In this paper, a reverse-phase protein microarray (RPPM) is used for the quantitative measurement of proteomic responses.

Results

To discover the signaling pathway responsive to RPPM, a new structure learning algorithm of Bayesian networks is developed based on mutual Information, conditional independence, and graph immorality. Trusted biology networks are thus predicted by the new approach. As an application example, we investigate signaling networks of ataxia telangiectasis mutation (ATM). The study was carried out at different time points under different dosages for cell lines with and without gene transfection. To validate the performance ofthe proposed algorithm, comparison experiments were also implemented using three well-known networks. From the experiment results, our approach produces more reliable networks with a relatively small number of wrong connection especially in mid-size networks. By using the proposed method, we predicted different networks for ATM under different doses of radiation treatment, and those networks were compared with results from eight different protein protein interaction (PPI) databases.

Conclusions

By using a new protein microarray technology in combination with a new computational framework, we demonstrate an application of the methodology to the study of biological networks of ATM cell lines under low dose ionization radiation.

The distinction between benign and malignant thyroid tumors is critical for the management of patients with thyroid nodules. We applied immunohistochemical staining for galectin-3, HBME-1, cytokeratin 19 (CK19), high molecular weight cytokeratin (HMWCK), cyclin D1 and p27kip1 in 295 thyroid lesions to determine their diagnostic accuracy. The expression of all markers was significantly associated with differentiated thyroid carcinoma (DTC).The sensitivity for the diagnosis of DTC was 94.7% with galectin-3, 91.3% with HBME-1, and 90.3% with CK19. The specificities of these markers were 95.5%, 69.7%, and 83.1%, respectively. Combining these markers, co-expression of galectin-3 and CK19 or galectin-3 and HBME-1 was seen in 93.2% of carcinomas but in none of the benign nodules. Comparing follicular variant of papillary carcinoma (FVPC) with follicular carcinoma (FC), the expression of galectin-3, CK19, and HMWCK was significantly higher in FVPC. When comparing FC with FA, the expression of galectin-3 and HBME-1 was significantly higher in FC. These results suggest that 1) galectin-3 is a useful marker in the distinction between benign and malignant thyroid tumors, 2) the combined use of HBME-1 and CK19 can increase the diagnostic accuracy, and 3) the use of CK19 and HMWCK can aid in the differential diagnosis between PC and FC.

We report the imaging findings in a case of fetal lymphangioma involving the retroperitoneum and right lower extremity, and diagnosed by ultrasonography and magnetic resonance (MR) imaging at 26 weeks of gestation. Prenatal ultrasonograms and T2-weighted single-shot fast spin-echo MR images clearly revealed an extensive, multilocular cystic mass with internal hemorrhage in the retroperitoneum extending to the lower extremity.