GWAS on your notebook: Fast semi-parallel linear and logistic regression for genome-wide association studies

Background: Genome-wide association studies have become very popular in identifying genetic contributions to phenotypes. Millions of SNPs are being tested for their association with diseases and traits using linear or logistic regression models. This conceptually simple strategy encounters the following computational issues: a large number of tests and very large genotype files (many Gigabytes) which cannot be directly loaded into the software memory. One of the solutions applied on a grand scale is cluster computing involving large-scale resources. We show how to speed up the computations using matrix operations in pure R code.Results: We improve speed: computation time from 6 hours is reduced to 10-15 minutes. Our approach can handle essentially an unlimited amount of covariates efficiently, using projections. Data files in GWAS are vast and reading them into computer memory becomes an important issue. However, much improvement can be made if the data is structured beforehand in a way allowing for easy access to blocks of SNPs. We propose several solutions based on the R packages ff and ncdf.We adapted the semi-parallel computations for logistic regression. We show that in a typical GWAS setting, where SNP effects are very small, we do not lose any precision and our computations are few hundreds times faster than standard procedures.Conclusions: We provide very fast algorithms for GWAS written in pure R code. We also show how to rearrange SNP data for fast access

Genome-wide Analysis of Large-scale Longitudinal Outcomes using Penalization - GALLOP algorithm

Genome-wide association studies (GWAS) with longitudinal phenotypes provide opportunities to identify genetic variations associated with changes in human traits over time. Mixed models are used to correct for the correlated nature of longitudinal data. GWA studies are notorious for their computational challenges, which are considerable when mixed models for thousands of individuals are fitted to millions of SNPs. We present a new algorithm that speeds up a genome-wide analysis of longitudinal data by several orders of magnitude. It solves the equivalent penalized least squares problem efficiently, computing variances in an initial step. Factorizations and transformations are used to avoid inversion of large matrices. Because the system of equations is bordered, we can re-use components, which can be precomputed for the mixed model without a SNP. Two SNP effects (main and its interaction with time) are obtained. Our method completes the analysis a thousand times faster than the R package lme4, providing an almost identical solution for the coefficients and p-values. We provide an R implementation of our algorithm

Phase 3 Randomized Trial of Prophylactic Cranial Irradiation With or Without Hippocampus Avoidance in SCLC (NCT01780675)

Introduction: To compare neurocognitive functioning in patients with SCLC who received prophylactic cranial irradiation (PCI) with or without hippocampus avoidance (HA). Methods: In a multicenter, randomized phase 3 trial (NCT01780675), patients with SCLC were randomized to standard PCI or HA-PCI of 25 Gy in 10 fractions. Neuropsychological tests were performed at baseline and 4, 8, 12, 18, and 24 months after PCI. The primary end point was total recall on the Hopkins Verbal Learning Test-Revised at 4 months; a decline of at least five points from baseline was considered a failure. Secondary end points included other cognitive outcomes, evaluation of the incidence, location of brain metastases, and overall survival. Results: From April 2013 to March 2018, a total of 168 patients were randomized. The median follow-up time was 26.6 months. In both treatment arms, 70% of the patients had limited disease and baseline characteristics were well balanced. Decline on the Hopkins Verbal Learning Test-Revised total recall score at 4 months was not significantly different between the arms: 29% of patients on PCI and 28% of patients on HA-PCI dropped greater than or equal to five points (p = 1.000). Performance on other cognitive tests measuring memory, executive function, attention, motor function, and processing speed did not change significantly different over time between the groups. The overall survival was not significantly different (p = 0.43). The cumulative incidence of brain metastases at 2 years was 20% (95% confidence interval: 12%-29%) for the PCI arm and 16% (95% confidence interval: 7%-24%) for the HA-PCI arm. Conclusions: This randomized phase 3 trial did not find a lower probability of cognitive decline in patients with SCLC receiving HA-PCI compared with conventional PCI. No increase in brain metastases at 2 years was observed in the HA-PCI arm. (C) 2021 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved

CRITICS-II: a multicentre randomised phase II trial of neo-adjuvant chemotherapy followed by surgery versus neo-adjuvant chemotherapy and subsequent chemoradiotherapy followed by surgery versus neo-adjuvant chemoradiotherapy followed by surgery in resectable gastric cancer

Background: Although radical surgery remains the cornerstone of cure in resectable gastric cancer, survival remains poor. Current evidence-based (neo)adjuvant strategies have shown to improve outcome, including perioperative chemotherapy, postoperative chemoradiotherapy and postoperative chemotherapy. However, these regimens suffer from poor patient compliance, particularly in the postoperative phase of treatment. The CRITICS-II trial aims to optimize preoperative treatment by comparing three treatment regimens: (1) chemotherapy, (2) chemotherapy followed by chemoradiotherapy and (3) chemoradiotherapy. Methods: In this multicentre phase II non-comparative study, patients with clinical stage IB-IIIC (TNM 8th edition) resectable gastric adenocarcinoma are randomised between: (1) 4 cycles of docetaxel+oxaliplatin+capecitabine (DOC), (2) 2 cycles of DOC followed by chemoradiotherapy (45Gy in combination with weekly paclitaxel and carboplatin) or (3) chemoradiotherapy. Primary endpoint is event-free survival, 1 year after randomisation (events are local and/or regional recurrence or progression, distant recurrence, or death from any cause). Secondary endpoints include: toxicity, surgical outcomes, percentage radical (R0) resections, pathological tumour response, disease recurrence, overall survival, and health related quality of life. Exploratory endpoints include translational studies on predictive and prognostic biomarkers. Discussion: The aim of this study is to select the most promising among three preoperative treatment arms in patients with resectable gastric adenocarcinoma. This treatment regimen will subsequently be compared with the standard therapy in a phase III trial

Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group

Funder: U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI)Funder: National Center for Research Resources under award number 1 C06 RR12463-01, VA Merit Review Award IBX004121A from the United States Department of Veterans Affairs Biomedical Laboratory Research and Development Service, the DOD Prostate Cancer Idea Development Award (W81XWH-15-1-0558), the DOD Lung Cancer Investigator-Initiated Translational Research Award (W81XWH-18-1-0440), the DOD Peer Reviewed Cancer Research Program (W81XWH-16-1-0329), the Ohio Third Frontier Technology Validation Fund, the Wallace H. Coulter Foundation Program in the Department of Biomedical Engineering and the Clinical and Translational Science Award Program (CTSA) at Case Western Reserve University.Funder: Susan G Komen Foundation (CCR CCR18547966) and a Young Investigator Grant from the Breast Cancer Alliance.Funder: The Canadian Cancer SocietyFunder: Breast Cancer Research Foundation (BCRF), Grant No. 17-194Abstract: Assessment of tumor-infiltrating lymphocytes (TILs) is increasingly recognized as an integral part of the prognostic workflow in triple-negative (TNBC) and HER2-positive breast cancer, as well as many other solid tumors. This recognition has come about thanks to standardized visual reporting guidelines, which helped to reduce inter-reader variability. Now, there are ripe opportunities to employ computational methods that extract spatio-morphologic predictive features, enabling computer-aided diagnostics. We detail the benefits of computational TILs assessment, the readiness of TILs scoring for computational assessment, and outline considerations for overcoming key barriers to clinical translation in this arena. Specifically, we discuss: 1. ensuring computational workflows closely capture visual guidelines and standards; 2. challenges and thoughts standards for assessment of algorithms including training, preanalytical, analytical, and clinical validation; 3. perspectives on how to realize the potential of machine learning models and to overcome the perceptual and practical limits of visual scoring

Application of a risk-management framework for integration of stromal tumor-infiltrating lymphocytes in clinical trials

Funder: Breast Cancer Research Foundation (BCRF); doi: https://doi.org/10.13039/100001006Abstract: Stromal tumor-infiltrating lymphocytes (sTILs) are a potential predictive biomarker for immunotherapy response in metastatic triple-negative breast cancer (TNBC). To incorporate sTILs into clinical trials and diagnostics, reliable assessment is essential. In this review, we propose a new concept, namely the implementation of a risk-management framework that enables the use of sTILs as a stratification factor in clinical trials. We present the design of a biomarker risk-mitigation workflow that can be applied to any biomarker incorporation in clinical trials. We demonstrate the implementation of this concept using sTILs as an integral biomarker in a single-center phase II immunotherapy trial for metastatic TNBC (TONIC trial, NCT02499367), using this workflow to mitigate risks of suboptimal inclusion of sTILs in this specific trial. In this review, we demonstrate that a web-based scoring platform can mitigate potential risk factors when including sTILs in clinical trials, and we argue that this framework can be applied for any future biomarker-driven clinical trial setting

Pitfalls in assessing stromal tumor infiltrating lymphocytes (sTILs) in breast cancer

Abstract: Stromal tumor-infiltrating lymphocytes (sTILs) are important prognostic and predictive biomarkers in triple-negative (TNBC) and HER2-positive breast cancer. Incorporating sTILs into clinical practice necessitates reproducible assessment. Previously developed standardized scoring guidelines have been widely embraced by the clinical and research communities. We evaluated sources of variability in sTIL assessment by pathologists in three previous sTIL ring studies. We identify common challenges and evaluate impact of discrepancies on outcome estimates in early TNBC using a newly-developed prognostic tool. Discordant sTIL assessment is driven by heterogeneity in lymphocyte distribution. Additional factors include: technical slide-related issues; scoring outside the tumor boundary; tumors with minimal assessable stroma; including lymphocytes associated with other structures; and including other inflammatory cells. Small variations in sTIL assessment modestly alter risk estimation in early TNBC but have the potential to affect treatment selection if cutpoints are employed. Scoring and averaging multiple areas, as well as use of reference images, improve consistency of sTIL evaluation. Moreover, to assist in avoiding the pitfalls identified in this analysis, we developed an educational resource available at www.tilsinbreastcancer.org/pitfalls

Kidney and urinary tract imaging: Triple-bolus multidetector CT urography as a one-stop shop - Protocol design, opacification, and image quality analysis

Purpose: To retrospectively evaluate renal, vascular, and urinary tract visualization following a single postcontrast multidetector computed tomographic (CT) urographic sequence performed with three limited-volume bolus injections. Materials and Methods: The institutional review board approved this retrospective study. Patient informed consent was waived. Triple-bolus multidetector CT urography was performed in 110 patients. Triple-bolus protocol consisted of 30 mL of contrast material at 2 mL/sec at 0 seconds, 50 mL at 1.5 mL/sec at 435 seconds, 65 mL at 3 mL/sec at 488 seconds, with total abdominal scanning time of 510 seconds. Two independent readers rated urinary tract opacification and qualitatively and quantitatively assessed renal parenchymal and vascular contrast enhancement. Upper urinary tract (UUT) distention was measured by one reader. Interobserver agreement was assessed by using κ statistics. Results: Complete opacification of the intrarenal collecting system and proximal ureter was achieved in 91% (184 of 202) (κ = 0.62) and 82% (166 of 202) (κ = 0.94) of segments, respectively. The distal ureter was not opacified in 21% of the cases (κ = 0.92), and the bladder was not opacified in 20% of the cases. Mean distention was higher for proximal (3.9 mm) than for distal (3.7 mm) segments. Image quality of renal parenchymal enhancement was excellent in 76% of cases. Arteries showed better contrast enhancement than veins (excellent rating in 89% vs 59% of the cases). Radiation dose calculated for triple-bolus acquisition was 9.8 mSv. Conclusion: Triple-bolus multidetector CT urography is a dose-efficient protocol acquiring corticomedullary-nephrographic-excretory and vascular enhancement phases in a single acquisition and provides sufficient opacification and distention of the UUT. Simultaneously, adequate image quality of renal parenchyma and vascular anatomy is achieved