The studies described herein assess the potential of combining platinum-based chemotherapy with high-linear energy transfer (LET) α-particle-targeted radiation therapy using trastuzumab as the delivery vehicle. An initial study explored the combination of cisplatin with 213Bi-trastuzumab in the LS-174T i.p. xenograft model. This initial study determined the administration sequence of cisplatin and 213Bi-trastuzumab. Cisplatin coinjected with 213Bi-trastuzumab increased the median survival (MS) to 90 days versus 65 days for 213Bi-trastuzumab alone. Toxicity was observed with a weight loss of 17.6% in some of the combined treatment groups. Carboplatin proved to be better tolerated. Maximal therapeutic benefit, that is, a 5.1-fold increase in MS, was obtained in the group injected with 213Bi-trastuzumab, followed by carboplatin 24 hours later. This was further improved by administration of multiple weekly doses of carboplatin. The MS achieved with administration of 3 doses of carboplatin was 180 days versus 60 days with 213Bi-trastuzumab alone. The combination of carboplatin with 212Pb radioimmunotherapy was also evaluated. The therapeutic efficacy of 212Pb-trastuzumab (58-day MS) increased when the mice were pretreated with carboplatin 24 hours prior (157-day MS). These results again demonstrate the necessity of empirically determining the administration sequence when combining therapeutic modalities.
α-particle; 213Bi; carboplatin; cisplatin; HER2; 212Pb; radioimmunotherapy; trastuzumab
We consider weighted logrank tests for interval censored data when assessment times may depend on treatment, and for each individual we only use the two assessment times that bracket the event of interest. It is known that treating finite right endpoints as observed events can substantially inflate the type I error rate under assessment-treatment dependence (ATD), but the validity of several other implementations of weighted logrank tests (score tests, permutation tests, multiple imputation tests) has not been studied in this situation. With a bounded number of unique assessment times, the score test under the grouped continuous model retains the type I error rate asymptotically under ATD; however, although the approximate permutation test based on the permutation central limit theorem is not asymptotically valid under every ATD scenario, we show through simulation that in many ATD scenarios it retains the type I error rate better than the score test. We show a case where the approximate permutation test retains the type I error rate when the exact permutation test does not. We study and modify the multiple imputation logrank tests of Huang, Lee and Yu (2008, Statistics in Medicine, 27: 3217–3226), showing that the distribution of the rank-like scores asymptotically does not depend on the assessment times. We show through simulations that our modifications of the multiple imputation logrank tests retain the type I error rate in all cases studied, even with ATD and a small number of individuals in each treatment group. Simulations were performed using the interval R package. US Government work, in the Public Domain
interval censoring; multiple imputation; rank test; permutation test; survival analysis; within cluster resampling
We evaluated the kinetics of 18F-sodium fluoride (NaF) and reassessed the recommended dose, optimal uptake period, and reproducibility using a current-generation PET/CT scanner.
In this prospective study, 73 patients (31 patients with multiple myeloma or myeloma precursor disease and 42 with prostate cancer) were injected with a mean administered dose of 141 MBq of 18F-NaF. Sixty patients underwent 3 sequential sessions of 3-dimensional PET/CT of the torso beginning ~15 min after 18F-NaF injection, followed by a whole-body 3-dimensional PET/CT at 2 h. The remaining 13 prostate cancer patients were imaged only at 2 and 3 h after injection. Twenty-one prostate cancer patients underwent repeat baseline studies (mean interval, 5.9 d) to evaluate reproducibility.
The measured effective dose was 0.017 mSv/MBq, with the urinary bladder, osteogenic cells, and red marrow receiving the highest doses at 0.080, 0.077, and 0.028 mGy/MBq, respectively. Visual analysis showed that uptake in both normal and abnormal bone increased with time; however, the rate of increase decreased with time. A semiautomated workflow provided objective uptake parameters, including the mean standardized uptake value of all pixels within bone with SUVs greater than 10 and the average of the mean SUV of all malignant lesions identified by the algorithm. The values of these parameters for the images beginning at ~15 min and ~35 min were significantly different (0.3% change/minute). Differences between the later imaging time points were not significant (P < 0.01). Repeat baseline studies showed high intraclass correlations (>0.9) and relatively low critical percent change (the value above which a change can be considered real) for these parameters. The tumor-to-normal bone ratio, based on the SUVmax of identified malignant lesions, decreased with time; however, this difference was small, estimated at ~0.16%/min in the first hour.
18F-NaF PET/CT images obtained with modest radiation exposures can result in highly reproducible imaging parameters. Although the tumor-to-normal bone ratio decreases slightly with time, the high temporal dependence during uptake periods < 30 min may limit accurate quantitation. An uptake period of 60 ± 30 min has limited temporal dependence while maintaining high tumor-to-normal bone ratio.
bone scanning; oncology; pet/ct; prostate cancer; multiple myeloma
The purpose of this study was to evaluate the activity of single-agent bevacizumab in patients with recurrent anaplastic glioma and assess correlative advanced imaging parameters. Patients with recurrent anaplastic glioma were treated with bevacizumab 10 mg/kg every 2 weeks. Complete patient evaluations were repeated every 4 weeks. Correlative dynamic contrast-enhanced MR and 18fluorodeoxyglucose PET imaging studies were obtained to evaluate physiologic changes in tumor and tumor vasculature at time points including baseline, 96 h after the first dose, and after the first 4 weeks of therapy. Median overall survival was 12 months (95% confidence interval [CI]: 6.08–22.8). Median progression-free survival was 2.93 months (95% CI: 2.01–4.93), and 6-month progression-free survival was 20.9% (95% CI: 10.3%–42.5%). Thirteen (43%) patients achieved a partial response. The most common grade ≥3 treatment-related toxicities were hypertension, hypophosphatemia, and thromboembolism. Single-agent bevacizumab produces significant radiographic response in patients with recurrent anaplastic glioma but did not meet the 6-month progression-free survival endpoint. Early change in enhancing tumor volume at 4 days after start of therapy was the most significant prognostic factor for overall and progression-free survival.
anaplastic glioma; bevacizumab; FDG; perfusion MRI
Noninvasive evaluation using MRI is the primary means to routinely assess children with diffuse intrinsic pontine gliomas (DIPGs). However, no standard MR sequence has correlated with outcome in these patients. In this study, patients with DIPGs were assessed to determine the combined prognostic value via dynamic susceptibility contrast (DSC) MRI, single-voxel spectroscopy (SVS), multivoxel MR spectroscopy (MRS), and T1-weighted post-gadolinium imaging. Eligible patients had clinical and radiographic findings consistent with a DIPG. Imaging studies were acquired on a 1.5T MRI at various time points during each patient's course. Data were evaluated using a Cox proportional hazard model, a time-dependent covariant Cox model, a Wald test, and a Kaplan–Meier analysis. Ninety-eight studies were performed on 34 patients of median age 5.5 years. Median survival from diagnosis was 468 days. At baseline imaging only, increased ratio of choline to n-acetylaspartate (Cho:NAA) on SVS and increased perfusion on DSC-MRI each predicted shorter survival (relative risk [RR] = 1.48, P = .015 and RR = 4.91, P = .0012, respectively). When analyzing all subsequent time points, increased maximum Cho:NAA on MRS (RR = 1.45, P = .042), increased Cho:NAA on SVS (RR = 1.69, P = .003), increased perfusion (RR = 4.68, P = .0016), and the presence of enhancement (RR = 5.69, P = .022) each predicted shorter survival. Kaplan–Meier analysis showed shorter survival associated with increased perfusion at baseline (P = .0004). Increased perfusion at any time point predicts a significantly shorter survival in children with DIPG. In addition, enhancement, increased Cho:NAA on SVS, and increased maximum Cho:NAA on chemical shift imaging are predictive of shorter survival over time. Routine baseline and subsequent imaging for children with DIPG should, at minimum, incorporate DSC-MRI and SVS.
diffuse intrinsic pontine glioma; MR spectroscopy; pediatric; prognosis; susceptibility perfusion
Esophageal squamous cell carcinoma (ESCC), the predominant histological subtype of esophageal cancer, is characterized by high mortality. Previous work identified important mRNA expression differences between normal and tumor cells; however, to date there are limited ex vivo studies examining expression changes occurring during normal esophageal squamous cell differentiation versus those associated with tumorigenesis. In this study, we used a unique tissue microdissection strategy and microarrays to measure gene expression profiles associated with cell differentiation versus tumorigenesis in twelve cases of patient-matched normal basal squamous epithelial cells (NB), normal differentiated squamous epithelium (ND), and squamous cell cancer. Class comparison and pathway analysis were used to compare NB versus tumor in a search for unique therapeutic targets.
As a first step towards this goal, gene expression profiles and pathways were evaluated. Overall, ND expression patterns were markedly different from NB and tumor; whereas, tumor and NB were more closely related. Tumor showed a general decrease in differentially expressed genes relative to NB as opposed to ND that exhibited the opposite trend. FSH and IgG networks were most highly dysregulated in normal differentiation and tumorigenesis, respectively. DNA repair pathways were generally elevated in NB and tumor relative to ND indicating involvement in both normal and pathological growth. PDGF signaling pathway and 12 individual genes unique to the tumor/NB comparison were identified as therapeutic targets, and 10 associated ESCC gene-drug pairs were identified. We further examined the protein expression level and the distribution patterns of four genes: ODC1, POSTN, ASPA and IGF2BP3. Ultimately, three genes (ODC1, POSTN, ASPA) were verified to be dysregulated in the same pattern at both the mRNA and protein levels.
These data reveal insight into genes and molecular pathways mediating ESCC development and provide information potentially useful in designing novel therapeutic interventions for this tumor type.
Patients with diffuse intrinsic pontine glioma (DIPG) face a grim prognosis with limited treatment options. Many patients will enroll on investigational trials though the role of chemotherapy or immunotherapy is unclear. Radiographic changes on conventional MRI are used to evaluate tumor response and progression, but are not predictive of outcome in these patients. More sensitive measures of tumor biology are needed to improve patient management. We evaluated changes in magnetic resonance spectroscopy (MRS) biomarkers in patients with DIPG. Thirty-eight patients were enrolled prospectively on an IRB-approved protocol, which included standard MRI, single voxel spectroscopy (SVS) and multi-slice multi-voxel spectroscopy (MRSI). Scans were performed at multiple time points during each patient’s clinical course, with a total of 142 scans. The prognostic values of Choline:N-acetylaspartate (Cho:NAA), Cho:Creatine (Cho:Cr) and the presence of lactate and lipids (+Lac/Lip) were evaluated. Cho:NAA and variance in Cho:NAA values among different voxels within a tumor were each predictive of shorter survival. This prospective study shows that MRS can be used to identify high-risk patients and monitor changes in tumor metabolism, which may reflect changes in tumor behavior.
pediatric; brain; brainstem tumor; MRI; MR spectroscopy; prognosis
A novel platform was developed that fuses pre-biopsy magnetic resonance imaging with real-time transrectal ultrasound imaging to identify and biopsy lesions suspicious for prostate cancer. The cancer detection rates for the first 101 patients are reported.
Materials and Methods
This prospective, single institution study was approved by the institutional review board. Patients underwent 3.0 T multiparametric magnetic resonance imaging with endorectal coil, which included T2-weighted, spectroscopic, dynamic contrast enhanced and diffusion weighted magnetic resonance imaging sequences. Lesions suspicious for cancer were graded according to the number of sequences suspicious for cancer as low (2 or less), moderate (3) and high (4) suspicion. Patients underwent standard 12-core transrectal ultrasound biopsy and magnetic resonance imaging/ultrasound fusion guided biopsy with electromagnetic tracking of magnetic resonance imaging lesions. Chi-square and within cluster resampling analyses were used to correlate suspicion on magnetic resonance imaging and the incidence of cancer detected on biopsy.
Mean patient age was 63 years old. Median prostate specific antigen at biopsy was 5.8 ng/ml and 90.1% of patients had a negative digital rectal examination. Of patients with low, moderate and high suspicion on magnetic resonance imaging 27.9%, 66.7% and 89.5% were diagnosed with cancer, respectively (p <0.0001). Magnetic resonance imaging/ultrasound fusion guided biopsy detected more cancer per core than standard 12-core transrectal ultrasound biopsy for all levels of suspicion on magnetic resonance imaging.
Prostate cancer localized on magnetic resonance imaging may be targeted using this novel magnetic resonance imaging/ultrasound fusion guided biopsy platform. Further research is needed to determine the role of this platform in cancer detection, active surveillance and focal therapy, and to determine which patients may benefit.
prostatic neoplasms; biopsy; magnetic resonance imaging; ultrasonography; early detection of cancer
In many medical studies, patients are followed longitudinally and interest is on assessing the relationship between longitudinal measurements and time to an event. Recently, various authors have proposed joint modeling approaches for longitudinal and time-to-event data for a single longitudinal variable. These joint modeling approaches become intractable with even a few longitudinal variables. In this paper we propose a regression calibration approach for jointly modeling multiple longitudinal measurements and discrete time-to-event data. Ideally, a two-stage modeling approach could be applied in which the multiple longitudinal measurements are modeled in the first stage and the longitudinal model is related to the time-to-event data in the second stage. Biased parameter estimation due to informative dropout makes this direct two-stage modeling approach problematic. We propose a regression calibration approach which appropriately accounts for informative dropout. We approximate the conditional distribution of the multiple longitudinal measurements given the event time by modeling all pairwise combinations of the longitudinal measurements using a bivariate linear mixed model which conditions on the event time. Complete data are then simulated based on estimates from these pairwise conditional models, and regression calibration is used to estimate the relationship between longitudinal data and time-to-event data using the complete data. We show that this approach performs well in estimating the relationship between multivariate longitudinal measurements and the time-to-event data and in estimating the parameters of the multiple longitudinal process subject to informative dropout. We illustrate this methodology with simulations and with an analysis of primary biliary cirrhosis (PBC) data.
Joint models; shared random parameter models; informative dropout; regression calibration
In genetic family studies, ages at onset of diseases are routinely collected. Often one is interested in assessing the familial association of ages at onset of a certain disease type. However, when a competing risk is present and is related to the disease of interest, the usual measure of association by treating the competing event as an independent censoring event is biased. We propose a bivariate model that incorporates two types of association: one is between the first event time of paired members, and the other is between the failure types given the first event time. We consider flexible measures for both types of association, and estimate the corresponding association parameters by adopting the two-stage estimation of Shih and Louis (1995) and Nan et al. (2006). The proposed method is illustrated using the kinship data from the Washington Ashkenazi Study.
cause-specific cross-ratio; competing risk; familial association; odds-ratio
Cancer patients have highly variable clinical outcomes owing to many factors, among which are genes that determine the likelihood of invasion and metastasis. This predisposition can be reflected in the gene expression pattern of the primary tumor, which may predict outcomes and guide the choice of treatment better than other clinical predictors.
We developed an mRNA expression-based model that can predict prognosis/outcomes of human breast cancer patients regardless of microarray platform and patient group. Our model was developed using genes differentially expressed in mouse plasma cell tumors growing in vivo versus those growing in vitro. The prediction system was validated using published data from three cohorts of patients for whom microarray and clinical data had been compiled. The model stratified patients into four independent survival groups (BEST, GOOD, BAD, and WORST: log-rank test p = 1.7×10−8).
Our model significantly improved the survival prediction over other expression-based models and permitted recognition of patients with different prognoses within the estrogen receptor-positive group and within a single pathological tumor class. Basing our predictor on a dataset that originated in a different species and a different cell type may have rendered it less sensitive to proliferation differences and endowed it with wide applicability.
Prognosis prediction for patients with breast cancer is currently based on histopathological typing and estrogen receptor positivity. Yet both assays define groups that are heterogeneous in survival. Gene expression profiling allows subdivision of these groups and recognition of patients whose tumors are very unlikely to be lethal and those with much grimmer outlooks, which can augment the predictive power of conventional tumor analysis and aid the clinician in choosing relaxed vs. aggressive therapy.
Gene expression profiling by microarray analysis of cells enriched by laser capture microdissection (LCM) faces several technical challenges. Frozen sections yield higher quality RNA than paraffin-imbedded sections, but even with frozen sections, the staining methods used for histological identification of cells of interest could still damage the mRNA in the cells. To study the contribution of staining methods to degradation of results from gene expression profiling of LCM samples, we subjected pellets of the mouse plasma cell tumor cell line TEPC 1165 to direct RNA extraction and to parallel frozen sectioning for LCM and subsequent RNA extraction. We used microarray hybridization analysis to compare gene expression profiles of RNA from cell pellets with gene expression profiles of RNA from frozen sections that had been stained with hematoxylin and eosin (H&E), Nissl Stain (NS), and for immunofluorescence (IF) as well as with the plasma cell-revealing methyl green pyronin (MGP) stain. All RNAs were amplified with two rounds of T7-based in vitro transcription and analyzed by two-color expression analysis on 10-K cDNA microarrays.
The MGP-stained samples showed the least introduction of mRNA loss, followed by H&E and immunofluorescence. Nissl staining was significantly more detrimental to gene expression profiles, presumably owing to an aqueous step in which RNA may have been damaged by endogenous or exogenous RNAases.
RNA damage can occur during the staining steps preparatory to laser capture microdissection, with the consequence of loss of representation of certain genes in microarray hybridization analysis. Inclusion of RNAase inhibitor in aqueous staining solutions appears to be important in protecting RNA from loss of gene transcripts.
The most used prognostic scheme for malignant gliomas only included patients between ages 18 to 70 years. The purpose of this study was to develop a prognostic model for patients ≥70 years of age with newly diagnosed glioblastoma.
Four hundred and thirty-seven patients ≥70 years of age with newly diagnosed glioblastoma, pooled from two tertiary academic institutions, were identified for recursive partitioning analysis (RPA). A resulting prognostic model, based on the final pruned RPA tree, was validated using two hundred and sixty-five glioblastoma patients ≥70 years of age from a dataset independently compiled by a French consortium.
RPA produced nine terminal nodes, which were pruned to four prognostic subgroups with markedly different median survivals: I – patients <75.5 years of age who underwent surgical resection (9.3 mos); II – patients ≥75.5 years of age who underwent surgical resection (6.4 mos); III – patients with KPS of 70–100 who underwent biopsy only (4.6 mos); and IV – patients with KPS <70 who underwent biopsy only (2.3 mos). Application of this prognostic model to the French cohort also resulted in significantly different (P<0.0001) median survivals for subgroups I (8.5 mos), II (7.7 mos), III (4.3 mos), and IV (3.1 mos).
This model divides elderly glioblastoma patients into prognostic subgroups that can be easily implemented in both the patient care and the clinical trial settings. This purely clinical prognostic model serves as a backbone for the future incorporation of the increasing number of potential molecular prognostic markers.
The dismal lethality of lung cancer is due to late stage at diagnosis and inherent therapeutic resistance. The incorporation of targeted therapies has modestly improved clinical outcomes, but the identification of new targets could further improve clinical outcomes by guiding stratification of poor-risk early stage patients and individualizing therapeutic choices. We hypothesized that a sequential, combined microarray approach would be valuable to identify and validate new targets in lung cancer. We profiled gene expression signatures during lung epithelial cell immortalization and transformation, and showed that genes involved in mitosis were progressively enhanced in carcinogenesis. 28 genes were validated by immunoblotting and 4 genes were further evaluated in non-small cell lung cancer tissue microarrays. Although CDK1 was highly expressed in tumor tissues, its loss from the cytoplasm unexpectedly predicted poor survival and conferred resistance to chemotherapy in multiple cell lines, especially microtubule-directed agents. An analysis of expression of CDK1 and CDK1-associated genes in the NCI60 cell line database confirmed the broad association of these genes with chemotherapeutic responsiveness. These results have implications for personalizing lung cancer therapy and highlight the potential of combined approaches for biomarker discovery.
Tobacco smoking is responsible for over 90% of lung cancer cases, and yet the precise molecular alterations induced by smoking in lung that develop into cancer and impact survival have remained obscure.
We performed gene expression analysis using HG-U133A Affymetrix chips on 135 fresh frozen tissue samples of adenocarcinoma and paired noninvolved lung tissue from current, former and never smokers, with biochemically validated smoking information. ANOVA analysis adjusted for potential confounders, multiple testing procedure, Gene Set Enrichment Analysis, and GO-functional classification were conducted for gene selection. Results were confirmed in independent adenocarcinoma and non-tumor tissues from two studies. We identified a gene expression signature characteristic of smoking that includes cell cycle genes, particularly those involved in the mitotic spindle formation (e.g., NEK2, TTK, PRC1). Expression of these genes strongly differentiated both smokers from non-smokers in lung tumors and early stage tumor tissue from non-tumor tissue (p<0.001 and fold-change >1.5, for each comparison), consistent with an important role for this pathway in lung carcinogenesis induced by smoking. These changes persisted many years after smoking cessation. NEK2 (p<0.001) and TTK (p = 0.002) expression in the noninvolved lung tissue was also associated with a 3-fold increased risk of mortality from lung adenocarcinoma in smokers.
Our work provides insight into the smoking-related mechanisms of lung neoplasia, and shows that the very mitotic genes known to be involved in cancer development are induced by smoking and affect survival. These genes are candidate targets for chemoprevention and treatment of lung cancer in smokers.