2025 Sequencing Strategies for Population and Cancer Epidemiology Studies (SeqSPACE)

2026 SeqSPACE Abstract Submission Form

Thank you for your interest in submitting an abstract for the 2026 Sequencing Strategies for Population and Cancer Epidemiology Studies (SeqSPACE) webinar series. The SeqSPACE Planning Committee seeks to highlight the work of Junior Investigators for our upcoming webinars in Fall/Winter 2026. If you are interested in applying, please fill out the form below.

Who Should Apply

For the purposes of this series, a Junior Investigator includes upper-level PhD, MD, MD/PhD, DrPH, or students in equivalent degree-related programs and postdocs, as well as early career faculty.

Submission Deadline

Abstract submissions are due by June 5, 2026, 5:00 p.m. ET.

Once you select Submit, you will receive a confirmation email with a personalized link that allows you to view and edit your submission prior to the deadline.

Review and Selection Process

All submitted abstracts will be reviewed by the SeqSPACE Planning Committee. Abstracts will be selected based on the research’s rigor, novelty, potential impact, and relevance to the application of sequencing technologies in population studies and cancer epidemiology. Abstracts from projects that leverage existing resources are strongly encouraged.

Applicants will be notified of final abstract selections no later than August 21, 2026, via email. More information on webinar format and logistics will be provided at a later date.

For further information or questions, please contact NCISeqSPACE@mail.nih.gov.

Learn more about the SeqSPACE webinar series here: epi.grants.cancer.gov/events/seqSPACE.

Submission information

Submission Number: 7

Submission ID: 151039

Submission UUID: 9e79232f-edc4-4cee-9e94-6b91a2d4d9e0

Submission URI: /egrp/seqspaceabstracts

Submission Update: /egrp/seqspaceabstracts?token=Hq5KyuhoXML7VhOZM41wBGebWbvoPfeWzM0Z6dSytO0

Created: Fri, 09/05/2025 - 12:41

Completed: Fri, 09/05/2025 - 12:41

Changed: Fri, 09/05/2025 - 12:41

Remote IP address: 10.208.24.84

Submitted by: Anonymous

Language: English

Is draft: No

Webform: seqspace (Abstracts)

Submitted to: 2025 Sequencing Strategies for Population and Cancer Epidemiology Studies (SeqSPACE)

OMB No.: 0925-0740
Expiration Date: 9/30/2025

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Presenter Information

Please enter information for the person who will be the primary presenter/speaker/author.

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Degree(s)

Please use the following formatting for these degrees: M.D. Ph.D. MPH

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Abstract Information

Abstract Title

Abstract Summary

Purpose: While previous studies have assessed associations between rare genetic variation and cancer, they have mostly 1) examined a limited number of cancer types and 2) included only European genetic ancestry individuals. The generation sequencing data by large population-based biobanks enables more comprehensive examinations of the relationships between rare genetic variants and multiple cancers across populations. We assessed associations between rare genetic variants and over 70 cancer types using sequencing data from 431,961 and 297,508 multi-ancestry participants from the UK Biobank (UKB) and All of Us Research Program (AoU) cohorts, respectively. Methods: We used three approaches to characterize the influences of rare coding variants on risk for various cancers. First, we used generalized linear mixed models to conduct gene-based burden tests and single variant tests for over 70 individual cancers and groups of cancers in the full multi-ancestry UKB and AoU cohorts. Second, we estimated the contributions of rare coding variants to breast, colorectal, and prostate cancer heritability in genetic ancestry-stratified groups in the UKB and AoU cohorts using methods that generate both aggregate and gene-level heritability estimates. Third, we developed polygenic scores (PGS) that integrated existing common variant PGS and rare variant effects for breast, colorectal, and prostate cancers and evaluated the performance of these PGS across genetic ancestry groups in the UKB and AoU cohorts. Results: We identified 15 genes (ASXL1, ATM, BRCA1, BRCA2, CDKN2A, CHEK2, DNMT3A, MLH1, PALB2, POT1, PPM1D, RTEL1, SAMHD1, TET2, and TP53) that showed associations across a range of the individual cancer types tested. We estimated small heritability contributions from rare variants that were enriched in known cancer risk genes. Conclusions: Our results suggest that utilizing the expansive sequencing and cancer diagnosis data in large population-based biobanks could expand our understanding of the role of rare genetic variants in cancer risk.