Anti-TIGIT antibody improves PD-L1 blockade through myeloid and Treg cells.

Tiragolumab, an anti-TIGIT antibody with an active IgG1κ Fc, demonstrated improved outcomes in the phase 2 CITYSCAPE trial (ClinicalTrials.gov: NCT03563716 ) when combined with atezolizumab (anti-PD-L1) versus atezolizumab alone1. However, there remains little consensus on the mechanism(s) of response with this combination2. Here we find that a high baseline of intratumoural macrophages and regulatory T cells is associated with better outcomes in patients treated with atezolizumab plus tiragolumab but not with atezolizumab alone. Serum sample analysis revealed that macrophage activation is associated with a clinical benefit in patients who received the combination treatment. In mouse tumour models, tiragolumab surrogate antibodies inflamed tumour-associated macrophages, monocytes and dendritic cells through Fcγ receptors (FcγR), in turn driving anti-tumour CD8+ T cells from an exhausted effector-like state to a more memory-like state. These results reveal a mechanism of action through which TIGIT checkpoint inhibitors can remodel immunosuppressive tumour microenvironments, and suggest that FcγR engagement is an important consideration in anti-TIGIT antibody development.

Single-Agent Divarasib (GDC-6036) in Solid Tumors with a KRAS G12C Mutation.

BACKGROUND: Divarasib (GDC-6036) is a covalent KRAS G12C inhibitor that was designed to have high potency and selectivity. METHODS: In a phase 1 study, we evaluated divarasib administered orally once daily (at doses ranging from 50 to 400 mg) in patients who had advanced or metastatic solid tumors that harbor a KRAS G12C mutation. The primary objective was an assessment of safety; pharmacokinetics, investigator-evaluated antitumor activity, and biomarkers of response and resistance were also assessed. RESULTS: A total of 137 patients (60 with non-small-cell lung cancer [NSCLC], 55 with colorectal cancer, and 22 with other solid tumors) received divarasib. No dose-limiting toxic effects or treatment-related deaths were reported. Treatment-related adverse events occurred in 127 patients (93%); grade 3 events occurred in 15 patients (11%) and a grade 4 event in 1 patient (1%). Treatment-related adverse events resulted in a dose reduction in 19 patients (14%) and discontinuation of treatment in 4 patients (3%). Among patients with NSCLC, a confirmed response was observed in 53.4% of patients (95% confidence interval [CI], 39.9 to 66.7), and the median progression-free survival was 13.1 months (95% CI, 8.8 to could not be estimated). Among patients with colorectal cancer, a confirmed response was observed in 29.1% of patients (95% CI, 17.6 to 42.9), and the median progression-free survival was 5.6 months (95% CI, 4.1 to 8.2). Responses were also observed in patients with other solid tumors. Serial assessment of circulating tumor DNA showed declines in KRAS G12C variant allele frequency associated with response and identified genomic alterations that may confer resistance to divarasib. CONCLUSIONS: Treatment with divarasib resulted in durable clinical responses across KRAS G12C-positive tumors, with mostly low-grade adverse events. (Funded by Genentech; ClinicalTrials.gov number, NCT04449874.).

Utility of a Molecular Classifier as a Complement to High-Resolution Computed Tomography to Identify Usual Interstitial Pneumonia.

Rationale: Usual interstitial pneumonia (UIP) is the defining morphology of idiopathic pulmonary fibrosis (IPF). Guidelines for IPF diagnosis conditionally recommend surgical lung biopsy for histopathology diagnosis of UIP when radiology and clinical context are not definitive. A "molecular diagnosis of UIP" in transbronchial lung biopsy, the Envisia Genomic Classifier, accurately predicted histopathologic UIP.Objectives: We evaluated the combined accuracy of the Envisia Genomic Classifier and local radiology in the detection of UIP pattern.Methods: Ninety-six patients who had diagnostic lung pathology as well as a transbronchial lung biopsy for molecular testing with Envisia Genomic Classifier were included in this analysis. The classifier results were scored against reference pathology. UIP identified on high-resolution computed tomography (HRCT) as documented by features in local radiologists' reports was compared with histopathology.Measurements and Main Results: In 96 patients, the Envisia Classifier achieved a specificity of 92.1% (confidence interval [CI],78.6-98.3%) and a sensitivity of 60.3% (CI, 46.6-73.0%) for histology-proven UIP pattern. Local radiologists identified UIP in 18 of 53 patients with UIP histopathology, with a sensitivity of 34.0% (CI, 21.5-48.3%) and a specificity of 96.9% (CI, 83.8-100%). In conjunction with HRCT patterns of UIP, the Envisia Classifier results identified 24 additional patients with UIP (sensitivity 79.2%; specificity 90.6%).Conclusions: In 96 patients with suspected interstitial lung disease, the Envisia Genomic Classifier identified UIP regardless of HRCT pattern. These results suggest that recognition of a UIP pattern by the Envisia Genomic Classifier combined with HRCT and clinical factors in a multidisciplinary discussion may assist clinicians in making an interstitial lung disease (especially IPF) diagnosis without the need for a surgical lung biopsy.

Variation and genetic control of protein abundance in humans.

Gene expression differs among individuals and populations and is thought to be a major determinant of phenotypic variation. Although variation and genetic loci responsible for RNA expression levels have been analysed extensively in human populations, our knowledge is limited regarding the differences in human protein abundance and the genetic basis for this difference. Variation in messenger RNA expression is not a perfect surrogate for protein expression because the latter is influenced by an array of post-transcriptional regulatory mechanisms, and, empirically, the correlation between protein and mRNA levels is generally modest. Here we used isobaric tag-based quantitative mass spectrometry to determine relative protein levels of 5,953 genes in lymphoblastoid cell lines from 95 diverse individuals genotyped in the HapMap Project. We found that protein levels are heritable molecular phenotypes that exhibit considerable variation between individuals, populations and sexes. Levels of specific sets of proteins involved in the same biological process covary among individuals, indicating that these processes are tightly regulated at the protein level. We identified cis-pQTLs (protein quantitative trait loci), including variants not detected by previous transcriptome studies. This study demonstrates the feasibility of high-throughput human proteome quantification that, when integrated with DNA variation and transcriptome information, adds a new dimension to the characterization of gene expression regulation.

Genome-wide survey in African Americans demonstrates potential epistasis of fitness in the human genome.

The role played by epistasis between alleles at unlinked loci in shaping population fitness has been debated for many years and the existing evidence has been mainly accumulated from model organisms. In model organisms, fitness epistasis can be systematically inferred by detecting nonindependence of genotypic values between loci in a population and confirmed through examining the number of offspring produced in two-locus genotype groups. No systematic study has been conducted to detect epistasis of fitness in humans owing to experimental constraints. In this study, we developed a novel method to detect fitness epistasis by testing the correlation between local ancestries on different chromosomes in an admixed population. We inferred local ancestry across the genome in 16,252 unrelated African Americans and systematically examined the pairwise correlations between the genomic regions on different chromosomes. Our analysis revealed a pair of genomic regions on chromosomes 4 and 6 that show significant local ancestry correlation (P-value = 4.01 × 10-8 ) that can be potentially attributed to fitness epistasis. However, we also observed substantial local ancestry correlation that cannot be explained by systemic ancestry inference bias. To our knowledge, this study is the first to systematically examine evidence of fitness epistasis across the human genome.

Identification of usual interstitial pneumonia pattern using RNA-Seq and machine learning: challenges and solutions.

BACKGROUND: We developed a classifier using RNA sequencing data that identifies the usual interstitial pneumonia (UIP) pattern for the diagnosis of idiopathic pulmonary fibrosis. We addressed significant challenges, including limited sample size, biological and technical sample heterogeneity, and reagent and assay batch effects. RESULTS: We identified inter- and intra-patient heterogeneity, particularly within the non-UIP group. The models classified UIP on transbronchial biopsy samples with a receiver-operating characteristic area under the curve of ~ 0.9 in cross-validation. Using in silico mixed samples in training, we prospectively defined a decision boundary to optimize specificity at ≥85%. The penalized logistic regression model showed greater reproducibility across technical replicates and was chosen as the final model. The final model showed sensitivity of 70% and specificity of 88% in the test set. CONCLUSIONS: We demonstrated that the suggested methodologies appropriately addressed challenges of the sample size, disease heterogeneity and technical batch effects and developed a highly accurate and robust classifier leveraging RNA sequencing for the classification of UIP.

Analytical performance of Envisia: a genomic classifier for usual interstitial pneumonia.

BACKGROUND: Clinical guidelines specify that diagnosis of interstitial pulmonary fibrosis (IPF) requires identification of usual interstitial pneumonia (UIP) pattern. While UIP can be identified by high resolution CT of the chest, the results are often inconclusive, making surgical lung biopsy necessary to reach a definitive diagnosis (Raghu et al., Am J Respir Crit Care Med 183(6):788-824, 2011). The Envisia genomic classifier differentiates UIP from non-UIP pathology in transbronchial biopsies (TBB), potentially allowing patients to avoid an invasive procedure (Brown et al., Am J Respir Crit Care Med 195:A6792, 2017). To ensure patient safety and efficacy, a laboratory developed test (LDT) must meet strict regulatory requirements for accuracy, reproducibility and robustness. The analytical characteristics of the Envisia test are assessed and reported here. METHODS: The Envisia test utilizes total RNA extracted from TBB samples to perform Next Generation RNA Sequencing. The gene count data from 190 genes are then input to the Envisia genomic classifier, a machine learning algorithm, to output either a UIP or non-UIP classification result. We characterized the stability of RNA in TBBs during collection and shipment, and evaluated input RNA mass and proportions on the limit of detection of UIP. We evaluated potentially interfering substances such as blood and genomic DNA. Intra-run, inter-run, and inter-laboratory reproducibility of test results were also characterized. RESULTS: RNA content within TBBs preserved in RNAprotect is stable for up to 14 days with no detectable change in RNA quality. The Envisia test is tolerant to variation in RNA input (5 to 30 ng), with no impact on classifier results. The Envisia test can tolerate dilution of non-UIP and UIP classification signals at the RNA level by up to 60% and 20%, respectively. Analytical specificity studies utilizing UIP and non-UIP samples mixed with genomic DNA (up to 30% relative input) demonstrated no impact to classifier results. The Envisia test tolerates up to 22% of blood contamination, well beyond the level observed in TBBs. The test is reproducible from RNA extraction through to Envisia test result (standard deviation of 0.20 for Envisia classification scores on > 7-unit scale). CONCLUSIONS: The Envisia test demonstrates the robust analytical performance required of an LDT. Envisia can be used to inform the diagnoses of patients with suspected IPF.

Analytical performance of a bronchial genomic classifier.

BACKGROUND: The current standard practice of lung lesion diagnosis often leads to inconclusive results, requiring additional diagnostic follow up procedures that are invasive and often unnecessary due to the high benign rate in such lesions (Chest 143:e78S-e92, 2013). The Percepta bronchial genomic classifier was developed and clinically validated to provide more accurate classification of lung nodules and lesions that are inconclusive by bronchoscopy, using bronchial brushing specimens (N Engl J Med 373:243-51, 2015, BMC Med Genomics 8:18, 2015). The analytical performance of the Percepta test is reported here. METHODS: Analytical performance studies were designed to characterize the stability of RNA in bronchial brushing specimens during collection and shipment; analytical sensitivity defined as input RNA mass; analytical specificity (i.e. potentially interfering substances) as tested on blood and genomic DNA; and assay performance studies including intra-run, inter-run, and inter-laboratory reproducibility. RESULTS: RNA content within bronchial brushing specimens preserved in RNAprotect is stable for up to 20 days at 4 °C with no changes in RNA yield or integrity. Analytical sensitivity studies demonstrated tolerance to variation in RNA input (157 ng to 243 ng). Analytical specificity studies utilizing cancer positive and cancer negative samples mixed with either blood (up to 10 % input mass) or genomic DNA (up to 10 % input mass) demonstrated no assay interference. The test is reproducible from RNA extraction through to Percepta test result, including variation across operators, runs, reagent lots, and laboratories (standard deviation of 0.26 for scores on > 6 unit scale). CONCLUSIONS: Analytical sensitivity, analytical specificity and robustness of the Percepta test were successfully verified, supporting its suitability for clinical use.

Impact of a bronchial genomic classifier on clinical decision making in patients undergoing diagnostic evaluation for lung cancer.

BACKGROUND: Bronchoscopy is frequently used for the evaluation of suspicious pulmonary lesions found on computed tomography, but its sensitivity for detecting lung cancer is limited. Recently, a bronchial genomic classifier was validated to improve the sensitivity of bronchoscopy for lung cancer detection, demonstrating a high sensitivity and negative predictive value among patients at intermediate risk (10-60 %) for lung cancer with an inconclusive bronchoscopy. Our objective for this study was to determine if a negative genomic classifier result that down-classifies a patient from intermediate risk to low risk (<10 %) for lung cancer would reduce the rate that physicians recommend more invasive testing among patients with an inconclusive bronchoscopy. METHODS: We conducted a randomized, prospective, decision impact survey study assessing pulmonologist recommendations in patients undergoing workup for lung cancer who had an inconclusive bronchoscopy. Cases with an intermediate pretest risk for lung cancer were selected from the AEGIS trials and presented in a randomized fashion to pulmonologists either with or without the patient's bronchial genomic classifier result to determine how the classifier results impacted physician decisions. RESULTS: Two hundred two physicians provided 1523 case evaluations on 36 patients. Invasive procedure recommendations were reduced from 57 % without the classifier result to 18 % with a negative (low risk) classifier result (p < 0.001). Invasive procedure recommendations increased from 50 to 65 % with a positive (intermediate risk) classifier result (p < 0.001). When stratifying by ultimate disease diagnosis, there was an overall reduction in invasive procedure recommendations in patients with benign disease when classifier results were reported (54 to 41 %, p < 0.001). For patients ultimately diagnosed with malignant disease, there was an overall increase in invasive procedure recommendations when the classifier results were reported (50 to 64 %, p = 0.003). CONCLUSIONS: Our findings suggest that a negative (low risk) bronchial genomic classifier result reduces invasive procedure recommendations following an inconclusive bronchoscopy and that the classifier overall reduces invasive procedure recommendations among patients ultimately diagnosed with benign disease. These results support the potential clinical utility of the classifier to improve management of patients undergoing bronchoscopy for suspect lung cancer by reducing additional invasive procedures in the setting of benign disease.

Genome-wide association of familial late-onset Alzheimer's disease replicates BIN1 and CLU and nominates CUGBP2 in interaction with APOE.

Late-onset Alzheimer's disease (LOAD) is the most common form of dementia in the elderly. The National Institute of Aging-Late Onset Alzheimer's Disease Family Study and the National Cell Repository for Alzheimer's Disease conducted a joint genome-wide association study (GWAS) of multiplex LOAD families (3,839 affected and unaffected individuals from 992 families plus additional unrelated neurologically evaluated normal subjects) using the 610 IlluminaQuad panel. This cohort represents the largest family-based GWAS of LOAD to date, with analyses limited here to the European-American subjects. SNPs near APOE gave highly significant results (e.g., rs2075650, p = 3.2×10(-81)), but no other genome-wide significant evidence for association was obtained in the full sample. Analyses that stratified on APOE genotypes identified SNPs on chromosome 10p14 in CUGBP2 with genome-wide significant evidence for association within APOE ε4 homozygotes (e.g., rs201119, p = 1.5×10(-8)). Association in this gene was replicated in an independent sample consisting of three cohorts. There was evidence of association for recently-reported LOAD risk loci, including BIN1 (rs7561528, p = 0.009 with, and p = 0.03 without, APOE adjustment) and CLU (rs11136000, p = 0.023 with, and p = 0.008 without, APOE adjustment), with weaker support for CR1. However, our results provide strong evidence that association with PICALM (rs3851179, p = 0.69 with, and p = 0.039 without, APOE adjustment) and EXOC3L2 is affected by correlation with APOE, and thus may represent spurious association. Our results indicate that genetic structure coupled with ascertainment bias resulting from the strong APOE association affect genome-wide results and interpretation of some recently reported associations. We show that a locus such as APOE, with large effects and strong association with disease, can lead to samples that require appropriate adjustment for this locus to avoid both false positive and false negative evidence of association. We suggest that similar adjustments may also be needed for many other large multi-site studies.

Sweet-bitter taste interactions in binary mixtures of sweeteners: Relationship between taste receptor activities and sensory perception.

This study investigated the effects of various binary sweetener mixtures on sweetness enhancement and their interactions with sweet or bitter taste receptors, focusing on sensory perception and receptor activity. Acesulfame K or saccharin was mixed with allulose, aspartame, erythritol, fructose, glucose, or sucrose to match a target sucrose sweetness. The effects of the mixtures on sweet and bitter taste receptors (in the human embryonic kidney -293 cells) and sensory taste intensities were evaluated. Sweetness enhancement at the sweet taste receptor level was observed in some cases, with several monosaccharides reducing the acesulfame K- or saccharin-induced bitter taste receptor activity. Combining acesulfame K or saccharin with any of the six sweeteners perceptually enhanced sweetness (60% âˆ¼ 100% in 50:50 ratio), correlating with a reduction in inherent bitterness (-35% âˆ¼ -63% in 50:50 ratio). This finding suggests that sweetness perception likely increased because the monosaccharides mitigate the activation of bitter receptors caused by high-potency sweeteners.

Umami taste receptor suppresses cancer cachexia by regulating skeletal muscle atrophy in vivo and in vitro.

BACKGROUND/OBJECTIVES: The umami taste receptor (TAS1R1/TAS1R3) is endogenously expressed in skeletal muscle and is involved in myogenesis; however, there is a lack of evidence about whether the expression of the umami taste receptor is involved in muscular diseases. This study aimed to elucidate the effects of the umami taste receptor and its mechanism on muscle wasting in cancer cachexia using in vivo and in vitro models. MATERIALS/METHODS: The Lewis lung carcinoma-induced cancer cachexia model was used in vivo and in vitro, and the expressions of umami taste receptor and muscle atrophy-related markers, muscle atrophy F-box protein, and muscle RING-finger protein-1 were analyzed. RESULTS: Results showed that TAS1R1 was significantly downregulated in vivo and in vitro under the muscle wasting condition. Moreover, overexpression of TAS1R1 in vitro in the human primary cell model protected the cells from muscle atrophy, and knockdown of TAS1R1 using siRNA exacerbated muscle atrophy. CONCLUSION: Taken together, the umami taste receptor exerts protective effects on muscle-wasting conditions by restoring dysregulated muscle atrophy in cancer cachexia. In conclusion, this result provided evidence that the umami taste receptor exerts a therapeutic anti-cancer cachexia effect by restoring muscle atrophy.

Circulating tumor DNA dynamics reveal KRAS G12C mutation heterogeneity and response to treatment with the KRAS G12C inhibitor divarasib in solid tumors.

PURPOSE: To inform prognosis, treatment response, disease biology, and KRAS G12C mutation heterogeneity, we conducted exploratory circulating tumor DNA (ctDNA) profiling on 134 patients with solid tumors harboring a KRAS G12C mutation treated with single-agent divarasib (GDC-6036) in a phase 1 study. EXPERIMENTAL DESIGN: Plasma samples were collected for serial ctDNA profiling at baseline (Cycle 1 Day 1 prior to treatment) and multiple on-treatment time points (Cycle 1 Day 15 and Cycle 3 Day 1). RESULTS: KRAS G12C ctDNA was detectable from plasma samples in 72.9% (43/59) and 92.6% (50/54) of patients with non-small cell lung cancer and colorectal cancer, respectively, the majority of whom were eligible for study participation based on a local test detecting the KRAS G12C mutation in tumor tissue. Baseline ctDNA tumor fraction was associated with tumor type, disease burden, and metastatic sites. A decline in ctDNA level was observed as early as Cycle 1 Day 15. Serial assessment showed a decline in ctDNA tumor fraction associated with response and progression-free survival. Except for a few cases of KRAS G12C sub-clonality, on-treatment changes in KRAS G12C variant allele frequency mirrored changes in the overall ctDNA tumor fraction. CONCLUSION: Across tumor types, the KRAS G12C mutation likely represents a truncal mutation in the majority of patients. Rapid and deep decline in ctDNA tumor fraction was observed in patients responding to divarasib treatment. Early on-treatment dynamics of ctDNA were associated with patient outcomes and tumor response to divarasib treatment.

Divarasib plus cetuximab in KRAS G12C-positive colorectal cancer: a phase 1b trial.

KRAS G12C mutation is prevalent in ~4% of colorectal cancer (CRC) and is associated with poor prognosis. Divarasib, a KRAS G12C inhibitor, has shown modest activity as a single agent in KRAS G12C-positive CRC at 400 mg. Epidermal growth factor receptor has been recognized as a major upstream activator of RAS-MAPK signaling, a proposed key mechanism of resistance to KRAS G12C inhibition in CRC. Here, we report on divarasib plus cetuximab (epidermal growth factor receptor inhibitor) in patients with KRAS G12C-positive CRC (n = 29) from arm C of an ongoing phase 1b trial. The primary objective was to evaluate safety. Secondary objectives included preliminary antitumor activity. The safety profile of this combination was consistent with those of single-agent divarasib and cetuximab. Treatment-related adverse events led to divarasib dose reductions in four patients (13.8%); there were no treatment withdrawals. The objective response rate was 62.5% (95% confidence interval: 40.6%, 81.2%) in KRAS G12C inhibitor-naive patients (n = 24). The median duration of response was 6.9 months. The median progression-free survival was 8.1 months (95% confidence interval: 5.5, 12.3). As an exploratory objective, we observed a decline in KRAS G12C variant allele frequency associated with response and identified acquired genomic alterations at disease progression that may be associated with resistance. The manageable safety profile and encouraging antitumor activity of divarasib plus cetuximab support the further investigation of this combination in KRAS G12C-positive CRC.ClinicalTrials.gov identifier: NCT04449874.

Transcriptomic profiles and 5-year results from the randomized CLL14 study of venetoclax plus obinutuzumab versus chlorambucil plus obinutuzumab in chronic lymphocytic leukemia.

Data on long-term outcomes and biological drivers associated with depth of remission after BCL2 inhibition by venetoclax in the treatment of chronic lymphocytic leukemia (CLL) are limited. In this open-label parallel-group phase-3 study, 432 patients with previously untreated CLL were randomized (1:1) to receive either 1-year venetoclax-obinutuzumab (Ven-Obi, 216 patients) or chlorambucil-Obi (Clb-Obi, 216 patients) therapy (NCT02242942). The primary endpoint was investigator-assessed progression-free survival (PFS); secondary endpoints included minimal residual disease (MRD) and overall survival. RNA sequencing of CD19-enriched blood was conducted for exploratory post-hoc analyses. After a median follow-up of 65.4 months, PFS is significantly superior for Ven-Obi compared to Clb-Obi (Hazard ratio [HR] 0.35 [95% CI 0.26-0.46], p < 0.0001). At 5 years after randomization, the estimated PFS rate is 62.6% after Ven-Obi and 27.0% after Clb-Obi. In both arms, MRD status at the end of therapy is associated with longer PFS. MRD + ( ≥ 10-4) status is associated with increased expression of multi-drug resistance gene ABCB1 (MDR1), whereas MRD6 (< 10-6) is associated with BCL2L11 (BIM) expression. Inflammatory response pathways are enriched in MRD+ patient solely in the Ven-Obi arm. These data indicate sustained long-term efficacy of fixed-duration Ven-Obi in patients with previously untreated CLL. The distinct transcriptomic profile of MRD+ status suggests possible biological vulnerabilities.

TRAIL Score: A Simple Model to Predict Immunochemotherapy Tolerability in Patients With Diffuse Large B-Cell Lymphoma.

PURPOSE: Rituximab with cyclophosphamide, doxorubicin, vincristine, and prednisolone (R-CHOP) represents the standard of care for first-line treatment of diffuse large B-cell lymphoma (DLBCL). However, many patients are unable to tolerate R-CHOP and have inferior outcomes. This study aimed to develop a practical tool to help physicians identify patients with newly diagnosed DLBCL unlikely to tolerate a full course of R-CHOP. METHODS: We developed a predictive model (Tolerability of R-CHOP in Aggressive Lymphoma [TRAIL]) on the basis of a training data set from the phase III GOYA trial (obinutuzumab with CHOP v R-CHOP in 1L DLBCL) using a composite binary end point, identifying patients who prematurely stopped or required reductions of R-CHOP. Candidate predictive variables were selected on the basis of known baseline characteristics that contribute to patient frailty, comorbidity, and/or chemotherapy toxicity. TRAIL was developed using an iterative trial-and-error modeling process to fit a logistic regression model. The final model was evaluated for robustness using a GOYA holdout data set and the phase III MAIN (R-CHOP with or without bevacizumab in 1L DLBCL) R-CHOP-21 data set as external validation. RESULTS: TRAIL includes four simple predictors available in the routine clinical setting: Charlson Comorbidity Index, presence of cardiovascular disease or diabetes, serum albumin, and creatinine clearance. Model generalization performance estimated by the area under the curve was around or above 0.70 across GOYA training, GOYA holdout, and MAIN data sets. Classifying patients into low-, intermediate- and high-risk categories, the proportion of patients experiencing a tolerability event was 3.3%, 12.4%, and 32.9%, respectively, in GOYA holdout, and 9.7%, 9.7%, and 34.2%, respectively, in MAIN. CONCLUSION: TRAIL may be useful as a clinical decision support tool for treatment decisions in patients with DLBCL who may not tolerate standard chemoimmunotherapies.

Identification of novel susceptibility loci for Guam neurodegenerative disease: challenges of genome scans in genetic isolates.

Amyotrophic lateral sclerosis/parkinsonism-dementia complex (ALS/PDC) is a fatal neurodegenerative disease found in the Chamorro people of Guam and other Pacific Island populations. The etiology is unknown, although both genetic and environmental factors appear important. To identify loci for ALS/PDC, we conducted both genome-wide linkage and association analyses, using approximately 400 microsatellite markers, in the largest sample assembled to date, comprising a nearly complete sample of all living and previously sampled deceased cases. A single, large, complex pedigree was ascertained from a village on Guam, with smaller families and a case-control sample ascertained from the rest of Guam by population-based neurological screening and archival review. We found significant evidence for two regions with novel ALS/PDC loci on chromosome 12 and supportive evidence for the involvement of the MAPT region on chromosome 17. D12S1617 on 12p gave the strongest evidence of linkage (maximum LOD score, Z(max) = 4.03) in our initial scan, with additional support in the complete case-control sample in the form of evidence of allelic association at this marker and another nearby marker. D12S79 on 12q also provided significant evidence of linkage (Z(max) = 3.14) with support from flanking markers. Our results suggest that ALS/PDC may be influenced by as many as three loci, while illustrating challenges that are intrinsic in genetic analyses of isolated populations, as well as analytical strategies that are useful in this context. Elucidation of the genetic basis of ALS/PDC should improve our understanding of related neurodegenerative disorders including Alzheimer disease, Parkinson disease, frontotemporal dementia and ALS.