EVALUATION OF ACCURACY AND INTRINSIC UNCERTAINTY OF AUTOMATED IMAGE REGISTRATION FOR A 6D KV-CBCT IMAGE GUIDANCE SYSTEM: A CONCURRENT ANALYSIS WITH A MACHINE PERFORMANCE CHECK.

The accuracy and uncertainty of the automated image registration (AIR) algorithm in a six-dimensional (6D) kilovoltage cone-beam computed tomography (kV-CBCT) image-guided radiation therapy (IGRT) system were evaluated with a concurrent analysis of machine performance check (MPC). The MPC was performed before (MPCpre) and after (MPCpost) each accuracy and intrinsic uncertainty measurement. The accuracy was evaluated for 25 sets of the known shifts applied to the Catphan-504 phantom through a 6D robotic couch in the head, thorax, and pelvis CBCT acquisition modes. The uncertainty was evaluated for the intensity range, soft tissue, and bone matching filters in the head, thorax and pelvis CBCT acquisition modes. The mean ΔMPC (MPCpost-MPCpre) for all test parameters was within 0.02 ± 0.08 mm and 0.00 ± 0.02°. The overall average accuracy in AIR of 6D kV-CBCT IGRT in all translational and rotational axes was within 0.05 ± 0.76 mm and 0.02 ± 0.07°, respectively, for all CBCT modes. The overall mean population (Mpop), systematic (Σ) and random (σ) errors were within 0.47, 0.53 and 0.24 mm and within 0.03, 0.08 and 0.07° in translational and rotational axes, respectively, for all matching filters in all CBCT modes. The accuracy and intrinsic uncertainty in the AIR of the 6D kV-CBCT IGRT were within acceptable limits for clinical use.

The landscape of alternative splicing in buccal mucosa squamous cell carcinoma.

OBJECTIVES: Alternative splicing (AS) is a key regulatory mechanism in the process of protein synthesis generating transcriptome and proteome diversity. In this study, we attempted to identify alternative splicing in a pair of BMSCC cancer and adjacent normal tissue using RNAseq datasets and also assessed the potential of these datasets to provide quantitative measurements for alternative splicing levels. MATERIALS AND METHODS: We performed high-throughput sequencing of buccal mucosal cancer and healthy tissue cDNA library which resulted in a transcriptome map of BMSCC cancer. RNAseq analysis was performed to assess alternative splicing complexity in cancer tissue and to search splice junction sequences that represent candidate 'new' splicing events. The splice junctions were predicted by SpliceMap software and putative assembled transcripts validated using the RT-PCR. We also analyzed the coding potential of alternative spliced candidate by HMMER. RESULTS: We detected a total of 11 novel splice junctions derived mostly from alternate 5' splice site; including two of them which contained new translation initiation sites (TISs). We have identified novel IgG pseudogene and a fusion transcript of MEMO1 and RPS9, which were further confirmed by PCR from genomic DNA. We also found novel putative long non-coding RNA (lncRNA), which is antisense to SPINK5 gene. The coding potential of these AS variants revealed that alternative splicing caused premature termination, insertion/deletion of amino acid (s) or formation of novel N-terminus. CONCLUSIONS: Differential splicing of these novel AS variants between cancer and adjacent normal tissue suggests their involvement in BMSCC cancer development and progression.

Identification of novel transcripts deregulated in buccal cancer by RNA-seq.

The differential transcriptome analysis provides better understanding of molecular pathways leading to cancer, which in turn allows designing the effective strategies for diagnosis, therapeutic intervention and prediction of therapeutic outcome. This study describes the transcriptome analysis of buccal cancer and normal tissue by CLC Genomics Workbench from the data generated by Roche's 454 sequencing platform, which identified total of 1797 and 2655 genes uniquely expressed in normal and cancer tissues, respectively with 2466 genes expressed in both tissues. Among the genes expressed in both tissues, 1842 were up-regulated whereas 624 were down-regulated in cancer tissue. Besides transcripts known to be involved in cancer, this study led to the identification of novel transcripts, with significantly altered expression in buccal cancer tissue, providing potential targets for diagnosis and cancer therapeutics. The functional categorization by the KEGG pathway and gene ontology analysis revealed enrichment of differentially expressed transcripts to various pathways leading to cancer, including the p53 signaling pathway. Moreover, the gene ontology analysis unfolded suppression of transcripts involved in actin mediated cell contraction process. The down-regulation of four of these transcripts MYL1, ACTA1, TCAP and DESMIN in buccal cancer were further supported by quantitative PCR signifying its possible implication in the cancer progression.