Subtypes Of Pancreatic Adenocarcinoma Research Articles

Discovering ferroptosis-associated tumor antigens and ferroptosis subtypes in pancreatic adenocarcinoma to facilitate mRNA vaccine development

Pancreatic adenocarcinoma (PAAD) is an aggressive, heterogeneous malignancy. We studied the potential of ferroptosis-related tumor vaccines for PAAD treatment. Ferroptosis-related genes, gene expression profiles, and clinical information were extracted from the FerrDB, UCSC Xena, and International Cancer Genome Consortium databases. Differential expression levels and prognostic indices were calculated, genetic alterations and correlations with immune-infiltrating cells were explored, and consensus clustering analysis was performed to identify ferroptosis subtypes and gene modules. Immune enrichment scores were calculated using gene set enrichment analysis, and gene modules were screened using weighted gene co-expression network analysis. The ferroptosis subtype distribution was visualized using graph learning-based dimensionality reduction analysis of the Monocle package with a Gaussian distribution. We identified four ferroptosis-related tumor antigens, AGPS, KDM5A, NRAS, and OSBPL9, which were associated with pancreatic cancer prognosis and antigen-presenting cell infiltration. We determined three minor ferroptosis subtypes, with different clinical prognosis and tumor immune status. Of the subtypes, FS3 may be more suitable for mRNA therapy. We constructed a PAAD ferroptosis landscape to identify the ferroptosis status of patients and predict their prognosis. Finally, we found that the eigengene of the green module was an independent prognostic factor, with a significantly better prognosis in the high-score group than in the low-score group. In conclusion, we identified four ferroptosis-related genes as targets for mRNA vaccines and three ferroptosis subtypes, providing a theoretical basis for the anti-PAAD mRNA vaccine and defining suitable patients for vaccination.

A prospective prognostic signature for pancreatic adenocarcinoma based on ubiquitination-related mRNA-lncRNA with experimental validation in vitro and vivo

Ubiquitination-related genes (URGs) exerted a crucial part in a variety of human disease disorders; however, their association with pancreatic adenocarcinoma (PAAD) had yet to be clearly described. We aimed to comprehensively characterize the contributions of URGs in PAAD through in silico analysis and experimental validation, and then identified a robust mRNA-lncRNA-based molecular prognostic panel for patients with PAAD using bulk RNA-sequencing and single-cell RNA-sequencing data. Initially, we collected the multi-omics data from TCGA platform to depict a comprehensive landscape of URGs in pan-cancer. Furthermore, we were accurate to PAAD for in-depth analysis. Significant differences of the activation of ubiquitination pathways and the expression of URGs were detected between normal and malignant cells. Unsupervised hierarchical clustering determined two PAAD subtypes with distinct clinical outcomes, ubiquitination pathway activities, immune microenvironment, and functional annotation characteristics. The expression profiles of ubiquitination-associated mRNAs and lncRNAs in the training and validation datasets were utilized to develop and verify a novel ubiquitination-related mRNA-lncRNA prognostic panel, which had a satisfied prediction efficiency. Our ubiquitination-associated model could function as an effective prognostic index and outperformed four other recognized panels in evaluating PAAD patients’ survival status. Tumor immune microenvironment, mutation burden, and chemotherapy response were intensively explored to demonstrate the underlying mechanism of prognostic difference according to our panel. Our findings also revealed that FTI-277, a farnesyltransferase inhibitor, had a better curative effect in high-risk patients, while MK-2206, an Akt allosteric inhibitor, had a superior therapeutic effect in low-risk patients. The real-time PCR results uncovered the RNA expression of AC005062.1 in all the three PAAD cell lines was elevated several thousandfold. In conclusion, our URGs-based classification panel could be triumphantly served as a prediction tool for survival evaluation in patients with PAAD, and the genes in this panel could be developed as a potential target in PAAD therapy.

Pacpaint: a histology-based deep learning model uncovers the extensive intratumor molecular heterogeneity of pancreatic adenocarcinoma

Two tumor (Classical/Basal) and stroma (Inactive/active) subtypes of Pancreatic adenocarcinoma (PDAC) with prognostic and theragnostic implications have been described. These molecular subtypes were defined by RNAseq, a costly technique sensitive to sample quality and cellularity, not used in routine practice. To allow rapid PDAC molecular subtyping and study PDAC heterogeneity, we develop PACpAInt, a multi-step deep learning model. PACpAInt is trained on a multicentric cohort (n = 202) and validated on 4 independent cohorts including biopsies (surgical cohorts n = 148; 97; 126 / biopsy cohort n = 25), all with transcriptomic data (n = 598) to predict tumor tissue, tumor cells from stroma, and their transcriptomic molecular subtypes, either at the whole slide or tile level (112 µm squares). PACpAInt correctly predicts tumor subtypes at the whole slide level on surgical and biopsies specimens and independently predicts survival. PACpAInt highlights the presence of a minor aggressive Basal contingent that negatively impacts survival in 39% of RNA-defined classical cases. Tile-level analysis ( > 6 millions) redefines PDAC microheterogeneity showing codependencies in the distribution of tumor and stroma subtypes, and demonstrates that, in addition to the Classical and Basal tumors, there are Hybrid tumors that combine the latter subtypes, and Intermediate tumors that may represent a transition state during PDAC evolution.

Classification and Prognosis Analysis of Pancreatic Cancer Based on DNA Methylation Profile and Clinical Information.

Pancreatic adenocarcinoma (PAAD) has a poor prognosis with high individual variation in the treatment response among patients; however, there is no standard molecular typing method for PAAD prognosis in clinical practice. We analyzed DNA methylation data from The Cancer Genome Atlas database, which identified 1235 differentially methylated DNA genes between PAAD and adjacent tissue samples. Among these, 78 methylation markers independently affecting PAAD prognosis were identified after adjusting for significant clinical factors. Based on these genes, two subtypes of PAAD were identified through consistent clustering. Fourteen specifically methylated genes were further identified to be associated with survival. Further analyses of the transcriptome data identified 301 differentially expressed cancer driver genes between the two PAAD subtypes and the degree of immune cell infiltration differed significantly between the subtypes. The 14 specific genes characterizing the unique methylation patterns of the subtypes were used to construct a Bayesian network-based prognostic prediction model for typing that showed good predictive value (area under the curve value of 0.937). This study provides new insight into the heterogeneity of pancreatic tumors from an epigenetic perspective, offering new strategies and targets for personalized treatment plan evaluation and precision medicine for patients with PAAD.

Mitophagy-mediated molecular subtypes depict the hallmarks of the tumour metabolism and guide precision chemotherapy in pancreatic adenocarcinoma.

Background: Mitophagy is closely related to cancer initiation and progression. However, heterogeneity with reference to mitophagy remains unexplored in pancreatic adenocarcinoma (PAAD). Materials and methods: We used Reactome database to download the mitophagy-related, glycolysis-related and cholesterol biosynthesis-related signaling pathways. Unsupervised clustering using the “ConsensusClusterPlus” R package was performed to identify molecular subtypes related to mitophagy and metabolism. Prognosis-related mitophagy regulators were identified by univariate Cox regression analysis. Receiver operating characteristics (ROC) and Kaplan-Meier (K-M) survival analyses were used to assess the diagnostic and prognostic role of the hub genes and prognosis risk model. Weighted gene co-expression network analysis (WGCNA) was utilized for screening the mitophagy subtype-related hub genes. Metascape was utilized to carry out functional enrichment analysis. The “glmnet” R package was utilised for LASSO, and the “e1071” R package was utilised for SVM. Chemotherapeutic drug sensitivity was estimated using the R package “pRRophetic” and Genomics of Drug Sensitivity in Cancer (GDSC) database. The nomogram was established by the “rms” R package. Results: Three distinct mitophagy subtypes (low, high and intermediate) of PAAD were identified based on the landscape of mitophagy regulators. The high mitophagy subtype had the worst prognosis, highest mRNA expression-based stemness index scores and most hypoxic environment compared to the other subtypes. Additionally, glycolysis and cholesterol biosynthesis were significantly elevated. Three mitophagy subtype-specific gene signatures (CAST, CCDC6, and ERLIN1) were extracted using WGCNA and machine learning. Moreover, PAAD tumours were insensitive to Erlotinib, Sunitinib and Imatinib in the high mitophagy subtype and high CAST, CCDC6, and ERLIN1 expressed subtypes. Furthermore, CAST, CCDC6, and ERLIN1 affected immune cell infiltration (M1 and CD8Tcm), resulting in the altered prognosis of patients with PAAD. A nomogram was constructed to screen patients with the low mitophagy subtype, which showed a higher sensitivity to chemotherapeutic agents. Conclusion: Based on various bioinformatics tools and databases, the PAAD heterogeneity regarding mitophagy was systematically examined. Three different PAAD subtypes having different outcomes, metabolism patterns and chemosensitivity were observed. Moreover, three novel biomarkers that are closely associated with mitophagy and have the potential to guide individualised treatment regimens in PAAD were obtained.

Abstract 472: PACpAInt: A deep learning approach to identify molecular subtypes of pancreatic adenocarcinoma on histology slides

Abstract Introduction: Pancreatic adenocarcinoma (PAC) is highly heterogeneous, resulting in overall ineffectiveness of most anti-tumor treatments. Two tumor subtypes (Classical and Basal) and two stromal subtypes (“active” and “inactive”) have been described. The Basal and the active stroma have worse prognosis. These subtypes could also be predictive of the response to different chemotherapies. To date, molecular subtype classification or phenotype quantification can only be defined by RNAseq, a complex technique sensitive to the quantity and quality of samples, requiring a timescale limiting its routine application. We propose a deep learning approach (PACpAInt) to predict molecular subtypes in PAC on routine histological slides. Patients and Methods: 424 digitalized HES slides of 202 resected PAC from 3 centers with clinical and transcriptomic data were used as training cohort. 3 validation cohorts were used (i) 250 resected PAC from a 4th center including 97 cases with an exact HES/RNAseq spatial match and all tumor slides digitalized (n = 891); (ii) 126 resected PAC from the TCGA (HES + RNAseq); (iii) 25 liver biopsies from metastatic PAC (HES + RNAseq). A multi-step deep learning model was developed to recognize tumor tissue, tumor from stroma cells, and then predicts their transcriptomic molecular subtypes, either at the level of an entire slide, or at the tile level (squares of 112 μm) allowing to study intratumor heterogeneity. Results: PACpAInt correctly predicted the tumor subtype at the whole slide level (AUC = 0.86 and 0.81 in 2 validation cohorts) and improved for samples with unambiguous molecular subtype (AUC = 0.91 and 0.88) confirming the limit of a binary approach. Similar results were obtained on liver biopsies (AUC = 0.85 and 0.92 on unambiguous cases). PACpAInt independently predicted progression-free and overall survival (PFS HR=1.37 [1.16 - 1.62] and OS HR=1.27 [1.08 - 1.49]). Analysis of all tumor slides from 77 Classical cases showed that 39% were heterogeneous with a Basal contingent. These cases had shorter PFS (15 vs. 47 months, p= 0.001) and OS (31 vs. 64 months, p= 5e-5).The analysis of intratumoral heterogeneity using PACpAInt predicted the molecular subtype of tumor and stroma cells of each tile within a slide (> 6 million tiles analyzed). 61% of cases had a main subtype either Classical (42%) or Basal (19%). 39% of the cases were ambiguous could be considered either hybrid (10%) with coexistence of Basal and Classical cells, or intermediate (29%) corresponding to homogeneous tumors but of intermediate differentiation. This classification had a strong prognostic impact (OS: 45.1 vs 33.0 vs 23.4 vs 13.6 months, resp. Classical, intermediate, hybrid, Basal; p <e-12). Conclusion: This study provides the first PAC subtyping tool widely usable in clinical practice, opening the possibility of molecular classification useful for routine care and clinical trials. Citation Format: Charlie Saillard, Flore Delecourt, Benoit Schmauch, Olivier Moindrot, Magali Svrcek, Armelle Bardier-Dupas, Jean Francois Emile, Mira Ayadi, Vinciane Rebours, Louis De Mestier, Pascal Hammel, Cindy Neuzillet, Jean Baptiste Bachet, Juan Iovanna, Nelson Dusetti, Yuna Blum, Magali Richard, Yasmina Kermezli, Valerie Paradis, Mikhail Zaslavskiy, Pierre Courtiol, Aurelie Kamoun, Remy Nicolle, Jerome Cros. PACpAInt: A deep learning approach to identify molecular subtypes of pancreatic adenocarcinoma on histology slides [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 472.

Pyroptosis Landscape and Subtypes in Pancreatic Adenocarcinoma: Prognostic Significance and Predictive of Therapeutic Response

Pyroptosis Landscape and Subtypes in Pancreatic Adenocarcinoma: Prognostic Significance and Predictive of Therapeutic Response

Abstract PO-068: Cholesterol auxotrophy promotes the expansion of centroacinar cells giving rise to the basal subtype of pancreatic adenocarcinoma

Abstract Gene expression analyses established at least two molecular subtypes of pancreatic adenocarcinoma (PDAC), the classical (or glandular), and the basal (or mesenchymal), each of which is associated with distinct prognoses and sensitivity to chemotherapy. It remains unclear, however, whether the basal carcinoma cells arise from a separate cell-of-origin, or are emerging from the pre-existing well-differentiated “classical” PDAC cells. To distinguish these alternatives, we conducted single-cell transcriptome analyses and virtual lineage tracing comparing cellular populations at pre-malignant stages in basal versus classical PDAC mouse models. We previously reported that chemical or genetic inhibition of the cholesterol biosynthetic pathway in KrasG12D; Trp53 (KPPC) mice predisposes to basal rather than glandular PDAC development because of the pancreas-specific increased sterol response element-binding protein 1 (SREBP1) activity and TGFβ signaling that induces cancer cell stemness and the EMT (PMID: 32976774). Pancreas-selective knockout of a conditional allele of cholesterol pathway gene, Nsdhl (NAD(P)-dependent steroid dehydrogenase-like), renders pancreatic epithelial cells cholesterol auxotrophs and drives basal PDAC in the majority of animals (KPPCN mice). At 5-6 weeks of age, grossly and microscopically tumor-free pancreatic tissues were selected for single-cell isolation and single-cell RNA sequencing (scRNA seq) using the 10X platform. After standard filtering and sample normalization procedures, downstream analyses included identification of relevant cell clusters using Seurat, lineage tracing algorithms, and in silico modeling of autocrine and paracrine signaling interactions between subsets of PDAC and non-malignant cells. Our key findings are as follows: 1) premalignant KPPCN pancreata exhibit a massive expansion of cancer-associated fibroblasts (CAFs) of predominantly inflammatory differentiation (iCAFs); 2) despite relatively fewer ADM and PanIN pre-malignant lesions in KPPCN compared to KPPC, scRNA seq identifies the significant expansion of epithelial cells with features of centroacinar and stem-like cells (increased expression of Aldh1a2, Nes, Sox9, Ly6a, Cxcl12, and Met); these centroacinar-like cells, while retaining epithelial identity (Epcam, Cdh1), also exhibit features of pluripotency by co-expression of Ins2 and other stem cell markers; 3) alignment with basal PDAC (KPPCN) and classical (KPPC) carcinoma cell populations strongly suggests the continuity of clonal evolution of the centroacinar-like cells towards the basal PDAC. While our genetic model does not recapitulate the multiple alternative pathways leading to basal PDAC development, cholesterol auxotrophy via SREBP1 may be a factor governing the expansion of undifferentiated precursors, which via interactions with cancer-promoting iCAFs, drive basal PDAC development. Citation Format: Michael Kotliar, Aizhan Surumbayeva, Linara Gabitova, Suraj Peri, Diana Restifo, Kathy Q. Cai, Artem Barski, Igor Astsaturov. Cholesterol auxotrophy promotes the expansion of centroacinar cells giving rise to the basal subtype of pancreatic adenocarcinoma [abstract]. In: Proceedings of the AACR Virtual Special Conference on Pancreatic Cancer; 2021 Sep 29-30. Philadelphia (PA): AACR; Cancer Res 2021;81(22 Suppl):Abstract nr PO-068.

Molecular subtypes of pancreatic adenocarcinoma stratified based on copy number variation profile.

e16232 Background: Pancreatic adenocarcinoma (PAAD) is one of the most lethal carcinomas all over the world, with an estimate of 60,430 new cases and 48,220 deaths in United States according to the cancer statistics of 2021. It is important and urgent to identify molecular subtypes for stratifying PAAD into different groups with respective genomic footprint, appropriate treatment and prognosis status. Methods: We profiled a comprehensive landscape of genomic alterations for 608 PAAD patients in a Chinese cohort, including somatic mutations, pathogenic germline variants and copy number variations (CNVs). 233 out of 608 PAAD had disease-free survival (DFS) information with at least 6-month follow-up. Focusing on this subset of PAAD, we explored prognostic values for several kinds of genomic alterations and finally identified four molecular subtypes based on CNV profile. Results: For point mutations in highly mutated genes ( KRAS, TP53, CDKN2A and SMAD4) or homologous recombination repair (HRR) genes ( ATM, ATR, BARD1, BLM, BRCA1/2, BRIP1, CDK12, CHEK1/2, NBN, PALB2, RAD50/ 51B/ 51C/ 51D/54L and MRE11A), we found no associations between them and prognosis of PAAD patients. Instead, PAAD could be stratified into four molecular subtypes based on CNV profile through unsupervised clustering and CNV score defined by principle component analysis (PCA). According to amplification and deletion pattern of genes in DNA repair and receptor tyrosine kinase related signaling pathways, we named these four subtypes as repair-deficient, proliferation-active, repair-proficient and repair-enhanced ones. Among them, repair-deficient PAAD had the best prognosis with median DFS of 410 days, repair-proficient and proliferation-active one had median DFS of 239 and 197 days, respectively, while repair-enhanced one had the worst prognosis with DFS of 48 days. Genomic footprint analysis showed that both of repair-deficient and proliferation-active subtypes of PAAD possessed higher copy number instability (CNI), while both of repair-proficient and repair-enhanced subtypes possessed higher tumor mutational burden (TMB), implying that the former two subtypes suited for DNA damage therapies (such as platinum-based chemotherapy and PARPi) and the latter two subtypes suited for immunotherapy. Conclusions: We identified four molecular subtypes for PAAD based on CNV profile and found their respective genomic footprint, suited treatment and prognosis status, pacing key steps to precision medicine in PAAD field.

Identification of Copy Number Variation-Driven Molecular Subtypes in Pancreatic Adenocarcinoma of Chinese Cohort

Pancreatic adenocarcinoma (PAAD) is one of the most lethal carcinomas all over the world. The current histopathological classifications for PAAD are of limited use to guide clinical decision-making, and there is an unmet need to identify new biomarkers for molecular subtyping. We profiled a comprehensive landscape of genomic alterations for 608 PAAD patients in a Chinese cohort, including somatic mutations, pathogenic germline variants and copy number variations (CNV). Our data provided no evidence of associations with prognosis based on the information of point mutations in either highly mutated genes (such as KRAS, TP53, CDKN2A and SMAD4) or homologous recombination repair genes. Instead, associated with worse prognosis were amplified genes involved in DNA repair and receptor tyrosine kinase related signaling pathways. Motivated by this observation, we categorized patients into four molecular subtypes (namely repair-deficient, proliferation-active, repair-proficient and repair-enhanced) that differed in prognosis. Together with the evidence from genomic footprint analysis, we suggested that repair-deficient and proliferation-active subtypes were better suited for DNA damage therapies, while immunotherapy was highly recommended for repair-proficient and repair-enhanced subtypes. Collectively, our findings represent a significant step in improving diagnosis and management for PAAD patients. Funding Statement: This work was supported by the National Natural Science Foundation of China (grant numbers 81470894, 81502695, 81672325, 81871906, 82073326) and the Shanghai Sailing Program (grant number 20YF1426900). Declaration of Interests: The authors declare no potential conflicts of interest. Ethics Approval Statement: The overall study protocol was approved by the Medical Ethical Committee of Ruijin Hospital and the research was conducted in accordance with relevant ethical guidelines.

Abstract B10: Transcriptome analysis of mouse PDA subtypes

Abstract Patients with Pancreatic Adenocarcinoma (PDA) often present with advanced stage disease including widespread metastasis and have dismal 5-year survival rates. The molecular mechanism promoting PDA progression and metastasis remain poorly understood. We have previously demonstrated that tumor cells undergo Epithelial-to-Mesenchymal Transition (EMT) in mouse models of PDA [Rhim et al., 2012]. EMT is a developmental process where cells loss epithelial characteristics and transdifferentiate into a mesenchymal-like state that is highly associated with increased invasion and metastasis. To better understand molecular mechanisms of PDA development and metastatic disease, we subjected tumors cells from a lineage labeled mouse model of PDA to RNA sequencing to identify global transcriptional changes. Interestingly, we discovered that there are at least two distinct subtypes of PDA based on transcriptome profiling. Comparison of gene expression profiles from mouse PDA subtypes to established subtypes from human PDA datasets [Collisson et al., 2011] revealed that mouse PDA is transcriptionally similar to the human disease. Differences in transcriptional profiling between PDA subtypes may dictate response to chemotherapeutics and metastatic competency. Citation Format: David Balli, Nicole Aiello, Robert Norgard, Jingyang Li, Amine Sahmoud, Ben Stanger. Transcriptome analysis of mouse PDA subtypes. [abstract]. In: Proceedings of the AACR Special Conference on Tumor Metastasis; 2015 Nov 30-Dec 3; Austin, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(7 Suppl):Abstract nr B10.

Candidate DNA repair susceptibility genes identified by exome sequencing in high-risk pancreatic cancer

The genetic basis underlying the majority of hereditary pancreatic adenocarcinoma (PC) is unknown. Since DNA repair genes are widely implicated in gastrointestinal malignancies, including PC, we hypothesized that there are novel DNA repair PC susceptibility genes. As germline DNA repair gene mutations may lead to PC subtypes with selective therapeutic responses, we also hypothesized that there is an overall survival (OS) difference in mutation carriers versus non-carriers. We therefore interrogated the germline exomes of 109 high-risk PC cases for rare protein-truncating variants (PTVs) in 513 putative DNA repair genes. We identified PTVs in 41 novel genes among 36 kindred. Additional genetic evidence for causality was obtained for 17 genes, with FAN1, NEK1 and RHNO1 emerging as the strongest candidates. An OS difference was observed for carriers versus non-carriers of PTVs with early stage (≤IIB) disease. This adverse survival trend in carriers with early stage disease was also observed in an independent series of 130 PC cases. We identified candidate DNA repair PC susceptibility genes and suggest that carriers of a germline PTV in a DNA repair gene with early stage disease have worse survival.

Identification of Molecular Subtypes in Pancreatic Adenocarcinoma with Predictive and Prognostic Importance

Identification of Molecular Subtypes in Pancreatic Adenocarcinoma with Predictive and Prognostic Importance

Efficacy of platinum chemotherapy agents in the adjuvant setting for adenosquamous carcinoma of the pancreas.

e15028 Background: Pancreatic adenosquamous carcinoma (PASC) is a rare morphological subtype of pancreatic adenocarcinoma. PASC accounts for only 1-4% of exocrine pancreatic cancers and carries a particularly poor prognosis. Due to the rarity of PASC, studies of therapies specifically targeting this histopathologic entity are exceedingly limited. Based on efficacy exhibited by platinum agents against squamous carcinoma of other body sites, addition of these agents to adjuvant regimens may benefit patients with PASC. This retrospective study was performed among the largest series of patients with PASC identified to date in order to determine whether addition of platinum agents improves survival. Methods: Records of all patients who underwent pancreatic resection at our institution from 1986-2012 were reviewed to identify those with PASC. Demographic, surgical, pathologic, adjuvant therapy, and survival data were collected. Patients were divided into non-platinum (NPG) and platinum (PG) groups based on whether or not they received a platinum agent as part of adjuvant therapy. Results: In total, 62 patients with PASC were identified among 5,627 cases (1.1%). Fourteen patients received a platinum agent in the adjuvant setting (PG), while 48 did not (NPG). These two groups were comparable in regard to median age (65 vs. 69 yrs, p=0.34), gender (36 vs. 46% female, p=0.50), performance status (78 vs. 79% ECOG 0, p=0.98), histologic grade (86 vs. 77% grade 3, p=0.49), positive resection margins (14 vs. 29%, p=0.26), lymph node involvement (71 vs. 79%, p=0.54), median tumor diameter (4.0 vs. 4.3 cm, p=0.64), and proportion receiving radiotherapy (57 vs. 42%, p=0.31). PG patients received a median of 5.5 cycles (IQR, 3.3-6.0) of platinum chemotherapy, with 10 patients (71%) receiving cisplatin-based regimens and 4 (29%) receiving oxaliplatin-based regimens. PG patients experienced significantly longer median survival (19.1 months, 95% CI 12.8-25.4) compared to NPG patients (9.8 months, 95% CI 7.3-12.4) (p=0.024). Conclusions: Addition of a platinum agent to adjuvant regimens for resected PASC may improve survival among these high risk patients, though collaborative prospective investigation is needed.

Abstract LB-24: Molecular subtypes of pancreatic adenocarcinoma with different biological characteristics and therapeutical responses

Abstract Pancreatic ductal adenocarcinoma (PDAC) is an invariably lethal disease. Due to its late clinical presentation, surgical cure is attempted in only a minority, and resected patients usually recur quickly with incurable, metastatic disease. These attributes may reflect the variable and often disappointing responses seen when deploying the standard treatment, gemicitabine alone or in combination with other chemotherapeutic agents in unselected PDAC populations. Studies in other solid tumors have shown that heterogeneity in therapeutic responses can be anticipated by molecular differences between tumors, and targeting drugs specific to tumor subtypes in which they are predicted to be selectively effective can indeed improve treatment. Seeking to extend this new paradigm of personalized medicine to PDAC, we performed an integrative analysis of transcriptional profiles of human primary PDAC tumors (n = 143) and cell lines (n = 35). We have defined 62 gene (PDAssigner) signature that classifies the human PDAC tumors into three subtypes (classical, QM-PDAC and exocrine-like tumors) and present evidence that two (classical and QM-PDAC) of these three are present in human and mouse PDAC cell lines. Interestingly, we found that PDAC subtype classification is an independent predictor of overall survival, and patients with classical PDAC subtype tumors have significantly better survival than those with QM-PDA tumors. In addition, the expression of GATA6 (a transcriptional factor involved in the embryonic pancreas development) and KRAS (mutated in majority of PDACs) are functionally associated with classical PDAC subtype relative to QM-PDAC subtype. Intriguingly, treatment of PDAC cell lines with gemcitabine or erlotinib shows significantly differential and opposing responses between classical and QM-PDAC subtypes. Overall, we describe here a broadly integrative approach to PDAC subtype discovery and analysis that identifies gene expression signature with prognostic significance in primary patient samples and couples them with biological information and subtype specific drug responses. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr LB-24. doi:10.1158/1538-7445.AM2011-LB-24

Identification of Molecular Subtypes in Pancreatic Adenocarcinoma with Predictive and Prognostic Importance

Identification of Molecular Subtypes in Pancreatic Adenocarcinoma with Predictive and Prognostic Importance