Cytidine deaminases APOBEC3C and APOBEC3D promote DNA replication stress resistance in pancreatic cancer cells.

Gemcitabine is a potent inhibitor of DNA replication and is a mainstay therapeutic for diverse cancers, particularly pancreatic ductal adenocarcinoma (PDAC). However, most tumors remain refractory to gemcitabine therapies. Here, to define the cancer cell response to gemcitabine, we performed genome-scale CRISPR-Cas9 chemical-genetic screens in PDAC cells and found selective loss of cell fitness upon disruption of the cytidine deaminases APOBEC3C and APOBEC3D. Following gemcitabine treatment, APOBEC3C and APOBEC3D promote DNA replication stress resistance and cell survival by deaminating cytidines in the nuclear genome to ensure DNA replication fork restart and repair in PDAC cells. We provide evidence that the chemical-genetic interaction between APOBEC3C or APOBEC3D and gemcitabine is absent in nontransformed cells but is recapitulated across different PDAC cell lines, in PDAC organoids and in PDAC xenografts. Thus, we uncover roles for APOBEC3C and APOBEC3D in DNA replication stress resistance and offer plausible targets for improving gemcitabine-based therapies for PDAC.

Clinically impactful metabolic subtypes of pancreatic ductal adenocarcinoma (PDAC).

Background: Pancreatic ductal adenocarcinoma (PDAC) is a lethal disease characterized by a diverse tumor microenvironment. The heterogeneous cellular composition of PDAC makes it challenging to study molecular features of tumor cells using extracts from bulk tumor. The metabolic features in tumor cells from clinical samples are poorly understood, and their impact on clinical outcomes are unknown. Our objective was to identify the metabolic features in the tumor compartment that are most clinically impactful. Methods: A computational deconvolution approach using the DeMixT algorithm was applied to bulk RNASeq data from The Cancer Genome Atlas to determine the proportion of each gene's expression that was attributable to the tumor compartment. A machine learning algorithm designed to identify features most closely associated with survival outcomes was used to identify the most clinically impactful metabolic genes. Results: Two metabolic subtypes (M1 and M2) were identified, based on the pattern of expression of the 26 most important metabolic genes. The M2 phenotype had a significantly worse survival, which was replicated in three external PDAC cohorts. This PDAC subtype was characterized by net glycogen catabolism, accelerated glycolysis, and increased proliferation and cellular migration. Single cell data demonstrated substantial intercellular heterogeneity in the metabolic features that typified this aggressive phenotype. Conclusion: By focusing on features within the tumor compartment, two novel and clinically impactful metabolic subtypes of PDAC were identified. Our study emphasizes the challenges of defining tumor phenotypes in the face of the significant intratumoral heterogeneity that typifies PDAC. Further studies are required to understand the microenvironmental factors that drive the appearance of the metabolic features characteristic of the aggressive M2 PDAC phenotype.

Hourglass, a rapid analysis framework for heterogeneous bioimaging data, identifies sex disparity in IL-6/STAT3-associated immune phenotypes in pancreatic cancer.

Integration and mining of bioimaging data remains a challenge and lags behind the rapidly expanding digital pathology field. We introduce Hourglass, an open-access analytical framework that streamlines biology-driven visualization, interrogation, and statistical assessment of multiparametric datasets. Cognizant of tissue and clinical heterogeneity, Hourglass systematically organizes observations across spatial and global levels and within patient subgroups. Applied to an extensive bioimaging dataset, Hourglass promptly consolidated a breadth of known interleukin-6 (IL-6) functions via its downstream effector STAT3 and uncovered a so-far unknown sexual dimorphism in the IL-6/STAT3-linked intratumoral T-cell response in human pancreatic cancer. As an R package and cross-platform application, Hourglass facilitates knowledge extraction from multi-layered bioimaging datasets for users with or without computational proficiency and provides unique and widely accessible analytical means to harness insights hidden within heterogeneous tissues at the sample and patient level. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Chemokine expression predicts T cell-inflammation and improved survival with checkpoint inhibition across solid cancers.

Immune checkpoint inhibitors (ICI) are highly effective in specific cancers where canonical markers of antitumor immunity are used for patient selection. Improved predictors of T cell-inflammation are needed to identify ICI-responsive tumor subsets in additional cancer types. We investigated associations of a 4-chemokine expression signature (c-Score: CCL4, CCL5, CXCL9, CXCL10) with metrics of antitumor immunity across tumor types. Across cancer entities from The Cancer Genome Atlas, subgroups of tumors displayed high expression of the c-Score (c-Scorehi) with increased expression of immune checkpoint (IC) genes and transcriptional hallmarks of the cancer-immunity cycle. There was an incomplete association of the c-Score with high tumor mutation burden (TMB), with only 15% of c-Scorehi tumors displaying ≥10 mutations per megabase. In a heterogeneous pan-cancer cohort of 82 patients, with advanced and previously treated solid cancers, c-Scorehi tumors had a longer median time to progression (103 versus 72 days, P = 0.012) and overall survival (382 versus 196 days, P = 0.038) following ICI therapy initiation, compared to patients with low c-Score expression. We also found c-Score stratification to outperform TMB assignment for overall survival prediction (HR = 0.42 [0.22-0.79], P = 0.008 versus HR = 0.60 [0.29-1.27], P = 0.18, respectively). Assessment of the c-Score using the TIDE and PredictIO databases, which include ICI treatment outcomes from 10 tumor types, provided further support for the c-Score as a predictive ICI therapeutic biomarker. In summary, the c-Score identifies patients with hallmarks of T cell-inflammation and potential response to ICI treatment across cancer types, which is missed by TMB assignment.

RBFOX2 modulates a metastatic signature of alternative splicing in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDA) is characterized by aggressive local invasion and metastatic spread, leading to high lethality. Although driver gene mutations during PDA progression are conserved, no specific mutation is correlated with the dissemination of metastases1-3. Here we analysed RNA splicing data of a large cohort of primary and metastatic PDA tumours to identify differentially spliced events that correlate with PDA progression. De novo motif analysis of these events detected enrichment of motifs with high similarity to the RBFOX2 motif. Overexpression of RBFOX2 in a patient-derived xenograft (PDX) metastatic PDA cell line drastically reduced the metastatic potential of these cells in vitro and in vivo, whereas depletion of RBFOX2 in primary pancreatic tumour cell lines increased the metastatic potential of these cells. These findings support the role of RBFOX2 as a potent metastatic suppressor in PDA. RNA-sequencing and splicing analysis of RBFOX2 target genes revealed enrichment of genes in the RHO GTPase pathways, suggesting a role of RBFOX2 splicing activity in cytoskeletal organization and focal adhesion formation. Modulation of RBFOX2-regulated splicing events, such as via myosin phosphatase RHO-interacting protein (MPRIP), is associated with PDA metastases, altered cytoskeletal organization and the induction of focal adhesion formation. Our results implicate the splicing-regulatory function of RBFOX2 as a tumour suppressor in PDA and suggest a therapeutic approach for metastatic PDA.

Systemic inflammatory prognostic scores in advanced pancreatic adenocarcinoma.

BACKGROUND: Systemic inflammatory scores may aid prognostication and patient selection for trials. We compared five scores in advanced pancreatic adenocarcinoma (PDAC). METHODS: Unresectable/metastatic PDAC patients enrolled in the Comprehensive Molecular Characterisation of Advanced Pancreatic Ductal Adenocarcinoma for Better Treatment Selection trial (NCT02750657) were included. Patients had pre-treatment biopsies for whole genome and RNA sequencing. CD8 immunohistochemistry was available in a subset. The neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio, Prognostic Nutritional Index, Gustave Roussy Immune Score (GRIm-S), and Memorial Sloan Kettering Prognostic Score (MPS) were calculated. Overall survival (OS) was estimated using Kaplan-Meier methods. Associations between inflammatory scores, clinical/genomic characteristics, and OS were analysed. RESULTS: We analysed 263 patients. High-risk NLR, GRIm-S and MPS were poorly prognostic. The GRIm-S had the highest predictive ability: median OS 6.4 vs. 10 months for high risk vs. low-risk (P < 0.001); HR 2.26 (P < 0.001). ECOG ≥ 1, the basal-like subtype, and low-HRDetect were additional poor prognostic factors (P < 0.01). Inflammatory scores did not associate with RNA-based classifiers or homologous recombination repair deficiency genotypes. High-risk MPS (P = 0.04) and GRIm-S (P = 0.02) patients had lower median CD8 + tumour-infiltrating lymphocytes. CONCLUSIONS: Inflammatory scores incorporating NLR have prognostic value in advanced PDAC. Understanding immunophenotypes of poor-risk patients and using these scores in trials will advance the field.

Molecular characterisation of pancreatic ductal adenocarcinoma with NTRK fusions and review of the literature.

AIMS: The majority of pancreatic ductal adenocarcinomas (PDACs) harbour oncogenic mutations in KRAS with variants in TP53, CDKN2A and SMAD4 also prevalent. The presence of oncogenic fusions including NTRK fusions are rare but important to identify. Here we ascertain the prevalence of NTRK fusions and document their genomic characteristics in a large series of PDAC. METHODS: Whole genome sequencing and RNAseq were performed on a series of patients with resected or locally advanced/metastatic PDAC collected between 2008 and 2020 at a single institution. A subset of specimens underwent immunohistochemistry (IHC) analysis. Clinical and molecular characterisation and IHC sensitivity and specificity were evaluated. RESULTS: 400 patients were included (resected n=167; locally advanced/metastatic n=233). Three patients were identified as harbouring an NTRK fusion, two EML4-NTRK3 (KRAS-WT) and a single novel KANK1-NTRK3 fusion. The latter occurring in the presence of a subclonal KRAS mutation. Typical PDAC drivers were present including mutations in TP53 and CDKN2A. Substitution base signatures and tumour mutational burden were similar to typical PDAC. The prevalence of NTRK fusions was 0.8% (3/400), while in KRAS wild-type tumours, it was 6.25% (2/32). DNA prediction alone documented six false-positive cases. RNA analysis correctly identified the in-frame fusion transcripts. IHC analysis was negative in the KANK1-NTRK3 fusion but positive in a EML4-NTRK3 case, highlighting lower sensitivity of IHC. CONCLUSION: NTRK fusions are rare; however, with emerging therapeutic options targeting these fusions, detection is vital. Reflex testing for KRAS mutations and subsequent RNA-based screening could help identify these cases in PDAC.

GATA4 and GATA6 loss-of-expression is associated with extinction of the classical programme and poor outcome in pancreatic ductal adenocarcinoma.

OBJECTIVE: GATA6 is a key regulator of the classical phenotype in pancreatic ductal adenocarcinoma (PDAC). Low GATA6 expression associates with poor patient outcome. GATA4 is the second most expressed GATA factor in the pancreas. We assessed whether, and how, GATA4 contributes to PDAC phenotype and analysed the association of expression with outcome and response to chemotherapy. DESIGN: We analysed PDAC transcriptomic data, stratifying cases according to GATA4 and GATA6 expression and identified differentially expressed genes and pathways. The genome-wide distribution of GATA4 was assessed, as well as the effects of GATA4 knockdown. A multicentre tissue microarray study to assess GATA4 and GATA6 expression in samples (n=745) from patients with resectable was performed. GATA4 and GATA6 levels were dichotomised into high/low categorical variables; association with outcome was assessed using univariable and multivariable Cox regression models. RESULTS: GATA4 messenger RNA is enriched in classical, compared with basal-like tumours. We classified samples in 4 groups as high/low for GATA4 and GATA6. Reduced expression of GATA4 had a minor transcriptional impact but low expression of GATA4 enhanced the effects of GATA6 low expression. GATA4 and GATA6 display a partially overlapping genome-wide distribution, mainly at promoters. Reduced expression of both proteins in tumours was associated with the worst patient survival. GATA4 and GATA6 expression significantly decreased in metastases and negatively correlated with basal markers. CONCLUSIONS: GATA4 and GATA6 cooperate to maintain the classical phenotype. Our findings provide compelling rationale to assess their expression as biomarkers of poor prognosis and therapeutic response.

Widespread hypertranscription in aggressive human cancers.

Cancers are often defined by the dysregulation of specific transcriptional programs; however, the importance of global transcriptional changes is less understood. Hypertranscription is the genome-wide increase in RNA output. Hypertranscription's prevalence, underlying drivers, and prognostic significance are undefined in primary human cancer. This is due, in part, to limitations of expression profiling methods, which assume equal RNA output between samples. Here, we developed a computational method to directly measure hypertranscription in 7494 human tumors, spanning 31 cancer types. Hypertranscription is ubiquitous across cancer, especially in aggressive disease. It defines patient subgroups with worse survival, even within well-established subtypes. Our data suggest that loss of transcriptional suppression underpins the hypertranscriptional phenotype. Single-cell analysis reveals hypertranscriptional clones, which dominate transcript production regardless of their size. Last, patients with hypertranscribed mutations have improved response to immune checkpoint therapy. Our results provide fundamental insights into gene dysregulation across human cancers and may prove useful in identifying patients who would benefit from novel therapies.

hENT1 Expression Predicts Response to Gemcitabine and Nab-Paclitaxel in Advanced Pancreatic Ductal Adenocarcinoma.

PURPOSE: Modified FOLFIRINOX (mFFX) and gemcitabine/nab-paclitaxel (GnP) remain standard first-line options for patients with advanced pancreatic ductal adenocarcinoma (PDAC). Human equilibrative nucleoside transporter 1 (hENT1) was hypothesized to be a biomarker of gemcitabine in the adjuvant setting, with conflicting results. In this study, we explore hENT1 mRNA expression as a predictive biomarker in advanced PDAC. EXPERIMENTAL DESIGN: COMPASS was a prospective observational trial of patients with advanced PDAC. A biopsy was required prior to initiating chemotherapy, as determined by treating physician. Biopsies underwent laser capture microdissection prior to whole genome and RNA sequencing. The cut-off thresholds for hENT1 expression were determined using the maximal χ2 statistic. RESULTS: 253 patients were included in the analyses with a median follow-up of 32 months, with 138 patients receiving mFFX and 92 receiving GnP. In the intention to treat population, median overall survival (OS) was 10.0 months in hENT1high versus 7.9 months in hENT1low (P = 0.02). In patients receiving mFFX, there was no difference in overall response rate (ORR; 35% vs. 28%, P = 0.56) or median OS (10.6 vs. 10.5 months, P = 0.45). However, in patients treated with GnP, the ORR was significantly higher in hENT1high compared with hENT1low tumors (43% vs. 21%, P = 0.038). Median OS in this GnP-treated cohort was 10.6 months in hENT1high versus 6.7 months hENT1low (P < 0.001). In an interaction analysis, hENT1 was predictive of treatment response to GnP (interaction P = 0.002). CONCLUSIONS: In advanced PDAC, hENT1 mRNA expression predicts ORR and OS in patients receiving GnP.

Integrative analysis of KRAS wildtype metastatic pancreatic ductal adenocarcinoma reveals mutation and expression-based similarities to cholangiocarcinoma.

Oncogenic KRAS mutations are absent in approximately 10% of patients with metastatic pancreatic ductal adenocarcinoma (mPDAC) and may represent a subgroup of mPDAC with therapeutic options beyond standard-of-care cytotoxic chemotherapy. While distinct gene fusions have been implicated in KRAS wildtype mPDAC, information regarding other types of mutations remain limited, and gene expression patterns associated with KRAS wildtype mPDAC have not been reported. Here, we leverage sequencing data from the PanGen trial to perform comprehensive characterization of the molecular landscape of KRAS wildtype mPDAC and reveal increased frequency of chr1q amplification encompassing transcription factors PROX1 and NR5A2. By leveraging data from colorectal adenocarcinoma and cholangiocarcinoma samples, we highlight similarities between cholangiocarcinoma and KRAS wildtype mPDAC involving both mutation and expression-based signatures and validate these findings using an independent dataset. These data further establish KRAS wildtype mPDAC as a unique molecular entity, with therapeutic opportunities extending beyond gene fusion events.

Mitochondrial fitness and cancer risk.

Changes in metabolism are a hallmark of cancer, but molecular signatures of altered bioenergetics to aid in clinical decision-making do not currently exist. We recently identified a group of human tumors with constitutively reduced expression of the mitochondrial structural protein, Mic60, also called mitofilin or inner membrane mitochondrial protein (IMMT). These Mic60-low tumors exhibit severe loss of mitochondrial fitness, paradoxically accompanied by increased metastatic propensity and upregulation of a unique transcriptome of Interferon (IFN) signaling and Senescence-Associated Secretory Phenotype (SASP). Here, we show that an optimized, 11-gene signature of Mic60-low tumors is differentially expressed in multiple malignancies, compared to normal tissues, and correlates with poor patient outcome. When analyzed in three independent patient cohorts of pancreatic ductal adenocarcinoma (PDAC), the Mic60-low gene signature was associated with aggressive disease variants, local inflammation, FOLFIRINOX failure and shortened survival, independently of age, gender, or stage. Therefore, the 11-gene Mic60-low signature may provide an easily accessible molecular tool to stratify patient risk in PDAC and potentially other malignancies.

Intra-Tumoral CD8+ T-Cell Infiltration and PD-L1 Positivity in Homologous Recombination Deficient Pancreatic Ductal Adenocarcinoma.

The immune contexture of pancreatic ductal adenocarcinoma (PDAC) is generally immunosuppressive. A role for immune checkpoint inhibitors (ICIs) in PDAC has only been demonstrated for the rare and hypermutated mismatch repair (MMR) deficient (MMR-d) subtype. Homologous recombination repair (HR) deficient (HR-d) PDAC is more prevalent and may encompass up to 20% of PDAC. Its genomic instability may promote a T-cell mediated anti-tumor response with therapeutic sensitivity to ICIs. To investigate the immunogenicity of HR-d PDAC, we used multiplex immunohistochemistry (IHC) to compare the density and spatial distribution of CD8+ cytotoxic T-cells, FOXP3+ regulatory T-cells (Tregs), and CD68+ tumor-associated macrophages (TAMs) in HR-d versus HR/MMR-intact PDAC. We also evaluated the IHC positivity of programmed death-ligand 1 (PD-L1) across the subgroups. 192 tumors were evaluated and classified as HR/MMR-intact (n=166), HR-d (n=25) or MMR-d (n=1) based on germline testing and tumor molecular hallmarks. Intra-tumoral CD8+ T-cell infiltration was higher in HR-d versus HR/MMR-intact PDAC (p<0.0001), while CD8+ T-cell densities in the peri-tumoral and stromal regions were similar in both groups. HR-d PDAC also displayed increased intra-tumoral FOXP3+ Tregs (p=0.049) and had a higher CD8+:FOXP3+ ratio (p=0.023). CD68+ TAM expression was similar in HR-d and HR/MMR-intact PDAC. Finally, 6 of the 25 HR-d cases showed a PD-L1 Combined Positive Score of >=1, whereas none of the HR/MMR-intact cases met this threshold (p<0.00001). These results provide immunohistochemical evidence for intra-tumoral CD8+ T-cell enrichment and PD-L1 positivity in HR-d PDAC, suggesting that HR-d PDAC may be amenable to ICI treatment strategies.

Tryptophan-derived microbial metabolites activate the aryl hydrocarbon receptor in tumor-associated macrophages to suppress anti-tumor immunity.

The aryl hydrocarbon receptor (AhR) is a sensor of products of tryptophan metabolism and a potent modulator of immunity. Here, we examined the impact of AhR in tumor-associated macrophage (TAM) function in pancreatic ductal adenocarcinoma (PDAC). TAMs exhibited high AhR activity and Ahr-deficient macrophages developed an inflammatory phenotype. Deletion of Ahr in myeloid cells or pharmacologic inhibition of AhR reduced PDAC growth, improved efficacy of immune checkpoint blockade, and increased intra-tumoral frequencies of IFNγ+CD8+ T cells. Macrophage tryptophan metabolism was not required for this effect. Rather, macrophage AhR activity was dependent on Lactobacillus metabolization of dietary tryptophan to indoles. Removal of dietary tryptophan reduced TAM AhR activity and promoted intra-tumoral accumulation of TNFα+IFNγ+CD8+ T cells; provision of dietary indoles blocked this effect. In patients with PDAC, high AHR expression associated with rapid disease progression and mortality, as well as with an immune-suppressive TAM phenotype, suggesting conservation of this regulatory axis in human disease.

A phase II trial of GSK2256098 and trametinib in patients with advanced pancreatic ductal adenocarcinoma.

Background: Mitogen-activated protein kinase kinase (MEK) is activated by mutated KRAS in >90% of pancreatic ductal adenocarcinoma (PDAC). MEK and focal adhesion kinase (FAK) are frequently co-activated in PDAC providing a rationale for combining trametinib, an oral allosteric MEK1/2 inhibitor, with GSK2256098, an oral FAK inhibitor. Methods: Advanced PDAC patients whose disease progressed after first line palliative chemotherapy were treated with GSK2256098 250 mg twice daily and trametinib 0.5 mg once daily orally. The primary endpoint was clinical benefit (CB; complete response, partial response, or stable disease ≥24 weeks). Twenty-four patients were planned to enroll using a 2-stage minimax design (P0=0.15, P1=0.40; alpha =0.05, power 0.86). The combination would be considered inactive if 2/12 or fewer patients achieved CB at the end of stage 1, and would be considered active if >7/24 response-evaluable patients achieved CB by the end of stage 2. Serial blood samples were collected for circulating tumor DNA (ctDNA) mutation profiling. Results: Sixteen patients were enrolled and 11 were response evaluable. Of those 11, 10 had progressive disease as best tumor response and one had stable disease for 4 months. No treatment related grade ≥3 adverse events (AEs) were observed. The median progression free survival (PFS) was 1.6 (95% CI: 1.5-1.8) months and the median overall survival (OS) was 3.6 (95% CI: 2.7-not reached) months. One response-inevaluable patient achieved clinical stability for 5 months with reduction in CA19-9 and ctDNA levels with a MAP2K1 treatment resistance mutation detected in ctDNA at clinical progression. Conclusions: The combination of GSK2256098 and trametinib was well tolerated but was not active in unselected advanced PDAC.

Checking for model failure and for prior-data conflict with the constrained multinomial model.

Multinomial models can be difficult to use when constraints are placed on the probabilities. An exact model checking procedure for such models is developed based on a uniform prior on the full multinomial model. For inference, a nonuniform prior can be used and a consistency theorem is proved concerning a check for prior-data conflict with the chosen prior. Applications are presented and a new elicitation methodology is developed for multinomial models with ordered probabilities.

Spatially confined sub-tumor microenvironments in pancreatic cancer.

Intratumoral heterogeneity is a critical frontier in understanding how the tumor microenvironment (TME) propels malignant progression. Here, we deconvolute the human pancreatic TME through large-scale integration of histology-guided regional multiOMICs with clinical data and patient-derived preclinical models. We discover "subTMEs," histologically definable tissue states anchored in fibroblast plasticity, with regional relationships to tumor immunity, subtypes, differentiation, and treatment response. "Reactive" subTMEs rich in complex but functionally coordinated fibroblast communities were immune hot and inhabited by aggressive tumor cell phenotypes. The matrix-rich "deserted" subTMEs harbored fewer activated fibroblasts and tumor-suppressive features yet were markedly chemoprotective and enriched upon chemotherapy. SubTMEs originated in fibroblast differentiation trajectories, and transitory states were notable both in single-cell transcriptomics and in situ. The intratumoral co-occurrence of subTMEs produced patient-specific phenotypic and computationally predictable heterogeneity tightly linked to malignant biology. Therefore, heterogeneity within the plentiful, notorious pancreatic TME is not random but marks fundamental tissue organizational units.

The value of GATA6 immunohistochemistry and computer-assisted diagnosis to predict clinical outcome in advanced pancreatic cancer.

Combination chemotherapy, either modified FOLFIRINOX (mFFX) or gemcitabine-nabpaclitaxel, are used in the treatment of most patients with advanced pancreatic ductal adenocarcinoma (PDAC), yet robust biomarkers of outcome are currently lacking to guide regimen selection. Here, we tested GATA6 immunohistochemistry (IHC) as a putative biomarker in advanced PDAC. GATA6 is a transcription factor in normal pancreas development. Two pathologists, blinded to clinical and molecular data, independently assessed GATA6 IHC in biopsy specimens of 130 patients with advanced PDAC, in 2 distinct phases (without and with computer assistance using the open source software QuPath). Low GATA6 IHC expression was associated with shorter overall survival [median OS 6.2 months for patients with GATA6 low tumors vs. 11.5 months for patients with GATA6 high tumors, HR 1.66 (95% CI 1.15-2.40), P = 0.007]. Progression appears to be higher in GATA6-low tumors compared to GATA6-high tumors in patients treated with mFFX (P = 0.024) but not in patients treated with gemcitabine regimens. GATA6 IHC expression was significantly associated with molecular subtypes (P = 0.0003). Digital assistance markedly improved interrater concordance (Cohen's kappa scores of 0.32 vs. 0.95). Our results provide strong evidence that GATA6 IHC can be used as a single biomarker in the clinic to predict clinical outcome in advanced PDAC, warranting further investigation in prospective clinical trials. These results provide the basis for an improved classification of PDAC and future biomarker design using digital pathology workflow.