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Despite growing evidence of the relevance of alternative splicing (AS) to cancer development and progression, the biological implications of AS for tumor behaviors, including papillary thyroid cancer (PTC), remain elusive. With the aim of further understanding the molecular and histological subtypes of PTC, we in this study explored whether AS events might act as new molecular determinants. For this purpose, AS profiles were analyzed in RNA-sequencing data from The Cancer Genome Atlas (TCGA) and from a Korean patient dataset. A total of 23 distinct exon-skipping (ES) events that correlated significantly with PTC oncogenic activity and differentiation scores were identified. The two top-ranked ES events, NUMA1_17515 in exon 18 of NUMA1 and TUBB3_38175 in exon 6 of TUBB3, showed high correlations with oncogenic activities and discriminated histological and molecular subtypes of PTC. Furthermore, two novel intron-retention (IR) events for TUBB3 were uncovered. All ES and IR events for the TUBB3 gene were predicted to induce nonsense-mediated mRNA decay. The relative abundances of intron reads in the PTC dataset from TCGA showed IR levels to differ significantly among PTC subtypes, possibly reflecting their different tumor behaviors. This study provides a landscape of AS changes among PTC subtypes and identified two significant AS events, NUMA1_17515 and TUBB3_38175, as potential AS biomarkers for PTC subclassification and characterization. The AS events identified in this study may be involved in the development of phenotypic differences underlying the functional characteristics and histological differentiation of PTCs.

Bone destruction induced by breast cancer metastasis causes severe complications, including death, in breast cancer patients. Communication between cancer cells and skeletal cells in metastatic bone microenvironments is a principal element that drives tumor progression and osteolysis. Tumor-derived factors play fundamental roles in this form of communication. To identify soluble factors released from cancer cells in bone metastasis, we established a highly bone-metastatic subline of MDA-MB-231 breast cancer cells. This subline (mtMDA) showed a markedly elevated ability to secrete S100A4 protein, which directly stimulated osteoclast formation via surface receptor RAGE. Recombinant S100A4 stimulated osteoclastogenesis in vitro and bone loss in vivo. Conditioned medium from mtMDA cells in which S100A4 was knocked down had a reduced ability to stimulate osteoclasts. Furthermore, the S100A4 knockdown cells elicited less bone destruction in mice than the control knockdown cells. In addition, administration of an anti-S100A4 monoclonal antibody (mAb) that we developed attenuated the stimulation of osteoclastogenesis and bone loss by mtMDA in mice. Taken together, our results suggest that S100A4 released from breast cancer cells is an important player in the osteolysis caused by breast cancer bone metastasis.

Aim: Current gene-level prioritization methods aim to provide information for further prioritization of ‘disease-causing’ mutations. Since, they are inherently biased toward disease genes, methods specific to pharmacogenetic (PGx) genes are required. Methods: We proposed a gene-wise variant burden (GVB) method that integrates in silico deleteriousness scores of the multitude of variants of a given gene at a personal-genome level. Results: GVB in its simplest form outperformed the two state-of-the-art methods with regard to predicting pharmacogenes and complex disease genes but not for rare Mendelian disease genes. GVB* adjusted by paralog counts robustly performed well in most of the pharmacogenetic subcategories. Seven molecular genetic features well characterized the unique genomic properties of PGx, complex, and Mendelian disease genes. Conclusion: Altogether, GVB is an individual-specific genescore, especially advantageous for PGx studies.

Genetic variability can modulate individual drug responses. A significant portion of pharmacogenetic variants reside in the noncoding genome yet it is unclear if the noncoding variants directly influence protein function and expression or are present on a haplotype including a functionally relevant genetic variation (synthetic association). Gene-wise variant burden (GVB) is a gene-level measure of deleteriousness, reflecting the cumulative effects of deleterious coding variants, predicted in silico. To test potential associations between noncoding and coding pharmacogenetic variants, we computed a drug-level GVB for 5099 drugs from DrugBank for 2504 genomes of the 1000 Genomes Project and evaluated the correlation between the long-known noncoding variant-drug associations in PharmGKB, with functionally relevant rare and common coding variants aggregated into GVBs. We obtained the area under the receiver operating characteristics curve (AUC) by comparing the drug-level GVB ranks against the corresponding pharmacogenetic variants-drug associations in PharmGKB. We obtained high overall AUCs (0.710 &plusmn, 0.022&ndash, 0.734 &plusmn, 0.018) for six different methods (i.e., SIFT, MutationTaster, Polyphen-2 HVAR, Polyphen-2 HDIV, phyloP, and GERP++), and further improved the ethnicity-specific validations (0.759 &plusmn, 0.066&ndash, 0.791 &plusmn, 0.078). These results suggest that a significant portion of the long-known noncoding variant-drug associations can be explained as synthetic associations with rare and common coding variants burden of the corresponding pharmacogenes.

Preemptive and multi-variant genotyping is suggested to improve the safety of patient drug therapy. The number of South Koreans who would benefit from this approach is unknown. We aimed to quantify the number of patients who may experience serious adverse drug events (ADEs) due to high-risk pharmacogenetic variants and who may benefit from preemptive genotyping. The health claims dataset of the Korean Health Insurance Review and Assessment service for 3 % of the South Korean population for year 2011 was used to calculate the number of patients exposed to 84 drugs covered by National Health Insurance with pharmacogenomic biomarkers. The product of ADE risk-conferring genotype prevalence, ADE prevalence rates, and genotype effect sizes in South Koreans or East Asians derived from published literature and the 1000 Genomes Project, and the drug exposure data were solved to estimate the number of South Koreans in whom preemptive genotyping may prevent serious ADEs. Among 1,341,077 patients in the dataset with prescriptions, 47.4 % were prescribed a drug whose response was affected by genetic variants and 31.9 % were prescribed at least one drug with serious ADEs modulated by these variants. Without genetic testing, the number of South Korean patients predicted to experience serious ADEs due to their higher ADE risk genotypes was estimated at 729. Extrapolating this to the total South Korean population indicated that approximately 24,300 patients in 2011 might have benefitted from preemptive genotyping. This study quantified the number of South Korean patients predicted to have serious ADEs and demonstrated the need for preemptive genotyping to assist safer drug therapy in South Korea.