Steven Gallinger

BackgroundPancreatic ductal adenocarcinoma (PDAC) comprises two clinically relevant subtypes. Currently, determining the tumor subtype relies on tissue biopsies. Unfortunately, these biopsies are spatially biased, highly invasive, difficult to obtain, and unsuitable for monitoring tumor dynamics.MethodsWe employed whole transcriptome sequencing (WTS) on circulating cell-free (cf) RNA in plasma samples from patients with well-characterized tumor subtypes. Additionally, quantitative protein mass spectrometry was utilized to identify minimally invasive markers for tumor subtypes. We validated our findings using independent liquid and tissue samples from large clinical trials and investigated treatment-induced subtype dynamics and responses.ResultsAn exploratory analysis of 10 patients (four basal-like and six classical) was conducted using whole transcriptome sequencing (WTS). Following differential transcript abundance analysis and integration with expression data from tumor and non-tumor samples (N> 200), we identified 32 protein-coding subtype-specific cfRNA-defined transcripts. The subtype specificity of these transcripts was validated in two independent tissue cohorts comprising 195 and 250 cases, respectively. Three disease-relevant cfRNA-defined subtype markers (DEGS1, KDELC1, and RPL23AP7) consistently associated with basal-like tumors across all cohorts and were validated using machine learning. Further analysis of these markers using RT-ddPCR in over 160 patient sera and 24 samples from healthy donors revealed their predictive and prognostic value, as well as subtype specificity and therapy-induced …

638Background: In pancreatic ductal adenocarcinoma (PDAC), to identify prognostic factors for surgically treated patients, including vascular resections. Methods: Retrospective review (2011 – 2023) of pathologically proven PDAC treated with curative-intent surgery (n = 715) at a high-volume cancer center. We tested associations between clinicopathological and radiological data, perioperative therapy, time to recurrence (TTR) and overall survival (OS). Results: Demographic and clinicopathological variables were comparable to published surgical cohorts. Initial NCCN radiological staging was 533 (74.5%) resectable, 98 (13.7%) borderline, and 84 (11.7%) locally advanced PDAC. There were 467(65.3%) pancreaticoduodenectomies, 104 (14.5%) distal pancreatectomies, 31 (4.3%) total pancreatectomies and 112 (15.7%) aborted procedures, mostly due to metastatic disease (82.1%). Of the 603 resected cases …

Large-scale biorepositories and databases are essential to generate equitable, effective, and sustainable advances in cancer prevention, early detection, cancer therapy, cancer care, and surveillance. The Mutographs project has created a large genomic dataset and biorepository of over 7,800 cancer cases from 30 countries across five continents with extensive demographic, lifestyle, environmental, and clinical information. Whole-genome sequencing is being finalized for over 4,000 cases, with the primary goal of understanding the causes of cancer at eight anatomic sites. Genomic, exposure, and clinical data will be publicly available through the International Cancer Genome Consortium Accelerating Research in Genomic Oncology platform. The Mutographs sample and metadata biorepository constitutes a legacy resource for new projects and collaborations aiming to increase our current research efforts in …

Introduction: Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal neoplasm of the pancreas characterized by a low survival rate and limited treatment options. Despite the success of immunotherapy in various cancer types, its efficacy in PDAC remains low. The underlying reasons for this discrepancy are not fully understood, despite PDAC exhibiting a moderate mutation burden. One possible determinant could be the loss of heterozygosity (LOH) at the human leukocyte antigen (HLA) loci, resulting in compromised antigen presentation. In this work, we aim to identify and validate HLA LOH events in two independent cohorts to gain insights into both their prevalence and clinical and phenotypic impact on PDAC. Methods: We applied LOHHLA, a specialized pipeline to identify HLA LOH events from paired whole genome sequencing to two independent cohorts comprising over 650 patients. We contextualized …

Genome-wide association studies (GWAS) have identified more than 200 common genetic variants independently associated with colorectal cancer (CRC) risk, but the causal variants and target genes are mostly unknown. We sought to fine-map all known CRC risk loci using GWAS data from 100,204 cases and 154,587 controls of East Asian and European ancestry. Our stepwise conditional analyses revealed 238 independent association signals of CRC risk, each with a set of credible causal variants (CCVs), of which 28 signals had a single CCV. Our cis-eQTL/mQTL and colocalization analyses using colorectal tissue-specific transcriptome and methylome data separately from 1299 and 321 individuals, along with functional genomic investigation, uncovered 136 putative CRC susceptibility genes, including 56 genes not previously reported. Analyses of single-cell RNA-seq data from colorectal tissues revealed 17 …

Advancement of AI has opened new possibility for accurate diagnosis and prognosis using digital histopathology slides which not only saves hours of expert effort but also makes the estimation more standardized and accurate. However, preserving the AI model performance on the external sites is an extremely challenging problem in the histopathology domain which is primarily due to the difference in data acquisition and/or sampling bias. Although, AI models can also learn spurious correlation, they provide unequal performance across validation population. While it is crucial to detect and remove the bias from the AI model before the clinical application, the cause of the bias is often unknown. We proposed a Causal Survival model that can reduce the effect of unknown bias by leveraging the causal reasoning framework. We use the model to predict recurrence-free survival for the colorectal cancer patients using quantitative histopathology features from seven geographically distributed sites and achieve equalized performance compared to the baseline traditional Cox Proportional Hazards and DeepSurvival model. Through ablation study, we demonstrated benefit of novel addition of latent probability adjustment and auxiliary losses. Although detection of cause of unknown bias is unsolved, we proposed a causal debiasing solution to reduce the bias and improve the AI model generalizibility on the histopathology domain across sites.

Introduction: Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal neoplasm of the pancreas characterized by a low survival rate and limited treatment options. Despite the success of immunotherapy in various cancer types, its efficacy in PDAC remains low. The underlying reasons for this discrepancy are not fully understood, despite PDAC exhibiting a moderate mutation burden. One possible determinant could be the loss of heterozygosity (LOH) at the human leukocyte antigen (HLA) loci, resulting in compromised antigen presentation. In this work, we aim to identify and validate HLA LOH events in two independent cohorts to gain insights into both their prevalence and clinical and phenotypic impact on PDAC. Methods: We applied LOHHLA, a specialized pipeline to identify HLA LOH events from paired whole genome sequencing to two independent cohorts comprising over 650 patients. We contextualized …

697Background: Locally advanced pancreatic cancer (LAPC) accounts for approximately 30% of pancreatic ductal adenocarcinomas (PDAC). Optimal management for LAPC is controversial and combination treatments are extrapolated from treatment guidelines for metastatic disease. The biological underpinnings of LAPC remain unclear, although the loss of tumor suppressor SMAD4 has been associated with metastatic disease. Here we characterize the genomic landscape of LAPC in a large series of prospectively sequenced PDAC. Methods: Clinical, genomic and survival data were obtained from the COMPASS trial (NCT02750657), a prospective multi-institutional study that included patients with treatment-naïve advanced PDAC, with predominantly metastatic cases due to ease of biopsy. Fresh tumor tissue was acquired by percutaneous core biopsy for real-time whole genome sequencing (WGS) and RNA …