Analysis of Behavior Classification in Motivational Interviewing.

Analysis of client and therapist behavior in counseling sessions can provide helpful insights for assessing the quality of the session and consequently, the client's behavioral outcome. In this paper, we study the automatic classification of standardized behavior codes (i.e. annotations) used for assessment of psychotherapy sessions in Motivational Interviewing (MI). We develop models and examine the classification of client behaviors throughout MI sessions, comparing the performance by models trained on large pretrained embeddings (RoBERTa) versus interpretable and expert-selected features (LIWC). Our best performing model using the pretrained RoBERTa embeddings beats the baseline model, achieving an F1 score of 0.66 in the subject-independent 3-class classification. Through statistical analysis on the classification results, we identify prominent LIWC features that may not have been captured by the model using pretrained embeddings. Although classification using LIWC features underperforms RoBERTa, our findings motivate the future direction of incorporating auxiliary tasks in the classification of MI codes.

Convolutional Neural Network Models for Automatic Preoperative Severity Assessment in Unilateral Cleft Lip.

BACKGROUND: Despite the wide range of cleft lip morphology, consistent scales to categorize preoperative severity do not exist. Machine learning has been used to increase accuracy and efficiency in detection and rating of multiple conditions, yet it has not been applied to cleft disease. The authors tested a machine learning approach to automatically detect and measure facial landmarks and assign severity grades using preoperative photographs. METHODS: Preoperative images were collected from 800 unilateral cleft lip patients, manually annotated for cleft-specific landmarks, and rated using a previously validated severity scale by eight expert reviewers. Five convolutional neural network models were trained for landmark detection and severity grade assignment. Mean squared error loss and Pearson correlation coefficient for cleft width ratio, nostril width ratio, and severity grade assignment were calculated. RESULTS: All five models performed well in landmark detection and severity grade assignment, with the largest and most complex model, Residual Network, performing best (mean squared error, 24.41; cleft width ratio correlation, 0.943; nostril width ratio correlation, 0.879; severity correlation, 0.892). The mobile device-compatible network, MobileNet, also showed a high degree of accuracy (mean squared error, 36.66; cleft width ratio correlation, 0.901; nostril width ratio correlation, 0.705; severity correlation, 0.860). CONCLUSIONS: Machine learning models demonstrate the ability to accurately measure facial features and assign severity grades according to validated scales. Such models hold promise for the creation of a simple, automated approach to classifying cleft lip morphology. Further potential exists for a mobile telephone-based application to provide real-time feedback to improve clinical decision making and patient counseling.

Immune phenotype and histopathological growth pattern in patients with colorectal liver metastases.

BACKGROUND: Patients with desmoplastic (angiogenic) histopathological growth pattern (HGP) colorectal liver metastases (CLM) might derive more benefit from bevacizumab-based chemotherapy than those with replacement (non-angiogenic) HGP. This study investigated the association of HGP with the immune phenotype (IP) and clinical outcome after liver resection. METHODS: CLM of patients treated with perioperative bevacizumab-based chemotherapy and liver resection were investigated. Association of HGP and IP with response, recurrence-free survival (RFS) and overall survival (OS) was investigated. RESULTS: One hundred and eighteen patients (M/F 66/52, median age 62.3 (31.0-80.4) years, median follow-up 32.2 (5.0-92.7) months) were enrolled. The inflamed IP was associated with the desmoplastic HGP. The desmoplastic HGP was associated with better radiological and histological response compared to the replacement HGP, respectively. The replacement HGP was associated with shorter RFS (8.7 versus 16.3 months, HR 2.60, P = 0.001) and OS (36.6 months versus not reached, HR 2.32, P = 0.027), respectively. The non-inflamed IP was associated with shorter RFS (10.8 versus 16.5 months, HR 1.85, P = 0.029). The HGP but not the IP remained significant in multivariable analysis for RFS. CONCLUSIONS: The desmoplastic HGP is associated with the inflamed IP and HGP may be a potential biomarker for adjuvant treatment that includes targeting the immune contexture.

Multimodal Automatic Coding of Client Behavior in Motivational Interviewing.

Motivational Interviewing (MI) is defined as a collaborative conversation style that evokes the client's own intrinsic reasons for behavioral change. In MI research, the clients' attitude (willingness or resistance) toward change as expressed through language, has been identified as an important indicator of their subsequent behavior change. Automated coding of these indicators provides systematic and efficient means for the analysis and assessment of MI therapy sessions. In this paper, we study and analyze behavioral cues in client language and speech that bear indications of the client's behavior toward change during a therapy session, using a database of dyadic motivational interviews between therapists and clients with alcohol-related problems. Deep language and voice encoders, i.e., BERT and VGGish, trained on large amounts of data are used to extract features from each utterance. We develop a neural network to automatically detect the MI codes using both the clients' and therapists' language and clients' voice, and demonstrate the importance of semantic context in such detection. Additionally, we develop machine learning models for predicting alcohol-use behavioral outcomes of clients through language and voice analysis. Our analysis demonstrates that we are able to estimate MI codes using clients' textual utterances along with preceding textual context from both the therapist and client, reaching an F1-score of 0.72 for a speaker-independent three-class classification. We also report initial results for using the clients' data for predicting behavioral outcomes, which outlines the direction for future work.

Plasma Tie2 is a tumor vascular response biomarker for VEGF inhibitors in metastatic colorectal cancer.

Oncological use of anti-angiogenic VEGF inhibitors has been limited by the lack of informative biomarkers. Previously we reported circulating Tie2 as a vascular response biomarker for bevacizumab-treated ovarian cancer patients. Using advanced MRI and circulating biomarkers we have extended these findings in metastatic colorectal cancer (n = 70). Bevacizumab (10 mg/kg) was administered to elicit a biomarker response, followed by FOLFOX6-bevacizumab until disease progression. Bevacizumab induced a correlation between Tie2 and the tumor vascular imaging biomarker, Ktrans (R:-0.21 to 0.47) implying that Tie2 originated from the tumor vasculature. Tie2 trajectories were independently associated with pre-treatment tumor vascular characteristics, tumor response, progression free survival (HR for progression = 3.01, p = 0.00014; median PFS 248 vs. 348 days p = 0.0008) and the modeling of progressive disease (p < 0.0001), suggesting that Tie2 should be monitored clinically to optimize VEGF inhibitor use. A vascular response is defined as a 30% reduction in Tie2; vascular progression as a 40% increase in Tie2 above the nadir. Tie2 is the first, validated, tumor vascular response biomarker for VEGFi.

Perception of Virtual Audiences.

A growing body of evidence shows that virtual audiences are a valuable tool in the treatment of social anxiety, and recent works show that it also a useful in public-speaking training programs. However, little research has focused on how such audiences are perceived and on how the behavior of virtual audiences can be manipulated to create various types of stimuli. The authors used a crowdsourcing methodology to create a virtual audience nonverbal behavior model and, with it, created a dataset of videos with virtual audiences containing varying behaviors. Using this dataset, they investigated how virtual audiences are perceived and which factors affect this perception.

Assessing Tumor-infiltrating Lymphocytes in Solid Tumors: A Practical Review for Pathologists and Proposal for a Standardized Method From the International Immunooncology Biomarkers Working Group: Part 1: Assessing the Host Immune Response, TILs in Invasive Breast Carcinoma and Ductal Carcinoma In Situ, Metastatic Tumor Deposits and Areas for Further Research.

Assessment of tumor-infiltrating lymphocytes (TILs) in histopathologic specimens can provide important prognostic information in diverse solid tumor types, and may also be of value in predicting response to treatments. However, implementation as a routine clinical biomarker has not yet been achieved. As successful use of immune checkpoint inhibitors and other forms of immunotherapy become a clinical reality, the need for widely applicable, accessible, and reliable immunooncology biomarkers is clear. In part 1 of this review we briefly discuss the host immune response to tumors and different approaches to TIL assessment. We propose a standardized methodology to assess TILs in solid tumors on hematoxylin and eosin sections, in both primary and metastatic settings, based on the International Immuno-Oncology Biomarker Working Group guidelines for TIL assessment in invasive breast carcinoma. A review of the literature regarding the value of TIL assessment in different solid tumor types follows in part 2. The method we propose is reproducible, affordable, easily applied, and has demonstrated prognostic and predictive significance in invasive breast carcinoma. This standardized methodology may be used as a reference against which other methods are compared, and should be evaluated for clinical validity and utility. Standardization of TIL assessment will help to improve consistency and reproducibility in this field, enrich both the quality and quantity of comparable evidence, and help to thoroughly evaluate the utility of TILs assessment in this era of immunotherapy.

Assessing Tumor-Infiltrating Lymphocytes in Solid Tumors: A Practical Review for Pathologists and Proposal for a Standardized Method from the International Immuno-Oncology Biomarkers Working Group: Part 2: TILs in Melanoma, Gastrointestinal Tract Carcinomas, Non-Small Cell Lung Carcinoma and Mesothelioma, Endometrial and Ovarian Carcinomas, Squamous Cell Carcinoma of the Head and Neck, Genitourinary Carcinomas, and Primary Brain Tumors.

Assessment of the immune response to tumors is growing in importance as the prognostic implications of this response are increasingly recognized, and as immunotherapies are evaluated and implemented in different tumor types. However, many different approaches can be used to assess and describe the immune response, which limits efforts at implementation as a routine clinical biomarker. In part 1 of this review, we have proposed a standardized methodology to assess tumor-infiltrating lymphocytes (TILs) in solid tumors, based on the International Immuno-Oncology Biomarkers Working Group guidelines for invasive breast carcinoma. In part 2 of this review, we discuss the available evidence for the prognostic and predictive value of TILs in common solid tumors, including carcinomas of the lung, gastrointestinal tract, genitourinary system, gynecologic system, and head and neck, as well as primary brain tumors, mesothelioma and melanoma. The particularities and different emphases in TIL assessment in different tumor types are discussed. The standardized methodology we propose can be adapted to different tumor types and may be used as a standard against which other approaches can be compared. Standardization of TIL assessment will help clinicians, researchers and pathologists to conclusively evaluate the utility of this simple biomarker in the current era of immunotherapy.

The Multimodal Assessment of Adult Attachment Security: Developing the Biometric Attachment Test.

BACKGROUND: Attachment theory has been proven essential for mental health, including psychopathology, development, and interpersonal relationships. Validated psychometric instruments to measure attachment abound but suffer from shortcomings common to traditional psychometrics. Recent developments in multimodal fusion and machine learning pave the way for new automated and objective psychometric instruments for adult attachment that combine psychophysiological, linguistic, and behavioral analyses in the assessment of the construct. OBJECTIVE: The aim of this study was to present a new exposure-based, automatic, and objective adult-attachment assessment, the Biometric Attachment Test (BAT), which exposes participants to a short standardized set of visual and music stimuli, whereas their immediate reactions and verbal responses, captured by several computer sense modalities, are automatically analyzed for scoring and classification. We also aimed to empirically validate two of its assumptions: its capacity to measure attachment security and the viability of using themes as placeholders for rotating stimuli. METHODS: A total of 59 French participants from the general population were assessed using the Adult Attachment Questionnaire (AAQ), the Adult Attachment Projective Picture System (AAP), and the Attachment Multiple Model Interview (AMMI) as ground truth for attachment security. They were then exposed to three different BAT stimuli sets, whereas their faces, voices, heart rate (HR), and electrodermal activity (EDA) were recorded. Psychophysiological features, such as skin-conductance response (SCR) and Bayevsky stress index; behavioral features, such as gaze and facial expressions; as well as linguistic and paralinguistic features, were automatically extracted. An exploratory analysis was conducted using correlation matrices to uncover the features that are most associated with attachment security. A confirmatory analysis was conducted by creating a single composite effects index and by testing it for correlations with attachment security. The stability of the theory-consistent features across three different stimuli sets was explored using repeated measures analysis of variances (ANOVAs). RESULTS: In total, 46 theory-consistent correlations were found during the exploration (out of 65 total significant correlations). For example, attachment security as measured by the AAP was correlated with positive facial expressions (r=.36, P=.01). AMMI's security with the father was inversely correlated with the low frequency (LF) of HRV (r=-.87, P=.03). Attachment security to partners as measured by the AAQ was inversely correlated with anger facial expression (r=-.43, P=.001). The confirmatory analysis showed that the composite effects index was significantly correlated to security in the AAP (r=.26, P=.05) and the AAQ (r=.30, P=.04) but not in the AMMI. Repeated measures ANOVAs conducted individually on each of the theory-consistent features revealed that only 7 of the 46 (15%) features had significantly different values among responses to three different stimuli sets. CONCLUSIONS: We were able to validate two of the instrument's core assumptions: its capacity to measure attachment security and the viability of using themes as placeholders for rotating stimuli. Future validation of other of its dimensions, as well as the ongoing development of its scoring and classification algorithms is discussed.

HER2 Status in Advanced or Metastatic Gastric, Esophageal, or Gastroesophageal Adenocarcinoma for Entry to the TRIO-013/LOGiC Trial of Lapatinib.

HER2/ERBB2 status is used to select patients for HER2-targeted therapy. HER2/ERBB2 amplification/overexpression of upper gastrointestinal (UGI) adenocarcinomas was determined locally or in two central laboratories to select patients for the TRIO-013/LOGiC trial of chemotherapy with or without lapatinib. Patients selected locally had central laboratory confirmation of HER2 amplification for inclusion in the primary efficacy population. HER2 was assessed with PathVysion or IQ PharmDx FISH and HercepTest immunohistochemistry assays. Associations with outcomes were retrospectively evaluated. Overall, HER2 status was determined in UGI cancers from 4,674 patients in a central laboratory for eligibility (1,995 cases) and for confirmation of local HER2 results (333 cases). Of 1,995 adenocarcinomas screened centrally, 322 (16.1%) had HER2-amplified disease with 29 (1.5%) showing HER2 genomic heterogeneity. Men and older patients had higher rates of amplification. Of 545 patients accrued to the trial (gastric, 87.3%; GEJ, 8.3% and esophageal cancer, 4.4%), 487 patients (89%) were centrally confirmed as having HER2-amplified disease. Concordance between central and local HER2 testing was 83%. Concordance between PathVysion and IQ PharmDx FISH assays was 99% and FISH in the two central laboratories was 95%. Lapatinib-treated Asian participants and those less than 60 years had significant improvement in progression-free survival (PFS), particularly among those whose cancers had 5.01-10.0 and >10.0-fold amplification of HER2 In conclusion, HER2 is commonly amplified in UGI adenocarcinomas with amplification highly correlated to overexpression, and HER2 amplification levels correlated with PFS. While HER2 genomic heterogeneity occurs, its prevalence is low. Mol Cancer Ther; 16(1); 228-38. ©2016 AACR.

A Machine Learning Approach to Identifying the Thought Markers of Suicidal Subjects: A Prospective Multicenter Trial.

Death by suicide demonstrates profound personal suffering and societal failure. While basic sciences provide the opportunity to understand biological markers related to suicide, computer science provides opportunities to understand suicide thought markers. In this novel prospective, multimodal, multicenter, mixed demographic study, we used machine learning to measure and fuse two classes of suicidal thought markers: verbal and nonverbal. Machine learning algorithms were used with the subjects' words and vocal characteristics to classify 379 subjects recruited from two academic medical centers and a rural community hospital into one of three groups: suicidal, mentally ill but not suicidal, or controls. By combining linguistic and acoustic characteristics, subjects could be classified into one of the three groups with up to 85% accuracy. The results provide insight into how advanced technology can be used for suicide assessment and prevention.

Expression of Genes Involved in Vascular Morphogenesis and Maturation Predicts Efficacy of Bevacizumab-Based Chemotherapy in Patients Undergoing Liver Resection.

Angiogenesis-related gene expression is associated with the efficacy of anti-VEGF therapy. We tested whether intratumoral mRNA expression levels of genes involved in vascular morphogenesis and early vessel maturation predict response, recurrence-free survival (RFS), and overall survival (OS) in a unique cohort of patients with colorectal liver metastases (CLM) treated with bevacizumab-based chemotherapy followed by curative liver resection. Intratumoral mRNA was isolated from resected bevacizumab-pretreated CLM from 125 patients. In 42 patients, a matching primary tumor sample collected before bevacizumab treatment was available. Relative mRNA levels of 9 genes (ACVRL1, EGFL7, EPHB4, HIF1A, VEGFA, VEGFB, VEGFC, FLT1, and KDR) were analyzed by RT-PCR and evaluated for associations with response, RFS, and OS. P values for the associations between the individual dichotomized expression level and RFS were adjusted for choosing the optimal cut-off value. In CLM, high expression of VEGFB, VEGFC, HIF1A, and KDR and low expression of EGFL7 were associated with favorable RFS in multivariable analysis (P < 0.05). High ACVRL1 levels predicted favorable 3-year OS (P = 0.041) and radiologic response (PR = 1.093, SD = 0.539, P = 0.002). In primary tumors, low VEGFA and high EGFL7 were associated with radiologic and histologic response (P < 0.05). High VEGFA expression predicted shorter RFS (10.1 vs. 22.6 months; HR = 2.83, P = 0.038). High VEGFB (46% vs. 85%; HR = 5.75, P = 0.009) and low FLT1 (55% vs. 100%; P = 0.031) predicted lower 3-year OS rates. Our data suggest that intratumoral mRNA expression of genes involved in vascular morphogenesis and early vessel maturation may be promising predictive and/or prognostic biomarkers. Mol Cancer Ther; 15(11); 2814-21. ©2016 AACR.

Systematic analysis of circulating soluble angiogenesis-associated proteins in ICON7 identifies Tie2 as a biomarker of vascular progression on bevacizumab.

BACKGROUND: There is a critical need for predictive/resistance biomarkers for VEGF inhibitors to optimise their use. METHODS: Blood samples were collected during and following treatment and, where appropriate, upon progression from ovarian cancer patients in ICON7, a randomised phase III trial of carboplatin and paclitaxel with or without bevacizumab. Plasma concentrations of 15 circulating angio-biomarkers were measured using a validated multiplex ELISA, analysed through a novel network analysis and their relevance to the PFS then determined. RESULTS: Samples (n=650) were analysed from 92 patients. Bevacizumab induced correlative relationships between Ang1 and Tie2 plasma concentrations, which reduced after initiation of treatment and remained decreased until progressive disease occurred. A 50% increase from the nadir in the concentration of circulating Tie2 (or the product of circulating Ang1 and Tie2) predicted tumour progression. Combining Tie2 with GCIG-defined Ca125 data yielded a significant improvement in the prediction of progressive disease in patients receiving bevacizumab in comparison with Ca125 alone (74.1% vs 47.3%, P<1 × 10(-9)). CONCLUSIONS: Tie2 is a vascular progression marker for bevacizumab-treated ovarian cancer patients. Tie2 in combination with Ca125 provides superior information to clinicians on progressive disease in patients with VEGFi-treated ovarian cancers.

Evaluation of Angiopoietin-2 as a biomarker in gastric cancer: results from the randomised phase III AVAGAST trial.

BACKGROUND: In the phase III AVAGAST trial, the addition of bevacizumab to chemotherapy improved progression-free survival (PFS) but not overall survival (OS) in patients with advanced gastric cancer. We studied the role of Angiopoietin-2 (Ang-2), a key driver of tumour angiogenesis, metastasis and resistance to antiangiogenic treatment, as a biomarker. METHODS: Previously untreated, advanced gastric cancer patients were randomly assigned to receive bevacizumab (n=387) or placebo (n=387) in combination with chemotherapy. Plasma collected at baseline and at progression was analysed by ELISA. The role of Ang-2 as a prognostic and a predictive biomarker of bevacizumab efficacy was studied using a Cox proportional hazards model. Logistic regression analysis was applied for correlations with metastasis. RESULTS: Median baseline plasma Ang-2 levels were lower in Asian (2143 pg ml(-1)) vs non-Asian patients (3193 pg ml(-1)), P<0.0001. Baseline plasma Ang-2 was identified as an independent prognostic marker for OS but did not predict bevacizumab efficacy alone or in combination with baseline VEGF. Baseline plasma Ang-2 correlated with the frequency of liver metastasis (LM) at any time: Odds ratio per 1000 pg ml(-1) increase: 1.19; 95% CI 1.10-1.29; P<0.0001 (non-Asians) and 1.37; 95% CI 1.13-1.64; P=0.0010 (Asians). CONCLUSIONS: Baseline plasma Ang-2 is a novel prognostic biomarker for OS in advanced gastric cancer strongly associated with LM. Differences in Ang-2 mediated vascular response may, in part, account for outcome differences between Asian and non-Asian patients; however, data have to be further validated. Ang-2 is a promising drug target in gastric cancer.

Automatic Behavior Analysis During a Clinical Interview with a Virtual Human.

SimSensei is a Virtual Human (VH) interviewing platform that uses off-the-shelf sensors (i.e., webcams, Microsoft Kinect and a microphone) to capture and interpret real-time audiovisual behavioral signals from users interacting with the VH system. The system was specifically designed for clinical interviewing and health care support by providing a face-to-face interaction between a user and a VH that can automatically react to the inferred state of the user through analysis of behavioral signals gleaned from the user's facial expressions, body gestures and vocal parameters. Akin to how non-verbal behavioral signals have an impact on human-to-human interaction and communication, SimSensei aims to capture and infer user state from signals generated from user non-verbal communication to improve engagement between a VH and a user and to quantify user state from the data captured across a 20 minute interview. Results from of sample of service members (SMs) who were interviewed before and after a deployment to Afghanistan indicate that SMs reveal more PTSD symptoms to the VH than they report on the Post Deployment Health Assessment. Pre/Post deployment facial expression analysis indicated more sad expressions and few happy expressions at post deployment.

Primary tumor location as a prognostic factor in metastatic colorectal cancer.

BACKGROUND: We sought to clarify the prognostic impact of primary tumor location in metastatic colorectal cancer (mCRC). METHODS: We evaluated the association between tumor location and survival parameters in patients with previously untreated mCRC receiving first-line chemotherapy ± bevacizumab in three independent cohorts: a prospective pharmacogenetic study (PROVETTA) and two randomized phase III trials, AVF2107g and NO16966. Cancers proximal or distal of the splenic flexure were classified as right-sided or left-sided, respectively. The primary end point was overall survival (OS). Data were analyzed with Cox proportional hazards and logistic regression models. All statistical tests were two-sided. RESULTS: Among evaluable patients in the PROVETTA (n = 200), AVF2107g (n = 559), and NO16966 (n = 1268) studies, 72.0%, 63.1%, and 73.7% had left-sided tumors, respectively. In PROVETTA, patients with left-sided tumors had superior OS (left-sided vs right-sided: hazard ratio [HR] = .44, 95% confidence interval [CI] = .28 to .70, P < .001) and progression-free survival (HR = .52, 95% CI = .36 to .75, P < .001) outcomes. Multivariable analyses confirmed right-sided location as a negative prognostic variable, independent of mucinous histology and BRAF mutational status. Data from the AVF2107g (HR for OS = .55, 95% CI = .43 to .70) and NO16966 trials (HR for OS = .71, 95% CI = .62 to .82 both P < .001) also showed favorable outcomes in patients with left-sided tumors. In both randomized studies, the efficacy of bevacizumab was independent of tumor location. CONCLUSIONS: These data demonstrate that primary tumor location is an important prognostic factor in previously untreated mCRC. Given the consistency across an exploratory set and two confirmatory phase III studies, side of tumor origin should be considered for stratification in randomized trials.

Predictive tissue biomarkers for bevacizumab-containing therapy in metastatic colorectal cancer: an update.

Bevacizumab is the first anti-angiogenic agent approved for the treatment of metastatic colorectal cancer. The need for patient selection before initiating therapy necessitates the study of various proteins expressed in metastatic colorectal cancer tissue as candidate predictive markers. Immunohistochemistry is a valuable, commonly available and cost-effective method to assess predictive biomarkers. However, it is subject to variations and therefore requires rigorous protocol standardizations. Furthermore, validated quantification methodologies to study these angiogenic elements have to be applied. Based on their function in tumor angiogenesis and their relation to the mechanism of action of bevacizumab, protein markers were divided in four groups: VEGF A-signaling proteins; other relevant angiogenesis factors; factors regarding the tumor microenvironment and tumor intrinsic markers. Conceivably, nimbly selecting a small but relevant group of therapy-guided patients by the appropriate combination of predictive biomarkers may confer great value to this angiogenic inhibitor.

89Zr-bevacizumab PET visualizes heterogeneous tracer accumulation in tumor lesions of renal cell carcinoma patients and differential effects of antiangiogenic treatment.

UNLABELLED: No validated predictive biomarkers for antiangiogenic treatment of metastatic renal cell carcinoma (mRCC) exist. Tumor vascular endothelial growth factor A (VEGF-A) level may be useful. We determined tumor uptake of (89)Zr-bevacizumab, a VEGF-A-binding PET tracer, in mRCC patients before and during antiangiogenic treatment in a pilot study. METHODS: Patients underwent (89)Zr-bevacizumab PET scans at baseline and 2 and 6 wk after initiating either bevacizumab (10 mg/kg every 2 wk) with interferon-α (3-9 million IU 3 times/wk) (n = 11) or sunitinib (50 mg daily, 4 of every 6 wk) (n = 11). Standardized uptake values were compared with plasma VEGF-A and time to disease progression. RESULTS: (89)Zr-bevacizumab PET scans visualized 125 evaluable tumor lesions in 22 patients, with a median SUV(max) (maximum standardized uptake value) of 6.9 (range, 2.3-46.9). Bevacizumab/interferon-α induced a mean change in tumor SUV(max) of -47.0% (range, -84.7 to +20.0%; P < 0.0001) at 2 wk and an additional -9.7% (range, -44.8 to +38.9%; P = 0.015) at 6 wk. In the sunitinib group, the mean change in tumor SUV(max) was -14.3% at 2 wk (range, -80.4 to +269.9; P = 0.006), but at 6 wk the mean change in tumor SUV(max) was +72.6% (range, -46.4 to +236%; P < 0.0001) above baseline. SUV(max) was not related to plasma VEGF-A at all scan moments. A baseline mean tumor SUV(max) greater than 10.0 in the 3 most intense lesions corresponded with longer time to disease progression (89.7 vs. 23.0 wk; hazard ratio, 0.22; 95% confidence interval, 0.05-1.00). CONCLUSION: Tumor uptake of (89)Zr-bevacizumab is high in mRCC, with remarkable interpatient and intrapatient heterogeneity. Bevacizumab/interferon-α strongly decreases tumor uptake whereas sunitinib results in a modest reduction with an overshoot after 2 drug-free weeks. High baseline tumor SUV(max) was associated with longer time to progression.

Genetic variability of VEGF pathway genes in six randomized phase III trials assessing the addition of bevacizumab to standard therapy.

BACKGROUND: Despite extensive translational research, no validated biomarkers predictive of bevacizumab treatment outcome have been identified. METHODS: We performed a meta-analysis of individual patient data from six randomized phase III trials in colorectal, pancreatic, lung, renal, breast, and gastric cancer to explore the potential relationships between 195 common genetic variants in the vascular endothelial growth factor (VEGF) pathway and bevacizumab treatment outcome. RESULTS: The analysis included 1,402 patients (716 bevacizumab-treated and 686 placebo-treated). Twenty variants were associated (P < 0.05) with progression-free survival (PFS) in bevacizumab-treated patients. Of these, 4 variants in EPAS1 survived correction for multiple testing (q < 0.05). Genotype-by-treatment interaction tests revealed that, across these 20 variants, 3 variants in VEGF-C (rs12510099), EPAS1 (rs4953344), and IL8RA (rs2234671) were potentially predictive (P < 0.05), but not resistant to multiple testing (q > 0.05). A weak genotype-by-treatment interaction effect was also observed for rs699946 in VEGF-A, whereas Bayesian genewise analysis revealed that genetic variability in VHL was associated with PFS in the bevacizumab arm (q < 0.05). Variants in VEGF-A, EPAS1, and VHL were located in expression quantitative loci derived from lymphoblastoid cell lines, indicating that they affect the expression levels of their respective gene. CONCLUSIONS: This large genetic analysis suggests that variants in VEGF-A, EPAS1, IL8RA, VHL, and VEGF-C have potential value in predicting bevacizumab treatment outcome across tumor types. Although these associations did not survive correction for multiple testing in a genotype-by-interaction analysis, they are among the strongest predictive effects reported to date for genetic variants and bevacizumab efficacy.

The combination of circulating Ang1 and Tie2 levels predicts progression-free survival advantage in bevacizumab-treated patients with ovarian cancer.

PURPOSE: Randomized ovarian cancer trials, including ICON7, have reported improved progression-free survival (PFS) when bevacizumab was added to conventional cytotoxic therapy. The improvement was modest prompting the search for predictive biomarkers for bevacizumab. EXPERIMENTAL DESIGN: Pretreatment training (n=91) and validation (n=114) blood samples were provided by ICON7 patients. Plasma concentrations of 15 angio-associated factors were determined using validated multiplex ELISAs. Our statistical approach adopted PFS as the primary outcome measure and involved (i) searching for biomarkers with prognostic relevance or which related to between-individual variation in bevacizumab effect; (ii) unbiased determination of cutoffs for putative biomarker values; (iii) investigation of biologically meaningfully predictive combinations of putative biomarkers; and (iv) replicating the analysis on candidate biomarkers in the validation dataset. RESULTS: The combined values of circulating Ang1 (angiopoietin 1) and Tie2 (Tunica internal endothelial cell kinase 2) concentrations predicted improved PFS in bevacizumab-treated patients in the training set. Using median concentrations as cutoffs, high Ang1/low Tie2 values were associated with significantly improved PFS for bevacizumab-treated patients in both datasets (median, 23.0 months vs. 16.2; P=0.003) for the interaction of Ang1-Tie2 treatment in Cox regression analysis. The prognostic indices derived from the training set also distinguished high and low probability for progression in the validation set (P=0.008), generating similar values for HR (0.21 vs. 0.27) between treatment and control arms for patients with high Ang1 and low Tie2 values. CONCLUSIONS: The combined values of Ang1 and Tie2 are predictive biomarkers for improved PFS in bevacizumab-treated patients with ovarian cancer. These findings need to be validated in larger trials due to the limitation of sample size in this study.