Predicting soft tissue changes after orthognathic surgery: The sparse partial least squares method

OBJECTIVES

To develop a prediction algorithm for soft tissue changes after orthognathic surgery that would result in accurate predictions (1) regardless of types or complexity of operations and (2) with a minimum number of input variables.

MATERIALS AND METHODS

The subjects consisted of 318 patients who had undergone the surgical correction of Class II or Class III malocclusions. Two multivariate methods-the partial least squares (PLS) and the sparse partial least squares (SPLS) methods-were used to construct prediction equations. While the PLS prediction model included 232 input variables, the SPLS method included a reduced number of variables generated by a handicapping algorithm via the sparsity control. The accuracy between the PLS and SPLS models was compared.

RESULTS

There were no significant differences in prediction accuracy depending on surgical movements, the sex of the subjects, or additional surgeries. The predictive performance with a reduced set of 34 input variables chosen using the SPLS method was statistically indistinguishable from the full set of variables with the original PLS prediction model.

CONCLUSIONS

The prediction method proposed in the present study was accurate for a wide range of orthognathic surgeries. A reduced set of input variables could be selected through the SPLS method while simultaneously maintaining a prediction level that was as accurate as that of the original PLS prediction model.

A sparse principal component analysis of Class III malocclusions

OBJECTIVES

To identify the most characteristic variables out of a large number of anatomic landmark variables on three-dimensional computed tomography (CT) images. A modified principal component analysis (PCA) was used to identify which anatomic structures would demonstrate the major variabilities that would most characterize the patient.

MATERIALS AND METHODS

Data were collected from 217 patients with severe skeletal Class III malocclusions who had undergone orthognathic surgery. The input variables were composed of a total of 740 variables consisting of three-dimensional Cartesian coordinates and their Euclidean distances of 104 soft tissue and 81 hard tissue landmarks identified on the CT images. A statistical method, a modified PCA based on the penalized matrix decomposition, was performed to extract the principal components.

RESULTS

The first 10 (8 soft tissue, 2 hard tissue) principal components from the 740 input variables explained 63% of the total variance. The most conspicuous principal components indicated that groups of soft tissue variables on the nose, lips, and eyes explained more variability than skeletal variables did. In other words, these soft tissue components were most representative of the differences among the Class III patients.

CONCLUSIONS

On three-dimensional images, soft tissues had more variability than the skeletal anatomic structures. In the assessment of three-dimensional facial variability, a limited number of anatomic landmarks being used today did not seem sufficient. Nevertheless, this modified PCA may be used to analyze orthodontic three-dimensional images in the future, but it may not fully express the variability of the patients.

Characterization of Hepatocellular Carcinoma Patients with FGF19 Amplification Assessed by Fluorescence in situ Hybridization: A Large Cohort Study

BACKGROUND

FGF19 amplification is a relatively novel type of genetic aberration that has been proposed to be a driver of hepatocarcinogenesis. Selective inhibitors of FGFR4, a receptor of FGF19, have been developed as targeted therapies for hepatocellular carcinoma (HCC). Despite the role of FGF19 in mediating HCC progression, the clinicopathological characterization of patients exhibiting FGF19 amplification remains unclear. Immunohistochemical staining is the simplest and most widely used method of identifying aberrations in the FGF19 gene, although its specificity is very low.

METHODS

This study investigated the prognostic significance of FGF19 amplification in a large cohort of 989 HCC patients using fluorescence in situ hybridization (FISH), which has a high degree of specificity. In addition, FISH data from formalin-fixed, paraffin-embedded sections were compared with copy number variation (CNV) data obtained from fresh frozen sections to validate the use of FISH as a diagnostic tool.

RESULTS

FGF19 amplifications were detected by FISH in 51 (5.15%) of the 989 patients, and were independently associated with poor survival and a higher risk of tumor recurrence, as well as with poor prognostic factors such as a high α-fetoprotein level, hepatitis B or C virus infection, a large tumor size, microvascular invasion, and necrosis. In addition, FGF19 amplification was associated with TP53 mutation, and was mutually exclusive with CTNNB1 mutation. The results of the FISH and CNV analyses exhibited a significant concordance rate of 96% (κ = 0.618, p < 0.001).

CONCLUSIONS

These data indicate that FGF19 amplification represents a unique molecular subtype associated with poor prognostic characteristics, which supports the hypothesis that the FGF19-FGFR4 signaling pathway plays an important role in hepatocarcinogenesis. We have also demonstrated that FISH is a viable alternative to CNV analysis, offering a number of advantages in the clinical setting.

Novel endoscopic categorization for prediction of chemoradiotherapy response in locally advanced esophageal cancer

BACKGROUND AND AIM

Preoperative chemoradiotherapy (CRT) followed by esophagectomy is a well-known treatment modality for patients with locally advanced esophageal cancer (EC). This study developed an algorithm to predict pathological complete response (CR) in these patients using post-CRT endoscopic category with biopsy and validated the proposed algorithm.

METHODS

A retrospective review of 141 consecutive patients who completed preoperative CRT and underwent surgical resection for locally advanced EC was performed. The post-CRT endoscopic findings of each patient were stratified into five categories.

RESULTS

The distribution of post-CRT endoscopic categories was significantly different between the pathological CR and non-pathological CR groups (P < 0.001). About 76.8% (73/95) of patients in category 0, 1, or 2 achieved pathological CR. In contrast, 91.3% (42/46) of endoscopic categories 3 and 4 patients did not achieve pathological CR. Sensitivity of post-CRT biopsy was 11.1%. Therefore, an algorithm combining biopsy results and dichotomized post-CRT endoscopic category (category 0, 1, or 2 vs category 3 or 4) was developed. The sensitivity, specificity, and accuracy in predicting pathological CR by the proposed algorithm were 64.8%, 95.9%, and 82.8%, respectively. In the multivariate analysis, the proposed algorithm remained a significant negative factor of survival (P < 0.001).

CONCLUSIONS

Algorithm using post-CRT endoscopic category with biopsy may help identify locally advanced EC patients who achieved pathological CR after preoperative CRT. Modalities to accurately detect subepithelial remnant EC may further aid in predicting pathological CR.

Synaptonemal complex protein 3 is associated with lymphangiogenesis in non-small cell lung cancer patients with lymph node metastasis

Background

The interaction of vascular endothelial growth factor-C (VEGF-C)/VEGF-D/VEGF receptor-3 is considered to be a major driver of lymphangiogenesis, however the mechanism of this process remains unclear. We aimed to investigate the possible lymphangiogenic significance of synaptonemal complex protein 3 (SCP3) in non-small cell lung cancer (NSCLC).

Methods

The expression of SCP3, VEGF-C, and VEGF-D were measured and examined a correlation between SCP3 and VEGF-C or VEGF-D in various human lung cancer cell lines. Subsequently, we assessed SCP3, VEGF-A, VEGF-B, VEGF-C, and VEGF-D expression in archival tumor tissues from 89 NSCLC patients with lymph node (LN) metastasis by combined immunohistochemistry with quantitative digital image analysis.

Results

Positive correlations between SCP3 and VEGF-C expression (R² = 0.743) and VEGF-D expression (R² = 0.932) were detected in various human lung cancer cell lines. The high expression of SCP3, VEGF-A, VEGF-B, VEGF-C, and VEGF-D were detected in 24 (27.0%), 22 (24.7%), 27 (30.3%), 27 (30.3%), and 24 cases (27.0%), respectively. Notably, SCP3 positively correlated with VEGF-C and VEGF-D expression (for both, P < 0.001) and negatively correlated with VEGF-A and VEGF-B expression (P = 0.029 and P = 0.026, respectively). In multivariate analysis of patients with LN metastasis, SCP3 expression predicted worse overall survival (hazard ratio = 1.86, P = 0.008).

Conclusions

SCP3 is associated with lymphangiogenesis and provides insight into the SCP3-VEGF-C/VEGF-D axis based cancer therapy strategy.

Electronic supplementary material

The online version of this article (doi:10.1186/s12967-017-1241-5) contains supplementary material, which is available to authorized users.

Non-crossing weighted kernel quantile regression with right censored data

Regarding survival data analysis in regression modeling, multiple conditional quantiles are useful summary statistics to assess covariate effects on survival times. In this study, we consider an estimation problem of multiple nonlinear quantile functions with right censored survival data. To account for censoring in estimating a nonlinear quantile function, weighted kernel quantile regression (WKQR) has been developed by using the kernel trick and inverse-censoring-probability weights. However, the individually estimated quantile functions based on the WKQR often cross each other and consequently violate the basic properties of quantiles. To avoid this problem of quantile crossing, we propose the non-crossing weighted kernel quantile regression (NWKQR), which estimates multiple nonlinear conditional quantile functions simultaneously by enforcing the non-crossing constraints on kernel coefficients. The numerical results are presented to demonstrate the competitive performance of the proposed NWKQR over the WKQR.

Temperature changes in bulk-fill resin composite during photopolymerization

PURPOSE

To investigate the temperature changes at multiple sites within bulk-fill resin composites and in the pulp chamber during photopolymerization in the tooth cavity.

METHODS

Class 1 cavities (n = 5) prepared in extracted third molars were filled with SureFil SDR Flow, a newly developed bulk-fill composite. After securing the specimens in a water bath at 36.5 degrees C, eight thermocouples were used to measure the temperature at the bottom center (BC), middle center (MC), top center (TC), bottom edge (BE), middle edge (ME), and top edge (TE) of the restoration; the pulpal aspect of the dentin (PD); and the center of the curing light tip (CL) during photopolymerization.

RESULTS

The maximum temperature values (degrees C) differed among the measurement sites. TC exhibited the greatest temperature increase (72.3 ± 2.4), followed by MC, BC, TE, TE, ME, CL, and BE. The lowest temperature was observed at PD (41.1 ± 1.9). The peak temperatures within the composite were observed during the early stage of light-curing, while CL and PD exhibited the highest temperature at the end stage of light-curing.

Survival effect of tumor size and extrapancreatic extension in surgically resected pancreatic cancer: proposal for improved T classification

The T classification for pancreatic cancer of the American Joint Committee on Cancer may be inaccurate owing to lack of consideration of tumor size in cases of extension beyond the pancreas. To examine the accuracy of American Joint Committee on Cancer staging and to determine the prognostic implication of combined tumor size and extrapancreatic extension, 6145 cases of pancreatic ductal adenocarcinomas from the Surveillance, Epidemiology, and End Results database were categorized according to tumor size and extension as follows: group 1 (G1, ≤2 cm and limited to the pancreas), G2 (>2 cm and limited to the pancreas), G3 (≤2 cm with extrapancreatic extension), and G4 (>2 cm with extrapancreatic extension). The median survival of G1, G2, G3, and G4 were 23, 15, 19, and 14 months, respectively (P < .001), and the survival time in G3 was closer to that of G2 than G4. To test the classification system for accuracy of prognosis, G3 was merged with G2. The survival discrimination of this new grouping was greater (overall comparison, P < .001; G1 versus G2 + G3, P < .001; G2 + G3 versus G4, P < .001; χ(2) = 92.043) than that of the current T-classification scheme (overall comparison, P < .001; G1 versus G2, P < .001; G2 versus G3 + G4, P = .048; χ(2) = 60.424). To better discriminate survival, patients with a tumor less than or equal to 2 cm extending beyond the pancreas should be downstaged from the current class T3 to class T2.

Sarcomatoid features, necrosis, and grade are prognostic factors in metastatic clear cell renal cell carcinoma with vascular endothelial growth factor-targeted therapy

Various clinical and laboratory parameters are used to determine the prognosis of patients with renal cell carcinoma (RCC), but the prognostic significance of histologic features has not been fully examined in patients with metastatic clear cell RCC receiving vascular endothelial growth factor (VEGF)/tyrosine kinase inhibitor (TKI; VEGF-TKI)-targeted therapy. To define prognostic clinicopathological factors, 83 such patients were retrospectively analyzed. Of these patients, 38 (45.8%) showed response to VEGF-TKI, whereas 45 (54.2%) were nonresponsive. Response to VEGF-TKI was associated with less than 10% sarcomatoid features and less than 10% tumor necrosis. Multivariate analysis showed that tumor necrosis was independently prognostic of VEGF-TKI response. During a median follow-up of 18 months (range, 1-62 months), 54 patients (65.1%) showed disease progression and 44 (53.0%) died. Shorter progression-free survival and overall survival (OS) were associated with a period less than 1 year from initial diagnosis to VEGF-TKI initiation, high Fuhrman grade, at least 10% sarcomatoid features, and at least 10% tumor necrosis. In addition, thrombocytosis was associated with shorter OS. Multivariate analysis showed that sarcomatoid features was independently prognostic of progression-free survival, whereas time from initial diagnosis to VEGF-TKI initiation and sarcomatoid features were independent prognostic factors of OS. In summary, sarcomatoid features, tumor necrosis, and tumor grade are histologic prognostic factors and should be considered in determining whether to initiate targeted treatment in patients with metastatic clear cell RCC.

S100A4 expression is a prognostic indicator in small intestine adenocarcinoma

AIMS

Due to the rarity of small intestine adenocarcinoma (SIAC), estimating the prognosis for patients with surgically resected SIAC is difficult. Overexpression of S100A4 has been linked to worse patient survival in several malignant neoplasms, but its significance in SIAC has not been determined.

METHODS

S100A4 protein expression was assessed in 197 surgically resected SIAC cases and compared with clinicopathological factors, including patient survival.

RESULTS

A progressive increase in S100A4 labelling was observed in normal intestinal epithelium, adenoma and adenocarcinoma (p<0.001), and 50 SIAC cases (26.2%) showed strong S100A4 expression. Patients with SIAC with strong S100A4 expression had a higher pT classification (p=0.05), as well as increased lymph node metastasis (p=0.009) and perineural invasion (p=0.002). Patients with SIAC with strong S100A4 expression had significantly worse survival (median survival, 21 months) than those with weak/no S100A4 expression (42.5 months) by univariable (p=0.04) and multivariable (p=0.01) analyses.

CONCLUSIONS

S100A4 overexpression is observed in a subset of SIACs, is associated with advanced disease and can be used as a prognostic indicator of poor prognosis in patients with SIAC.

Outlier detection using projection quantile regression for mass spectrometry data with low replication

Background

Mass spectrometry (MS) data are often generated from various biological or chemical experiments and there may exist outlying observations, which are extreme due to technical reasons. The determination of outlying observations is important in the analysis of replicated MS data because elaborate pre-processing is essential for successful analysis with reliable results and manual outlier detection as one of pre-processing steps is time-consuming. The heterogeneity of variability and low replication are often obstacles to successful analysis, including outlier detection. Existing approaches, which assume constant variability, can generate many false positives (outliers) and/or false negatives (non-outliers). Thus, a more powerful and accurate approach is needed to account for the heterogeneity of variability and low replication.

Findings

We proposed an outlier detection algorithm using projection and quantile regression in MS data from multiple experiments. The performance of the algorithm and program was demonstrated by using both simulated and real-life data. The projection approach with linear, nonlinear, or nonparametric quantile regression was appropriate in heterogeneous high-throughput data with low replication.

Conclusion

Various quantile regression approaches combined with projection were proposed for detecting outliers. The choice among linear, nonlinear, and nonparametric regressions is dependent on the degree of heterogeneity of the data. The proposed approach was illustrated with MS data with two or more replicates.

Telomeres are shortened in acinar-to-ductal metaplasia lesions associated with pancreatic intraepithelial neoplasia but not in isolated acinar-to-ductal metaplasias

Telomeres protect against chromosomal breakage, fusion, and interchromosome bridges during cell division. Shortened telomeres have been observed in the lowest grade of pancreatic intraepithelial neoplasia (PanIN). Genetically engineered mouse models of pancreatic neoplasia develop acinar-to-ductal metaplasia prior to the development of PanIN, suggesting that acinar-to-ductal metaplasias can be an early precursor lesion to pancreatic cancer. Some human PanINs are associated with acinar-to-ductal metaplasias, and it has been suggested that these acinar-to-ductal metaplasias arise as a consequence of growth of adjacent PanINs. As the earliest known genetic lesions of PanINs is shortened telomeres, we compared the telomere lengths of acinar-to-ductal metaplasia lesions, PanINs, and adjacent normal cells of human pancreata to determine whether acinar-to-ductal metaplasias could be precursors to PanIN. We used quantitative fluorescent in situ hybridization to measure the telomere length of cells from pancreatic lesions and adjacent normal pancreata from 22 patients, including 20 isolated acinar-to-ductal metaplasias, 13 PanINs associated with acinar-to-ductal metaplasias, and 12 PanINs. Normalized mean telomere fluorescence was significantly different among the cell types analyzed; 12.6 ± 10.2 units in normal acinar cells, 10.2 ± 6.4 in ductal cells, 8.4 ± 5.9 in fibroblasts, 9.4 ± 7.3 in isolated acinar-to-ductal metaplasias, 4.1 ± 2.9 in PanIN-associated acinar-to-ductal metaplasias, and 1.6 ± 1.9 in PanINs, respectively (P<0.001, ANOVA with randomized block design). Telomeres were significantly shorter in PanIN-associated acinar-to-ductal metaplasias (P<0.05, post hoc Duncan test) and in PanINs (P<0.05), than in normal cells, or isolated acinar-to-ductal metaplasias. Thus, shortened telomeres are found in PanIN-associated acinar-to-ductal metaplasias, but not in isolated acinar-to-ductal metaplasia lesions. These results indicate that isolated acinar-to-ductal metaplasias are not a precursor to PanIN, and support the hypothesis that PanIN-associated acinar-to-ductal metaplasias arise secondary to PanIN lesions.