Challenges, opportunities, and innovative statistical designs for precision oncology trials.

In the era of precision oncology, improved understanding of tumor heterogeneity, particularly at the molecular level, has caused a shift from traditionally histology based cancer drug development to molecularly targeted drug development. The shift to the molecular view of cancer leads to increasingly small cancer populations for clinical trials which may be underpowered using traditional statistical designs. This paradigm shift lead to the recent developments of innovative clinical trial designs to address the challenges from precision oncology clinical trials. Hence, this paper reviewed and described innovative trial designs for precision oncology. Different strategies were discussed to account patient and treatment effect heterogeneity, including precision dose-finding designs that tailor the optimal dose to different patients at different time points, master protocol designs that match patients' molecular alterations with specific targeted agents, and adaptive enrichment designs that dynamically modify eligibility criteria and enroll patients that are most likely to benefit from the novel agents. Despite their superior performance, better understanding of practical barriers is needed to widen their implementation for precision oncology trials. Therefore, this paper also reviewed the practical challenges regarding the implementation of precision oncology clinical trials, along with the strength and weakness of various approaches of precision oncology clinical trial designs.

Enhanced degradation of tetracycline by Cu(II) complexation in the FeS/sulfite system.

This study applied a mineral material of FeS to activate sulfite for efficient degradation of TTC in the presence of Cu(II) based on the identified complexation mechanism through UV-Vis spectra, FTIR spectroscopy and DFT calculation. pH plays an important role in TTC degradation and the initial pH of 6 and 7 were the divide in the contributions of FeS/sulfite oxidation and complex-precipitation. TTC-Cu(II) exhibits a superior promoting effect on the TTC degradation in FeS/sulfite system due to the improvement of TTC electron transfer reactivity and Fe(II) dissolution from FeS. Moreover, the formation of Cu(I) improved the recycling of Fe(II) from Fe(III). Dissolved oxygen-dependent free radicals' generation was confirmed, and TTC degradation was mainly attributed to SO4·- and ·OH. The characterization of FeS surface through XPS, XRD, SEM-EDS, Fe(II) deactivation tests, together with the comparison of pseudo-first-order rate constants for TTC degradation by FeS and ferrous ion supported the important role of surface and dissolved Fe(II) in sulfite activation. Furthermore, reasonable degradation pathways of TTC have been proposed according to the detected products by LC-MS. This work highlights the important role of pH, DO and Cu(II) complexation in sulfite activation and TTC degradation, furnishing theoretical support for further relevant studies.

New insights into FeS/persulfate system for tetracycline elimination: Iron valence, homogeneous-heterogeneous reactions and degradation pathways.

In this study, complete tetracycline (TTC) and above 50% of total organic carbon (TOC) were removed by FeS/PS after 30 min under optimized conditions. Although free radicals and high-valent iron ions were identified to generate in the process, the apparent similarity between intermediate products of FeS/PS, Fe/PS, and UV/PS systems demonstrated that the degradation of TTC was due to sulfate radicals (SO4⋅-) and hydroxyl radicals (⋅OH). Based on the reaction between free radicals and organic matter, we speculated that TTC in the FeS/PS system was decomposed and mineralized by dehydration, dehydrogenation, hydroxyl addition, demethylation, substitution, E-transfer, and ring-opening. Furthermore, a new understanding of FeS-mediated PS activation based on stoichiometry and kinetic analysis showed that there were both homogeneous and heterogeneous reactions that occurred in the entire progress. However, due to the effect of pH on the dissolution of iron ions, the homogeneous reaction became the principal process with iron ions concentration exceeding 1.35 mg/L. This work provides a theoretical basis for the study of the degradation of TTC-containing wastewater by the iron-based advanced oxidation process.

phase1RMD: An R package for repeated measures dose-finding designs with novel toxicity and efficacy endpoints.

Traditional dose-finding designs are substantially inefficient for targeted agents and cancer immunotherapies by failing to incorporate efficacy signals, mild and moderate adverse events, and late, cumulative toxicities. However, the lack of user-friendly software is a barrier to the practical use of the novel phase I designs, despite their demonstrated superiority of traditional 3+3 designs. To overcome these barriers, we present an R package, phase1RMD, which provides a comprehensive implementation of novel designs with repeated toxicity measures and early efficacy. A novel phase I repeated measures design that used a continuous toxicity score from multiple treatment cycles was implemented. Furthermore, in studies where preliminary efficacy is evaluated, an adaptive, multi-stage design to identify the most efficacious dose with acceptable toxicity was demonstrated. Functions are provided to recommend the next dose based on the data collected in a phase I trial, as well as to assess trial characteristics given design parameters via simulations. The repeated measure designs accurately estimated both the magnitude and direction of toxicity trends in late treatment cycles, and allocated more patients at therapeutic doses. The R package for implementing these designs is available from the Comprehensive R Archive Network. To our best knowledge, this is the first software that implement novel phase I dose-finding designs that simultaneously accounts for the multiple-grade toxicity events over multiple treatment cycles and a continuous early efficacy outcome. With the software published on CRAN, we will pursue the implementation of these designs in phase I trials in real-life settings.

Determination of Methomyl Residue in Tobacco Samples by Heart-Cutting Two-Dimensional Liquid Chromatography with Tandem Mass Spectrometry.

A novel heart-cutting two-dimensional liquid chromatography coupled with tandem mass spectrometry (2D-LC-MS/MS) was developed for the qualitative and quantitative analysis of methomyl residue in tobacco. Compared to traditional methodologies, fairly high sensitivity and stability were achieved, and the sample procedure was simplified in the two-dimensional liquid chromatography (2D-LC) method. Although methomyl had poor retention performance in most of the reversed-phase liquid chromatography (RPLC) columns, an effective RP/RP strategy was successfully facilitated. An XB-Phenyl column was employed in the first dimension to effectively remove thousands of interference compounds in the matrix. In the second dimension, an ADME column was applied for further separation. After optimization of the separation conditions, a six-way valve was utilized for direct transformation of the target fraction from the 1st column to the 2nd column. A dynamic range of 2.5 ng/mL to 500 ng/mL was achieved with correlation coefficient (r 2) greater than 0.9995. The limit of detection and limit of quantification were determined to be 0.69 and 2.30 ng/mL, respectively. The 2D-LC method shows high sensitivity, good reproducibility, and recovery for methomyl in tobacco samples. Therefore, the new method was quite suitable for routine analysis.

Residue measurement of pendimethalin in tobacco by using heart-cutting two dimensional liquid chromatography coupled with tandem mass spectrometry.

A novel heart-cutting two-dimensional liquid chromatography coupled with tandem mass spectrometry method was developed for quantitative analysis of pendimethalin residue in tobacco. The strategy of reversed phase liquid chromatography coupled with another reversed-phase liquid chromatography was employed for high column efficiency and excellent compatibility of mobile phase. In the first dimensional chromatography, a cyano column with methanol/water as the eluent was applied to separate pendimethalin from thousands of interference components in tobacco. By heart-cutting technique, which effectively removed interference components, the target compound was cut to the second dimensional C18 column for further separation. The pendimethalin residue was finally determined by the tandem mass spectrometry under multiple reaction monitoring reversed-phase liquid chromatography mode. Sample pretreatment of the new method was simplified, involving only extraction and filtration. Compared with traditional methodologies, the new method showed fairly high selectivity and sensitivity with almost no matrix interference. The limit of quantitation for pendimethalin was 1.21 ng/mL, whereas the overall recoveries ranged from 95.7 to 103.3%. The new method has been successfully applied to non-stop measure of 200 real samples, without contamination of ion source. Detection results of the samples agreed well with standard method.

Population and allelic variation of A-to-I RNA editing in human transcriptomes.

BACKGROUND: A-to-I RNA editing is an important step in RNA processing in which specific adenosines in some RNA molecules are post-transcriptionally modified to inosines. RNA editing has emerged as a widespread mechanism for generating transcriptome diversity. However, there remain significant knowledge gaps about the variation and function of RNA editing. RESULTS: In order to determine the influence of genetic variation on A-to-I RNA editing, we integrate genomic and transcriptomic data from 445 human lymphoblastoid cell lines by combining an RNA editing QTL (edQTL) analysis with an allele-specific RNA editing (ASED) analysis. We identify 1054 RNA editing events associated with cis genetic polymorphisms. Additionally, we find that a subset of these polymorphisms is linked to genome-wide association study signals of complex traits or diseases. Finally, compared to random cis polymorphisms, polymorphisms associated with RNA editing variation are located closer spatially to their respective editing sites and have a more pronounced impact on RNA secondary structure. CONCLUSIONS: Our study reveals widespread cis variation in RNA editing among genetically distinct individuals and sheds light on possible phenotypic consequences of such variation on complex traits and diseases.

rMATS-DVR: rMATS discovery of differential variants in RNA.

MOTIVATION: RNA sequences of a gene can have single nucleotide variants (SNVs) due to single nucleotide polymorphisms (SNPs) in the genome, or RNA editing events within the RNA. By comparing RNA-seq data of a given cell type before and after a specific perturbation, we can detect and quantify SNVs in the RNA and discover SNVs with altered frequencies between distinct cellular states. Such differential variants in RNA (DVRs) may reflect allele-specific changes in gene expression or RNA processing, as well as changes in RNA editing in response to cellular perturbations or stimuli. RESULTS: We have developed rMATS-DVR, a convenient and user-friendly software program to streamline the discovery of DVRs between two RNA-seq sample groups with replicates. rMATS-DVR combines a stringent GATK-based pipeline for calling SNVs including SNPs and RNA editing events in RNA-seq reads, with our rigorous rMATS statistical model for identifying differential isoform ratios using RNA-seq sequence count data with replicates. We applied rMATS-DVR to RNA-seq data of the human chronic myeloid leukemia cell line K562 in response to shRNA knockdown of the RNA editing enzyme ADAR1. rMATS-DVR discovered 1372 significant DVRs between knockdown and control. These DVRs encompassed known SNPs and RNA editing sites as well as novel SNVs, with the majority of DVRs corresponding to known RNA editing sites repressed after ADAR1 knockdown. AVAILABILITY AND IMPLEMENTATION: rMATS-DVR is at https://github.com/Xinglab/rMATS-DVR . CONTACT: yxing@ucla.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Transcriptome sequencing reveals aberrant alternative splicing in Huntington's disease.

Huntington's disease (HD) is an autosomal dominant neurodegenerative disorder caused by a CAG expansion in the gene-encoding Huntingtin (HTT). Transcriptome dysregulation is a major feature of HD pathogenesis, as revealed by a large body of work on gene expression profiling of tissues from human HD patients and mouse models. These studies were primarily focused on transcriptional changes affecting steady-state overall gene expression levels using microarray based approaches. A major missing component, however, has been the study of transcriptome changes at the post-transcriptional level, such as alternative splicing. Alternative splicing is a critical mechanism for expanding regulatory and functional diversity from a limited number of genes, and is particularly complex in the mammalian brain. Here we carried out a deep RNA-seq analysis of the BA4 (Brodmann area 4) motor cortex from seven human HD brains and seven controls to systematically discover aberrant alternative splicing events and characterize potential associated splicing factors in HD. We identified 593 differential alternative splicing events between HD and control brains. Using two expanded panels with a total of 108 BA4 tissues from patients and controls, we identified four splicing factors exhibiting significantly altered expression levels in HD patient brains. Moreover, follow-up molecular analyses of one splicing factor PTBP1 revealed its impact on disease-associated splicing patterns in HD. Collectively, our data provide genomic evidence for widespread splicing dysregulation in HD brains, and suggest the role of aberrant alternative splicing in the pathogenesis of HD.

SURVIV for survival analysis of mRNA isoform variation.

The rapid accumulation of clinical RNA-seq data sets has provided the opportunity to associate mRNA isoform variations to clinical outcomes. Here we report a statistical method SURVIV (Survival analysis of mRNA Isoform Variation), designed for identifying mRNA isoform variation associated with patient survival time. A unique feature and major strength of SURVIV is that it models the measurement uncertainty of mRNA isoform ratio in RNA-seq data. Simulation studies suggest that SURVIV outperforms the conventional Cox regression survival analysis, especially for data sets with modest sequencing depth. We applied SURVIV to TCGA RNA-seq data of invasive ductal carcinoma as well as five additional cancer types. Alternative splicing-based survival predictors consistently outperform gene expression-based survival predictors, and the integration of clinical, gene expression and alternative splicing profiles leads to the best survival prediction. We anticipate that SURVIV will have broad utilities for analysing diverse types of mRNA isoform variation in large-scale clinical RNA-seq projects.

Challenges and Innovations in Phase I Dose-Finding Designs for Molecularly Targeted Agents and Cancer Immunotherapies.

Phase I oncology trials are designed to identify a safe dose with an acceptable toxicity profile. In traditional phase I dose-finding design, the dose is typically determined based on the probability of severe toxicity observed during the first treatment cycle. The recent development of molecularly targeted agents and cancer immunotherapies call for new innovations in phase I designs, because of prolonged treatment cycles often involved. Various phase I designs using toxicity and efficacy endpoints from multiple treatment cycles have been developed for these new treatment agents. Here, we will review the novel endpoints and designs for the phase I oncology clinical trials.

Low-Intensity Pulsed Ultrasound Treatment at an Early Osteoarthritis Stage Protects Rabbit Cartilage From Damage via the Integrin/Focal Adhesion Kinase/Mitogen-Activated Protein Kinase Signaling Pathway.

OBJECTIVES: To investigate whether low-intensity pulsed ultrasound (US) has different protective effects on early and late rabbit osteoarthritis cartilage via the integrin/focal adhesion kinase (FAK)/mitogen-activated protein kinase (MAPK) signaling pathway. METHODS: Thirty-six New Zealand White rabbits were divided into early control, early osteoarthritis, early treatment, late control, late osteoarthritis, and late treatment groups. The early and late osteoarthritis and treatment groups underwent anterior cruciate ligament transection. The remaining groups underwent sham operations with knee joint exposure. The early and late treatment groups were exposed to low-intensity pulsed US 4 and 8 weeks after surgery. After 6 weeks of US exposure, pathologic changes on the articular surface of the femoral condyle were assessed by modified Mankin scores. Expression of type II collagen, matrix metalloproteinase, integrin ß1, phosphorylated FAK, and MAPKs (including extracellular signal-regulated kinase 1/2, MAPK 38, and c-Jun N-terminal kinase) was assessed by Western blot analysis. RESULTS: Cartilage damage was less severe in the early treatment group than the early osteoarthritis group. The Mankin score was significantly lower in the early treatment group than the early osteoarthritis group (P < .05). There was no significant difference in cartilage damage or Mankin score between the late treatment and late osteoarthritis groups. There was a significant increase in type II collagen expression but a significant decrease in matrix metalloproteinase 13 expression in the early treatment group compared to the early osteoarthritis group, whereas no significant difference was found between the late treatment and late osteoarthritis groups. Integrin ß1 and phosphorylated FAK expression was significantly higher, and phosphorylated extracellular signal-regulated kinase 1/2 and phosphorylated MAPK 38 expression was significantly lower in the early treatment group than the early osteoarthritis group. CONCLUSIONS: Our findings indicate that low-intensity pulsed US protects cartilage from damage in early-stage osteoarthritis via the integrin/FAK/MAPK pathway.

Low-Intensity Pulsed Ultrasound Affects Chondrocyte Extracellular Matrix Production via an Integrin-Mediated p38 MAPK Signaling Pathway.

Although low-intensity pulsed ultrasound (LIPUS) regulates p38 mitogen-activated protein kinase (MAPK) and promotes cartilage repair in osteoarthritis, the role of integrin-mediated p38 MAPK in the effect of LIPUS on extracellular matrix (ECM) production of normal and OA chondrocytes remains unknown. The aim of this study was to investigate whether LIPUS affects ECM production in normal and OA rabbit chondrocytes through an integrin-p38 signaling pathway. A rabbit model of OA was established by anterior cruciate ligament transection, and chondrocytes were isolated from normal or OA cartilage and cultured in vitro. Chondrocytes were treated with LIPUS and then pre-incubated with the integrin inhibitor GRGDSP or the p38 inhibitor SB203580. Expression of type II collagen, MMP-13, integrin ß1, p38 and phosphorylated p38 was assessed by Western blot analysis. We found that type II collagen and integrin ß1 were upregulated (p < 0.05), whereas MMP-13 was downregulated (p < 0.05) in normal and OA chondrocytes. Furthermore, phosphorylated p38 was upregulated (p < 0.05) in normal chondrocytes, but downregulated (p < 0.05) in OA chondrocytes after LIPUS stimulation. Pre-incubation of chondrocytes with the integrin inhibitor disrupted the effects of LIPUS on normal and OA chondrocytes. Pre-incubation of chrondocytes with the p38 inhibitor reduced the effects of LIPUS on normal chondrocytes, but had no impact on OA chondrocytes. Our findings suggest that the integrin-p38 MAPK signaling pathway plays an important role in LIPUS-mediated ECM production in chondrocytes.

Transcriptome-wide landscape of pre-mRNA alternative splicing associated with metastatic colonization.

UNLABELLED: Metastatic colonization is an ominous feature of cancer progression. Recent studies have established the importance of pre-mRNA alternative splicing (AS) in cancer biology. However, little is known about the transcriptome-wide landscape of AS associated with metastatic colonization. Both in vitro and in vivo models of metastatic colonization were utilized to study AS regulation associated with cancer metastasis. Transcriptome profiling of prostate cancer cells and derivatives crossing in vitro or in vivo barriers of metastasis revealed splicing factors with significant gene expression changes associated with metastatic colonization. These include splicing factors known to be differentially regulated in epithelial-mesenchymal transition (ESRP1, ESRP2, and RBFOX2), a cellular process critical for cancer metastasis, as well as novel findings (NOVA1 and MBNL3). Finally, RNA-seq indicated a large network of AS events regulated by multiple splicing factors with altered gene expression or protein activity. These AS events are enriched for pathways important for cell motility and signaling, and affect key regulators of the invasive phenotype such as CD44 and GRHL1. IMPLICATIONS: Transcriptome-wide remodeling of AS is an integral regulatory process underlying metastatic colonization, and AS events affect the metastatic behavior of cancer cells.

rMATS: robust and flexible detection of differential alternative splicing from replicate RNA-Seq data.

Ultra-deep RNA sequencing (RNA-Seq) has become a powerful approach for genome-wide analysis of pre-mRNA alternative splicing. We previously developed multivariate analysis of transcript splicing (MATS), a statistical method for detecting differential alternative splicing between two RNA-Seq samples. Here we describe a new statistical model and computer program, replicate MATS (rMATS), designed for detection of differential alternative splicing from replicate RNA-Seq data. rMATS uses a hierarchical model to simultaneously account for sampling uncertainty in individual replicates and variability among replicates. In addition to the analysis of unpaired replicates, rMATS also includes a model specifically designed for paired replicates between sample groups. The hypothesis-testing framework of rMATS is flexible and can assess the statistical significance over any user-defined magnitude of splicing change. The performance of rMATS is evaluated by the analysis of simulated and real RNA-Seq data. rMATS outperformed two existing methods for replicate RNA-Seq data in all simulation settings, and RT-PCR yielded a high validation rate (94%) in an RNA-Seq dataset of prostate cancer cell lines. Our data also provide guiding principles for designing RNA-Seq studies of alternative splicing. We demonstrate that it is essential to incorporate biological replicates in the study design. Of note, pooling RNAs or merging RNA-Seq data from multiple replicates is not an effective approach to account for variability, and the result is particularly sensitive to outliers. The rMATS source code is freely available at rnaseq-mats.sourceforge.net/. As the popularity of RNA-Seq continues to grow, we expect rMATS will be useful for studies of alternative splicing in diverse RNA-Seq projects.

Effects of low-intensity pulsed ultrasound on integrin-FAK-PI3K/Akt mechanochemical transduction in rabbit osteoarthritis chondrocytes.

The effect of low-intensity pulsed ultrasound (LIPUS) on extracellular matrix (ECM) production via modulation of the integrin/focal adhesion kinase (FAK)/phosphatidylinositol 3-kinase (PI3K)/Akt pathway has been investigated in previous studies in normal chondrocytes, but not in osteoarthritis (OA). Therefore, we investigated the LIPUS-induced integrin ß1/FAK/PI3K/Akt mechanochemical transduction pathway in a single study in rabbit OA chondrocytes. Normal and OA chondrocytes were exposed to LIPUS, and mRNA and protein expression of cartilage, metalloproteinases and integrin-FAK-PI3K/Akt signal pathway-related genes was determined by quantitative reverse transcription polymerase chain reaction and Western blotting, respectively. Compared with levels in normal chondrocytes, expression levels of ECM-related genes were significantly lower in OA chondrocytes and those of metalloproteinase-related genes were significantly higher. In addition, integrin ß1 gene expression and the phosphorylation of FAK, PI3K and Akt were significantly higher in OA chondrocytes. The expression of all tested genes was significantly increased except for that of metalloproteinase, which was significantly decreased in the LIPUS-treated OA group compared to the untreated OA group. LIPUS may affect the integrin-FAK-PI3K/Akt mechanochemical transduction pathway and alter ECM production by OA chondrocytes. Our findings will aid the future development of a treatment or even cure for OA.

Similarity of markers identified from cancer gene expression studies: observations from GEO.

Gene expression profiling has been extensively conducted in cancer research. The analysis of multiple independent cancer gene expression datasets may provide additional information and complement single-dataset analysis. In this study, we conduct multi-dataset analysis and are interested in evaluating the similarity of cancer-associated genes identified from different datasets. The first objective of this study is to briefly review some statistical methods that can be used for such evaluation. Both marginal analysis and joint analysis methods are reviewed. The second objective is to apply those methods to 26 Gene Expression Omnibus (GEO) datasets on five types of cancers. Our analysis suggests that for the same cancer, the marker identification results may vary significantly across datasets, and different datasets share few common genes. In addition, datasets on different cancers share few common genes. The shared genetic basis of datasets on the same or different cancers, which has been suggested in the literature, is not observed in the analysis of GEO data.

The RNA binding protein RBM38 (RNPC1) regulates splicing during late erythroid differentiation.

Alternative pre-mRNA splicing is a prevalent mechanism in mammals that promotes proteomic diversity, including expression of cell-type specific protein isoforms. We characterized a role for RBM38 (RNPC1) in regulation of alternative splicing during late erythroid differentiation. We used an Affymetrix human exon junction (HJAY) splicing microarray to identify a panel of RBM38-regulated alternatively spliced transcripts. Using microarray databases, we noted high RBM38 expression levels in CD71(+) erythroid cells and thus chose to examine RBM38 expression during erythroid differentiation of human hematopoietic stem cells, detecting enhanced RBM38 expression during late erythroid differentiation. In differentiated erythroid cells, we validated a subset of RBM38-regulated splicing events and determined that RBM38 regulates activation of Protein 4.1R (EPB41) exon 16 during late erythroid differentiation. Using Epb41 minigenes, Rbm38 was found to be a robust activator of exon 16 splicing. To further address the mechanism of RBM38-regulated alternative splicing, a novel mammalian protein expression system, followed by SELEX-Seq, was used to identify a GU-rich RBM38 binding motif. Lastly, using a tethering assay, we determined that RBM38 can directly activate splicing when recruited to a downstream intron. Together, our data support the role of RBM38 in regulating alternative splicing during erythroid differentiation.

Identifying differential alternative splicing events from RNA sequencing data using RNASeq-MATS.

RNA sequencing (RNA-Seq) has emerged as a powerful and increasingly cost-effective technology for analysis of transcriptomes. RNA-Seq has several significant advantages over gene expression microarrays, including its high sensitivity and accuracy, broad dynamic range, nucleotide-level resolution, ability to detect novel mRNA transcripts, and ability to analyze pre-mRNA alternative splicing. A major application of RNA-Seq is to detect differential alternative splicing, i.e., differences in exon splicing patterns among different biological conditions. We recently developed a statistical method multivariate analysis of transcript splicing (MATS) for detecting differential alternative splicing events from RNA-Seq data. Here, we describe a computational pipeline RNASeq-MATS based on the MATS algorithm. This pipeline automatically detects and analyzes differential alternative splicing events corresponding to all major types of alternative splicing patterns from RNA-Seq data.

AAPL: Assessing Association between P-value Lists.

Joint analyses of high-throughput datasets generate the need to assess the association between two long lists of p-values. In such p-value lists, the vast majority of the features are insignificant. Ideally contributions of features that are null in both tests should be minimized. However, by random chance their p-values are uniformly distributed between zero and one, and weak correlations of the p-values may exist due to inherent biases in the high-throughput technology used to generate the multiple datasets. Rank-based agreement test may capture such unwanted effects. Testing contingency tables generated using hard cutoffs may be sensitive to arbitrary threshold choice. We develop a novel method based on feature-level concordance using local false discovery rate. The association score enjoys straight-forward interpretation. The method shows higher statistical power to detect association between p-value lists in simulation. We demonstrate its utility using real data analysis. The R implementation of the method is available at http://userwww.service.emory.edu/~tyu8/AAPL/.