Pengaruh Komunikasi Terapeutik Perawat Terhadap Kepuasan Pasien Di Rawat Jalan RSUD Jogja

The Objective of this study is to know influence of nurse therapeutic communication to satisfaction of patients satisfaction in RSUD Yogyakarta. The study was a quantitative research methods such as surveys of descriptive inferential research with cross sectional approach. Number of samples in this research is 285 sample in inpatient and 140 in emergency room. The instrument used a questionnaire. Analysis of data using multiple linear regression. This study show that there is the influence of therapeutic communication nurse to satisfaction of outpatients and Emergency room in RSUD Yogyakarta, and orientation phase is a phase that most influence on patient satisfaction. The most influential to therapeutic communication is termination stage

Additional file 1: of Multicenter Phase II study of FOLFOX or biweekly XELOX and Erbitux (cetuximab) as first-line therapy in patients with wild-type KRAS/BRAF metastatic colorectal cancer: The FLEET study

Table listing the Central ethics committee and the IRBs of the participating institutes. The IRB of each participating institute reviewed and approved the protocol of the present study. (DOCX 17 kb

Integrative analysis of genomic alterations in triple-negative breast cancer in association with homologous recombination deficiency

<div><p>Triple-negative breast cancer (TNBC) cells do not express estrogen receptors, progesterone receptors, or human epidermal growth factor receptor 2. Currently, apart from poly ADP-ribose polymerase inhibitors, there are few effective therapeutic options for this type of cancer. Here, we present comprehensive characterization of the genetic alterations in TNBC performed by high coverage whole genome sequencing together with transcriptome and whole exome sequencing. Silencing of the <i>BRCA1</i> gene impaired the homologous recombination pathway in a subset of TNBCs, which exhibited similar phenotypes to tumors with <i>BRCA1</i> mutations; they harbored many structural variations (SVs) with relative enrichment for tandem duplication. Clonal analysis suggested that <i>TP53</i> mutations and methylation of CpG dinucleotides in the <i>BRCA1</i> promoter were early events of carcinogenesis. SVs were associated with driver oncogenic events such as amplification of <i>MYC</i>, <i>NOTCH2</i>, or <i>NOTCH3</i> and affected tumor suppressor genes including <i>RB1</i>, <i>PTEN</i>, and <i>KMT2C</i>. Furthermore, we identified putative <i>TGFA</i> enhancer regions. Recurrent SVs that affected the <i>TGFA</i> enhancer region led to enhanced expression of the <i>TGFA</i> oncogene that encodes one of the high affinity ligands for epidermal growth factor receptor. We also identified a variety of oncogenes that could transform 3T3 mouse fibroblasts, suggesting that individual TNBC tumors may undergo a unique driver event that can be targetable. Thus, we revealed several features of TNBC with clinically important implications.</p></div

Various oncogenes in triple-negative breast cancer (TNBC).

<p>(<b>A</b>) NFKB1 mutations found in this study (above, TNBC) and in the TCGA data (below, various cancers). (<b>B</b>) Mutations in NOTCH1 found in this study (above, TNBC) and in the TCGA data (below, TNBC). (<b>C</b>) Mutations in ERBB2 found in this study (above, TNBC) and in the TCGA data (below, BC). (<b>D</b>) Diagram of the protein encoded by the <i>FGFR3</i>-<i>CAT</i> fusion gene. IG, immunoglobulin-like domain; TyrKc, tyrosine-protein kinase catalytic domain. (<b>E</b>) Anchorage-independent growth of 3T3 cells expressing the indicated proteins. The diagrams of the proteins in (<b>A</b>), (<b>B</b>), and (<b>C</b>) were generated using protein painter (<a href="http://explore.pediatriccancergenomeproject.org/proteinPainter" target="_blank">http://explore.pediatriccancergenomeproject.org/proteinPainter</a>). Mutations expected to be activating according to previous reports or experiments in this study are highlighted in red.</p

Mutational signatures of triple-negative breast cancer (TNBC).

<p>(<b>A</b>) Three trinucleotide mutational signatures of single nucleotide variations (SNVs) in whole genome sequencing (WGS) data. (<b>B</b>) Numbers of structural variants (SVs), SNVs, and indels in each tumor (middle panel) in association with <i>RAD51C</i> and <i>BRCA1</i> mRNA expression levels (left panel) and distributions of the distance between breakpoints (right panel). Data are arranged in descending order of <i>BRCA</i> signature ratios among SNVs. SNV bars contain both truncal and subclonal SNVs. IDs for samples with a defective homologous recombination (HR) pathway are highlighted in red. <i>BRCA1</i> mRNA expression levels in tumors with <i>BRCA1</i> mutation are shown in gray. Transloc., translocation; Tandem., tandem duplication; Inv., inverted rearrangement; Del., deletion; FPKM, fragments per kilobase of transcript per million mapped reads. (<b>C</b>) Proportions of tandem duplications among all SVs. Green, <i>BRCA1</i> silenced or mutated; red, <i>RAD51C</i> silenced; yellow, others. The outlier in the <i>BRCA1</i> intact group is from TN-27 in which only six SVs were detected.</p

Clonal architecture of triple-negative breast cancer (TNBC).

<p>(<b>A</b>) CN-based clonal analysis of TN-19. Red and blue lines indicate log R ratios of major and minor alleles, respectively (upper panel). The green line indicates the cellularity of tumor cells harboring the corresponding allelic loss (middle panel). The black line was generated by sorting the plots in the middle panel in descending order (bottom panel). Each dot in the bottom panel represents the single nucleotide polymorphism (SNP) used for the calculation and is color-coded for chromosomes, as indicated in the middle panel. (<b>B</b>) Clonality of each subclone in the tumors. To calculate clonality, the cellularity of the truncal clone was set at 100%. (<b>C</b>) Single nucleotide variations (SNVs; blue vertical lines) together with the copy number (CN) status of chromosomes 3 and 8 in TN-19. The height of each line represents the variant allele frequency (VAF). CN status is color-scaled: red, gain; blue, loss. Clonal analyses of the indicated regions in TN-19 are shown in the middle: red, observed VAFs; black, cellularity predicted using PyClone. Clonal analysis of VAFs in all low CN regions combined is shown in the right panel. (<b>D</b>) Cellularity of each tumor along with the CN-adjusted allele frequency (VAFa) of <i>TP53</i> mutations (open diamond) and methylated CpG dinucleotides in the promoter regions of <i>BRCA1</i> (red solid circle) and <i>RAD51C</i> (blue solid circle). In the right panel, the same data are presented as a scatter plot showing the relationship between cellularity and VAFa of <i>TP53</i> mutations (open diamond), or <i>BRCA1</i> or <i>RAD51C</i> promoter methylation (red and blue solid circles, respectively).</p

Enhanced expression of <i>TGFA</i> is associated with structural variations (SVs) in the putative regulatory region.

<p>(<b>A</b>) mRNA expression of <i>TGFA</i> in ER+ breast cancer (BC) (green), HER2+ BC (yellow), and triple-negative BC (TNBC) (red). IDs for samples with SVs within or near the <i>TGFA</i> locus are shown. (<b>B</b>) SV break points and copy number (CN) status of samples indicated in (<b>A</b>). (<b>C</b>) <i>TGFA</i> mRNA expression based on The Cancer Genome Atlas (TCGA) data, depending on whether the SV is within or near the <i>TGFA</i> locus (left) or according to the CN status (right). (<b>D</b>) CN status of BCs, based on TCGA data, with presumed SVs within or near the <i>TGFA</i> locus. IDs for TNBC cases are shown in red. (<b>E</b>) Acetylation of the lysine residue at position 27 of histone H3 (H3K27ac) detected by ChIP-seq along with the CN status obtained from Cancer Cell Line Encyclopedia (CCLE) data. Data for human mammary epithelial cells (HMECs) were obtained from the Encyclopedia of DNA Elements (ENCODE) project data. (<b>F</b>) <i>TGFA</i> mRNA expression in BICR6 cell lines in which H3K27ac-enriched putative enhancers (e1–e7) were deleted using the CRISPR-Cas9 system. <i>P</i>-values were derived from t-tests. (<b>G</b>) Luciferase reporter assays measuring the enhancer activity of e6 and e7 in BICR6 cells. The pGL4.10 plasmid without the enhancer region (empty) was used as a negative control. Relative luciferase units were normalized to Renilla luciferase signals. The normalized value for empty vector was set to 1. <i>P</i>-values were derived from t-tests. (<b>H</b>) MCF10A cells expressing enhanced green fluorescent protein (EGFP) alone or TGFA together with EGFP, cultured in complete medium or medium without epidermal growth factor.</p

Structural variations (SVs) in triple-negative breast cancer (TNBC).

<p>(<b>A</b>) Two-dimensional kernel density estimation for the distance between breakpoints and read number. The horizontal axis denotes the supporting read number. The vertical axis denotes the distance between breakpoints. (<b>B</b>) Diagrams of chromosome 8 in TN-19, chromosome 19 in TN-9, and chromosome 3 in TN-2, along with SV and copy number (CN) statuses (left). Brown hexagons indicate centromeres. Each pair of break points is connected by a color-coded arch: red, tandem duplication; magenta, inverted rearrangement; blue, deletion. Note that the arches for small SVs appear to be vertical lines owing to limited resolution. CN status is color-scaled: red, gain; blue, loss. Presumed chromosomal rearrangement events are shown in the rectangles in the middle and on the right along with the resultant chromosomes below.</p

Additional file 4: Figure S3. of Predictive biomarkers for the efficacy of peptide vaccine treatment: based on the results of a phase II study on advanced pancreatic cancer

Frequency of CD4+ CD45RA- CD25high cells and CD11b + CD33+ cells. (a), (c) There were no differences in the percentages of CD4+ CD45RA- CD25high cells and CD11b + CD33+ cells in the 46 patients before and after treatment. (b), (e) Before and after treatment, there were no differences in the percentages of CD4+ CD45RA- CD25high cells and CD11b + CD33+ cells between the patients with a long survival (n = 6) and the patients with a short survival (n = 19) in the HLA-A*2402-matched group. (c), (f) Before and after treatment, there were no differences in the percentages of CD4+ CD45RA- CD25high cells and CD11b + CD33+ cells between the patients with a long survival (n = 6) and the patients with a short survival (n = 15) in the HLA-A*2402-unmatched group. (TIF 60 kb

Additional file 2: Table S1. of Predictive biomarkers for the efficacy of peptide vaccine treatment: based on the results of a phase II study on advanced pancreatic cancer

Comparison of prognostic factors according to the numbers of peptide-specific responses (n = 36 HLA-A*2402-matched patients). (DOCX 28 kb