Pancreatic Ductal Adenocarcinoma Subtyping Using the Biomarkers Hepatocyte Nuclear Factor-1A and Cytokeratin-81 Correlates with Outcome and Treatment Response

Dual and triple gene combinations of KRT5, KRT17, and S100A2 identify basal-like subtype of pancreatic ductal adenocarcinoma and correlate with survival outcome

There is a significant difference in prognosis and response to chemotherapy between basal and classical subtypes of pancreatic ductal adenocarcinoma (PDAC). Further biomarkers are required to identify subtypes of PDAC. We selected candidate biomarkers via review articles. Correlations between these candidate markers and the PDAC molecular subtype gene sets were analyzed using bioinformatics, confirming the biomarkers for identifying classical and basal subtypes. Subsequently, 298 PDAC patients were included, and their tumor tissues were immunohistochemically stratified using these biomarkers. Survival data underwent analysis, including Cox proportional hazards modeling. Our results indicate that the pairwise and triple combinations of KRT5/KRT17/S100A2 exhibit a higher correlation coefficient with the basal-like subtype gene set, whereas the corresponding combinations of GATA6/HNF4A/TFF1 show a higher correlation with the classical subtype gene set. Whether analyzing unmatched or propensity-matched data, the overall survival time was significantly shorter for the basal subtype compared with the classical subtype (p < .001), with basal subtype patients also facing a higher risk of mortality (HR = 4.017, 95% CI 2.675-6.032, p < .001). In conclusion, the combined expression of KRT5, KRT17, and S100A2, in both pairwise and triple combinations, independently predicts shorter overall survival in PDAC patients and likely identifies the basal subtype. Similarly, the combined expression of GATA6, HNF4A, and TFF1, in the same manner, may indicate the classical subtype. In our study, the combined application of established biomarkers offers valuable insights for the prognostic evaluation of PDAC patients.

Transcriptomic subtyping of gastrointestinal malignancies

Gastrointestinal (GI) cancers are highly heterogeneous at multiple levels. Tumor heterogeneity can be captured by molecular profiling, such as genetic, epigenetic, proteomic, and transcriptomic classification. Transcriptomic subtyping has the advantage of combining genetic and epigenetic information, cancer cell-intrinsic properties, and the tumor microenvironment (TME). Unsupervised transcriptomic subtyping systems of different GI malignancies have gained interest because they reveal shared biological features across cancers and bear prognostic and predictive value. Importantly, transcriptomic subtypes accurately reflect complex phenotypic states varying not only per tumor region, but also throughout disease progression, with consequences for clinical management. Here, we discuss methodologies of transcriptomic subtyping, proposed taxonomies for GI malignancies, and the challenges posed to clinical implementation, highlighting opportunities for future transcriptomic profiling efforts to optimize clinical impact.

A Novel AMPK Inhibitor Sensitizes Pancreatic Cancer Cells to Ferroptosis Induction

Cancer cells must develop strategies to adapt to the dynamically changing stresses caused by intrinsic or extrinsic processes, or therapeutic agents. Metabolic adaptability is crucial to mitigate such challenges. Considering metabolism as a central node of adaptability, it is focused on an energy sensor, the AMP-activated protein kinase (AMPK). In a subtype of pancreatic ductal adenocarcinoma (PDAC) elevated AMPK expression and phosphorylation is identified. Using drug repurposing that combined screening experiments and chemoproteomic affinity profiling, it is identified and characterized PF-3758309, initially developed as an inhibitor of PAK4, as an AMPK inhibitor. PF-3758309 shows activity in pre-clinical PDAC models, including primary patient-derived organoids. Genetic loss-of-function experiments showed that AMPK limits the induction of ferroptosis, and consequently, PF-3758309 treatment restores the sensitivity toward ferroptosis inducers. The work established a chemical scaffold for the development of specific AMPK-targeting compounds and deciphered the framework for the development of AMPK inhibitor-based combination therapies tailored for PDAC.

A mucus production programme promotes classical pancreatic ductal adenocarcinoma

OBJECTIVE

The optimal therapeutic response in cancer patients is highly dependent upon the differentiation state of their tumours. Pancreatic ductal adenocarcinoma (PDA) is a lethal cancer that harbours distinct phenotypic subtypes with preferential sensitivities to standard therapies. This study aimed to investigate intratumour heterogeneity and plasticity of cancer cell states in PDA in order to reveal cell state-specific regulators.

DESIGN

We analysed single-cell expression profiling of mouse PDAs, revealing intratumour heterogeneity and cell plasticity and identified pathways activated in the different cell states. We performed comparative analysis of murine and human expression states and confirmed their phenotypic diversity in specimens by immunolabeling. We assessed the function of phenotypic regulators using mouse models of PDA, organoids, cell lines and orthotopically grafted tumour models.

RESULTS

Our expression analysis and immunolabeling analysis show that a mucus production programme regulated by the transcription factor SPDEF is highly active in precancerous lesions and the classical subtype of PDA - the most common differentiation state. SPDEF maintains the classical differentiation and supports PDA transformation in vivo. The SPDEF tumour-promoting function is mediated by its target genes AGR2 and ERN2/IRE1β that regulate mucus production, and inactivation of the SPDEF programme impairs tumour growth and facilitates subtype interconversion from classical towards basal-like differentiation.

CONCLUSIONS

Our findings expand our understanding of the transcriptional programmes active in precancerous lesions and PDAs of classical differentiation, determine the regulators of mucus production as specific vulnerabilities in these cell states and reveal phenotype switching as a response mechanism to inactivation of differentiation states determinants.

KRT81 and HNF1A expression in pancreatic ductal adenocarcinoma: investigation of predictive and prognostic value of immunohistochemistry-based subtyping

Even after decades of research, pancreatic ductal adenocarcinoma (PDAC) remains a highly lethal disease and responses to conventional treatments remain mostly poor. Subclassification of PDAC into distinct biological subtypes has been proposed by various groups to further improve patient outcome and reduce unnecessary side effects. Recently, an immunohistochemistry (IHC)-based subtyping method using cytokeratin-81 (KRT81) and hepatocyte nuclear factor 1A (HNF1A) could recapitulate some of the previously established molecular subtyping methods, while providing significant prognostic and, to a limited degree, also predictive information. We refined the KRT81/HNF1A subtyping method to classify PDAC into three distinct biological subtypes. The prognostic value of the IHC-based method was investigated in two primary resected cohorts, which include 269 and 286 patients, respectively. In the second cohort, we also assessed the predictive effect for response to erlotinib + gemcitabine. In both PDAC cohorts, the new HNF1A-positive subtype was associated with the best survival, the KRT81-positive subtype with the worst, and the double-negative with an intermediate survival (p < 0.001 and p < 0.001, respectively) in univariate and multivariate analyses. In the second cohort (CONKO-005), the IHC-based subtype was additionally found to have a potential predictive value for the erlotinib-based treatment effect. The revised IHC-based subtyping using KRT81 and HNF1A has prognostic significance for PDAC patients and may be of value in predicting treatment response to specific therapeutic agents.

Neoadjuvant treatment for pancreatic cancer: Controversies and advances

Despite the advancements in the treatment of localized pancreatic cancer, several unresolved issues persist in clinical practice, especially in the neoadjuvant setting. These include determining the criteria for selecting patients for treatment, identifying the most effective chemotherapy regimens, understanding the role of radiotherapy, and accurately assessing how patients respond to treatment. Current strategies for assessing patients before surgery involve thoroughly evaluating their overall health status, analyzing tumor markers, and using advanced imaging techniques. However, existing methods for staging the disease still have limitations when it comes to accurately detecting metastatic cancer. The ongoing debate between performing surgery upfront or administering neoadjuvant therapy highlights the need for robust clinical evidence to guide treatment decisions effectively. This review analyzes the evidence regarding controversial topics in neoadjuvant pancreatic cancer treatment and discusses further research efforts to enhance patient outcomes. To improve the outcomes found with surgery alone, multimodal treatment with chemotherapy.

Ectopic Expression of a Truncated Isoform of Hair Keratin 81 in Breast Cancer Alters Biophysical Characteristics to Promote Metastatic Propensity

Keratins are an integral part of cell structure and function. Here, it is shown that ectopic expression of a truncated isoform of keratin 81 (tKRT81) in breast cancer is upregulated in metastatic lesions compared to primary tumors and patient-derived circulating tumor cells, and is associated with more aggressive subtypes. tKRT81 physically interacts with keratin 18 (KRT18) and leads to changes in the cytosolic keratin intermediate filament network and desmosomal plaque formation. These structural changes are associated with a softer, more elastically deformable cancer cell with enhanced adhesion and clustering ability leading to greater in vivo lung metastatic burden. This work describes a novel biomechanical mechanism by which tKRT81 promotes metastasis, highlighting the importance of the biophysical characteristics of tumor cells.

Protocol of the IntenSify-Trial: An open-label phase I trial of the CYP3A inhibitor cobicistat and the cytostatics gemcitabine and nab-paclitaxel in patients with advanced stage or metastatic pancreatic ductal adenocarcinoma to evaluate the combination's pharmacokinetics, safety, and efficacy

Expression of CYP3A5 protein is a basal and acquired resistance mechanism of pancreatic ductal adenocarcinoma cells conferring protection against the CYP3A and CYP2C8 substrate paclitaxel through metabolic degradation. Inhibition of CYP3A isozymes restores the cells sensitivity to paclitaxel. The combination of gemcitabine and nab-paclitaxel is an established regimen for the treatment of metastasized or locally advanced inoperable pancreatic cancer. Cobicistat is a CYP3A inhibitor developed for the pharmacoenhancement of protease inhibitors. The addition of cobicistat to gemcitabine and nab-paclitaxel may increase the antitumor effect. We will conduct a phase I dose escalation trial with a classical 3 + 3 design to investigate the safety, tolerability, and pharmacokinetics (PKs) of gemcitabine, nab-paclitaxel, and cobicistat. Although the doses of gemcitabine (1000 mg/m2 ) and cobicistat (150 mg) are fixed, three dose levels of nab-paclitaxel (75, 100, and 125 mg/m2 ) will be explored to account for a potential PK drug interaction. After the dose escalation phase, we will set the recommended dose for expansion (RDE) and treat up to nine patients in an expansion part of the trial. The trial is registered under the following identifiers EudraCT-Nr. 2019-001439-29, drks.de: DRKS00029409, and ct.gov: NCT05494866. Overcoming resistance to paclitaxel by CYP3A5 inhibition may lead to an increased efficacy of the gemcitabine and nab-paclitaxel regimen. Safety, efficacy, PK, and RDE data need to be acquired before investigating this combination in a large-scale clinical study.

Differential chromatin accessibility and transcriptional dynamics define breast cancer subtypes and their lineages

Breast cancer is a heterogeneous disease, and treatment is guided by biomarker profiles representing distinct molecular subtypes. Breast cancer arises from the breast ductal epithelium, and experimental data suggests breast cancer subtypes have different cells of origin within that lineage. The precise cells of origin for each subtype and the transcriptional networks that characterize these tumor-normal lineages are not established. In this work, we applied bulk, single-cell (sc), and single-nucleus (sn) multi-omic techniques as well as spatial transcriptomics and multiplex imaging on 61 samples from 37 breast cancer patients to show characteristic links in gene expression and chromatin accessibility between breast cancer subtypes and their putative cells of origin. We applied the PAM50 subtyping algorithm in tandem with bulk RNA-seq and snRNA-seq to reliably subtype even low-purity tumor samples and confirm promoter accessibility using snATAC. Trajectory analysis of chromatin accessibility and differentially accessible motifs clearly connected progenitor populations with breast cancer subtypes supporting the cell of origin for basal-like and luminal A and B tumors. Regulatory network analysis of transcription factors underscored the importance of BHLHE40 in luminal breast cancer and luminal mature cells, and KLF5 in basal-like tumors and luminal progenitor cells. Furthermore, we identify key genes defining the basal-like ( PRKCA , SOX6 , RGS6 , KCNQ3 ) and luminal A/B ( FAM155A , LRP1B ) lineages, with expression in both precursor and cancer cells and further upregulation in tumors. Exhausted CTLA4-expressing CD8+ T cells were enriched in basal-like breast cancer, suggesting altered means of immune dysfunction among breast cancer subtypes. We used spatial transcriptomics and multiplex imaging to provide spatial detail for key markers of benign and malignant cell types and immune cell colocation. These findings demonstrate analysis of paired transcription and chromatin accessibility at the single cell level is a powerful tool for investigating breast cancer lineage development and highlight transcriptional networks that define basal and luminal breast cancer lineages.

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.

Complex glandular pattern is an aggressive morphology that predicts poor prognosis of pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignant neoplasm with various morphologies. Recognition of histological patterns that can predict prognosis is important in pathological examination. Recently, the complex glandular pattern was defined as a morphology associating the poor prognosis in lung adenocarcinoma. We investigated the significance of the complex glandular pattern in PDAC by performing a retrospective analysis. Among 240 consecutive cases of conventional PDACs, 21 cases in which complex glandular pattern constituted >50 % of the total tumor volume (CG-PDACs) were identified. The prevalence of CG-PDAC was 8.8 % among all preoperative therapy-naïve and surgically resected conventional PDACs. Compared to the control PDACs (n = 95), the CG-PDACs were characterized by significantly higher prevalence of small- to medium-sized artery invasion (71.4 % vs. 14.7 %, p < 0.0001), intratumoral necrosis (59.1 % vs. 16.8 %, p < 0.0001), tumor budding (mean: 15.5 vs. 12.5 per 0.785 mm², p = 0.04), significantly higher Ki67 proliferative index (mean: 75.0 % vs. 54.7 %, p < 0.0001), and the HNF1α-/KRT81+ (quasi-mesenchymal) immunophenotype (42.9 % vs. 19.0 %, p = 0.004). In Kaplan-Meier analyses, the CG-PDAC patients achieved significantly worse disease-free survival (DFS) and overall survival (OS) compared to the control PDAC patients; the respective median DFS and OS were 6.3 and 17.7 months for CG-PDACs, and 22.6 and 52.8 months for control PDACs. A multivariate Cox regression analysis showed that predominance of complex glandular pattern was an independent prognostic factor (hazard ratio: 2.95; 95 % confidence interval: 1.46-5.98; p = 0.003). Our results provide new insights into the complex glandular pattern in conventional PDACs as a novel and potentially useful prognostic factor.

Spatially Resolved Single-Cell Assessment of Pancreatic Cancer Expression Subtypes Reveals Co-expressor Phenotypes and Extensive Intratumoral Heterogeneity

Pancreatic ductal adenocarcinoma (PDAC) has been classified into classical and basal-like transcriptional subtypes by bulk RNA measurements. However, recent work has uncovered greater complexity to transcriptional subtypes than was initially appreciated using bulk RNA expression profiling. To provide a deeper understanding of PDAC subtypes, we developed a multiplex immunofluorescence (mIF) pipeline that quantifies protein expression of six PDAC subtype markers (CLDN18.2, TFF1, GATA6, KRT17, KRT5, and S100A2) and permits spatially resolved, single-cell interrogation of pancreatic tumors from resection specimens and core needle biopsies. Both primary and metastatic tumors displayed striking intratumoral subtype heterogeneity that was associated with patient outcomes, existed at the scale of individual glands, and was significantly reduced in patient-derived organoid cultures. Tumor cells co-expressing classical and basal markers were present in > 90% of tumors, existed on a basal-classical polarization continuum, and were enriched in tumors containing a greater admixture of basal and classical cell populations. Cell-cell neighbor analyses within tumor glands further suggested that co-expressor cells may represent an intermediate state between expression subtype poles. The extensive intratumoral heterogeneity identified through this clinically applicable mIF pipeline may inform prognosis and treatment selection for patients with PDAC.

SIGNIFICANCE

A high-throughput pipeline using multiplex immunofluorescence in pancreatic cancer reveals striking expression subtype intratumoral heterogeneity with implications for therapy selection and identifies co-expressor cells that may serve as intermediates during subtype switching.

Serum Amyloid a Predicts Prognosis and Chemotherapy Efficacy in Patients with Advanced Pancreatic Cancer

Purpose

There is an urgent need to discover a predictive biomarker to help patients with advanced pancreatic cancer (APC) choose appropriate chemotherapy regimens. This study aimed to determine whether baseline serum amyloid A (SAA) levels were associated with overall survival (OS), progression-free survival (PFS), and treatment response in patients with APC received chemotherapy.

Patients and Methods

This retrospective study included 268 patients with APC who received first-line chemotherapy at the Sun Yat-Sen University Cancer Center between January 2017 and December 2021. We examined the effect of baseline SAA on OS, PFS and chemotherapy response. The X-Tile program was used to determine the critical value for optimizing the significance of segmentation between Kaplan-Meier survival curves. The Kaplan-Meier curves and Cox regression analyses were used to analyze OS and PFS.

Results

The best cut-off value of baseline SAA levels for OS stratification was 8.2 mg/L. Multivariate analyses showed that SAA was an independent predictor of OS (Hazard Ratio (HR) = 1.694, 95% Confidence Interval (CI) = 1.247-2.301, p = 0.001) and PFS (HR = 1.555, 95% CI = 1.152-2.098, p = 0.004). Low SAA was associated with longer OS (median, 15.7 months vs 10.0 months, p < 0.001) and PFS (median, 7.6 months vs 4.8 months, p < 0.001). The patients with a low SAA who received mFOLFIRINOX had longer OS (median, 28.5 months vs 15.1 months, p = 0.019) and PFS (median, 12.0 months vs 7.4 months, p = 0.035) than those who received nab-paclitaxel plus gemcitabine (AG) or SOXIRI, whereas there was no significant difference among the three chemotherapy regimens in patients with a high SAA.

Conclusion

Owing to the rapid and simple analysis of peripheral blood, baseline SAA might be a useful clinical biomarker, not only as a prognostic biomarker for patients with APC, but also as a guide for the selection of chemotherapy regimens.

The Role of the Microbiome in Pancreatic Cancer

Simple Summary

Pancreatic cancer is deadly cancer characterized by dense stroma creating an immunosuppressive tumor microenvironment. Accumulating evidences indicate that the microbiome plays an important role in pancreatic cancer development and progression via the local and systemic inflammation and immune responses. The alteration of the microbiome modulates the tumor microenvironment and immune system in pancreatic cancer, which affects the efficacy of chemotherapies including immune-targeted therapies. Understanding the role of microbiome and underlying mechanisms may lead to novel biomarkers and therapeutic strategies for pancreatic cancer. This review summarizes the current evidence on the role of the microbiome in pancreatic cancer.

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies, with little improvement in outcomes in recent decades, although the molecular and phenotypic characterization of PDAC has contributed to advances in tailored therapies. PDAC is characterized by dense stroma surrounding tumor cells, which limits the efficacy of treatment due to the creation of a physical barrier and immunosuppressive environment. Emerging evidence regarding the microbiome in PDAC implies its potential role in the initiation and progression of PDAC. However, the underlying mechanisms of how the microbiome affects the local tumor microenvironment (TME) as well as the systemic immune system have not been elucidated in PDAC. In addition, therapeutic strategies based on the microbiome have not been established. In this review, we summarize the current evidence regarding the role of the microbiome in the development of PDAC and discuss a possible role for the microbiome in the early detection of PDAC in relation to premalignant pancreatic diseases, such as chronic pancreatitis and intraductal papillary mucinous neoplasm (IPMN). In addition, we discuss the potential role of the microbiome in the treatment of PDAC, especially in immunotherapy, although the biomarkers used to predict the efficacy of immunotherapy in PDAC are still unknown. A comprehensive understanding of tumor-associated immune responses, including those involving the microbiome, holds promise for new treatments in PDAC.

A GATA6-centred gene regulatory network involving HNFs and ΔNp63 controls plasticity and immune escape in pancreatic cancer

OBJECTIVE

Molecular taxonomy of tumours is the foundation of personalised medicine and is becoming of paramount importance for therapeutic purposes. Four transcriptomics-based classification systems of pancreatic ductal adenocarcinoma (PDAC) exist, which consistently identified a subtype of highly aggressive PDACs with basal-like features, including ΔNp63 expression and loss of the epithelial master regulator GATA6. We investigated the precise molecular events driving PDAC progression and the emergence of the basal programme.

DESIGN

We combined the analysis of patient-derived transcriptomics datasets and tissue samples with mechanistic experiments using a novel dual-recombinase mouse model for Gata6 deletion at late stages of KRasG12D-driven pancreatic tumorigenesis (Gata6LateKO).

RESULTS

This comprehensive human-to-mouse approach showed that GATA6 loss is necessary, but not sufficient, for the expression of ΔNp63 and the basal programme in patients and in mice. The concomitant loss of HNF1A and HNF4A, likely through epigenetic silencing, is required for the full phenotype switch. Moreover, Gata6 deletion in mice dramatically increased the metastatic rate, with a propensity for lung metastases. Through RNA-Seq analysis of primary cells isolated from mouse tumours, we show that Gata6 inhibits tumour cell plasticity and immune evasion, consistent with patient-derived data, suggesting that GATA6 works as a barrier for acquiring the fully developed basal and metastatic phenotype.

CONCLUSIONS

Our work provides both a mechanistic molecular link between the basal phenotype and metastasis and a valuable preclinical tool to investigate the most aggressive subtype of PDAC. These data, therefore, are important for understanding the pathobiological features underlying the heterogeneity of pancreatic cancer in both mice and human.

High expression of both desmoplastic stroma and epithelial to mesenchymal transition markers associate with shorter survival in pancreatic ductal adenocarcinoma

Desmoplastic stroma (DS) and the epithelial-to-mesenchymal transition (EMT) play a key role in pancreatic ductal adenocarcinoma (PDAC) progression. To date, however, the combined expression of DS and EMT markers, and their association with variations in survival within each clinical stage and degree of tumor differentiation is unknown. The purpose of this study was to investigate the association between expression of DS and EMT markers and survival variability in patients diagnosed with PDAC. We examined the expression levels of DS markers alpha smooth muscle actin (α-SMA), fibronectin, and vimentin, and the EMT markers epithelial cell adhesion molecule (EPCAM), pan-cytokeratin, and vimentin, by immunohistochemistry using a tissue microarray in a retrospective cohort of 25 patients with PDAC. The results were examined for association with survival by clinical stage and by degree of tumor differentiation. High expression of DS markers -α-SMA, fibronectin, and vimentin- was associated with decreased survival at intermediate and advanced clinical stages (p=0.006-0.03), as well as with both poorly and moderately differentiated tumor grades (p=0.01-0.02). Interestingly, the same pattern was observed for EMT markers, i.e., EPCAM, pan-cytokeratin, and vimentin (p=0.00008-0.03). High expression of DS and EMT markers within each clinical stage and degree of tumor differentiation was associated with lower PDAC survival. Evaluation of these markers may have a prognostic impact on survival time variation in patients with PDAC.

Prognosis and tumor biology of pancreatic cancer patients with isolated lung metastases: translational results from the German multicenter AIO-YMO-PAK-0515 study

Background

Pulmonary metastasis (M1-PUL) as first site of dissemination in pancreatic ductal adenocarcinoma (PDAC) is a rare event and may define a distinct biological subgroup.

Patients and methods

Arbeitsgemeinschaft Internistische Onkologie-Young Medical Oncologists-Pankreas-0515 study (AIO-YMO-PAK-0515) was a retrospective German multicenter study investigating clinical and molecular characteristics of M1-PUL PDAC patients; 115 M1-PUL PDAC patients from 7 participating centers were included. Clinical characteristics and potential prognostic factors were defined within the M1-PUL cohort. Archival tumor samples were analyzed for Her2/neu, HNF1A and KRT81 expression. Additionally, messenger RNA (mRNA) expression analysis (using a 770-gene immune profiling panel) was carried out in the M1-PUL and in a control cohort (M1-ANY).

Results

Median overall survival in the entire M1-PUL cohort was 20 months; the most favorable prognosis (median survival: 28 months) was observed in the subgroup of 66 PDAC patients with metachronous lung metastases after previous curative-intent surgery. The number of metastatic lesions, uni- or bilateral lung involvement as well as metastasectomy were identified as potential prognostic factors. Her2/neu expression and PDAC subtyping (by HNF1A and KRT81) did not differ between the M1-PUL and the M1-ANY cohort. mRNA expression analysis revealed significant differentially expressed genes between both cohorts: CD63 and LAMP1 were among the top 20 differentially expressed genes and were identified as potential mediators of organotropism and favorable survival outcome of M1-PUL patients.

Conclusion

M1-PUL represents a clinically favorable cohort in PDAC patients. Site of relapse might already be predetermined at the time of surgery and could potentially be predicted by gene expression profiling.

•

The retrospective multicenter AIO-YMO-PAK-0515 study defines M1-PUL as a clinically favorable subgroup in PDAC.

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The number of metastatic lesions, bilateral lung involvement and surgical metastasectomy may serve as prognostic factors.

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Immune-related gene expression differs between patients with isolated pulmonary relapse versus other sites of relapse.

BRCA 1/2 Germline Mutation Predicts the Treatment Response of FOLFIRINOX with Pancreatic Ductal Adenocarcinoma in Korean Patients

We evaluated the proportion of BRCA 1/2 germline mutations in Korean patients with sporadic pancreatic ductal adenocarcinoma (PDAC) and its effect on the chemotherapeutic response of FOLFIRINOX. This retrospective study included patients who were treated at two tertiary hospitals between 2012 and 2020, were pathologically confirmed to have PDAC, and had undergone targeted next-generation sequencing-based germline genetic testing. Sixty-six patients were included in the study (24 men; median age 57.5 years). In the germline test, BRCA 1/2 pathogenic mutations were found in nine patients (9/66, 13%, BRCA 1, n = 3; BRCA 2, n = 5; and BRCA 1/2, n = 1). There was no significant difference in the baseline characteristics according to BRCA mutation positivity. Among patients who underwent FOLFIRINOX chemotherapy, patients with a BRCA 1/2 mutation showed a higher overall response rate than those without a BRCA 1/2 mutation (71.4% vs. 13.9%, p = 0.004). Patients with a germline BRCA 1/2 mutation showed longer progression-free survival than those without a BRCA 1/2 mutation, without a significant time difference (18 months vs. 10 months, p = 0.297). Patients with a BRCA 1/2 mutation in the germline blood test had a higher response rate to FOLFIRINOX chemotherapy in PDAC. The high proportion of BRCA 1/2 germline mutations and response rate supports the need for germline testing in order to predict better treatment response.

Recent advances in artificial intelligence for pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) remains the most lethal type of cancer. The 5-year survival rate for patients with early-stage diagnosis can be as high as 20%, suggesting that early diagnosis plays a pivotal role in the prognostic improvement of PDAC cases. In the medical field, the broad availability of biomedical data has led to the advent of the "big data" era. To overcome this deadly disease, how to fully exploit big data is a new challenge in the era of precision medicine. Artificial intelligence (AI) is the ability of a machine to learn and display intelligence to solve problems. AI can help to transform big data into clinically actionable insights more efficiently, reduce inevitable errors to improve diagnostic accuracy, and make real-time predictions. AI-based omics analyses will become the next alterative approach to overcome this poor-prognostic disease by discovering biomarkers for early detection, providing molecular/genomic subtyping, offering treatment guidance, and predicting recurrence and survival. Advances in AI may therefore improve PDAC survival outcomes in the near future. The present review mainly focuses on recent advances of AI in PDAC for clinicians. We believe that breakthroughs will soon emerge to fight this deadly disease using AI-navigated precision medicine.

TNF-α-producing macrophages determine subtype identity and prognosis via AP1 enhancer reprogramming in pancreatic cancer

Large-scale genomic profiling of pancreatic cancer (PDAC) has revealed two distinct subtypes: 'classical' and 'basal-like'. Their variable coexistence within the stromal immune microenvironment is linked to differential prognosis; however, the extent to which these neoplastic subtypes shape the stromal immune landscape and impact clinical outcome remains unclear. By combining preclinical models, patient-derived xenografts, as well as FACS-sorted PDAC patient biopsies, we show that the basal-like neoplastic state is sustained via BRD4-mediated cJUN/AP1 expression, which induces CCL2 to recruit tumor necrosis factor (TNF)-α-secreting macrophages. TNF-α+ macrophages force classical neoplastic cells into an aggressive phenotypic state via lineage reprogramming. Integration of ATAC-, ChIP- and RNA-seq data revealed distinct JUNB/AP1 (classical) and cJUN/AP1 (basal-like)-driven regulation of PDAC subtype identity. Pharmacological inhibition of BRD4 led to suppression of the BRD4-cJUN-CCL2-TNF-α axis, restoration of classical subtype identity and a favorable prognosis. Hence, patient-tailored therapy for a cJUNhigh/TNF-αhigh subtype is paramount in overcoming highly inflamed and aggressive PDAC states.

Morphological and p40 immunohistochemical analysis of squamous differentiation in endoscopic ultrasound guided fine needle biopsies of pancreatic ductal adenocarcinoma

The basal-like molecular subtype of pancreatic ductal adenocarcinoma (PDAC) is associated with poor prognosis and upregulation in TP63ΔN (p40) network. Adenosquamous histology can be observed. This study assessed immunohistochemical p40 expression in fine needle biopsy (FNB) samples with PDAC and association with cytomorphological features of squamous differentiation and clinical data. 106 EUS FNBs with PDAC were assessed for eight cytomorphological features of squamous differentiation. P40 H-score (intensity 0-3 × percentage positive nuclei) was analysed for association with morphological features, patient age, gender, operability, chemotherapy and survival. P40 H-score in 14 paired FNBs and resections was compared. P40 h-score was 1-3 in 31%, 4-30 in 16% and > 30 in 13% of FNBs. It was significantly associated with intercellular bridges, elongated cell shape, sharp cell borders, angular nuclei with homogenous chromatin (p < 0.001) and dense cytoplasm (p = 0.002). Keratinisation was not seen. Inoperable patients (n = 81) had a shorter median survival for h-score > 30 (n = 9, 1.8 months) than for h-score ≤ 30 (n = 66, 6.7 months) not quite reaching statistical significance (p = 0.08). P40 was significantly associated with squamous morphology in FNBs with PDAC. P40 H-score > 30 showed a trend towards shorter survival in inoperable patients. Squamous differentiation may be a treatment target in PDAC.

Rationale for MYC imaging and targeting in pancreatic cancer

The incidence and lethality of pancreatic ductal adenocarcinoma (PDAC) will continue to increase in the next decade. For most patients, chemotherapeutic combination therapies remain the standard of care. The development and successful implementation of precision oncology in other gastrointestinal tumor entities point to opportunities also for PDAC. Therefore, markers linked to specific therapeutic responses and important subgroups of the disease are needed. The MYC oncogene is a relevant driver in PDAC and is linked to drug resistance and sensitivity. Here, we update recent insights into MYC biology in PDAC, summarize the connections between MYC and drug responses, and point to an opportunity to image MYC non-invasively. In sum, we propose MYC-associated biology as a basis for the development of concepts for precision oncology in PDAC.

Single-cell analysis of patient-derived PDAC organoids reveals cell state heterogeneity and a conserved developmental hierarchy

Pancreatic ductal adenocarcinoma (PDAC) is projected to be the second leading cause of cancer mortality by 2030. Bulk transcriptomic analyses have distinguished 'classical' from 'basal-like' tumors with more aggressive clinical behavior. We derive PDAC organoids from 18 primary tumors and two matched liver metastases, and show that 'classical' and 'basal-like' cells coexist in individual organoids. By single-cell transcriptome analysis of PDAC organoids and primary PDAC, we identify distinct tumor cell states shared across patients, including a cycling progenitor cell state and a differentiated secretory state. Cell states are connected by a differentiation hierarchy, with 'classical' cells concentrated at the endpoint. In an imaging-based drug screen, expression of 'classical' subtype genes correlates with better drug response. Our results thus uncover a functional hierarchy of PDAC cell states linked to transcriptional tumor subtypes, and support the use of PDAC organoids as a clinically relevant model for in vitro studies of tumor heterogeneity.

A Comparative Endocrine Trans-Differentiation Approach to Pancreatic Ductal Adenocarcinoma Cells with Different EMT Phenotypes Identifies Quasi-Mesenchymal Tumor Cells as Those with Highest Plasticity

Simple Summary

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancer types with the quasi-mesenchymal (QM) subtype of PDAC having the worst prognosis. De-differentiation of the ductal tumor cells to a mesenchymal phenotype occurs as a result of epithelial–mesenchymal transition (EMT), a process associated with the acquisition of stem cell traits. While QM tumor cells are highly metastatic and drug-resistant, their increased plasticity opens a window of opportunity for trans-differentiation into non-malignant pancreatic cells. In this study we compared established PDAC-derived cell lines of either epithelial (E) or QM phenotype for their potential to be differentiated to pancreatic endocrine cells. We found that QM cells responded more strongly than E cells with transcriptional activation of a pancreatic progenitor or pancreatic β cell-specific program. Our results bear strong implications for a novel type of targeted therapy, namely EMT-based trans-differentiation of highly metastatic PDAC cells in vivo to non-malignant endocrine cells.

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive and therapy-resistant cancer types which is largely due to tumor heterogeneity, cancer cell de-differentiation, and early metastatic spread. The major molecular subtypes of PDAC are designated classical/epithelial (E) and quasi-mesenchymal (QM) subtypes, with the latter having the worst prognosis. Epithelial–mesenchymal transition (EMT) and the reverse process, mesenchymal-epithelial transition (MET), are involved in regulating invasion/metastasis and stem cell generation in cancer cells but also early pancreatic endocrine differentiation or de-differentiation of adult pancreatic islet cells in vitro, suggesting that pancreatic ductal exocrine and endocrine cells share common EMT programs. Using a panel of PDAC-derived cell lines classified by epithelial/mesenchymal expression as either E or QM, we compared their trans-differentiation (TD) potential to endocrine progenitor or β cell-like cells since studies with human pancreatic cancer cells for possible future TD therapy in PDAC patients are not available so far. We observed that QM cell lines responded strongly to TD culture using as inducers 5′-aza-2′-deoxycytidine or growth factors/cytokines, while their E counterparts were refractory or showed only a weak response. Moreover, the gain of plasticity was associated with a decrease in proliferative and migratory activities and was directly related to epigenetic changes acquired during selection of a metastatic phenotype as revealed by TD experiments using the paired isogenic COLO 357-L3.6pl model. Our data indicate that a QM phenotype in PDAC coincides with increased plasticity and heightened trans-differentiation potential to activate a pancreatic β cell-specific transcriptional program. We strongly assume that this specific biological feature has potential to be exploited clinically in TD-based therapy to convert metastatic PDAC cells into less malignant or even benign cells.

Genomic Heterogeneity of Pancreatic Ductal Adenocarcinoma and Its Clinical Impact

Pancreatic ductal adenocarcinoma (PDAC) is one of the leading causes of cancer death due to limited advances in recent years in early diagnosis and personalized therapy capable of overcoming tumor resistance to chemotherapy. In the last decades, significant advances have been achieved in the identification of recurrent genetic and molecular alterations of PDAC including those involving the KRAS, CDKN2A, SMAD4, and TP53 driver genes. Despite these common genetic traits, PDAC are highly heterogeneous tumors at both the inter- and intra-tumoral genomic level, which might contribute to distinct tumor behavior and response to therapy, with variable patient outcomes. Despite this, genetic and genomic data on PDAC has had a limited impact on the clinical management of patients. Integration of genomic data for classification of PDAC into clinically defined entities-i.e., classical vs. squamous subtypes of PDAC-leading to different treatment approaches has the potential for significantly improving patient outcomes. In this review, we summarize current knowledge about the most relevant genomic subtypes of PDAC including the impact of distinct patterns of intra-tumoral genomic heterogeneity on the classification and clinical and therapeutic management of PDAC.

[Ductal adenocarcinoma of the pancreas: subtypes and molecular pathology]

Ductal adenocarcinoma is the most common tumor of the pancreas. Although relatively rare, it poses one of the greatest oncological challenges because of its poor prognosis, which has so far only slightly improved. Progress has been made in the more precise classification and standardization of the morphological assessment. In the current WHO classification, prognostically relevant subtypes are clearly delimited among themselves and from ductal adenocarcinoma not otherwise specified (NOS). In the recent TNM classification, a size-based T‑category was introduced. Diagnostically, the histological assessment of the resection specimen is relatively easy; on the other hand, assessment of the fine-needle biopsy from the primary tumor or a liver metastasis is still difficult. The molecular stratification of ductal adenocarcinoma and the other pancreatic neoplasms has made great progress. This not only defined the genetics of tumor entities, but also identified the prognosis and biology of tumor groups on the basis of RNA expression patterns. The range of treatment could be expanded by targeted molecular therapies (especially for patients with BRCA1/2 germline mutations, NTRK- or NRG1-fusions, or oncogenic BRAF and PIK3CA mutations as well as tumors with microsatellite instability (MSI)), even if targeted therapies are currently only available for a minority of patients (<10%).

Kallikrein-Related Peptidase 6 Is Associated with the Tumour Microenvironment of Pancreatic Ductal Adenocarcinoma

Simple Summary

Kallikrein-related peptidases have tumour-biological roles and are dysregulated in many cancers. Only a few studies have reported their upregulation in pancreatic cancer and linked them to poor prognosis. By interrogating publicly available and our own datasets, we studied their expression in patient-derived tissues and pancreatic cancer cells. We found several kallikrein-related peptidases that were upregulated, in particular kallikrein-related peptidase 6 at the forefront of the tumour area. We then tested the effect of a kallikrein-related peptidase 6 inhibitor on cancer cell functions. Because the majority of patients present with inoperable disease, a targeted therapeutic intervention may have a positive impact on the survival of this patient population.

Abstract

As cancer-associated factors, kallikrein-related peptidases (KLKs) are components of the tumour microenvironment, which represents a rich substrate repertoire, and considered attractive targets for the development of novel treatments. Standard-of-care therapy of pancreatic cancer shows unsatisfactory results, indicating the need for alternative therapeutic approaches. We aimed to investigate the expression of KLKs in pancreatic cancer and to inhibit the function of KLK6 in pancreatic cancer cells. KLK6, KLK7, KLK8, KLK10 and KLK11 were coexpressed and upregulated in tissues from pancreatic cancer patients compared to normal pancreas. Their high expression levels correlated with each other and were linked to shorter survival compared to low KLK levels. We then validated KLK6 mRNA and protein expression in patient-derived tissues and pancreatic cancer cells. Coexpression of KLK6 with KRT19, αSMA or CD68 was independent of tumour stage, while KLK6 was coexpressed with KRT19 and CD68 in the invasive tumour area. High KLK6 levels in tumour and CD68+ cells were linked to shorter survival. KLK6 inhibition reduced KLK6 mRNA expression, cell metabolic activity and KLK6 secretion and increased the secretion of other serine and aspartic lysosomal proteases. The association of high KLK levels and poor prognosis suggests that inhibiting KLKs may be a therapeutic strategy for precision medicine.

[18F]FDG PET/MRI enables early chemotherapy response prediction in pancreatic ductal adenocarcinoma

Purpose

In this prospective exploratory study, we evaluated the feasibility of [¹⁸F]fluorodeoxyglucose ([¹⁸F]FDG) PET/MRI-based chemotherapy response prediction in pancreatic ductal adenocarcinoma at two weeks upon therapy onset.

Material and methods

In a mixed cohort, seventeen patients treated with chemotherapy in neoadjuvant or palliative intent were enrolled. All patients were imaged by [¹⁸F]FDG PET/MRI before and two weeks after onset of chemotherapy. Response per RECIST1.1 was then assessed at 3 months [¹⁸F]FDG PET/MRI-derived parameters (MTV_50%, TLG_50%, MTV_2.5, TLG_2.5, SUV_max, SUV_peak, ADC_max, ADC_mean and ADC_min) were assessed, using multiple t-test, Man–Whitney-U test and Fisher’s exact test for binary features.

Results

At 72 ± 43 days, twelve patients were classified as responders and five patients as non-responders. An increase in ∆MTV_50% and ∆ADC (≥ 20% and 15%, respectively) and a decrease in ∆TLG_50% (≤ 20%) at 2 weeks after chemotherapy onset enabled prediction of responders and non-responders, respectively. Parameter combinations (∆TLG_50% and ∆ADC_max or ∆MTV_50% and ∆ADC_max) further improved discrimination.

Conclusion

Multiparametric [¹⁸F]FDG PET/MRI-derived parameters, in particular indicators of a change in tumor glycolysis and cellularity, may enable very early chemotherapy response prediction. Further prospective studies in larger patient cohorts are recommended to their clinical impact.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13550-021-00808-4.

Bcl3 Couples Cancer Stem Cell Enrichment With Pancreatic Cancer Molecular Subtypes

BACKGROUND & AIMS

The existence of different subtypes of pancreatic ductal adenocarcinoma (PDAC) and their correlation with patient outcome have shifted the emphasis on patient classification for better decision-making algorithms and personalized therapy. The contribution of mechanisms regulating the cancer stem cell (CSC) population in different subtypes remains unknown.

METHODS

Using RNA-seq, we identified B-cell CLL/lymphoma 3 (BCL3), an atypical nf-κb signaling member, as differing in pancreatic CSCs. To determine the biological consequences of BCL3 silencing in vivo and in vitro, we generated bcl3-deficient preclinical mouse models as well as murine cell lines and correlated our findings with human cell lines, PDX models, and 2 independent patient cohorts. We assessed the correlation of bcl3 expression pattern with clinical parameters and subtypes.

RESULTS

Bcl3 was significantly down-regulated in human CSCs. Recapitulating this phenotype in preclinical mouse models of PDAC via BCL3 genetic knockout enhanced tumor burden, metastasis, epithelial to mesenchymal transition, and reduced overall survival. Fluorescence-activated cell sorting analyses, together with oxygen consumption, sphere formation, and tumorigenicity assays, all indicated that BCL3 loss resulted in CSC compartment expansion promoting cellular dedifferentiation. Overexpression of BCL3 in human PDXs diminished tumor growth by significantly reducing the CSC population and promoting differentiation. Human PDACs with low BCL3 expression correlated with increased metastasis, and BCL3-negative tumors correlated with lower survival and nonclassical subtypes.

CONCLUSIONS

We demonstrate that bcl3 impacts pancreatic carcinogenesis by restraining CSC expansion and by curtailing an aggressive and metastatic tumor burden in PDAC across species. Levels of BCL3 expression are a useful stratification marker for predicting subtype characterization in PDAC, thereby allowing for personalized therapeutic approaches.

Molecular and Phenotypic Profiling for Precision Medicine in Pancreatic Cancer: Current Advances and Future Perspectives

Pancreatic cancer is the most common lethal malignancy, with little improvement in patient outcomes over the decades. The development of early detection methods and effective therapeutic strategies are needed to improve the prognosis of patients with this disease. Recent advances in cancer genomics have revealed the genetic landscape of pancreatic cancer, and clinical trials are currently being conducted to match the treatment to underlying mutations. Liquid biopsy-based diagnosis is a promising method to start personalized treatment. In addition to genome-based medicine, personalized models have been studied as a tool to test candidate drugs to select the most efficacious treatment. The innovative three-dimensional organoid culture platform, as well as patient-derived xenografts can be used to conduct genomic and functional studies to enable personalized treatment approaches. Combining genome-based medicine with drug screening based on personalized models may fulfill the promise of precision medicine for pancreatic cancer.

Elevated HNF1A expression promotes radiation-resistance via driving PI3K/AKT signaling pathway in esophageal squamous cell carcinoma cells

Purpose: Radiotherapy is a major modality for treatment of local advanced esophageal squamous cell carcinoma (ESCC). Hepatocyte nuclear factor 1-alpha (HNF1A) is involved in regulation of tumor cell proliferation, apoptosis, cycle distribution, invasion metastasis and chemical resistance. The aim of this study was to investigate the effect of HNF1A on radiosensitivity of ESCC cells. Methods: In our study, HNF1A expression was verified from GEPIA in multiple types of cancer. The prognostic value of HNF1A in ESCC was obtained by TCGA database. In addition, the expression of HNF1A in ESCC cell lines was verified by western blot. Subsequently, lentiviruses were used to construct HNF1A overexpressed cell lines TE1 and KYSE150.Then, the roles of HNF1A on cell proliferation, invasion, apoptosis, cell cycle distribution and radiosensitivity were verified. Furthermore, the relationship between HNF1A and γH2AX were determined by western blot and immunofluorescence. We also detected the expression changes of key factors in PI3K/AKT pathway after overexpression of HNF1A. Results: The results showed that the overexpression of HNF1A promoted cell proliferation and invasion with or without irradiation (IR), and potently radiation-resistance ESCC cells with a sensitization enhancement ratio (SER) of 0.76 and 0.87. In addition, HNF1A regulated Cyclin D1 and CDK4 proteins to promote the transition from radiation-induced G0/G1 phase arrest to S phase, and coordinated BAX and BCL2 proteins to reduce the occurrence of radiation-induced apoptosis. It was worth noting that HNF1A might be involved in radiation-induced DNA damage repair by regulating γH2AX though PI3K/AKT signal pathway. Conclusion: Our study preliminarily suggested that HNF1A was associated with the progression and radiosensitivity of ESCC cells, and it might reduce the radiosensitivity of ESCC cells by promoting cell proliferation, releasing G0/G1 phase arrest, reducing apoptosis, and regulating the expression of γH2AX protein though driving PI3K/AKT signal pathway.

Prediction of Tumor Cellularity in Resectable PDAC from Preoperative Computed Tomography Imaging

Simple Summary

Pancreatic ductal adenocarcinoma (PDAC) remains a devastating disease. However, variations in tumor biology influence individual patient outcomes greatly. We previously showed a strong association between magnetic resonance imaging-based tumor cell estimates and patient survival. In this study we aimed to transfer this finding to more broadly applied computed tomography (CT) imaging for non-invasive risk stratification. We correlated in vivo CT imaging with histopathological analyses and could show a strong association between regional Hounsfield Units (HU) and tumor cellularity. In conclusion, our study suggests CT-based tumor cell estimates as a widely applicable way of non-invasive tumor cellularity characterization in PDAC.

Abstract

Background: PDAC remains a tumor entity with poor prognosis and a 5-year survival rate below 10%. Recent research has revealed invasive biomarkers, such as distinct molecular subtypes, predictive for therapy response and patient survival. Non-invasive prediction of individual patient outcome however remains an unresolved task. Methods: Discrete cellularity regions of PDAC resection specimen (n = 43) were analyzed by routine histopathological work up. Regional tumor cellularity and CT-derived Hounsfield Units (HU, n = 66) as well as iodine concentrations were regionally matched. One-way ANOVA and pairwise t-tests were performed to assess the relationship between different cellularity level in conventional, virtual monoenergetic 40 keV (monoE 40 keV) and iodine map reconstructions. Results: A statistically significant negative correlation between regional tumor cellularity in histopathology and CT-derived HU from corresponding image regions was identified. Radiological differentiation was best possible in monoE 40 keV CT images. However, HU values differed significantly in conventional reconstructions as well, indicating the possibility of a broad clinical application of this finding. Conclusion: In this study we establish a novel method for CT-based prediction of tumor cellularity for in-vivo tumor characterization in PDAC patients.

Gene expression profiling of morphologic subtypes of pancreatic ductal adenocarcinoma using surgical and EUS-FNB specimens

BACKGROUND/OBJECTIVES

Various classifications of pancreatic ductal adenocarcinoma (PDAC) based on RNA profiling resulted in two main subtypes. Kalimuthu and coworkers proposed a morphology-based classification that concurred with these subtypes. Immune therapy approaches in PDAC were so far disappointing. Morphologic PDAC subtypes may differ regarding key immune-oncology pathways. We aimed to examine the reproducibility and prognostic value of Kalimuthu's morphologic classification, and to evaluate differences between subtypes regarding gene expression related to tumor biology and immune-oncology.

METHODS

PDAC specimens from 196 patients were included, 108 consecutive chemotherapy-naïve surgical specimens and 88 endoscopic ultrasound-guided fine needle biopsies (EUS-FNBs). The specimens were evaluated as per Kalimuthu by two pancreatic pathologists, resulting in Group A and Group B tumors. Digital mRNA expression profiling was performed, on the surgical specimens using the NanoString IO360 panel of 770 key tumor biology related and 30 custom-genes, and on the EUS-FNBs using a targeted panel of 123 genes.

RESULTS

Morphologic subtyping reached substantial interobserver agreement between the two pathologists. In the surgical and EUS-FNB cohorts, 44.4% and 38.6% were Group A tumors, which were associated with improved survival. Group A showed higher expression of immune-related genes and cytokine/chemokine/interleukin signaling and Group B of genes related to cancer cell proliferation and cell cycle regulation. Hierarchical clustering based on significant differences in gene expression levels between Groups A and B revealed clusters with prognostic value.

CONCLUSIONS

Morphologic subtyping according to Kalimuthu is reproducible and holds prognostic value, in surgical as well as EUS-FNB specimens. As upregulation of immune-related genes was found in Group A, future studies should evaluate the potential of immune therapy approaches with special emphasis on this subtype of PDAC.

Identification of laminin γ2 as a prognostic and predictive biomarker for determining response to gemcitabine-based therapy in pancreatic ductal adenocarcinoma

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies. While the extracellular matrix component plays an integral role in PDAC pathogenesis and mediating chemoresistance, its role in predicting response to chemotherapy in patients with PDAC remains unclear.

METHODS

We performed a systematic biomarker discovery by analysing genome-wide transcriptomic profiling data from 423 patients (GSE71729, GSE21501 and The Cancer Genome Atlas [TCGA]) for predicting overall survival (OS). This was subsequently validated in two independent clinical cohorts of 270 patients with PDAC (training cohort, n = 121, and validation cohort, n = 149). In addition, we investigated endoscopic ultrasound-fine needle aspiration biopsy specimens from 51 patients with PDAC with an unresectable cancer for predicting therapeutic response to gemcitabine-based therapy.

RESULTS

After rigorous bioinformatic analysis, we identified laminin γ2 (LAMC2) to be a significant prognostic factor in all three PDAC data sets (GSE71729: hazard ratio [HR] = 2.04, P = 0.002; GSE21501: HR = 2.17, P = 0.031; TCGA: HR = 2.57, P < 0.001). High LAMC2 expression in patients with PDAC was associated with a significantly poor OS and relapse-free survival in both the training (P < 0.001, P < 0.001) and validation cohorts (P = 0.001, P = 0.026). More importantly, LAMC2 expression robustly identified patients with PDAC and unresectable disease and those who responded to gemcitabine-based therapy (area under the curve = 0.79; 95% confidence interval [CI], 0.65-0.89). The univariate logistic regression analysis revealed that high LAMC2 expression was the only factor that predicted poor response to gemcitabine in patients with PDAC (odds ratio = 4.90; 95% CI, 1.45-16.6; P = 0.011).

CONCLUSION

We conclude that LAMC2 is a novel prognostic and predictive biomarker for gemcitabine-based therapy in both the adjuvant and palliative setting; which could have significant impact on precision and individualised treatment of patients with PDAC.

Pancreatic ductal adenocarcinoma progression is restrained by stromal matrix

Desmoplasia describes the deposition of extensive extracellular matrix and defines primary pancreatic ductal adenocarcinoma (PDA). The acellular component of this stroma has been implicated in PDA pathogenesis and is being targeted therapeutically in clinical trials. By analyzing the stromal content of PDA samples from numerous annotated PDA data sets and correlating stromal content with both anatomic site and clinical outcome, we found PDA metastases in the liver, the primary cause of mortality to have less stroma, have higher tumor cellularity than primary tumors. Experimentally manipulating stromal matrix with an anti-lysyl oxidase like-2 (anti-LOXL2) antibody in syngeneic orthotopic PDA mouse models significantly decreased matrix content, led to lower tissue stiffness, lower contrast retention on computed tomography, and accelerated tumor growth, resulting in diminished overall survival. These studies suggest an important protective role of stroma in PDA and urge caution in clinically deploying stromal depletion strategies.

Hepatocyte nuclear factor 1 alpha influences pancreatic cancer growth and metastasis

Hepatocyte nuclear factor 1 homeobox alpha (HNF1α) is a transcription factor involved in endodermal organogenesis and pancreatic precursor cell differentiation and development. Earlier studies have reported a role for HNF1α in pancreatic ductal adenocarcinoma (PDAC) but it is controversial. The mechanism by which it impacts PDAC is yet to be explored in depth. In this study, using the online databases we observed that HNF1α is upregulated in PDAC, which was also confirmed by our immunohistochemical analysis of PDAC tissue microarray. Silencing HNF1α reduced the proliferative, migratory, invasive and colony forming capabilities of pancreatic cancer cells. Key markers involved in these processes (pPI3K, pAKT, pERK, Bcl2, Zeb, Snail, Slug) were significantly changed in response to alterations in HNF1α expression. On the other hand, overexpression of HNF1α did not induce any significant change in the aggressiveness of pancreatic cancer cells. Our results demonstrate that reduced expression of HNF1α leads to inhibition of pancreatic cancer growth and progression, which indicates that it could be a potential oncogene and target for PDAC.

Targeting the ubiquitin-proteasome system in a pancreatic cancer subtype with hyperactive MYC

The myelocytomatosis oncogene (MYC) is an important driver in a subtype of pancreatic ductal adenocarcinoma (PDAC). However, MYC remains a challenging therapeutic target; therefore, identifying druggable synthetic lethal interactions in MYC‐active PDAC may lead to novel precise therapies. First, to identify networks with hyperactive MYC, we profiled transcriptomes of established human cell lines, murine primary PDAC cell lines, and accessed publicly available repositories to analyze transcriptomes of primary human PDAC. Networks active in MYC‐hyperactive subtypes were analyzed by gene set enrichment analysis. Next, we performed an unbiased pharmacological screen to define MYC‐associated vulnerabilities. Hits were validated by analysis of drug response repositories and genetic gain‐ and loss‐of‐function experiments. In these experiments, we discovered that the proteasome inhibitor bortezomib triggers a MYC‐associated vulnerability. In addition, by integrating publicly available data, we found the unfolded protein response as a signature connected to MYC. Furthermore, increased sensitivity of MYC‐hyperactive PDACs to bortezomib was validated in genetically modified PDAC cells. In sum, we provide evidence that perturbing the ubiquitin–proteasome system (UPS) might be an option to target MYC‐hyperactive PDAC cells. Our data provide the rationale to further develop precise targeting of the UPS as a subtype‐specific therapeutic approach.

CES2 Expression in Pancreatic Adenocarcinoma Is Predictive of Response to Irinotecan and Is Associated With Type 2 Diabetes

PURPOSE

The combination chemotherapy of fluorouracil, leucovorin, irinotecan, and oxaliplatin (FOLFIRINOX) has provided clinically meaningful improvement for pancreatic ductal adenocarcinoma (PDAC). We previously uncovered a role for the serine hydrolase carboxylesterase 2 (CES2) in mediating intratumoral activation of the prodrug irinotecan, a constituent of FOLFIRINOX. We aimed to further test the predictive value of CES2 for response to irinotecan using patient-derived xenograft (PDX) models and to elucidate the determinants of CES2 expression and response to FOLFIRINOX treatment among patients with PDAC.

METHODS

PDXs were engrafted subcutaneously into nude mice and treated for 4 weeks with either saline control or irinotecan. CES2 and hepatocyte nuclear factor 4 alpha (HNF4A) expression in PDAC tissues was evaluated by immunohistochemical and Western blot analysis. Kaplan-Meier and Cox regression analyses were applied to assess the association between overall survival and hemoglobin A1C (HbA1C) levels in patients who underwent neoadjuvant FOLFIRINOX treatment.

RESULTS

High CES2 activity in PDAC PDXs was associated with increased sensitivity to irinotecan. Integrated gene expression, proteomic analyses, and in vitro genetic experiments revealed that nuclear receptor HNF4A, which is upregulated in diabetes, is the upstream transcriptional regulator of CES2 expression. Elevated CES2 protein expression in PDAC tissues was positively associated with a history of type 2 diabetes (odds ratio, 4.84; P = .02). High HbA1C levels were associated with longer overall survival in patients who received neoadjuvant FOLFIRINOX treatment (P = .04).

CONCLUSION

To our knowledge, we provide, for the first time, evidence that CES2 expression is associated with a history of type 2 diabetes in PDAC and that elevated HbA1C, by predicting tumor CES2 expression, may represent a novel marker for stratifying patients most likely to respond to FOLFIRINOX therapy.

Detection of Chemotherapy-resistant Pancreatic Cancer Using a Glycan Biomarker, sTRA

PURPOSE

A subset of pancreatic ductal adenocarcinomas (PDACs) is highly resistant to systemic chemotherapy, but no markers are available in clinical settings to identify this subset. We hypothesized that a glycan biomarker for PDACs called sialylated tumor-related antigen (sTRA) could be used for this purpose.

EXPERIMENTAL DESIGN

We tested for differences between PDACs classified by glycan expression in multiple systems: sets of cell lines, organoids, and isogenic cell lines; primary tumors; and blood plasma from human subjects.

RESULTS

The sTRA-expressing models tended to have stem-like gene expression and the capacity for mesenchymal differentiation, in contrast to the nonexpressing models. The sTRA cell lines also had significantly increased resistance to seven different chemotherapeutics commonly used against pancreatic cancer. Patients with primary tumors that were positive for a gene expression classifier for sTRA received no statistically significant benefit from adjuvant chemotherapy, in contrast to those negative for the signature. In another cohort, based on direct measurements of sTRA in tissue microarrays, the patients who were high in sTRA again had no statistically significant benefit from adjuvant chemotherapy. Furthermore, a blood plasma test for the sTRA glycan identified the PDACs that showed rapid relapse following neoadjuvant chemotherapy.

CONCLUSIONS

This research demonstrates that a glycan biomarker could have value to detect chemotherapy-resistant PDAC in clinical settings. This capability could aid in the development of stratified treatment plans and facilitate biomarker-guided trials targeting resistant PDAC.

3D histopathology of human tumours by fast clearing and ultramicroscopy

Here, we describe a novel approach that allows pathologists to three-dimensionally analyse malignant tissues, including the tumour-host tissue interface. Our visualization technique utilizes a combination of ultrafast chemical tissue clearing and light-sheet microscopy to obtain virtual slices and 3D reconstructions of up to multiple centimetre sized tumour resectates. For the clearing of tumours we propose a preparation technique comprising three steps: (a) Fixation and enhancement of tissue autofluorescence with formalin/5-sulfosalicylic acid. (b) Ultrafast active chemical dehydration with 2,2-dimethoxypropane and (c) refractive index matching with dibenzyl ether at up to 56 °C. After clearing, the tumour resectates are imaged. The images are computationally post-processed for contrast enhancement and artefact removal and then 3D reconstructed. Importantly, the sequence a–c is fully reversible, allowing the morphological correlation of one and the same histological structures, once visualized with our novel technique and once visualized by standard H&E- and IHC-staining. After reverting the clearing procedure followed by standard H&E processing, the hallmarks of ductal carcinoma in situ (DCIS) found in the cleared samples could be successfully correlated with the corresponding structures present in H&E and IHC staining. Since the imaging of several thousands of optical sections is a fast process, it is possible to analyse a larger part of the tumour than by mechanical slicing. As this also adds further information about the 3D structure of malignancies, we expect that our technology will become a valuable addition for histological diagnosis in clinical pathology.

Intraductal Transplantation Models of Human Pancreatic Ductal Adenocarcinoma Reveal Progressive Transition of Molecular Subtypes

Pancreatic ductal adenocarcinoma (PDAC) is the most lethal common malignancy, with little improvement in patient outcomes over the past decades. Recently, subtypes of pancreatic cancer with different prognoses have been elaborated; however, the inability to model these subtypes has precluded mechanistic investigation of their origins. Here, we present a xenotransplantation model of PDAC in which neoplasms originate from patient-derived organoids injected directly into murine pancreatic ducts. Our model enables distinction of the two main PDAC subtypes: intraepithelial neoplasms from this model progress in an indolent or invasive manner representing the classical or basal-like subtypes of PDAC, respectively. Parameters that influence PDAC subtype specification in this intraductal model include cell plasticity and hyperactivation of the RAS pathway. Finally, through intratumoral dissection and the direct manipulation of RAS gene dosage, we identify a suite of RAS-regulated secreted and membrane-bound proteins that may represent potential candidates for therapeutic intervention in patients with PDAC. SIGNIFICANCE: Accurate modeling of the molecular subtypes of pancreatic cancer is crucial to facilitate the generation of effective therapies. We report the development of an intraductal organoid transplantation model of pancreatic cancer that models the progressive switching of subtypes, and identify stochastic and RAS-driven mechanisms that determine subtype specification.See related commentary by Pickering and Morton, p. 1448.This article is highlighted in the In This Issue feature, p. 1426.

Comparison of FOLFIRINOX and Gemcitabine Plus Nab-paclitaxel for Treatment of Metastatic Pancreatic Cancer: Using Korean Pancreatic Cancer (K-PaC) Registry

OBJECTIVE

By using the Korean Pancreatic Cancer (K-PaC) registry, we compared the clinical outcomes of FOLFIRINOX (FFX) and gemcitabine plus nab-paclitaxel (GNP) in patients with metastatic pancreatic cancer (MPC).

METHODS

We constructed a web-based database of 3748 anonymized patients diagnosed with pancreatic ductal adenocarcinoma. MPC patients who received first-line FFX or GNP were enrolled. Overall survival (OS), progression-free survival, grade III to IV toxicity, and cross-over treatment were analyzed.

RESULTS

A total of 413 patients (232 vs. 181, FFX vs. GNP; all data are presented in this sequence) were eligible. Median age was 63 years (60 vs. 69 y) with 43% (39% vs. 47%) comprising female individuals. The major metastatic sites were the liver (64%), peritoneum (25%), and distant lymph nodes (18%). The median OS was 11.5 versus 12.7 months (hazard ratio [HR]=0.87, 95% confidence interval [CI]: 0.68-1.12, P=0.286), and median progression-free survival was 7.5 versus 8.1 months (HR=0.92, 95% CI: 0.70-1.20, P=0.517), respectively. The frequency of grade III to IV febrile neutropenia was higher in the FFX group (18% vs. 11%, P=0.040), and that of peripheral neuropathy was higher in the GNP group (8% vs. 14%, P=0.046). The chance to receive second-line chemotherapy was higher in the GNP group (45% vs. 56%, P=0.036). In the cross-over treatment, the median OS of the FFX-GNP group (n=43) and the GNP-FFX group (n=47) was 16.8 versus 17.7 months (HR=0.79, 95% CI: 0.44-1.41, P=0.425).

CONCLUSIONS

FFX and GNP showed similar efficacy and comparable toxicity in MPC patients. Although the GNP group had a higher chance to receive second-line chemotherapy, they did not have improved overall survival.

Anti-Proliferative and Apoptosis-Promoting Effect of microRNA-125b on Pancreatic Cancer by Targeting NEDD9 via PI3K/AKT Signaling

PURPOSE

The expression of microRNA-125b (miR-125b) is low in a variety of cancers, including gastric, lung, bladder, thyroid, and esophageal cancers. However, its specific mechanism in pancreatic ductal adenocarcinoma (PDAC) remains unclear. This study is aimed to explore the role of miR-125b in PDAC.

METHODS

PDAC tissues and adjacent tissues were collected for miR-125b analysis by qRT-PCR. Different PDAC cell lines were cultured for miR-125b detection by qRT-PCR, and CAPAN1 cells were selected for the downstream experiments. Cell proliferation was characterized by methyl thiazolyl tetrazolium (MTT) and 5-bromo-2-deoxyUridine (BrdU) staining. Flow cytometry was utilized for apoptosis and cell cycle changes. Cell invasion was determined by the Transwell assay and the dual-luciferase assay was utilized for validating the target gene. Western blotting was used to detect apoptosis related and PI3K/AKT signaling proteins.

RESULTS

miR-125b was significantly down-regulated in human PDAC tissues and cell lines (P < 0.05). miR-125b inhibited the growth and invasion of CAPAN1 cells, facilitated apoptosis, and blocked the cell cycle at the G0/G1 phase. Furthermore, miR-125 directly targeted NEDD9. The high expression of NEDD9 impaired the anti-proliferative and anti-apoptotic activity of miR-125b. miR-125b also inhibited apoptosis-related proteins and PI3K/AKT signaling pathways via NEDD9.

CONCLUSION

miR-125b decreased cell growth and invasion, and facilitated apoptosis in CAPAN1 cells through PI3K/AKT inhibition via targeting NEDD9.

Implementing cell-free DNA of pancreatic cancer patient-derived organoids for personalized oncology

One of the major challenges in using pancreatic cancer patient-derived organoids (PDOs) in precision oncology is the time from biopsy to functional characterization. This is particularly true for endoscopic ultrasound-guided fine-needle aspiration biopsies, typically resulting in specimens with limited tumor cell yield. Here, we tested conditioned media of individual PDOs for cell-free DNA to detect driver mutations already early on during the expansion process to accelerate the genetic characterization of PDOs as well as subsequent functional testing. Importantly, genetic alterations detected in the PDO supernatant, collected as early as 72 hours after biopsy, recapitulate the mutational profile of the primary tumor, indicating suitability of this approach to subject PDOs to drug testing in a reduced time frame. In addition, we demonstrated that this workflow was practicable, even in patients for whom the amount of tumor material was not sufficient for molecular characterization by established means. Together, our findings demonstrate that generating PDOs from very limited biopsy material permits molecular profiling and drug testing. With our approach, this can be achieved in a rapid and feasible fashion with broad implications in clinical practice.

SUMO pathway inhibition targets an aggressive pancreatic cancer subtype

OBJECTIVE

Pancreatic ductal adenocarcinoma (PDAC) still carries a dismal prognosis with an overall 5-year survival rate of 9%. Conventional combination chemotherapies are a clear advance in the treatment of PDAC; however, subtypes of the disease exist, which exhibit extensive resistance to such therapies. Genomic MYC amplifications represent a distinct subset of PDAC with an aggressive tumour biology. It is clear that hyperactivation of MYC generates dependencies that can be exploited therapeutically. The aim of the study was to find and to target MYC-associated dependencies.

DESIGN

We analysed human PDAC gene expression datasets. Results were corroborated by the analysis of the small ubiquitin-like modifier (SUMO) pathway in a large PDAC cohort using immunohistochemistry. A SUMO inhibitor was used and characterised using human and murine two-dimensional, organoid and in vivo models of PDAC.

RESULTS

We observed that MYC is connected to the SUMOylation machinery in PDAC. Components of the SUMO pathway characterise a PDAC subtype with a dismal prognosis and we provide evidence that hyperactivation of MYC is connected to an increased sensitivity to pharmacological SUMO inhibition.

CONCLUSION

SUMO inhibitor-based therapies should be further developed for an aggressive PDAC subtype.

Epigenetic silencing of AATK in acinar to ductal metaplasia in murine model of pancreatic cancer

Background

Cancer subtype switching, which involves unclear cancer cell origin, cell fate decision, and transdifferentiation of cells within a confined tumor microenvironment, remains a major problem in pancreatic cancer (PDA).

Results

By analyzing PDA subtypes in The Cancer Genome Atlas, we identified that epigenetic silencing of apoptosis-associated tyrosine kinase (AATK) inversely was correlated with mRNA expression and was enriched in the quasi-mesenchymal cancer subtype. By comparing early mouse pancreatic lesions, the non-invasive regions showed AATK co-expression in cells with acinar-to-ductal metaplasia, nuclear VAV1 localization, and cell cycle suppression; but the invasive lesions conversely revealed diminished AATK expression in those with poorly differentiated histology, cytosolic VAV1 localization, and co-expression of p63 and HNF1α. Transiently activated AATK initiates acinar differentiation into a ductal cell fate to establish apical-basal polarization in acinar-to-ductal metaplasia. Silenced AATK and ectopically expressed p63 and HNF1α allow the proliferation of ductal PanINs in mice.

Conclusion

Epigenetic silencing of AATK regulates the cellular transdifferentiation, proliferation, and cell cycle progression in converting PDA-subtypes.

Multiparametric Modelling of Survival in Pancreatic Ductal Adenocarcinoma Using Clinical, Histomorphological, Genetic and Image-Derived Parameters

Rationale: Pancreatic ductal adenocarcinoma (PDAC) remains a tumor entity of exceptionally poor prognosis, and several biomarkers are under current investigation for the prediction of patient prognosis. Many studies focus on promoting newly developed imaging biomarkers without a rigorous comparison to other established parameters. To assess the true value and leverage the potential of all efforts in this field, a multi-parametric evaluation of the available biomarkers for PDAC survival prediction is warranted. Here we present a multiparametric analysis to assess the predictive value of established parameters and the added contribution of newly developed imaging features such as biomarkers for overall PDAC patient survival. Methods: 103 patients with resectable PDAC were retrospectively enrolled. Clinical and histopathological data (age, sex, chemotherapy regimens, tumor size, lymph node status, grading and resection status), morpho-molecular and genetic data (tumor morphology, molecular subtype, tp53, kras, smad4 and p16 genetics), image-derived features and the combination of all parameters were tested for their prognostic strength based on the concordance index (CI) of multivariate Cox proportional hazards survival modelling after unsupervised machine learning preprocessing. Results: The average CIs of the out-of-sample data were: 0.63 for the clinical and histopathological features, 0.53 for the morpho-molecular and genetic features, 0.65 for the imaging features and 0.65 for the combined model including all parameters. Conclusions: Imaging-derived features represent an independent survival predictor in PDAC and enable the multiparametric, machine learning-assisted modelling of postoperative overall survival with a high performance compared to clinical and morpho-molecular/genetic parameters. We propose that future studies systematically include imaging-derived features to benchmark their additive value when evaluating biomarker-based model performance.

Prognostic and predictive factors in pancreatic cancer

Pancreatic cancer is one of the leading causes of cancer death worldwide. Its high mortality rate has remained unchanged for years. Radiotherapy and surgery are considered standard treatments in early and locally advanced stages. Chemotherapy is the only option for metastatic patients. Two treatment regimens, i. e. the association of 5-fluorouracil- irinotecan-oxaliplatin (FOLFIRINOX) and the association of nab-paclitaxel with gemcitabine, have been shown to improve outcomes for metastatic pancreatic adenocarcinoma patients. However, there are not standardized predictive biomarkers able to identify patients who benefit most from treatments. CA19-9 is the most studied prognostic biomarker, its predictive role remains unclear. Other clinical, histological and molecular biomarkers are emerging in prognostic and predictive settings. The aim of this review is to provide an overview of prognostic and predictive markers used in clinical practice and to explore the most promising fields of research in terms of treatment selection and tailored therapy in pancreatic cancer.

Image-Based Molecular Phenotyping of Pancreatic Ductal Adenocarcinoma

To bridge the translational gap between recent discoveries of distinct molecular phenotypes of pancreatic cancer and tangible improvements in patient outcome, there is an urgent need to develop strategies and tools informing and improving the clinical decision process. Radiomics and machine learning approaches can offer non-invasive whole tumor analytics for clinical imaging data-based classification. The retrospective study assessed baseline computed tomography (CT) from 207 patients with proven pancreatic ductal adenocarcinoma (PDAC). Following expert level manual annotation, Pyradiomics was used for the extraction of 1474 radiomic features. The molecular tumor subtype was defined by immunohistochemical staining for KRT81 and HNF1a as quasi-mesenchymal (QM) vs. non-quasi-mesenchymal (non-QM). A Random Forest machine learning algorithm was developed to predict the molecular subtype from the radiomic features. The algorithm was then applied to an independent cohort of histopathologically unclassifiable tumors with distinct clinical outcomes. The classification algorithm achieved a sensitivity, specificity and ROC-AUC (area under the receiver operating characteristic curve) of 0.84 ± 0.05, 0.92 ± 0.01 and 0.93 ± 0.01, respectively. The median overall survival for predicted QM and non-QM tumors was 16.1 and 20.9 months, respectively, log-rank-test p = 0.02, harzard ratio (HR) 1.59. The application of the algorithm to histopathologically unclassifiable tumors revealed two groups with significantly different survival (8.9 and 39.8 months, log-rank-test p < 0.001, HR 4.33). The machine learning-based analysis of preoperative (CT) imaging allows the prediction of molecular PDAC subtypes highly relevant for patient survival, allowing advanced pre-operative patient stratification for precision medicine applications.

Role of imaging biomarkers for prognostic prediction in patients with pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive tumours. PDAC has a poor prognosis; therefore, it is necessary to perform further risk stratification. Identifying prognostic factors before treatment might help to implement suitable and personalised treatment for individuals and avoid side effects. Conventional staging systems and tumour biomarkers are fundamental to establish prognosis; however, they have obvious limitations. Novel imaging biomarkers extracted from advanced imaging techniques offer opportunities to evaluate underlying tumour physiological characteristics, such as mutational status, cellular composition, local microenvironment, tumour metabolism, and biological behaviour. Thus, imaging biomarkers might help the decision making of oncologists and surgeons. The present review discusses the functions of imaging biomarkers for prognostic prediction in patients with PDAC and their potential value for further translation in clinical practice.