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Supplementary Tables S1 - S12. Supplementary Table S1. Prioritization of candidate FPC susceptibility genes by private heterozygous PTVs. Supplementary Table S2. FPC patients harboring a private PTVs ASXL1, DNMT3A, and TET2. Supplementary Table S3. 87 genes analyzed in-depth in FPC patients and kindreds. Supplementary Table S4. Deleterious variants in FPC patients and kindreds. Supplementary Table S5. FPC samples with more than one deleterious variant. Supplementary Table S6. Deleterious variants in BCCS samples. Supplementary Table S7. Deleterious variants in FPC kindreds and BCCS samples. Supplementary Table S8. Differences in deleterious variants between FPC kindreds with three or more affected members and BCCS samples. Supplementary Table S9. Private heterozygous PTVs present in all sequenced affected members of a kindred. Supplementary Table S10. Deleterious variants shared between affected members of an FPC kindred. Supplementary Table S11. Somatic mutations in FPC patient tumors. Supplementary Table S12. Summary of somatic mutation data for FPC patient tumors by gene.

Supplementary Data from Clinico-genomic Characterization of ATM and HRD in Pancreas Cancer: Application for Practice

Supplementary Figure from Clinico-genomic Characterization of ATM and HRD in Pancreas Cancer: Application for Practice

Purpose:Characterizing germline and somatic ATM variants (gATMm, sATMm) zygosity and their contribution to homologous recombination deficiency (HRD) is important for therapeutic strategy in pancreatic ductal adenocarcinoma (PDAC).Experimental Design:Clinico-genomic data for patients with PDAC and other cancers with ATM variants were abstracted. Genomic instability scores (GIS) were derived from ATM-mutant cancers and overall survival (OS) was evaluated.Results:Forty-six patients had PDAC and pathogenic ATM variants including 24 (52%) stage III/IV: gATMm (N = 24), and sATMm (N = 22). Twenty-seven (59%) had biallelic, 15 (33%) monoallelic, and 4 indeterminate (8%) variants. Median OS for advanced-stage cohort at diagnosis (N = 24) was 19.7 months [95% confidence interval (CI): 12.3–not reached (NR)], 27.1 months (95% CI: 22.7–NR) for gATMm (n = 11), and 12.3 months for sATMm (n = 13; 95% CI: 11.9–NR; P = 0.025). GIS was computed for 33 patients with PDAC and compared with other ATM-mutant cancers enriched for HRD. The median was lower (median, 11; range, 2–29) relative to breast (18, 3–55) or ovarian (25, 3–56) ATM-mutant cancers (P < 0.001 and P = 0.003, respectively). Interestingly, biallelic pathogenic ATM variants were mutually exclusive with TP53. Other canonical driver gene (KRAS, CDKN2A, SMAD4) variants were less frequent in ATM-mutant PDAC.Conclusions:ATM variants in PDAC represent a distinct biologic group and appear to have favorable OS. Nonetheless, pathogenic ATM variants do not confer an HRD signature in PDAC and ATM should be considered as a non-core HR gene in this disease.

Cancer immunoediting1is a hallmark of cancer2that predicts that lymphocytes kill more immunogenic cancer cells to cause less immunogenic clones to dominate a population. Although proven in mice1,3, whether immunoediting occurs naturally in human cancers remains unclear. Here, to address this, we investigate how 70 human pancreatic cancers evolved over 10 years. We find that, despite having more time to accumulate mutations, rare long-term survivors of pancreatic cancer who have stronger T cell activity in primary tumours develop genetically less heterogeneous recurrent tumours with fewer immunogenic mutations (neoantigens). To quantify whether immunoediting underlies these observations, we infer that a neoantigen is immunogenic (high-quality) by two features—‘non-selfness’ based on neoantigen similarity to known antigens4,5, and ‘selfness’ based on the antigenic distance required for a neoantigen to differentially bind to the MHC or activate a T cell compared with its wild-type peptide. Using these features, we estimate cancer clone fitness as the aggregate cost of T cells recognizing high-quality neoantigens offset by gains from oncogenic mutations. With this model, we predict the clonal evolution of tumours to reveal that long-term survivors of pancreatic cancer develop recurrent tumours with fewer high-quality neoantigens. Thus, we submit evidence that that the human immune system naturally edits neoantigens. Furthermore, we present a model to predict how immune pressure induces cancer cell populations to evolve over time. More broadly, our results argue that the immune system fundamentally surveils host genetic changes to suppress cancer.

Supplementary Table 1 from An In vivo Platform for Translational Drug Development in Pancreatic Cancer

Effective development of targeted anticancer agents includes the definition of the optimal biological dose and biomarkers of drug activity. Currently available preclinical models are not optimal to this end. We aimed at generating a model for translational drug development using pancreatic cancer as a prototype. Resected pancreatic cancers from 14 patients were xenografted and expanded in successive groups of nude mice to develop cohorts of tumor-bearing mice suitable for drug therapy in simulated early clinical trials. The xenografted tumors maintain their fundamental genotypic features despite serial passages and recapitulate the genetic heterogeneity of pancreatic cancer. The in vivo platform is useful for integrating drug screening with biomarker discovery. Passages of tumors in successive cohorts of mice do not change their susceptibility to anticancer agents and represent a perpetual live bank, facilitating the application of new technologies that will result in the creation of an integrated stable database of tumor-drug response data and biomarkers.

Supplementary Figures 1-3, Table 1 from Integrin α2 Mediates Selective Metastasis to the Liver

Supplementary Table 1 from Methylation of TFPI2 in Stool DNA: A Potential Novel Biomarker for the Detection of Colorectal Cancer

Supplementary Table 1 and Figure Legend from Blockade of Hedgehog Signaling Inhibits Pancreatic Cancer Invasion and Metastases: A New Paradigm for Combination Therapy in Solid Cancers

Supplementary Figure 1 from Blockade of Hedgehog Signaling Inhibits Pancreatic Cancer Invasion and Metastases: A New Paradigm for Combination Therapy in Solid Cancers

We have used a gene expression array–based strategy to identify the methylation of tissue factor pathway inhibitor 2 (TFPI2), a potential tumor suppressor gene, as a frequent event in human colorectal cancers (CRC). TFPI2 belongs to the recently described group of embryonic cell Polycomb group (PcG)–marked genes that may be predisposed to aberrant DNA methylation in early stages of colorectal carcinogenesis. Aberrant methylation of TFPI2 was detected in almost all CRC adenomas (97%, n = 56) and stages I to IV CRCs (99%, n = 115). We further explored the potential of TFPI2 as a biomarker for the early detection of CRC using stool DNA–based assays in patients with nonmetastatic CRC and average-risk noncancer controls who were candidates for screening. TFPI2 methylation was detected in stool DNA from stage I to III CRC patients with a sensitivity of 76% to 89% and a specificity of 79% to 93%. Detection of TFPI2 methylation in stool DNA may act as a useful adjunct to the noninvasive strategies for screening of CRCs in the future. [Cancer Res 2009;69(11):4691–9]

Supplementary Figure 1 from Coordinated Epidermal Growth Factor Receptor Pathway Gene Overexpression Predicts Epidermal Growth Factor Receptor Inhibitor Sensitivity in Pancreatic Cancer

Supplementary Figures 1-4 from Methylation of TFPI2 in Stool DNA: A Potential Novel Biomarker for the Detection of Colorectal Cancer

In the context of pancreatic cancer, metastasis remains the most critical determinant of resectability, and hence survival. The objective of this study was to determine whether Hedgehog (Hh) signaling plays a role in pancreatic cancer invasion and metastasis because this is likely to have profound clinical implications. In pancreatic cancer cell lines, Hh inhibition with cyclopamine resulted in down-regulation of snail and up-regulation of E-cadherin, consistent with inhibition of epithelial-to-mesenchymal transition, and was mirrored by a striking reduction of in vitro invasive capacity (P < 0.0001). Conversely, Gli1 overexpression in immortalized human pancreatic ductal epithelial cells led to a markedly invasive phenotype (P < 0.0001) and near total down-regulation of E-cadherin. In an orthotopic xenograft model, cyclopamine profoundly inhibited metastatic spread; only one of seven cyclopamine-treated mice developed pulmonary micrometastases versus seven of seven mice with multiple macrometastases in control animals. Combination of gemcitabine and cyclopamine completely abrogated metastases while also significantly reducing the size of “primary” tumors. Gli1 levels were up-regulated in tissue samples of metastatic human pancreatic cancer samples compared with matched primary tumors. Aldehyde dehydrogenase (ALDH) overexpression is characteristic for both hematopoietic progenitors and leukemic stem cells; cyclopamine preferentially reduced “ALDH-high” cells by ∼3-fold (P = 0.048). We confirm pharmacologic Hh pathway inhibition as a valid therapeutic strategy for pancreatic cancer and show for the first time its particular efficacy against metastatic spread. By targeting specific cellular subpopulations likely involved in tumor initiation at metastatic sites, Hh inhibitors may provide a new paradigm for therapy of disseminated malignancies, particularly when used in combination with conventional antimetabolites that reduce “bulk” tumor size. [Cancer Res 2007;67(5):2187–96]

Supplementary Table 1 from Coordinated Epidermal Growth Factor Receptor Pathway Gene Overexpression Predicts Epidermal Growth Factor Receptor Inhibitor Sensitivity in Pancreatic Cancer

Supplementary Table 2 from Coordinated Epidermal Growth Factor Receptor Pathway Gene Overexpression Predicts Epidermal Growth Factor Receptor Inhibitor Sensitivity in Pancreatic Cancer

The epidermal growth factor receptor (EGFR) inhibitor erlotinib is approved for treatment of pancreatic cancer but the overall activity is minimal, and known predictive factors for EGFR inhibitor efficacy are infrequent in this disease. We tested the hypothesis that global activation of the EGFR pathway is predictive of EGFR inhibitor efficacy. Pancreatic cancer tumors directly xenografted at surgery were treated with the EGFR inhibitors erlotinib and cetuximab and analyzed for biological features. Two of 10 tumors were sensitive, and by global gene expression profiling with gene set enrichment analysis, the EGFR pathway was highly expressed in sensitive compared with resistant tumors. The core gene components driving EGFR pathway overexpression were pathway ligands and positive effectors. In a prospective validation, the EGFR pathway-based signature correctly predicted anti-EGFR treatment response in eight additional tumors and was not predictive of response to gemcitabine and CI1040 (a MEK inhibitor). Analysis of EGFR, KRAS, and PIK3CA mutations and gene amplification by fluorescence in situ hybridization and multiplex ligation-dependent probe amplification showed that none of these genetic abnormalities were neither predictive nor responsible for the EGFR pathway activation. Coordinated overexpression of the EGFR pathway predicts susceptibility to EGFR inhibitors in pancreatic cancer. These results suggest a phenomenon of pathway addiction and support the value of unbiased system biology approaches in drug development. [Cancer Res 2008;68(8):2841–9]

Tumors consist of subpopulations of cells that harbor distinct collections of somatic mutations. These mutations range in scale from single nucleotide variants (SNVs) to large-scale copy-number aberrations (CNAs). While many approaches infer tumor phylogenies using SNVs as phylogenetic markers, CNAs that overlap SNVs may lead to erroneous phylogenetic inference. Specifically, an SNV may be lost in a cell due to a deletion of the genomic segment containing the SNV. Unfortunately, no current single-cell DNA sequencing (scDNA-seq) technology produces accurate measurements of both SNVs and CNAs. For instance, recenttargetedscDNA-seq technologies, such as Mission Bio Tapestri, measure SNVs with high fidelity in individual cells, but yield much less reliable measurements of CNAs. We introduce a new evolutionary model, theconstrained k-Dollo model, that uses SNVs as phylogenetic markers and partial information about CNAs in the form of clustering of cells with similar copy-number profiles. This copy-number clustering constrains where loss of SNVs can occur in the phylogeny. We develop ConDoR (Constrained Dollo Reconstruction), an algorithm to infer tumor phylogenies from targeted scDNA-seq data using the constrainedk-Dollo model. We show that ConDoR outperforms existing methods on simulated data. We use ConDoR to analyze a new multi-region targeted scDNA-seq dataset of 2153 cells from a pancreatic ductal adenocarcinoma (PDAC) tumor and produce a more plausible phylogeny compared to existing methods that conforms to histological results for the tumor from a previous study. We also analyze a metastatic colorectal cancer dataset, deriving a more parsimonious phylogeny than previously published analyses and with a simpler monoclonal origin of metastasis compared to the original study.Code availabilitySoftware is available athttps://github.com/raphael-group/constrained-Dollo

Most pancreatic ductal adenocarcinomas (PDAC) are lethal and resistant to immunotherapy. Thus, identifying the immunogenic subgroup (iPDAC) and therapeutic targets can save lives. Herein, we present molecular features of iPDAC. 3 cohorts (A, B, C) from 288 patients whose sequenced tumors (MSK-IMPACT) were classified by homologous recombination deficiency groups. MSI-H were excluded. Survival, tumor mutation burden, genomic instability score, and enriched pathways for each cohort are included in Table 1. Patients in A (BRCA1/2/PALB2) had longer survivals vs B/C. 61 samples were selected for bulk RNAseq analysis for A vs C. Gene Ontology was enriched for upregulated humoral, T cell, and neutrophil immunity. CIBERSORT suggested higher infiltration of gamma delta T (Tgd) cells (p=0.039) and neutrophils (p=0.012), but lower Treg (p=0.001). Multidimensional insights in cellular components of cancer, immune, stroma, and neural genes were obtained by single nuclear RNA (snRNAseq) analysis from 30 biopsies for A vs C. 10x Genomics Chromium platform for library and Scanpy for computational analysis after Cell Ranger pipelines were used. 61,868 nuclei were profiled from 18 (13 baseline and 5 matched longitudinal) samples after quality evaluation. UMAP accurately clustered cells from each patient. Long-term survivors (LTS) had heterogenous baseline immune cell infiltrates of plasma cells, neutrophils, and CD8 (+) cytotoxic T cells. In matched samples of LTS, evolution of more prominent CD8 (+) T cells, macrophage, plasma cell, and neutrophil were observed. Single nucleus T-Cell Receptor sequencing for clonal trajectory inference will be done to determine the associated single cell molecular features contributing to iPDAC and identify novel targets for future intervention. Table 1. Cohort (Total: N=288) A: core HRD (BRCA1/2/PALB2) B: non-core HRD (ATM, BARD1, BLM, CHEK2, RAD50, RAD51C, RTEL1, MUTYH) C: others without HR-gene alterations Number (%) 48 (16.6) 19 (6.5) 221 (76) Median overall survival (95% confidence Interval) 33 months (3.6-64) 16 (11- not reached) 16 (14-18) Tumor Mutation Burden (TMB) 4.4 3.5 3.9 Genomic Instability Score (GIS, HRD score) 26 12 13 Gene Ongology term, enrichment score, adjusted p-value Adaptive immune response, GO:0002250, 0.49, 1.69e-10 Not included Reference to cohort A Humoral immune response, GO:0006959, 0.58, 1.67e-9 T cell activation, GO:0042110, 0.44, 2.75e-8 Neutrophil chemotaxis, GO:0030593, 0.73, 4.3e-10 Citation Format: Wungki Park, Catherine O'Connor, Shigeaki Umeda, Roshan Sharma, Yingjie Zhu, Elias-Ramzey Karnoub, Anna Varghese, Kevin C. Soares, Alejandro Jimemez, Asli Yavas, Kenneth H. Yu, Balachandran P. Vinod, Joanne F. Chou, Danny N. Khalil, Kelsen David, Hulya Sahin Ozkan, Olca Basturk, Marinela Capanu, Tal Nawy, Michael F. Berger, Ghassan K. Abou-Alfa, Jorge S. Reis-Filho, Ronan Chaligne, Nadeem Riaz, Dana Pe'er, Christine Iacobuzio-Donahue, Eileen M. O'Reilly. Molecular profiles and single cell analysis identify immunogenic pancreatic ductal adenocarcinoma (iPDAC) [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 6421.

Mechanisms behind the evolution of normal pancreas tissue into pancreatic ductal adenocarcinoma (PDAC) are still poorly understood. More thorough characterization of mutational processes and development of clones is possible with single-cell DNA sequencing (scDNA-seq) of normal pancreas tissue. We developed a custom panel with 596 amplicons targeting over 200 genes known to be important in PDAC for use with Mission Bio’s Tapestri platform. We have recently optimized this method with nuclei which have been extracted from thirty frozen normal pancreas tissues, each from a different patient. Of these tissues, twenty-five were derived from rapid autopsies of patients with brain tumors to minimize the possibility of tumor cells being present in the pancreas. Normal pancreas tissue was verified by hematoxylin and eosin staining. Nuclei were extracted using the S2 Genomics Singulator 100 and counted with DAPI using the Countess 3 FL to ensure the concentration was adequate and that the sample was clean without excessive debris before library preparation and sequencing. Bulk whole exome sequencing (WES) and digital droplet polymerase chain reaction (ddPCR) were performed on several of these sample to validate certain mutations seen in scDNA-seq. Patients of a variety of ages ranging from five to 74 and with various risk factors including smoking and diabetes were chosen to better understand the impact on clonal expansion and genetic patterns present in normal pancreas tissue. For each of the thirty samples, an average of 2464 good quality nuclei were sequenced with over 70 reads per cell per amplicon on average. Mutations that were present in high quantities of cells were confirmed with WES and ddPCR. We found that older patients and patients that either smoke or those with diabetes had not only an increased number of mutations, but each individual cell, on average, had a significantly higher mutation count. The associated clones were also much greater in size in the higher-risk patients’ tissues. Furthermore, there was an increase in heterogeneity in the form of mutually exclusive clusters of cells. These results highlight the effects of various risk factors on normal pancreas tissue and potentially describe novel mechanisms of tumorigenesis. Citation Format: Elias-Ramzey R. Karnoub, Haochen Zhang, Shigeaki Umeda, Ignas Masilionis, Ronan Chaligné, Christine Iacobuzio-Donahue. Genetic characterization of normal pancreas tissue using single-cell technology [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 1517.

Understanding the rewired metabolism of organ-specific metastasis in breast cancer is an under-appreciated problem, with implications for the treatment and prevention of metastatic disease. Here, we used a systems biology approach and the MDA-MB 231 model to compare metabolic fluxes used by parental breast cancer cells and their brain- and lung-homing derivatives. We combined metabolomic profiling, flux measurements, spatial tissue mimetic systems, and mathematical modeling to dissect the cells’ metabolic rewiring, and identified changes specific for lung metastatic selection. We validated our results in other cell lines as well as patient data from project GENIE and the MBCP. Our results produced five biological insights: First, levels of mRNA and metabolic intermediates may anticorrelate with flux. Second, different lineages evolved from the same line can have distinct heritable metabolic fluxes. Metastatic lineages in our model display higher glycolytic flux and bioenergetics than parental cells, with lung-homing cells exhibiting by far the greatest glucose uptake and lactate production. Importantly, this occurs despite low levels of glycolytic intermediates in lung-homing cells. Third, this apparent paradox can be reconciled if feedback inhibition of the glycolysis pathway is prevented, a finding we modeled with flux-balance analysis and confirmed by 13C glucose tracing and measuring glycolytic enzymatic activities directly. Fourth, this distinct metabolic behavior in lung-homing cells is maintained by a high ratio of lactate dehydrogenase (LDH) to pyruvate dehydrogenase (PDH) gene expression, which also correlates with lung metastases in patients with breast cancer. Feature classification models trained on clinical characteristics alone were unable to predict tropism; however, the LDH/PDH ratio was a significant predictor for lung but not brain metastases, independent of other transcriptomic signatures, suggesting that this feature is a potential biomarker for lung metastasis. Fifth, this metabolic effect did not increase cellular growth rate, suggesting that lactate secretion may itself be a trait under selection in breast cancer lung metastasis. Follow up experiments and game theory-based models in a spatially structured tissue-mimetic system showed that lung-homing cells grow more favorably than brain-homing cells in nutrient-deprived gradients, demonstrating how divergent metabolisms of the lineages could lead to selection in different environments. Notably, lung metastases in a mouse model of pancreatic cancer had higher lactate production than other metastases, suggesting that this metabolic trait could be important for other cancer types. Together, our in vitro, in silico, and clinical data analyses highlight that metabolism—currency of all physiological processes—plays an essential role in the connection from gene to phenotype in metastatic disease. Citation Format: Deepti Mathur, Chen Liao, Wendy Lin, Alessandro La Ferlita, Salvatore Alaimo, Alfredo Ferro, Yi Zhong, Christine Iacobuzio-Donahue, Joao Xavier. The ratio of key metabolic transcripts is a predictive biomarker of breast cancer metastasis to the lung. [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 4254.

Objective: The osteosarcoma genome is characterized by high levels of genomic instability, however whether there is pervasive ongoing genomic instability, or instability introduced by an early catastrophic event, is still unsettled. Methods: We performed 30-80x whole genome sequencing (WGS) of 37 tumor samples from 8 patients with relapsed or refractory osteosarcoma. Each patient had at least one sample from a primary site and one sample from a metastatic or relapse site. A set of high confidence single nucleotide variants (SNV), copy number alterations (CNA), structural variations (SV) were called for each sample using our pediatric expanded genomics pipeline and an analysis focused on markers of genomic instability was performed using a custom pipeline of computational tools. Results: Of the 8 patients in our cohort, 4 had localized disease at diagnosis (OSCE4, OSCE5, OSCE6, OSCE9) and 4 had metastatic disease at diagnosis (OSCE1, OSCE2, OSCE3, OSCE10). There were 17 samples from primary sites, 7 pretreatment biopsies, 10 on therapy primary resections, 20 metastatic sites, 15 of which were from lung metastases. We have previously reported on the clonal evolution regarding SNVs and CNAs within this cohort. TP53 structural variants involving intron 1/2 were seen in 6/8 patients (OSCE2, OSCE3, OSCE4, OSCE6, OSCE9, OSCE10). No new structural variants in consensus driver genes emerged in metastatic or relapse samples. Comparing the earliest sample to most recent sample in each patient, only OSCE1, OSCE9, and OSCE10 demonstrated an increase of ≥100 structural variants at the final timepoint. In OSCE2, OSCE5, and OSCE6, there were less structural variants identified at the final timepoint when compared to the earliest timepoint. Homologous recombination deficiency (HRD) scores were calculated for each sample. Only 4/8 patients (OSCE3, OSCE4, OSCE9, OSCE10) had an HRD score in the most recently acquired sample higher than the score from the primary site. Regions of hypermutation consistent with kataegis were identified for each sample, with the number of kataegis events remaining unchanged or decreasing in some instances. Kataegis events co-localized with rearrangement events a majority of the time (range 50-100%, Avg= 72.6%). Complex rearrangements such as chromothripsis and chromoplexy were assesed. In 6 patients there were > 9 chromosomal arms involved in complex rearrangements that were shared between primary sites and metastatic/recurrent sites, while ≤ 4 chromosomal arms were involved with new complex rearrangements unique to the metastatic sites. Conclusion: The patterns observed in our cohort reveal that osteosarcoma is relatively stable from diagnosis through subsequent relapses, supporting the model that an early catastrophic event accounts for the genomic instability observed in osteosarcoma. Citation Format: Michael David Kinnaman, Simone Zaccaria, Alvin Makohon-Moore, Gunes Gundem, Juan E. Arango Ossa, Filemon S. Dela Cruz, Paul A. Meyers, Meera Hameed, William D. Tap, Julia Lynne Glade Bender, Elli Papaemmanuil, Andrew Kung, Christine Iacobuzio Donahue. Assessing patterns of genomic instability in recurrent osteosarcoma. [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 3556.

Purpose: Characterizing germline and somatic ATM variants (gATMm, sATMm) zygosity and their contribution to homologous recombination deficiency (HRD) is important for therapeutic strategy in pancreatic ductal adenocarcinoma (PDAC). Experimental Design: Clinico-genomic data for patients with PDAC and other cancers with ATM variants were abstracted. Genomic instability scores (GIS) were derived from ATM-mutant cancers and overall survival (OS) was evaluated. Results: Forty-six patients had PDAC and pathogenic ATM variants including 24 (52%) stage III/IV: gATMm (N = 24), and sATMm (N = 22). Twenty-seven (59%) had biallelic, 15 (33%) monoallelic, and 4 indeterminate (8%) variants. Median OS for advanced-stage cohort at diagnosis (N = 24) was 19.7 months [95% confidence interval (CI): 12.3–not reached (NR)], 27.1 months (95% CI: 22.7–NR) for gATMm (n = 11), and 12.3 months for sATMm (n = 13; 95% CI: 11.9–NR; P = 0.025). GIS was computed for 33 patients with PDAC and compared with other ATM-mutant cancers enriched for HRD. The median was lower (median, 11; range, 2–29) relative to breast (18, 3–55) or ovarian (25, 3–56) ATM-mutant cancers (P < 0.001 and P = 0.003, respectively). Interestingly, biallelic pathogenic ATM variants were mutually exclusive with TP53. Other canonical driver gene (KRAS, CDKN2A, SMAD4) variants were less frequent in ATM-mutant PDAC. Conclusions: ATM variants in PDAC represent a distinct biologic group and appear to have favorable OS. Nonetheless, pathogenic ATM variants do not confer an HRD signature in PDAC and ATM should be considered as a non-core HR gene in this disease.

Despite insights gained by bulk DNA sequencing of cancer it remains challenging to resolve the admixture of normal and tumor cells, and/or of distinct tumor subclones; high throughput single-cell DNA sequencing circumvents these and brings cancer genomic studies to higher resolution. However, its application has been limited to liquid tumors or a small batch of solid tumors, mainly because of the lack of a scalable workflow to process solid tumor samples. Here we optimized a highly automated nuclei extraction workflow that achieved fast and reliable targeted single-nucleus DNA library preparation of 38 samples from 16 pancreatic adenocarcinoma (PDAC) patients, with an average library yield per sample of 2867 single nuclei. We demonstrate that this workflow not only performs well using low cellularity or low tumor purity samples but reveals novel genomic evolution patterns of PDAC as well.

Purpose of study: Despite insights gained by bulk DNA sequencing of cancer it remains challenging to resolve “mixed signals”, i.e. the admixture of normal and tumor cells, and/or of distinct tumor subclones. Bulk sequencing of pancreatic ductal adenocarcinoma (PDAC) has been particularly problematic due to the high stromal content and resulting low tumor cellularity. Strategies to account for this have included laser capture microdissection yet this is a laborious process not amenable to high-throughput pipelines. We sought to develop and apply a high-throughput, high-depth, targeted single-cell DNA sequencing (scDNA-seq) method to account for these issues, including the ability to extract high quality genomic information from low purity and archival samples. Experimental procedures: Bulk whole exome sequencing (WES) was performed on 29 biologically distinct samples. For single cell sequencing, we developed a custom panel containing 186 amplicons covering 93 genes that represent the most common germline and somatic targets reported in PDAC. Based on a commercially available system that enables automatic enzymatic and mechanical tissue disruption with integrated fluidic processes, we optimized a nuclei extraction workflow from frozen tissues that is highly compatible with downstream microdroplet-based single-cell encapsulation and library preparation. With it we generated scDNA-seq data from archival tissues of 15 PDAC patients at varying stages of the disease. Results were compared to that found in matched bulk sequencing data. Summary of new, unpublished data and conclusions: 42 samples were analyzed by single cell sequencing. Our nuclei extraction workflow generated on average 2867 single cell libraries per sample at >80X read depth. The single-cell results aligned well with matched bulk data in terms of the detection of key genetic variants and their variant allele frequency (VAF). We also identified additional driver variants not seen by WES, some with direct clinical evidence. Benefits of this workflow over preexisting methods are its speed of sample preparation, efficiency of sample use (particularly for small samples), flexibility by allowing for storage of excess extracted nuclei, and economy of scale. Together, these features support preparation of large numbers of cancer samples in a relatively short period of time. Citation Format: Haochen Zhang, Elias-Ramzey Karnoub, Ronan Chaligné, Ignas Masilionis, Alvin Makohon-Moore, Jungeui Hong, Christine Iacobuzio-Donahue. Optimization of high-throughput, high-depth, targeted single-cell DNA sequencing to pancreatic ductal adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 59.

Metastatic pancreatic ductal adenocarcinoma (PDAC) is one of the leading causes of cancer-related deaths with very few treatment options and low-success rates. Generally speaking metastatic PDAC remains incurable. One reason behind PDAC morbidity and mortality is intratumor heterogeneity which allows metastatic dispersion and treatment resistance. We hypothesize that given multiple selective bottlenecks during metastatic progression, only a set of non-random gene programs are required for tumor cells to metastasize to different organs. To identify gene programs that become selected during PDAC metastatic progression we collected multiple (>20) metastatic tissue samples from different local and distant organs, from two clinically non-redundant human rapid-autopsies as part of the Human Tumor Atlas Network. We generated single-nuclei RNA-seq and Multiplexed Ion Beam Imaging data from these samples. Using trajectory analysis we inferred gene program dynamics between primary and metastatic samples and found an epithelial-to-mesenchymal-to-epithelial axis general to the metastases, suggesting that epithelial-mesenchymal plasticity is needed for cells to colonize other tissues. However, different organs have vastly different cell type compositions and may represent significantly different evolutionary bottlenecks. We employed archetype analysis as a tool to distinguish optimized phenotypes that may be shared or unique across colonized tissues. Archetype analysis revealed multiple gene programs, some of which are specific to a particular tissue and others ubiquitous. An epithelial-to-mesenchymal gene program was found to be shared across all samples at varying proportions, together with an extracellular matrix deposition/interaction program. Other gene programs identified include angiogenesis, hypoxia, cell cycle, immune interaction, lipid metabolism, autophagy/stress response, and cell migration. Some of these programs are present in various different metastases while others are unique to a specific site (e.g. Lipid metabolism in peritoneal metastasis). Together these programs shed light into organ tropism, metastatic modes of spread, adaptation to local tumor microenvironments, and cell-cell interactions with stromal cells. Further validation of these optimized phenotypes and integration of their spatial context will provide a deeper molecular understanding of metastatic PDAC and provide a source for data-driven therapeutic targets. [A. J-S. and Y.X contributed equally to this work.] Citation Format: Alejandro Jiménez-Sánchez, Yubin Xie, Roshan Sharma, Tin Yi Chu, Vincent Liu, Wungki Park, Akimasa Hayashi, Shigeaki Umeda, Linas Mazutis, Tal Nawy, Christine Iacobuzio-Donahue, Dana Pe’er. Optimal tumor metastatic gene programs in pancreatic cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 279.

Sonic Hedgehog (Shh) signaling is deregulated in pancreatic cancer and can drive tumor onset and progression. Previous attempts to block Shh signaling used Smoothened (Smo) inhibitors, which target canonical Shh signaling. These approaches met with limited success, due to development of resistance, and contributions from non-canonical, Smo-independent signaling pathways that operate within tumor epithelial cells. Here, we show that Hedgehog acyltransferase (Hhat), the enzyme responsible for palmitoylation of Shh, is a novel target for inhibition of Shh signaling in human and mouse pancreatic cancer cells and tumors. TDI-003410, a small molecule inhibitor of Hhat recently developed by our group, reduced proliferation of AsPC1 cells, a human pancreatic cancer cell line, in vitroand in subcutaneous xenografts in mice in vivo. The mechanism is via induction of a G2/M cell cycle arrest leading to apoptosis. We next used cell lines isolated from tumors formed in KPC (K-RasG12D/p53R172H) mice, a genetically engineered mouse model of pancreatic cancer.TDI-003410 inhibited the growth of KPC cell linesand also reduced Gli1 levelsin vitro. Neither LDE225, a Smo inhibitor, nor SAG, a Smo activator, had any effect on KPC cell proliferation or Gli1 levels in vitro. In orthotopic xenografts using KPC cells implanted into the pancreas, TDI-3410 treatment significantly reducedin vivotumor burden. No significant changes in CD31 or Trichrome (collagen) stainingwith TDI-3410 were detected in KPC orthotopic tumor tissue. However, Gli-1 levels in tumor tissue from TDI-3410 treated mice were significantly reduced compared to the vehicle controls. These findings provide proof of concept for the potential therapeutic efficacy of Hhat inhibition in pancreatic cancer. The concept of using an Hhat inhibitor is unique: Hhat is a novel target that hits upstream, directly at hedgehog ligands. This approach can inhibit both canonical and non-canonical (Smo-independent) as well as autocrine and paracrine Shh signaling. Citation Format: Atul Khire, Yi Zhong, Kalpana Rajanala, Christine Iacobuzio-Donahue, Marilyn D. Resh. A novel hedgehog signaling inhibitor for targeting pancreatic ductal adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3083.

Pancreatic ductal adenocarcinoma (PDAC), either sporadic or familial, has a dismal prognosis and finding candidate genes involved in development of the cancer is crucial for the patient care. First, we identified two patients with germline alterations in or adjacent to CDH10 by chromosome studies and sequencing analyses in 41 familial pancreatic cancer (FPC) cases. One patient had a balanced translocation between chromosome 5 and 20. The breakpoint on chromosome band 5p14.2 was ~810 Kb upstream of CDH10, while that on chromosome arm 20p was in the pericentromeric region which might result in inactivation of one copy of the gene leading to reduced expression of CDH10. This interpretation was supported by loss of heterozygosity (LOH) seen in this region as determined by short tandem repeat analyses. Another patient had a single nucleotide variant in exon 12 (p.Arg688Gln) of CDH10. This amino acid was conserved among vertebrates and the mutation was predicted to have a pathogenic effect on the protein by several prediction algorithms. Next, we analyzed LOH status in the CDH10 region in sporadic PDAC and at least 24% of tumors had evidence of LOH. Immunohistochemical stains with CDH10 antibody showed a different staining pattern between normal pancreatic ducts and PDAC. Taken together, our data supports the notion that CDH10 is involved in sporadic pancreatic carcinogenesis, and might have a role in rare cases of FPC. Further functional studies are needed to elucidate the tumor suppressive role of CDH10 in pancreatic carcinogenesis.

Novel therapeutic agents that are safe and effective are needed for the treatment of pancreatic, ovarian, lung adenocarcinomas and mesotheliomas. Mesothelin is a glycosyl-phosphatidyl inositol (GPI)-linked membrane protein of 40 kDa over-expressed in all pancreatic adenocarcinoma and mesothelioma, in70% of ovarian adenocarcinoma, and in non-small cell lung and colorectal cancers. The biological functions of mesothelin are not known, although it appears to be involved in cell adhesion via its interaction with MUC16. We have recently developed MORAb-009, a mouse-human chimeric IgG1kappa monoclonal antibody with an affinity of 1.5 nM for human mesothelin. Here we provide evidence that MORAb-009 prevents adhesion of mesothelin-bearing tumor cells to MUC16 positive cells and can elicit cell-mediated cytotoxicity on mesothelin-bearing tumor cells. Treatment that included MORAb-009 in combination with chemotherapy led to a marked reduction in tumor growth of mesothelin-expressing tumors in nude mice compared to chemotherapy or MORAb-009 treatment alone. No adverse effects of MORAb-009 were noted during toxicology studies conducted in non-human primates. The preclinical data obtained from our studies warrants pursuing clinical testing of MORAb-009. We have in fact initiated a Phase I clinical study enrolling patients with mesothelin-positive pancreatic, mesothelioma, non-small cell lung and ovarian cancers.

There are many types of pancreatic neoplasms. Pathologic examination, which includes both routine (e.g., hematoxylin-and-eosin staining) and ancillary (e.g., immunohistochemistry and in situ hybridization) techniques, is essential in correctly typing a pancreatic neoplasm. This chapter focuses on the use of immunohistochemistry and in situ hybridization in the differentiation of pancreatic neoplasms. The materials and methods of these two techniques are described in detail.

Complementary DNA (cDNA) microarrays are a powerful tool for genomic analysis, but have noise components that make inferences regarding gene expression inefficient and potentially misleading. Background fluorescence, whether attributable to non-specific binding or other sources, is an important component of noise. The decision to subtract background fluorescence from foreground signal has been controversial, with no clear criteria for determining circumstances that may favor, or disfavor, background correction. While it is generally accepted that subtracting background reduces bias but ncreases variance in the estimates of the ratios of interest,no formal analysis of the bias-variance trade off of background subtraction has been undertaken. In this paper, we use simulation to systematically examine the bias-variance trade off under a variety of possible experimental conditions. Our simulation is based on data obtained from a self versus self microarray experiment and is free of distributional assumptions. Our results identify factors that are important for determining whether to background subtract,including the correlation of foreground to background signal. Using these results we develop recommendations for diagnostic visualizations that can help decisions about background subtraction.

Objective: Pancreatic adenocarcinoma is a deadly disease with an overall 5-year patient survival of less than 5%. This dismal prognosis of pancreatic cancer is largely due to the advanced stage of the disease at presentation. If pancreatic cancer could be diagnosed more readily and accurately using serum markers, patient survival could theoretically be improved by enabling more patients to avail of surgical resection. One candidate tumor marker recently identified by global gene expression analysis of pancreatic cancer is the secreted glycophosphoprotein osteopontin (OPN). In this study, we evaluate OPN as a serum marker of pancreatic adenocarcinoma. Methods: In situ hybridization for OPN was performed on a pancreatic adenocarcinoma tissue microarray. Serum OPN levels were determined in preoperative sera from 50 patients with pancreatic cancer and 22 healthy control individuals by competitive ELISA. Results: In situ hybridization for OPN performed on a tissue microarray revealed strong OPN mRNA signal in tumor-infiltrating macrophages in 8 of 14 pancreatic adenocarcinomas. In contrast, OPN expression was not seen in the pancreatic cancer cells themselves, nor was it seen in normal pancreatic tissue or in the macrophages distant from the infiltrating cancer. Serum OPN levels, as measured by ELISA, were elevated in the sera of 50 patients with resectable pancreatic adenocarcinoma compared to 22 healthy control individuals (mean ± SD for OPN was 482 ± 170 ng/ml and 204 ± 65 ng/ml, respectively; P < 0.001). Using a cutoff level of 2 SD above the mean for healthy individuals, elevated OPN had sensitivity of 80% and specificity of 97% for pancreatic cancer. In contrast, only 62% of these patients with resectable pancreatic cancer had elevated CA19-9. Conclusion: Serum OPN may have utility as a diagnostic marker in patients with pancreatic cancer.

Colchicine effect has been described recently in gastrointestinal biopsies, where it can result in accumulation of metaphase mitoses and epithelial disorganization. We describe the case of a colonic hyperplastic polyp with colchicine effect from a 52-year-old woman who was receiving colchicine for primary biliary cirrhosis. Biopsy of the polyp revealed prominent metaphase mitoses and focal loss of nuclear polarity in the surface epithelium, features that mimicked a serrated adenoma. Distinguishing between hyperplastic polyp and serrated adenoma is important because of the different management implications and the increased potential for neoplastic progression in the latter.