Pei Fang Su

Using multiplexed assays of oncogenic drivers in lung cancers to select targeted drugs.

IMPORTANCE Targeting oncogenic drivers (genomic alterations critical to cancer development and maintenance) has transformed the care of patients with lung adenocarcinomas. The Lung Cancer Mutation Consortium was formed to perform multiplexed assays testing adenocarcinomas of the lung for drivers in 10 genes to enable clinicians to select targeted treatments and enroll patients into clinical trials. OBJECTIVES To determine the frequency of oncogenic drivers in patients with lung adenocarcinomas and to use the data to select treatments targeting the identified driver(s) and measure survival. DESIGN, SETTING, AND PARTICIPANTS From 2009 through 2012, 14 sites in the United States enrolled patients with metastatic lung adenocarcinomas and a performance status of 0 through 2 and tested their tumors for 10 drivers. Information was collected on patients, therapies, and survival. INTERVENTIONS Tumors were tested for 10 oncogenic drivers, and results were used to select matched targeted therapies. MAIN OUTCOMES AND MEASURES Determination of the frequency of oncogenic drivers, the proportion of patients treated with genotype-directed therapy, and survival. RESULTS From 2009 through 2012, tumors from 1007 patients were tested for at least 1 gene and 733 for 10 genes (patients with full genotyping). An oncogenic driver was found in 466 of 733 patients (64%). Among these 733 tumors, 182 tumors (25%) had the KRAS driver; sensitizing EGFR, 122 (17%); ALK rearrangements, 57 (8%); other EGFR, 29 (4%); 2 or more genes, 24 (3%); ERBB2 (formerly HER2), 19 (3%); BRAF, 16 (2%); PIK3CA, 6 (<1%); MET amplification, 5 (<1%); NRAS, 5 (<1%); MEK1, 1 (<1%); AKT1, 0. Results were used to select a targeted therapy or trial in 275 of 1007 patients (28%). The median survival was 3.5 years (interquartile range [IQR], 1.96-7.70) for the 260 patients with an oncogenic driver and genotype-directed therapy compared with 2.4 years (IQR, 0.88-6.20) for the 318 patients with any oncogenic driver(s) who did not receive genotype-directed therapy (propensity score-adjusted hazard ratio, 0.69 [95% CI, 0.53-0.9], P = .006). CONCLUSIONS AND RELEVANCE Actionable drivers were detected in 64% of lung adenocarcinomas. Multiplexed testing aided physicians in selecting therapies. Although individuals with drivers receiving a matched targeted agent lived longer, randomized trials are required to determine if targeting therapy based on oncogenic drivers improves survival. TRIAL REGISTRATION clinicaltrials.gov Identifier: NCT01014286.

Mitoflash frequency in early adulthood predicts lifespan in Caenorhabditis elegans

It has been theorized for decades that mitochondria act as the biological clock of ageing, but the evidence is incomplete. Here we show a strong coupling between mitochondrial function and ageing by in vivo visualization of the mitochondrial flash (mitoflash), a frequency-coded optical readout reflecting free-radical production and energy metabolism at the single-mitochondrion level. Mitoflash activity in Caenorhabditis elegans pharyngeal muscles peaked on adult day 3 during active reproduction and on day 9 when animals started to die off. A plethora of genetic mutations and environmental factors inversely modified the lifespan and the day-3 mitoflash frequency. Even within an isogenic population, the day-3 mitoflash frequency was negatively correlated with the lifespan of individual animals. Furthermore, enhanced activity of the glyoxylate cycle contributed to the decreased day-3 mitoflash frequency and the longevity of daf-2 mutant animals. These results demonstrate that the day-3 mitoflash frequency is a powerful predictor of C. elegans lifespan across genetic, environmental and stochastic factors. They also support the notion that the rate of ageing, although adjustable in later life, has been set to a considerable degree before reproduction ceases.

The Prognostic Significance of RON and MET Receptor Coexpression in Patients with Colorectal Cancer

PurposeAlthough Recepteur d’Origine Nantais (RON), a member of the MET receptor tyrosine kinase family, is overexpressed and constitutively active in some primary tumors and tumor cell lines, its expression pattern and clinical significance in colorectal cancer are not well documented.MethodsBy using immunohistochemical staining, we examined RON and MET expression in 135 colorectal cancer specimens and investigated the association of the immunoreactivity of both receptors with colorectal cancer clinical parameters and prognosis.ResultsWe found moderate to strong expression in 99 cases (73 percent) for RON and 97 cases (72 percent) for MET. Univariate analysis showed that increased immunoreactivity of RON or MET was associated with shorter patient survival and that moderate to strong coexpression of both receptors was associated with a significantly worse prognosis. Multivariate Cox analysis showed that the risk of tumor recurrence for patients with high-RON/high-MET expression was approximately 11 times greater than for patients with low-RON/low-MET expression (P = 0.001). In addition, RON and MET expression levels were positively correlated (P ≤ 0.001; τ = 0.306).ConclusionsThe crosstalk between RON and MET in colorectal cancer seems important. Evaluating the expression patterns of RON and MET was predictive of clinical outcome for patients with colorectal cancer.

Early assessment of breast cancer response to neoadjuvant chemotherapy by semi-quantitative analysis of high-temporal resolution DCE-MRI: Preliminary results

PURPOSE To evaluate whether semi-quantitative analysis of high temporal resolution dynamic contrast-enhanced MRI (DCE-MRI) acquired early in treatment can predict the response of locally advanced breast cancer (LABC) to neoadjuvant chemotherapy (NAC). MATERIALS AND METHODS As part of an IRB-approved prospective study, 21 patients with LABC provided informed consent and underwent high temporal resolution 3T DCE-MRI before and after 1cycle of NAC. Using measurements performed by two radiologists, the following parameters were extracted for lesions at both examinations: lesion size (short and long axes, in both early and late phases of enhancement), radiologists subjective assessment of lesion enhancement, and percentages of voxels within the lesion demonstrating progressive, plateau, or washout kinetics. The latter data were calculated using two filters, one selecting for voxels enhancing ≥50% over baseline and one for voxels enhancing ≥100% over baseline. Pretreatment imaging parameters and parameter changes following cycle 1 of NAC were evaluated for their ability to discriminate patients with an eventual pathological complete response (pCR). RESULTS All 21 patients completed NAC followed by surgery, with 9 patients achieving a pCR. No pretreatment imaging parameters were predictive of pCR. However, change after cycle 1 of NAC in percentage of voxels demonstrating washout kinetics with a 100% enhancement filter discriminated patients with an eventual pCR with an area under the receiver operating characteristic curve (AUC) of 0.77. Changes in other parameters, including lesion size, did not predict pCR. CONCLUSION Semi-quantitative analysis of high temporal resolution DCE-MRI in patients with LABC can discriminate patients with an eventual pCR after one cycle of NAC.

Immunohistochemical analysis of epidermal growth factor receptor family members in stage I non-small cell lung cancer

BACKGROUND To elucidate the relationship between the expression of epidermal growth factor receptor family members (ErbB-1, neu/ErbB-2, ErbB-3, and ErbB-4) and tumor recurrence. METHODS We used immunohistochemistry to examine the expression of four epidermal growth factor receptor family members in 73 patients with stage I non-small cell lung cancer. RESULTS Using Cox univariate analysis, we determined that angiolymphatic tumor emboli and non-well-differentiated tumor cells were two significant conventional pathologic predictors of tumor recurrence, and that ErbB-1 and ErbB-3 were also significant predictors. Co-expression of ErbB-1+, -3+, or expression of three or more epidermal growth factor receptor family members had a significant effect on lung cancer recurrence. A stepwise multivariate Cox proportional hazards regression analysis provided a predictive model for tumor recurrence. CONCLUSIONS The present study shows that in patients with a non-well-differentiated tumor, overexpression of ErbB-3 is a useful marker for predicting tumor recurrence. The present study also confirmed that ErbB-1 expression increased in proportion to the loss of tumor differentiation. The correlation between ErbB-3 and distant metastasis was good.

Association Between Level of Hepatitis B Surface Antigen and Relapse After Entecavir Therapy for Chronic Hepatitis B Virus Infection.

BACKGROUND & AIMS We investigated the rate of relapse of hepatitis B virus (HBV) infection after entecavir therapy for chronic hepatitis B and the association between level of hepatitis B surface antigen (HBsAg) and relapse. METHODS In a retrospective study, we analyzed data from 252 patients with chronic HBV infection who were treated with entecavir and met the Asian Pacific Association for the Study of the Liver treatment stopping rules (mean time, 164 ± 45 weeks) from January 2007 through June 2011 in Taiwan. Eighty-three were hepatitis B e antigen (HBeAg)-positive, and 169 were HBeAg-negative. Patients had regular post-treatment follow-up examinations for at least 12 months. Virologic relapse was defined on the basis of serum HBV DNA >2000 IU/mL after entecavir therapy. Clinical relapse was defined as a level of alanine aminotransferase > 2-fold the upper limit of normal and HBV DNA > 2000 IU/mL. RESULTS Two years after therapy ended, 42% of HBeAg-positive patients had a virologic relapse, and 37.6% had a clinical relapse; 3 years after therapy ended, these rates were 64.3% and 51.6% for HBeAg-negative patients, respectively. On the basis of Cox regression analysis, factors independently associated with virologic and clinical relapse included old age, HBV genotype C, and higher baseline levels of HBsAg for HBeAg-positive patients and old age and higher end-of-treatment levels of HBsAg for HBeAg-negative patients. In HBeAg-positive patients, risk of HBV relapse increased with age ≥ 40 years and HBsAg level ≥ 1000 IU/mL at baseline (P < .001). In HBeAg-negative patients, the combination of age (< 55 years) and HBsAg level (< 150 IU/mL) at the end of treatment was associated with a lower rate of virologic relapse (4.5% of HBeAg-negative patients had viral relapse at year 3). The decrease in level of HBsAg from month 12 of treatment until the end of treatment was greater in patients who did lose HBsAg after entecavir therapy compared with those who did not. CONCLUSIONS The combination of age and level of HBsAg is associated with relapse of HBV infection after treatment with entecavir. HBsAg levels might be used to guide the timing of cessation of entecavir treatment in patients with chronic HBV infection.

Abdominal obesity is the most significant metabolic syndrome component predictive of cardiovascular events in chronic hemodialysis patients

BACKGROUND Five components of metabolic syndrome (MetS) have been identified as predictive of cardiovascular events (CVEs) in the general population: impaired fasting glucose, abdominal obesity, hypertriglyceridemia, hypertension and low high-density lipoprotein cholesterol. Whether MetS and its components are also predictive of CVEs in chronic hemodialysis (HD) patients remains unclear. We therefore investigated the role of MetS and its components in patients on chronic HD. METHODS MetS at baseline was diagnosed in 91 HD patients based on the American Heart Association/National Heart, Lung and Blood Institute (AHA/NHLBI) and the International Diabetes Federation (IDF) definitions. During a 3-year period, all hospitalizations, CVEs and deaths were recorded and analyzed using Kaplan-Meier survival analysis and Cox regression. RESULTS There were no differences in the number of CVEs, hospitalizations or deaths between patients with and without AHA/NHLBI-defined MetS; however, patients with IDF-defined MetS were found to be at a higher risk for CVEs (P = 0.006). Cox regression analysis showed that, of the MetS components, abdominal obesity was the single most significant predictor of CVEs (hazard ratio 6.25; 95% confidence interval: 1.65-23.6; P = 0.007). CONCLUSIONS IDF-defined MetS was more predictive of CVEs than AHA/NHLBI-defined MetS. Of the MetS components, abdominal obesity was the single most significant predictor of CVEs in chronic HD patients.

PPM1A is a RelA phosphatase with tumor suppressor-like activity

Nuclear factor-κB (NF-κB) signaling contributes to human disease processes, notably inflammatory diseases and cancer. NF-κB has a role in tumorigenesis and tumor growth, as well as promotion of metastases. Mechanisms responsible for abnormal NF-κB activation are not fully elucidated; however, RelA phosphorylation, particularly at serine residues S536 and S276, is critical for RelA function. Kinases that phosphorylate RelA promote oncogenic behaviors, suggesting that phosphatases targeting RelA could have tumor-inhibiting activities; however, few RelA phosphatases have been identified. Here, we identified tumor inhibitory and RelA phosphatase activities of the protein phosphatase 2C (PP2C) phosphatase family member, PPM1A. We show that PPM1A directly dephosphorylated RelA at residues S536 and S276 and selectively inhibited NF-κB transcriptional activity, resulting in decreased expression of monocyte chemotactic protein-1/chemokine (C–C motif) ligand 2 and interleukin-6, cytokines implicated in cancer metastasis. PPM1A depletion enhanced NF-κB-dependent cell invasion, whereas PPM1A expression inhibited invasion. Analyses of human expression data revealed that metastatic prostate cancer deposits had lower PPM1A expression compared with primary tumors without distant metastases. A hematogenous metastasis mouse model revealed that PPM1A expression inhibited bony metastases of prostate cancer cells after vascular injection. In summary, our findings suggest that PPM1A is a RelA phosphatase that regulates NF-κB activity and that PPM1A has tumor suppressor-like activity. Our analyses also suggest that PPM1A inhibits prostate cancer metastases and as neither gene deletions nor inactivating mutations of PPM1A have been described, increasing PPM1A activity in tumors represents a potential therapeutic strategy to inhibit NF-κB signaling or bony metastases in human cancer.

Sample size calculation based on exact test for assessing differential expression analysis in RNA-seq data

BackgroundSample size calculation is an important issue in the experimental design of biomedical research. For RNA-seq experiments, the sample size calculation method based on the Poisson model has been proposed; however, when there are biological replicates, RNA-seq data could exhibit variation significantly greater than the mean (i.e. over-dispersion). The Poisson model cannot appropriately model the over-dispersion, and in such cases, the negative binomial model has been used as a natural extension of the Poisson model. Because the field currently lacks a sample size calculation method based on the negative binomial model for assessing differential expression analysis of RNA-seq data, we propose a method to calculate the sample size.ResultsWe propose a sample size calculation method based on the exact test for assessing differential expression analysis of RNA-seq data.ConclusionsThe proposed sample size calculation method is straightforward and not computationally intensive. Simulation studies to evaluate the performance of the proposed sample size method are presented; the results indicate our method works well, with achievement of desired power.

Sample size calculation for differential expression analysis of RNA-seq data under Poisson distribution

Sample size determination is an important issue in the experimental design of biomedical research. Because of the complexity of RNA-seq experiments, however, the field currently lacks a sample size method widely applicable to differential expression studies utilising RNA-seq technology. In this report, we propose several methods for sample size calculation for single-gene differential expression analysis of RNA-seq data under Poisson distribution. These methods are then extended to multiple genes, with consideration for addressing the multiple testing problem by controlling false discovery rate. Moreover, most of the proposed methods allow for closed-form sample size formulas with specification of the desired minimum fold change and minimum average read count, and thus are not computationally intensive. Simulation studies to evaluate the performance of the proposed sample size formulas are presented; the results indicate that our methods work well, with achievement of desired power. Finally, our sample size calculation methods are applied to three real RNA-seq data sets.