Concordance between single-nucleotide polymorphism-based genomic instability assays and a next-generation sequencing-based homologous recombination deficiency test.

BACKGROUND: We evaluated the performance of single-nucleotide polymorphism (SNP) genotyping arrays OncoScan (Thermo Fisher Scientific, San Diego, CA) and Infinium CytoSNP-850K (CytoSNP; Illumina, Waltham, MA) for assessing homologous recombination deficiency (HRD) genomic instability. METHODS: DNA (pretreatment samples) across 20 tumor types was evaluated with OncoScan, CytoSNP, and the clinically validated HRD test. Copy number variation (CNV) and loss of heterozygosity (LOH) analyses were performed with ASCATv2.5.1. Aggregate HRD genomic metrics included LOH, telomeric-allelic imbalance number (TAI), and large-scale state transition (LST). Associations between BRCA mutation (BRCAm) status and the clinically validated HRD test metric (dichotomized at a clinical cut-off) were evaluated using area under the receiver operating characteristic (AUROC); Spearman ρ was calculated for continuous metrics. CNV segmentation and HRD genomic metrics were calculated (n = 120, n = 106, and n = 126 for OncoScan, CytoSNP and clinically validated HRD test, respectively). RESULTS: When assessed by SNP arrays, the genomic metric demonstrated good association with BRCAm (AUROC of HRD: OncoScan, 0.87; CytoSNP, 0.75) and the clinically validated test (cut-off, 42; AUROC of HRD: OncoScan, 0.92; CytoSNP, 0.91). The genomic metrics demonstrated good correlation with the clinically validated aggregate HRD test metric (ρ: OncoScan, 0.82; CytoSNP, 0.81) and for each component (ρ: OncoScan, 0.68 [LOH], 0.76 [TAI], and 0.78 [LST]; CytoSNP, 0.59 [LOH], 0.77 [TAI], and 0.82 [LST]). HRD assessed by SNP genotyping arrays and the clinically validated test showed good correlation. CONCLUSION: OncoScan and CytoSNP may potentially identify most HRD-positive tumors with appropriate clinically relevant cut-offs.

Baseline and post-treatment biomarkers of resistance to anti-PD-1 therapy in acral and mucosal melanoma: an observational study.

BACKGROUND: Immunotherapies targeting programmed cell death-1 (PD-1) and its ligands have improved clinical outcomes for advanced melanoma. However, many tumors exhibit primary resistance or acquire secondary resistance after an initial positive response. The mechanisms of resistance are not well understood, and no validated predictive biomarkers are available. This exploratory study aimed to characterize baseline differences and molecular changes arising during treatment in acral and mucosal melanomas that exhibited primary or secondary resistance to anti-PD-1 monotherapy. METHODS: This was an observational retrospective study of 124 patients who had been treated for metastatic acral or mucosal melanoma with anti-PD-1 monotherapy. Tumor samples were collected at baseline (all patients) and post-treatment (resistant tumors only) and were assayed by immunohistochemistry, whole-exome sequencing, and RNA sequencing. RESULTS: At baseline, more non-progressor than resistant tumors exhibited expression of PD-L1, immune cell infiltration, and high tumor mutational burden (TMB); baseline PD-L1 expression was also more common in secondary-resistant than in primary-resistant tumors as well as in late versus early secondary-resistant tumors. Non-progressor tumors also had higher median baseline expression of an 18-gene T cell-inflamed gene expression profile (TcellinfGEP). Among resistant tumors, the proportion of PD-L1-positive melanomas and the expression of the TcellinfGEP mRNA signature increased during treatment, while the expression of mRNA signatures related to WNT and INFA1 signaling decreased. There was evidence for greater changes from baseline in secondary-resistant versus primary-resistant tumors for some markers, including expression of RAS-related and WNT-related mRNA signatures and density of CD11c+ and FOXP3+ T cells. Greater changes in CD11c+ cell density were observed in early compared with late secondary-resistant tumors. CONCLUSIONS: Our findings suggest that TcellinfGEP and PD-L1 expression, TMB, immune cell infiltration, and RAS and WNT signaling warrant further investigation as potential mechanisms and/or biomarkers of anti-PD-1 therapy resistance in acral and mucosal melanomas. Confirmation of these findings in larger populations is needed.

Immune Biomarkers in Metastatic Castration-resistant Prostate Cancer.

BACKGROUND: Metastatic castration-resistant prostate cancer (mCRPC) is a heterogeneous disease in which molecular stratification is needed to improve clinical outcomes. The identification of predictive biomarkers can have a major impact on the care of these patients, but the availability of metastatic tissue samples for research in this setting is limited. OBJECTIVE: To study the prevalence of immune biomarkers of potential clinical utility to immunotherapy in mCRPC and to determine their association with overall survival (OS). DESIGN, SETTING, AND PARTICIPANTS: From 100 patients, mCRPC biopsies were assayed by whole exome sequencing, targeted next-generation sequencing, RNA sequencing, tumor mutational burden, T-cell-inflamed gene expression profile (TcellinfGEP) score (Nanostring), and immunohistochemistry for programmed cell death 1 ligand 1 (PD-L1), ataxia-telangiectasia mutated (ATM), phosphatase and tensin homolog (PTEN), SRY homology box 2 (SOX2), and the presence of neuroendocrine features. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The phi coefficient determined correlations between biomarkers of interest. OS was assessed using Kaplan-Meier curves and adjusted hazard ratios (aHRs) from Cox regression. RESULTS AND LIMITATIONS: PD-L1 and SOX2 protein expression was detected by immunohistochemistry (combined positive score ≥1 and >5% cells, respectively) in 24 (33%) and 27 (27%) mCRPC biopsies, respectively; 23 (26%) mCRPC biopsies had high TcellinfGEP scores (>-0.318). PD-L1 protein expression and TcellinfGEP scores were positively correlated (phi 0.63 [0.45; 0.76]). PD-L1 protein expression (aHR: 1.90 [1.05; 3.45]), high TcellinfGEP score (aHR: 1.86 [1.04; 3.31]), and SOX2 expression (aHR: 2.09 [1.20; 3.64]) were associated with worse OS. CONCLUSIONS: PD-L1, TcellinfGEP score, and SOX2 are prognostic of outcome from the mCRPC setting. If validated, predictive biomarker studies incorporating survival endpoints need to take these findings into consideration. PATIENT SUMMARY: This study presents an analysis of immune biomarkers in biopsies from patients with metastatic prostate cancer. We describe tumor alterations that predict prognosis that can impact future studies.

Tumor mutational burden predicts the efficacy of pembrolizumab monotherapy: a pan-tumor retrospective analysis of participants with advanced solid tumors.

BACKGROUND: Several studies have evaluated the relationship between tumor mutational burden (TMB) and outcomes of immune checkpoint inhibitors. In the phase II KEYNOTE-158 study of pembrolizumab monotherapy for previously treated recurrent or metastatic cancer, high TMB as assessed by the FoundationOne CDx was associated with an improved objective response rate (ORR). METHODS: We retrospectively assessed the relationship between TMB and efficacy in participants with previously treated advanced solid tumors enrolled in 12 trials that evaluated pembrolizumab monotherapy, including 3 randomized trials that compared pembrolizumab with chemotherapy. TMB was assessed in formalin-fixed, paraffin-embedded pretreatment tumor samples by whole-exome sequencing. High TMB was defined as ≥175 mutations/exome. Microsatellite instability (MSI) phenotype was based on whole-exome sequencing results. Programmed death ligand 1 (PD-L1) expression was assessed by immunohistochemistry. The primary end point was ORR assessed per RECIST V.1.1 by independent central review. Other end points included progression-free survival (PFS) assessed per RECIST V.1.1 by independent central review and overall survival (OS). RESULTS: Of the 2234 participants in the analysis, 1772 received pembrolizumab monotherapy and 462 received chemotherapy. Among the pembrolizumab-treated participants, ORR was 31.4% (95% CI 27.1 to 36.0) in the 433 participants with TMB ≥175 mutations/exome and 9.5% (95% CI 8.0 to 11.2) in the 1339 participants with TMB <175 mutations/exome. The association of TMB with ORR was observed regardless of PD-L1 expression and not driven by specific tumor types or participants with very high TMB or high MSI. In the 3 randomized controlled trials, TMB was associated with ORR (p≤0.016), PFS (p≤0.005), and OS (p≤0.029) of pembrolizumab but not of chemotherapy (p≥0.340, p≥0.643, and p≥0.174, respectively), and pembrolizumab improved efficacy versus chemotherapy in participants with TMB ≥175 mutations/exome. CONCLUSIONS: TMB ≥175 mutations/exome is associated with clinically meaningful improvement in the efficacy of pembrolizumab monotherapy and improved outcomes for pembrolizumab versus chemotherapy across a wide range of previously treated advanced solid tumor types. These data suggest TMB has broad clinical utility irrespective of tumor type, PD-L1 expression, or MSI status and support its use as a predictive biomarker for pembrolizumab monotherapy in participants with previously treated advanced solid tumors.

Temperature change and electricity consumption of the group living: A case study of college students.

The relationship between energy use and climate change is the center of analysis about mitigation and adaptation. Yet current studies of the electricity-climate relationship focus on developed countries. Little was known about the energy-use behavior in group living. By using college students' monthly electricity-use data from September 2018 to August 2019 in Beijing, China, we build a weighted least square regression model and found a U-shaped relationship between temperature and electricity consumption. The results show that one additional day of temperature exceeding 30 °C would cause a 16.8% increase in monthly electricity consumption with reference to 18-22 °C while one additional day of temperature below -6 °C will increase it by 6%. The magnitudes of temperature effect on electricity are much greater than those in Shanghai and California. Further, we find that building structures, such as windows orientation and floor height, play important roles in the temperature-electricity relationship. Finally, we predict the changes in electricity use in a collection of Representative Concentration Pathways (RCP). It finds that the electricity use in summer in north China would increase by 72.8% in RCP 4.5, 79.5% in RCP6.0, and 91.2% in RCP8.5. Our study could be extended to the urban area in northern China, and indicates how the electricity use would respond to climate change in the Beijing-Tianjin-Hebei Urban Agglomeration, covering 8.1% of China's population and 8.4% of gross domestic product. Climate change impact on electricity use in residential and commercial sectors is significant and varying in regions. To achieve sustainable and environmental-friendly development, building structures could play a more effective role in energy-saving and adaptation to climate change.

Pan-tumor genomic biomarkers for PD-1 checkpoint blockade-based immunotherapy.

Programmed cell death protein-1 (PD-1) and programmed cell death ligand-1 (PD-L1) checkpoint blockade immunotherapy elicits durable antitumor effects in multiple cancers, yet not all patients respond. We report the evaluation of >300 patient samples across 22 tumor types from four KEYNOTE clinical trials. Tumor mutational burden (TMB) and a T cell-inflamed gene expression profile (GEP) exhibited joint predictive utility in identifying responders and nonresponders to the PD-1 antibody pembrolizumab. TMB and GEP were independently predictive of response and demonstrated low correlation, suggesting that they capture distinct features of neoantigenicity and T cell activation. Analysis of The Cancer Genome Atlas database showed TMB and GEP to have a low correlation, and analysis by joint stratification revealed biomarker-defined patterns of targetable-resistance biology. These biomarkers may have utility in clinical trial design by guiding rational selection of anti-PD-1 monotherapy and combination immunotherapy regimens.

Comprehensive molecular characterization of clinical responses to PD-1 inhibition in metastatic gastric cancer.

Clinical studies support the efficacy of programmed cell death 1 (PD-1) targeted therapy in a subset of patients with metastatic gastric cancer (mGC). With the goal of identifying determinants of response, we performed molecular characterization of tissues and circulating tumor DNA (ctDNA) from 61 patients with mGC who were treated with pembrolizumab as salvage treatment in a prospective phase 2 clinical trial. In patients with microsatellite instability-high and Epstein-Barr virus-positive tumors, which are mutually exclusive, dramatic responses to pembrolizumab were observed (overall response rate (ORR) 85.7% in microsatellite instability-high mGC and ORR 100% in Epstein-Barr virus-positive mGC). For the 55 patients for whom programmed death-ligand 1 (PD-L1) combined positive score positivity was available (combined positive score cut-off value ≥1%), ORR was significantly higher in PD-L1(+) gastric cancer when compared to PD-L1(-) tumors (50.0% versus 0.0%, P value <0.001). Changes in ctDNA levels at six weeks post-treatment predicted response and progression-free survival, and decreased ctDNA was associated with improved outcomes. Our findings provide insight into the molecular features associated with response to pembrolizumab in patients with mGC and provide biomarkers potentially relevant for the selection of patients who may derive greater benefit from PD-1 inhibition.

[The effects of different occluder selection on cardiac remodeling post transcatheter closure in patients with secundum atrial septal defect].

OBJECTIVE: To evaluate the effects on cardiac remodeling post transcatheter closure by Amplatzer septal occluder selected by oval circumference formula in patients with atrial septal defect (ASD). METHODS: A total of 146 patients with ASD (68 males,mean 33.5 years) treated by transcatheter closure with the Amplatzer occluder were enrolled in this study. The diameter of defects was corrected with the oval circumference formula (group A, 73 cases) or by echocardiography (group B, 73 cases). Cardiac remodeling was assessed by transthoracic echocardiography (TTE) before the procedure, 3 days, 3 months and 6 months after ASD closure. RESULTS: The mean ASD diameter was similar between the two groups [(20.16 +/- 4.98) mm vs. (21.36 +/- 5.69) mm, P > 0.05] and the mean diameter of the selected occluder of group A was significantly smaller than that in group B [(21.95 +/- 6.78) mm vs. (25.85 +/- 6.75) mm, P < 0.05]. Procedural success rate was identical between the two groups (97.3%) and the defects were completely occluded and there was no residual shunt during the 6 months follow up period, there were also no complications during and after the procedure. The lateral diameter of right atrial (RALD), the diastolic diameter of right ventricle (RVDD), RALD/LALD, RVDD/LVDD and pulmonary diameter (PD) were significantly decreased while the lateral diameter of left atrial (LALD) and left ventricle (LVDD) were significantly increased post ASD closure in both groups. At 6 months follow up, RALD decreased by (18.63 +/- 10.59)% in group A versus (10.14 +/- 6.59)% in group B, LALD increased by (13.42 +/- 8.38)% in group A versus (9.28 +/- 4.95)% in group B and RALD/LALD ratio decreased by (26.35 +/- 11.24)% in group A versus (13.98 +/- 8.96)% in groups B (all P < 0.05). CONCLUSION: ASD occluder selection based on the oval circumferen ce formula is superior to that made by echocardiography in terms of more favorable cardiac remodeling post ASD closure.

CPC: assess the protein-coding potential of transcripts using sequence features and support vector machine.

Recent transcriptome studies have revealed that a large number of transcripts in mammals and other organisms do not encode proteins but function as noncoding RNAs (ncRNAs) instead. As millions of transcripts are generated by large-scale cDNA and EST sequencing projects every year, there is a need for automatic methods to distinguish protein-coding RNAs from noncoding RNAs accurately and quickly. We developed a support vector machine-based classifier, named Coding Potential Calculator (CPC), to assess the protein-coding potential of a transcript based on six biologically meaningful sequence features. Tenfold cross-validation on the training dataset and further testing on several large datasets showed that CPC can discriminate coding from noncoding transcripts with high accuracy. Furthermore, CPC also runs an order-of-magnitude faster than a previous state-of-the-art tool and has higher accuracy. We developed a user-friendly web-based interface of CPC at http://cpc.cbi.pku.edu.cn. In addition to predicting the coding potential of the input transcripts, the CPC web server also graphically displays detailed sequence features and additional annotations of the transcript that may facilitate users' further investigation.

Finding new structural and sequence attributes to predict possible disease association of single amino acid polymorphism (SAP).

MOTIVATION: The rapid accumulation of single amino acid polymorphisms (SAPs), also known as non-synonymous single nucleotide polymorphisms (nsSNPs), brings the opportunities and needs to understand and predict their disease association. Currently published attributes are limited, the detailed mechanisms governing the disease association of a SAP remain unclear and thus, further investigation of new attributes and improvement of the prediction are desired. RESULTS: A SAP dataset was compiled from the Swiss-Prot variant pages. We extracted and demonstrated the effectiveness of several new biologically informative attributes including the structural neighbor profiles that describe the SAP's microenvironment, nearby functional sites that measure the structure-based and sequence-based distances between the SAP site and its nearby functional sites, aggregation properties that measure the likelihood of protein aggregation and disordered regions that consider whether the SAP is located in structurally disordered regions. The new attributes provided insights into the mechanisms of the disease association of SAPs. We built a support vector machines (SVMs) classifier employing a carefully selected set of new and previously published attributes. Through a strict protein-level 5-fold cross-validation, we attained an overall accuracy of 82.61%, and an MCC of 0.60. Moreover, a web server was developed to provide a user-friendly interface for biologists. AVAILABILITY: The web server is available at http://sapred.cbi.pku.edu.cn/