14 research outputs found
Combination of a six microRNA expression profile with four clinicopathological factors for response prediction of systemic treatment in patients with advanced colorectal cancer
Background First line chemotherapy is effective in 75 to 80% of patients with metastatic colorectal cancer (mCRC). We studied whether microRNA (miR) expression profiles can predict treatment outcome for first line fluoropyrimidine containing systemic therapy in patients with mCRC. Methods MiR expression levels were determined by next generation sequencing from snap frozen tumor samples of 88 patients with mCRC. Predictive miRs were selected with penalized logistic regression and posterior forward selection. The prediction co-efficients of the miRs were re-estimated and validated by real-time quantitative PCR in an independent cohort of 81 patients with mCRC. Results Expression levels of miR-17-5p, miR-20a-5p, miR-30a-5p, miR-92a-3p, miR-92b-3p and miR-98-5p in combination with age, tumor differentiation, adjuvant therapy and type of systemic treatment, were predictive for clinical benefit in the training cohort with an AUC of 0.78. In the validation cohort the addition of the six miR signature to the four clinicopathological factors demonstrated a significant increased AUC for predicting treatment response versus those with stable disease (SD) from 0.79 to 0.90. The increase for predicting treatment response versus progressive disease (PD) and for patients with SD versus those with PD was not significant. in the validation cohort. MiR-17-5p, miR-20a-5p and miR-92a-3p were significantly upregulated in patients with treatment response in both the training and validation cohorts. Conclusion A six miR exp
Graft failure and revision rate after ACL repair with dynamic intraligamentary stabilization. One-year results of a prospective case series of 155 patients
Abstract Purpose The aim of this study was to assess graft failure, revision rate, and functional outcomes after treatment of acute ACL rupture with dynamic intraligamentary stabilization (DIS) Ligamys device one year post surgery. Additionally, differences in functional outcome between patients with and without anteroposterior laxity were assessed. It was hypothesized that the failure rate of DIS was non-inferior to that of previously reported ACL reconstruction (10%). Methods In this prospectively designed multicenter study, including patients with an acute ACL rupture, DIS was performed within 21 days after rupture. Primary outcome was failure of the graft at 1 year post surgery, defined as 1) re-rupture of the graft, 2) revision of DIS, or 3) a > 3 mm side-to-side difference in anterior tibial translation compared to the non-operated knee (∆ATT), measured by the KT1000 device. Additional analysis was performed using a 5 mm threshold. The subjective International Knee Documentation Committee Score (IKDC) and Numerical Rating Scales (NRS) for pain and confidence were used to evaluate functional outcome. Results A total of 155 patients were included with a mean age at surgery of 27.8 years (SD 9.4). The mean interval from rupture to DIS was 16.4 days (SD 5.2). At a median follow-up of 13 months (IQR 12–18) the failure rate of the graft was 30.2% (95%CI:22.0–39.4); 11 patients (7%) required secondary reconstructive surgery and of the 105 patients who attended ATT measurement, 24 patients (23%) had an ∆ATT > 3 mm. Secondary analysis, based on a 5 mm threshold, revealed a failure rate of 22.4% (95%CI: 15.2; 31.1). A total of 39 patients (25%) reported at least one complication, comprising mainly arthrofibrosis, traumatic re-rupture and pain. In these patients, removal of the monoblock was performed in 21 cases (13.5%). At follow-up no significant differences in functional outcomes between patients with ∆ATT > 3 mm and stable ATT were observed. Conclusion This prospective multicenter study found a high failure rate at one year follow-up of 30% (7% revision surgery and 23% > 3 mm side-to-side difference in anterior tibial translation) in patients treated by primary repair of the ACL with DIS, and did therefore not demonstrate non-inferiority to ACL reconstruction. For patients who did not require secondary reconstructive surgery, this study found good functional outcomes, also in case of persistent anteroposterior knee laxity (∆ATT > 3 mm). Level of evidence Level IV
Facteurs de risque influençant la douleur postopératoire dans les trois premières semaines après chirurgie de l’épaule arthroscopique ou à ciel ouvert
The effect of timing of mechanical stimulation on proliferation and differentiation of goat bone marrow stem cells cultured on braided PLGA scaffolds
Bone marrow stromal cells (BMSCs) have been shown to proliferate and produce matrix when seeded onto braided poly(L-lactide/glycolide) acid (PLGA) scaffolds. Mechanical stimulation may be applied to stimulate tissue formation during ligament tissue engineering. This study describes for the first time the effect of constant load on BMSCs seeded onto a braided PLGA scaffold. The seeded scaffolds were subjected to four different loading regimes: Scaffolds were unloaded, loaded during seeding, immediately after seeding, or 2 days after seeding. During the first 5 days, changing the mechanical environment seemed to inhibit proliferation, because cells on scaffolds loaded immediately after seeding or after a 2-day delay, contained fewer cells than on unloaded scaffolds or scaffolds loaded during seeding (p <0.01 for scaffolds loaded after 2 days). During this period, differentiation increased with the period of load applied. After day 5, differences in cell content and collagen production leveled off. After day 11, cell number decreased, whereas collagen production continued to increase. Cell number and differentiation at day 23 were independent of the timing of the mechanical stimulation applied. In conclusion, static load applied to BMSCs cultured on PLGA scaffolds allows for proliferation and differentiation, with loading during seeding yielding the most rapid response. Future research should be aimed at elucidating the biomechanical and biochemical characteristics of tissue formed by BMSCs on PLGA under mechanical stimulation
The Effect of Timing of Mechanical Stimulation on Proliferation and Differentiation of Goat Bone Marrow Stem Cells Cultured on Braided PLGA Scaffolds
Combination of a six microRNA expression profile with four clinicopathological factors for response prediction of systemic treatment in patients with advanced colorectal cancer.
BACKGROUND:First line chemotherapy is effective in 75 to 80% of patients with metastatic colorectal cancer (mCRC). We studied whether microRNA (miR) expression profiles can predict treatment outcome for first line fluoropyrimidine containing systemic therapy in patients with mCRC. METHODS:MiR expression levels were determined by next generation sequencing from snap frozen tumor samples of 88 patients with mCRC. Predictive miRs were selected with penalized logistic regression and posterior forward selection. The prediction co-efficients of the miRs were re-estimated and validated by real-time quantitative PCR in an independent cohort of 81 patients with mCRC. RESULTS:Expression levels of miR-17-5p, miR-20a-5p, miR-30a-5p, miR-92a-3p, miR-92b-3p and miR-98-5p in combination with age, tumor differentiation, adjuvant therapy and type of systemic treatment, were predictive for clinical benefit in the training cohort with an AUC of 0.78. In the validation cohort the addition of the six miR signature to the four clinicopathological factors demonstrated a significant increased AUC for predicting treatment response versus those with stable disease (SD) from 0.79 to 0.90. The increase for predicting treatment response versus progressive disease (PD) and for patients with SD versus those with PD was not significant. in the validation cohort. MiR-17-5p, miR-20a-5p and miR-92a-3p were significantly upregulated in patients with treatment response in both the training and validation cohorts. CONCLUSION:A six miR expression signature was identified that predicted treatment response to fluoropyrimidine containing first line systemic treatment in patients with mCRC when combined with four clinicopathological factors. Independent validation demonstrated added predictive value of this miR-signature for predicting treatment response versus SD. However, added predicted value for separating patients with PD could not be validated. The clinical relevance of the identified miRs for predicting treatment response has to be further explored
Performance of the classifier in the validation cohort.
<p><b>(A)</b> ROC curve of the predictive classifier in the validation cohort for patients with PR or CR on first line systemic treatment (n = 38) compared to patients with PD (n = 15). Included in the classifier are miR-92a-3p, miR-92b-3p and four clinicopathological covariates. On the x-axis the false positive rate (1-specificity) is depicted, on the y-axis the sensitivity is depicted. The AUC of the model for predicting treatment response without miRs is 0.85, compared to 0.90 when including miR-92a-3p and miR-92b-3p to the model, this difference is not significant (p = 0.12). <b>(B)</b> ROC curve of the predictive classifier in the validation cohort for patients with SD on first line systemic treatment (n = 28) compared to patients with PD (n = 15). Included in the classifier are miR-30a-5p and therapy regimen. On the x-axis the false positive rate (1-specificity) is depicted, on the y-axis the sensitivity is depicted. The AUC of the model for predicting SD without miRs is 0.69, compared to 0.72 when including miR-30a-5p to the model, this difference is not significant (p = 0.37). <b>(C)</b> ROC curve of the predictive classifier in the validation cohort for patients with PR or CR on first line systemic treatment (n = 38) compared to patients with SD (n = 28). Included in the classifier are miR-17-5p, miR-92a-3p, miR-92b-3p and miR-98-5p and differentiation grade of the primary tumor. On the x-axis the false positive rate (1-specificity) is depicted, on the y-axis the sensitivity is depicted. The AUC of the model for predicting treatment response without miRs is 0.79, which increased significantly to 0.90 when including miR-17-5p, miR-92a-3p, miR-92b-3p and miR-98-5p to the model (p = 0.02).</p
Box-plots of the expression levels of selected miRs in the validation cohort.
<p>Expression levels of <b>(A)</b> miR-17-5p, <b>(B)</b> miR-20a-5p, <b>(C)</b> miR-30a-5p, <b>(D)</b> miR-92a-3p, <b>(E)</b> miR-92b-3p and <b>(F)</b> miR-98-5p for patients with PR or CR, those with SD and those with PD. Median delta Cq values were normalized to miR-16-5p. MiR-17-5p is significantly higher expressed in patients with response compared to patients with SD (p = 0.004), but not with PD (p = 0.108). Also miR-20a-5p and miR-92a-3p are significantly higher expressed in patients with response compared to patients with SD (p = 0.006 and p = 0.005), but not with PD (p = 0.790 and p = 0.179). MiR-30a-5p, miR-92b-3p and miR-98-5p were not significantly differently expressed between the three groups.</p
Performance of the classifier in the training cohort.
<p><b>(A)</b> Receiver operating characteristic (ROC) curve of six-miR classifier predictive for response to first line systemic treatment for patients with mCRC based on the training cohort (n = 88), resulting in an area under the curve (AUC) of 0.78. Included in the classifier are miR-17-5p, miR-20a-5p, miR-30a-5p, miR-92a-3p, miR-92b-3p and miR-98-5p and four clinicopathological covariates; prior use of adjuvant therapy, the type of systemic treatment regimen, age and primary tumor differentiation. When excluding the miRs from the prediction algorithm the AUC drops to 0.35. The false positive rate (1-specificity) is depicted on the x-axis and, the sensitivity is depicted on the y-axis. <b>(B)</b> Boxplot of the internal cross validated predicted probabilities for clinical benefit. The median predicted probability for the 70 patients with clinical benefit was 0.90 (IQR: 0.77–0.97). For the 18 patients with progressive disease the median predicted probability for clinical benefit was 0.60 (IQR: 0.47–0.84). Predicted probabilities were calculated using the expression levels of the six selected miRs and four clinicopathological covariates. <b>(C)</b> Correlation between the predicted probabilities for clinical benefit (y-axis) with progression free survival (x-axis) of the training cohort. There is a significant correlation of 0.30 (spearman’s rho) (p = 0.006). <b>(D)</b> Correlation between the predicted probabilities for clinical benefit (y-axis) with overall survival (x-axis) of the training cohort. There is a correlation of 0.19 (spearman’s rho), which is not significant (p = 0.08).</p
Baseline characteristics of the 169 patients with advanced colorectal cancer included in the training and validation cohorts.
<p>Baseline characteristics of the 169 patients with advanced colorectal cancer included in the training and validation cohorts.</p