Boyle TA , Quinn GP , Schabath MB , Muñoz-Antonia T , Saller JJ , Duarte LF , Hair LS , Teer JK , Chiang DY , Leary R , Wong CC , Savchenko A , Singh AP , Charette L , Mendell K , Gorgun G , Antonia SJ , Chiappori AA , Creelan BC , Gray JE , Haura EB .

P30 CA076292 NCI NIH HHS , R21 CA194932 NCI NIH HHS

	Figure 1. Flowchart overview of steps involved in the process of collection of tissue from donors participating in the rapid tissue donation project. In short, medical oncologists introduced the rapid tissue donation project to patients at an appropriate time. If interest was expressed from a patient, consent was subsequently requested. Posthumous tissue was rapidly collected by a medical examiner in the community at a facility as close as possible to the funeral service
	Figure 2. A, Hematoxylin and eosin stained slides at 200× magnification depicting well‐preserved kidney (on left, arrow indicates preserved glomerulus) and pancreas (on right, arrow indicates preserved pancreatic islet) from rapid tissue donation patient 1. B, Images of slides stained by immunohistochemistry with the E1L3N® anti‐PD‐L1 rabbit monoclonal antibody from one representative lung tumor and one lymph node with metastatic lung cancer from donors 1, 4, 6, and 7 which had tumor with any positivity for PD‐L1 expression. C, Representative images of slides stained by immunohistochemistry with for Ki67, CD8, CD31, and pSTAT3
	Figure 3. Genomic heterogeneity of mutations among multiple tumor sites. The columns represent specimen results from sequencing 13 specimens from 5 donors with a customized 567‐gene Agilent SureSelectXT panel. Each column represents one specimen with the top bar color representing which donor the specimen is from: 1 (black), 3 (red), 4 (green), 6 (dark blue), and 7 (light blue). For each gene on the left, there is an orange bar if a frame shift (FS) mutation, nonsense mutation, or splice variant is identified, a green bar if a missense mutation is identified, and a red bar if amplification is identified in that gene. If no colored bar is present (gray background), the specimen was negative for mutations in that gene. Abbreviations: FS, frameshift; purity, calculated tumor percentage; MutLoad, mutation load (number of mutations identified)
	Figure 4. Compilation of RNA Results. A, Global similarity of RNA profiles among multiple tumor sites. The first and third principal components are shown for the normalized log2 RNA‐seq counts per million for all genes. A, The third principal component is shown instead of the second as this corrects for elevated levels of liver‐specific transcripts. B, The second principal component is shown instead of the third to show results without correction for elevated levels of liver‐specific transcripts. C‐E, Concordance between RNA‐seq and IHC for PD‐L1, CD8, and Ki‐67. The vertical axis denotes the normalized log2 RNA‐seq counts per million for the indicated genes. The horizontal axis denotes the final categorical result for PD‐L1, CD8, and Ki‐67 expression by immunohistochemistry analyses as outlined in Table S1. PD‐L1 immunochemistry data was generated using the PD‐L1 antibody clone 28‐8 with ≥1% tumor proportion score considered as “Positive”

Adiconis, Comparative analysis of RNA sequencing methods for degraded or low-input samples. 2013, Pubmed

Adiconis, Comparative analysis of RNA sequencing methods for degraded or low-input samples. 2013, Pubmed
Alsop, A community-based model of rapid autopsy in end-stage cancer patients. 2016, Pubmed
Anders, HTSeq--a Python framework to work with high-throughput sequencing data. 2015, Pubmed
Cibulskis, Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples. 2013, Pubmed
Cocariu, Correlations Between the Autolytic Changes and Postmortem Interval in Refrigerated Cadavers. 2016, Pubmed
DePristo, A framework for variation discovery and genotyping using next-generation DNA sequencing data. 2011, Pubmed
Dill, PD-L1 Expression and Intratumoral Heterogeneity Across Breast Cancer Subtypes and Stages: An Assessment of 245 Primary and 40 Metastatic Tumors. 2017, Pubmed
Dobin, STAR: ultrafast universal RNA-seq aligner. 2013, Pubmed
Edge, The American Joint Committee on Cancer: the 7th edition of the AJCC cancer staging manual and the future of TNM. 2010, Pubmed
Farago, Beyond ALK and ROS1: RET, NTRK, EGFR and BRAF gene rearrangements in non-small cell lung cancer. 2017, Pubmed
Howell, Hospice referral: an important responsibility of the oncologist. 2008, Pubmed
Lindell, Lessons from our patients: development of a warm autopsy program. 2006, Pubmed
McKenna, The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. 2010, Pubmed
Morlan, Selective depletion of rRNA enables whole transcriptome profiling of archival fixed tissue. 2012, Pubmed
Negrao, TRACERx: Tracking tumor evolution to impact the course of lung cancer. 2018, Pubmed
Parra, Comparison of Different Antibody Clones for Immunohistochemistry Detection of Programmed Cell Death Ligand 1 (PD-L1) on Non-Small Cell Lung Carcinoma. 2018, Pubmed
Pisapia, Next-Generation Rapid Autopsies Enable Tumor Evolution Tracking and Generation of Preclinical Models. 2017, Pubmed
Quinn, Patient, caregiver and physician perspectives on participating in a thoracic rapid tissue donation program. 2018, Pubmed
Rehman, Quantitative and pathologist-read comparison of the heterogeneity of programmed death-ligand 1 (PD-L1) expression in non-small cell lung cancer. 2017, Pubmed
Riester, PureCN: copy number calling and SNV classification using targeted short read sequencing. 2016, Pubmed
Roper, APOBEC Mutagenesis and Copy-Number Alterations Are Drivers of Proteogenomic Tumor Evolution and Heterogeneity in Metastatic Thoracic Tumors. 2019, Pubmed
Ross, The distribution of BRAF gene fusions in solid tumors and response to targeted therapy. 2016, Pubmed
Schröder, Socrates: identification of genomic rearrangements in tumour genomes by re-aligning soft clipped reads. 2014, Pubmed
Shah, Androgen-independent prostate cancer is a heterogeneous group of diseases: lessons from a rapid autopsy program. 2004, Pubmed
Shimizu, Postmortem autolysis in the pancreas: multivariate statistical study. The influence of clinicopathological conditions. 1990, Pubmed
Suda, Innate Genetic Evolution of Lung Cancers and Spatial Heterogeneity: Analysis of Treatment-Naïve Lesions. 2018, Pubmed
Vojnic, Acquired BRAF Rearrangements Induce Secondary Resistance to EGFR therapy in EGFR-Mutated Lung Cancers. 2019, Pubmed
Yap, Elucidating therapeutic molecular targets in premenopausal Asian women with recurrent breast cancers. 2018, Pubmed
Ye, Pindel: a pattern growth approach to detect break points of large deletions and medium sized insertions from paired-end short reads. 2009, Pubmed
van der Linden, Post-mortem tissue biopsies obtained at minimally invasive autopsy: an RNA-quality analysis. 2014, Pubmed