Gene Selection using a High-Dimensional Regression Model with Microarrays in Cancer Prognostic Studies

Mining of gene expression data to identify genes associated with patient survival is an ongoing problem in cancer prognostic studies using microarrays in order to use such genes to achieve more accurate prognoses. The least absolute shrinkage and selection operator (lasso) is often used for gene selection and parameter estimation in high-dimensional microarray data. The lasso shrinks some of the coefficients to zero, and the amount of shrinkage is determined by the tuning parameter, often determined by cross validation. The model determined by this cross validation contains many false positives whose coefficients are actually zero. We propose a method for estimating the false positive rate (FPR) for lasso estimates in a high-dimensional Cox model. We performed a simulation study to examine the precision of the FPR estimate by the proposed method. We applied the proposed method to real data and illustrated the identification of false positive genes

A New Test Statistic Based on Shrunken Sample Variance for Identifying Differentially Expressed Genes in Small Microarray Experiments

Choosing an appropriate statistic and precisely evaluating the false discovery rate (FDR) are both essential for devising an effective method for identifying differentially expressed genes in microarray data. The t-type score proposed by Pan et al. (2003) succeeded in suppressing false positives by controlling the underestimation of variance but left the overestimation uncontrolled. For controlling the overestimation, we devised a new test statistic (variance stabilized t-type score) by placing shrunken sample variances of the James-Stein type in the denominator of the t-type score. Since the relative superiority of the mean and median FDRs was unclear in the widely adopted Significance Analysis of Microarrays (SAM), we conducted simulation studies to examine the performance of the variance stabilized t-type score and the characteristics of the two FDRs. The variance stabilized t-type score was generally better than or at least as good as the t-type score, irrespective of the sample size and proportion of differentially expressed genes. In terms of accuracy, the median FDR was superior to the mean FDR when the proportion of differentially expressed genes was large. The variance stabilized t-type score with the median FDR was applied to actual colorectal cancer data and yielded a reasonable result

Estimating the False Discovery Rate Using Mixed Normal Distribution for Identifying Differentially Expressed Genes in Microarray Data Analysis

The recent development of DNA microarray technology allows us to measure simultaneously the expression levels of thousands of genes and to identify truly correlated genes with anticancer drug response (differentially expressed genes) from many candidate genes. Significance Analysis of Microarray (SAM) is often used to estimate the false discovery rate (FDR), which is an index for optimizing the identifiability of differentially expressed genes, while the accuracy of the estimated FDR by SAM is not necessarily confirmed. We propose a new method for estimating the FDR assuming a mixed normal distribution on the test statistic and examine the performance of the proposed method and SAM using simulated data. The simulation results indicate that the accuracy of the estimated FDR by the proposed method and SAM, varied depending on the experimental conditions. We applied both methods to actual data comprised of expression levels of 12,625 genes of 10 responders and 14 non-responders to docetaxel for breast cancer. The proposed method identified 280 differentially expressed genes correlated with docetaxel response using a cut-off value for achieving FDR <0.01 to prevent false-positive genes, although 92 genes were previously thought to be correlated with docetaxel response ones

A phase 2 basket trial of combination therapy with trastuzumab and pertuzumab in patients with solid cancers harboring human epidermal growth factor receptor 2 amplification (JUPITER trial)

Introduction: Human epidermal growth factor receptor 2 (HER2) gene amplification and mutations have emerged as oncogenic drivers and therapeutic targets not limited to breast and gastric cancers, but also in a variety of cancers. However, even if an actionable gene alteration is found, the incidence of HER2 amplification in these cancers is less than 5%. It is too difficult to conduct a conventional randomized, controlled trial in a rare fraction. Therefore, we have designed a organ-agnostic basket study, which covers a variety of solid cancers harboring HER2 amplification, in 1 study protocol. Methods/Design: This trial is a multicenter, single-arm, basket phase 2 study in Japan. Patients with solid cancers harboring HER2 amplification that have progressed with standard treatment, or rare cancers for which there is no standard treatment, will be eligible. Target cancers include bile duct, urothelial, uterine, ovarian, and other solid cancers where HER2 amplification is detected by comprehensive genomic profiling using next-generation sequencing technology. A total of 38 patients will be treated with combination therapy with trastuzumab and pertuzumab every 3 weeks until disease progression, unmanageable toxicity, death, or patient refusal. The primary endpoint is the objective response rate, and secondary endpoints are progression-free survival, overall survival, and duration of response. Discussion: The aim of this trial is to evaluate the safety and efficacy of combination therapy with trastuzumab and pertuzumab in patients with locally advanced or metastatic, solid cancers harboring HER2 amplification. Instead of focusing on 1 organ type, our trial design uses a basket study focusing on HER2 amplification, regardless of the site or origin of the cancer. The results of our study will advance clinical and scientific knowledge concerning the treatment of locally advanced, rare solid cancers harboring HER2 amplification, using the combination of trastuzumab and pertuzumab. Trial registration: This trial was registered in Japan Registry of Clinical Trials (jCRT) on February 25, 2019, as jRCT2031180150

Administration of Bone Marrow-Derived Mononuclear Cells Contributed to the Reduction of Hypoxic-Ischemic Brain Injury in Neonatal Rats

Background/Objective: Perinatal hypoxic-ischemia (HI) causes neonatal death and permanent neurological deficits. Cell therapy using various cell sources has been recently identified as a novel therapy for perinatal HI. Among the available types of cell sources, bone marrow-derived mononuclear cells (BMMNCs) have unique features for clinical application. For example, stem cells can be collected after admission, thus enabling us to perform autologous transplantation. This study aimed to investigate whether the administration of BMMNCs ameliorated HI brain injury in a neonatal rat model.Methods: Seven-day-old rats underwent left carotid artery ligation and were exposed to 8% oxygen for 60 min. BMMNCs were collected from the femurs and tibias of juvenile rats using the Ficoll–Hypaque technique and injected intravenously 24 h after the insult (1 × 105 cells). Active caspase-3, as an apoptosis marker, and ED1, as an activated microglia/macrophage marker, were evaluated immunohistochemically 48 h after the insult (vehicle, n = 9; BMMNC, n = 10). Behavioral assessments using the rotarod treadmill, gait analysis, and active avoidance tests were initiated 3 weeks after the insult (sham, n = 9, vehicle, n = 8; BMMNC, n = 8). After these behavioral tests (6 weeks after the insult), we evaluated the volumes of their hippocampi, cortices, thalami, striata, and globus pallidus.Results: The mean cell densities of the sum of four parts that were positive for active caspase-3 significantly decreased in the BMMNC group (p &lt; 0.05), whereas in the hippocampi, cortices, thalami, and striata cell densities decreased by 42, 60, 56, and 47%, respectively, although statistical significance was not attained. The number of ED1 positive cells for the sum of the four parts also significantly decreased in the BMMNC group compared to the vehicle group (p &lt; 0.05), whereas in each of the four parts the decrease was 35, 39, 47, and 36%, respectively, although statistical significance was not attained. In gait analysis, the BMMNC normalized the contact area of the affected hind paw widened by HI. The volumes of the affected striata and globus pallidus were significantly larger in the BMMNC group than in the control group.Conclusion: These results indicated that the injection of BMMNCs ameliorated HI brain injury in a neonatal rat model

Consistency between chromosomal status analysis of biopsied human blastocyst trophectoderm cells and whole blastocyst cells

Purpose This study investigated the consistency between results of preimplantation genetic testing for aneuploidy performed on trophectoderm (TE) cells and remaining blastocyst cells. Methods TE biopsy was performed on 29 surplus cryopreserved human blastocysts. Biopsy samples and remaining blastocysts were processed using the VeriSeq PGS kit, and chromosomal statuses were compared by next-generation sequencing. Results Discordance was observed in the chromosomal status of 11 out of 29 blastocysts between the biopsied TE and remaining blastocysts. Concordance was observed in 11 of 12 blastocysts classified as euploid by TE biopsy and in 7 of 17 blastocysts classified as aneuploid. There was 100% concordance (7/7) in cases diagnosed as aneuploid with no mosaicism by TE biopsy. However, discordance was observed in all 10 cases showing mosaicism or partial chromosomal abnormality. Conclusion Chromosomal status analysis based on TE biopsy does not accurately reflect the chromosomal status of the whole blastocyst. The chromosomal status is usually the same between the TE and remaining blastocyst cells in cases diagnosed as euploid or aneuploid with no mosaicism. However, mosaic blastocysts and those with other types of structural rearrangements have a higher risk of inconsistency, warranting caution during embryo selection

Immunohistochemical Profile for Unknown Primary Adenocarcinoma

BACKGROUND: Development of tailored treatment based on immunohistochemical profiles (IPs) of tumors for cancers of unknown primary is needed. METHODOLOGY/PRINCIPAL FINDINGS: We developed an algorithm based on primary known adenocarcinoma for testing sensitivity and specificity. Formalin-fixed paraffin-embedded tissue samples from 71 patients of unfavorable subsets of unknown primary adenocarcinoma were obtained. We examined 15 molecular markers using the algorithm incorporating these IPs and classified the tumours into 9 subsets based on the primary tumour site. The sensitivity and specificity of this algorithm were 80.3% and 97.6%, respectively. Apparent primary sites were lung in 17 patients, digestive organs in 13, gynecological organs in 9, prostate in 7, liver or kidney in 6, breast in 4, urothelial organ in 2, biliary tract and pancreatic profile in none, and unclassified in 13. The response rate to chemotherapy was highest for the gynecological IPs. Patients with gynecological or lung cancer IPs had longer median progression-free survival than those with others: 11.2 months for gynecological IPs (p<0.001) and 6.8 months for lung IPs (p = 0.05). Lung, digestive, prostate, and gynecological profiles were associated with significantly longer median survival time than the other profiles. Multivariate analysis confirmed that the IPs were independent prognostic factors for survival. CONCLUSIONS/SIGNIFICANCE: The IPs identified in this study can be used to further stratify patient prognosis for unfavorable subsets of unknown primary adenocarcinoma

Enhancing the Lasso Approach for Developing a Survival Prediction Model Based on Gene Expression Data

In the past decade, researchers in oncology have sought to develop survival prediction models using gene expression data. The least absolute shrinkage and selection operator (lasso) has been widely used to select genes that truly correlated with a patient’s survival. The lasso selects genes for prediction by shrinking a large number of coefficients of the candidate genes towards zero based on a tuning parameter that is often determined by a cross-validation (CV). However, this method can pass over (or fail to identify) true positive genes (i.e., it identifies false negatives) in certain instances, because the lasso tends to favor the development of a simple prediction model. Here, we attempt to monitor the identification of false negatives by developing a method for estimating the number of true positive (TP) genes for a series of values of a tuning parameter that assumes a mixture distribution for the lasso estimates. Using our developed method, we performed a simulation study to examine its precision in estimating the number of TP genes. Additionally, we applied our method to a real gene expression dataset and found that it was able to identify genes correlated with survival that a CV method was unable to detect

Dose-finding designs for early-phase cancer clinical trials: a brief guidebook to theory and practice

This book provides a comprehensive introduction to statistical methods for designing early phase dose-finding clinical trials. It will serve as a textbook or handbook for graduate students and practitioners in biostatistics and clinical investigators who are involved in designing, conducting, monitoring, and analyzing dose-finding trials. The book will also provide an overview of advanced topics and discussions in this field for the benefit of researchers in biostatistics and statistical science. Beginning with backgrounds and fundamental notions on dose finding in early phase clinical trials, the book then provides traditional and recent dose-finding designs of phase I trials for, e.g., cytotoxic agents in oncology, to evaluate toxicity outcome. Included are rule-based and model-based designs, such as 3 + 3 designs, accelerated titration designs, toxicity probability interval designs, continual reassessment method and related designs, and escalation overdose control designs. This book also covers more complex and updated dose-finding designs of phase I-II and I/II trials for cytotoxic agents, and cytostatic agents, focusing on both toxicity and efficacy outcomes, such as designs with covariates and drug combinations, maximum tolerated dose-schedule finding designs, and so on