About

John H. Blume is a Professor and the Samuel F. Leibowitz Professor of Trial Techniques at Cornell University. He is also the Director of the Cornell Death Penalty Project. His academic affiliation is with the Department of Psychology, and he is involved in research and teaching related to trial techniques and issues surrounding the death penalty. His work is situated within the broader context of psychological sciences and human development, and he is engaged in activities that support public engagement and legal scholarship.

Research topics

• Political Science
• Sociology
• Law
• Criminology
• Psychiatry
• Internal medicine
• Biology
• Psychology
• Clinical psychology
• Medicine
• Bioinformatics
• Genetics
• Oncology

Selected publications

• The Supreme Court's "New" Nexus Requirement

  SSRN Electronic Journal · 2026-01-01

  preprintOpen access1st authorCorresponding
  PublisherDOI

• 6 Controlling Condemned Bodies

  New York University Press eBooks · 2025-12-11

  book-chapter1st authorCorresponding
  PublisherDOI

• Analyzing the Successful Incompetent to Be Executed Cases in the United States: A First Pass

  Behavioral Sciences · 2025-03-06

  articleOpen access

  More than three decades ago, the Supreme Court of the United States (SCOTUS) ruled that individuals who are not competent (alternatively referred to by the Court as insane) at the time of their scheduled execution cannot be put to death. Despite the years that have passed since the Court’s decision and the literal life-or-death stakes involved, competency for execution (CFE) remains underexplored in the psychological, psychiatric, and legal literature. A number of important legal and ethical issues that arise when a person on death row maintains they are not competent to be executed are still unresolved even after the landmark Supreme Court cases such as Ford v. Wainwright (1986), Panetti v. Quarterman (2007), and Madison v. Alabama (2019). In this first-of-its-kind descriptive study, we analyzed the demographic and case characteristics of the 28 successful Ford claimants—individuals in the United States who have been found to be incompetent to be executed and compared them to the general death row population and homicide cases nationwide. Our findings reveal some similarities but also some differences between these claimants and the general death row population and homicide cases: the successful Ford claimants are exclusively male (in keeping with the general prison population on death row), relatively older, and underrepresented among White and Latinx inmates (i.e., Black claimants are more successful than their White and Latinx counterparts at evading execution). Nearly all (96%) suffer from schizophrenia, with 79% experiencing psychiatric comorbidity, yet only 54% received any significant treatment before or after the criminal offense. The claimants’ cases also involve a higher proportion of child victims, male family members, and female non-family member victims, as well as more multiple-victim cases (not indiscriminate) and fewer intraracial homicides. Fewer victims are male, and more are female. However, the cases do not align with typical male-on-male violent crimes or femicide patterns, such as those involving sexual or domestic violence. Additionally, systematic psycho-legal deficiencies are prevalent, including a low rate of mental health evidence (61%) presented at trials and some cases lacking psychiatric involvement in CFE evaluations. Temporal influence and drastic state variations on CFE evaluation are also noted. Although the small sample size limits generalizability, this small-scale descriptive study offers a number of important insights into the complexities of CFE decisions and lays the groundwork for future research and policy development.

  PublisherOA PDFDOI

• Analyzing the Successful Incompetent to be-Executed Cases in the United States: A First Pass

  Preprints.org · 2025-01-30

  preprintOpen access

  More than three decades ago, the Supreme Court of the United States (SCOTUS) ruled that individuals who are not competent (alternatively referred to by the Court as insane) at the time of their scheduled execution cannot be put to death. Despite the years that have passed since the Court’s decision and the literal life or death stakes involved, competency for execution (CFE) remains underexplored in the psychological and legal literature. A number of important legal and ethical issues that arise when a person on death row maintains they are not competent to be executed are still unresolved even after landmark Supreme Court cases such as Ford v. Wainwright (1986), Panetti v. Quarterman (2007), and Madison v. Alabama (2019). In this first-of-its-kind descriptive study, we analyze the demographic and case characteristics of the 28 successful Ford-Panetti claimants—individuals in the United States who have been found to be incompetent to be executed. Our findings reveal some similarities but also some significant differences between these claimants and the general death row population: the successful claimants are exclusively male (in keeping with the general prison population on death row), significantly older, and underrepresented among White and Latinx inmates (i.e., Black claimants are more successful than their White and Latinx counterparts at evading execution). Nearly all (96%) suffer from schizophrenia, with 79% experiencing psychiatric comorbidity, yet only 54% received any significant treatment before or after the criminal offense. The claimants’ cases also involve a higher proportion of child victims, family members, and strangers, as well as more multiple-victim cases (not indiscriminate) and fewer intraracial homicides. Fewer victims are male, and more are female. However, the cases do not align with typical male-on-male violent crimes or femicide patterns, such as those involving sexual or domestic violence. Additionally, psycho-legal deficiencies are prevalent, including a low rate of mental health evidence (61%) presented at trials and some cases lacking psychiatric involvement in CFE evaluations. Temporal influence and drastic state variations on CFE evaluation are also noted. Although the small sample size limits generalizability, this small-scale descriptive study offers a number of important insights into the complexities of CFE decisions and lays the groundwork for future research and policy development.

  PublisherOA PDFDOI

• Analyzing the Successful Incompetent to Be Executed Cases in the United States: A First Pass

  SSRN Electronic Journal · 2025-01-01

  articleOpen access
  PublisherDOI

• Caged Birds and Those That Hear Their Songs: Effects of Race and Sex in South Carolina Parole Hearings

  SSRN Electronic Journal · 2024-01-01

  articleOpen accessSenior author
  PublisherDOI

• Quantifying disparate questioning of Black and White jurors in capital jury selection

  Journal of Empirical Legal Studies · 2023 · 1 citations

  • Political Science
  • Law
  • Sociology

  Abstract Numerous studies have demonstrated that female and Black jurors are under‐represented on juries in criminal cases, especially so when the prosecution seeks the death penalty. The primary, but not exclusive, way in which this happens is that prosecutors remove them from the jury pool through the exercise of peremptory challenges. The practice remains widespread despite the Supreme Court's decision more than 30 years ago holding that using such challenges in a racially (or gender based) discriminatory manner violates the Equal Protection Clause of the Fourteenth Amendment. In the years since, enforcement by the Supreme Court and state and federal courts has been uneven. However, in several recent cases, in finding that prosecutors struck Black venire persons because of their race, the Supreme Court relied in part on evidence that the prosecution questioned Black and White venire persons differently. The legal term of art for this practice is “disparate questioning.”

  PublisherOA PDFDOI

• Issue Information

  Journal of Empirical Legal Studies · 2023-08-09

  paratextOpen access

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  PublisherOA PDFDOI

• Abstract 6597: A multi-omics classifier achieves high sensitivity and specificity for pancreatic ductal adenocarcinoma in a case-control study of 146 subjects

  Cancer Research · 2023 · 1 citations

  1st authorCorresponding
  • Medicine
  • Bioinformatics
  • Internal medicine

  Abstract Pancreatic ductal adenocarcinoma (PDAC) is currently the 3rd leading cause of cancer-related deaths in the US. Although the all-stage 5-year survival rate is ~10%, early-stage 5-year survival is markedly superior and in excess of 40%. Hence, early detection of PDAC via blood-based liquid biopsies holds promise to reduce morbidity and mortality. PrognomiQ’s multi-omics platform performs deep and unbiased molecular profiling of blood samples to detect proteins, metabolites, lipids, mRNA, miRNA, cfDNA fragmentation and copy-number, and CpG methylation. Here we report results from training and validation of a classifier on a subset of that multi-omic data with the potential to enable the development of high sensitivity and specificity tests for early detection of PDAC.We conducted a case-control study comprising 146 subjects across 16 clinical sites, including 63 pathology-confirmed, untreated PDAC cases (12 stage I, 8 stage II, 4 stage III, 36 stage IV, and 3 stage unknown) and 83 age- and gender- matched controls without any known cancer. For each subject, venous blood samples including plasma were collected. Unbiased LCMS was used to detect and quantify proteins, and targeted, multiplexed MRM-LCMS assays were used for both metabolites and lipids. After data processing, we detected 54,114 proteomic features, 898 lipids, and 373 metabolites. 445 proteomic features, 170 lipids, and 37 metabolites were found to be significantly different as determined by Bonferroni-corrected Wilcoxon tests with FWER < 0.05. For classification, the dataset was split into training (37 cases and 37 controls) and validation (26 cases and 46 controls) sets, with control for collection site and date, age, and gender. XGBoost models were constructed for each analyte class using ten repeats of 10-fold cross-validation. To improve specificity to PDAC, all proteomic features which mapped to GOBP terms associated with acute-phase response, inflammation, and immune response were excluded prior to training. The best-performing hyperparameters were used for a final model built on the full training set and then used for inference on the validation set. At 99% specificity, the proteomic classifier had sensitivities of 77%, 57%, and 88% for Stages 1-4, Stages 1-2, and Stages 3-4, respectively, estimated by bootstrap re-sampling of the validation results. Metabolomics had sensitivities of 81%, 71%, and 88%. Lipidomics had sensitivities of 65%, 71%, and 65%. A joint, multi-omic model was constructed by averaging the scaled probabilities of all models. This joint model improved performance at 99% specificity with sensitivities of 92%, 86%, and 94%, highlighting the synergy of multi-omics data, particularly phenotypically related omics such as those described here. Multi-omic classifiers such as these can serve as the foundation for blood-based liquid biopsies for the early detection of PDAC. Citation Format: John Blume, Ghristine Bundalian, Jessica Chan, Connie Chao-Shern, Jinlyung Choi, Rea Cuaresma, Kevin Dai, Sara N. Golmaei, Jun Heok Jang, Manoj Khadka, Ehdieh Khaledian, Thidar Khin, Yuya Kodama, Ajinkya Kokate, Joon-Yong Lee, Manway Liu, Hoda Malekpour, Megan Mora, Nithya Mudaliar, Preethi Prasad, Madhuvanthi Ramaiah, Saividya Ramaswamy, Peter Spiro, Kavya Swaminathan, Dijana Vitko, James Yee, Brian Young, Susan Zhang, Chinmay Belthangady, Bruce Wilcox, Brian Koh, Philip Ma. A multi-omics classifier achieves high sensitivity and specificity for pancreatic ductal adenocarcinoma in a case-control study of 146 subjects [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6597.

  PublisherDOI

• Abstract 6606: Biomarker discovery in non-small-cell lung cancer enabled by deep multi-omics profiling of proteins, metabolites, transcripts, and genes in blood

  Cancer Research · 2023-04-04

  article

  Abstract Lung cancer is the leading cause of cancer-related deaths in the United States, with estimates of 236,740 new cases and 118,830 deaths in 2022 secondary to the disease. Blood-based liquid biopsies hold promise to reduce morbidity and mortality from lung cancer by enabling early detection to downstage disease at diagnosis, theragnostic identification of patients most likely to be helped or harmed by therapy, monitoring of therapeutic efficacy, and detection of residual disease. PrognomiQ’s multi-omics platform comprehensively profiles proteins, metabolites, lipids, mRNA, and cfDNA in blood samples which can be used for the development of liquid biopsy tests with high sensitivity and specificity for lung cancer. We conducted a case-control study comprising 1031 subjects: 361 subjects with untreated non-small-cell lung cancer (NSCLC) and 670 matched controls which included 340 subjects with salient pulmonary and gastrointestinal co-morbidities. Blood samples from each subject were processed to provide 7 different `omics readouts. LCMS was used to detect and quantify proteins, metabolites, and lipids. In addition, cfDNA and mRNA were assayed using next-generation sequencing. cfDNA reads were analyzed to estimate fragment-lengths, copy-number variation, and CpG site methylation. All molecular data were normalized using standard methods specific to each assay. Univariate analyses of cases vs controls were performed to identify differentially abundant features on all available samples per assay. We detected 9,868 proteins, 605 lipids, 329 metabolites, and 109,070 mRNA transcripts. Of these, 3,098 proteins, 210 lipids, 57 metabolites, and 30,236 mRNA transcripts were significantly different (FWER < 0.05) in cases versus controls. Gene set enrichment analysis on statistically significant transcripts and proteins identified multiple gene-ontology terms associated with cancer including the Wnt signaling process and IgA immunoglobulin complex, respectively. From cfDNA data, we identified 234 non-contiguous genomic regions associated with the fragment-length disorder, 4,790 with copy-number variation, and 74 differentially methylated genomic regions spanning 184 CpG sites (FWER < 0.05). With the premise that deviations from copy number neutrality are more likely to indicate a tumor contribution, we then focused our examination on those differentially expressed proteins that overlap with differentially expressed mRNA transcripts as well as CNV genomic regions. We identified 52 protein coding genes including E-cadherin (associated with EMT) and related binding proteins such as RAB11B, CAPZB, EPS15, FLNB, MYH9, STK24 and YWHAE. Ongoing machine-learning-based classifier training to distinguish between cancer and non-cancer can serve as the basis for the development of high-sensitivity liquid-biopsy tests for lung cancer. Citation Format: Jinlyung Choi, Ajinkya Kokate, Ehdieh Khaledian, Manway Liu, Preethi Prasad, John Blume, Jessica Chan, Rea Cuaresma, Kevin Dai, Manoj Khadka, Thidar Khin, Yuya Kodama, Joon-Yong Lee, Hoda Malekpour, Megan Mora, Nithya Mudaliar, Sara Nouri Golmaei, Madhuvanthi Ramaiah, Saividya Ramaswamy, Peter Spiro, Dijana Vitko, Kavya Swaminathan, James Yee, Brian Young, Chinmay Belthangady, Bruce Wilcox, Brian Koh, Philip Ma. Biomarker discovery in non-small-cell lung cancer enabled by deep multi-omics profiling of proteins, metabolites, transcripts, and genes in blood. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6606.

  PublisherDOI

Frequent coauthors

• Sheri L. Johnson

  University of California, Berkeley

  43 shared

• Amelia Courtney Hritz

  15 shared

• Theodore Eisenberg

  13 shared

• Emily C. Paavola

  11 shared

• Caisa Elizabeth Royer

  University of Utah

  10 shared

• Valerie P. Hans

  8 shared

• Martin T. Wells

  Cornell University

  7 shared

• Stephen P. Garvey

  Coventry University

  6 shared