Desmoplasia and Biophysics in Pancreatic Ductal Adenocarcinoma: Can We Learn From Breast Cancer?

MRI-based multiregional radiomics for desmoplastic reaction classification and prognosis stratification in stage II rectal cancer: A bicenter study

PURPOSE

To develop an MRI-based multiregional radiomics model for the noninvasive desmoplastic reaction (DR) classification and prognosis stratification in stage II rectal cancer (RC) patients.

MATERIALS AND METHODS

This study retrospectively involved 336 patients with RC from two centers, with 239 from Center 1 divided into training (n = 191) and internal validation (n = 48) datasets at an 8:2 ratio, and 97 from Center 2 serving as external validation dataset. Radiomics features were extracted, and a multiregional radiomics DR (M-RDR) signature was established using multi-level feature selection procedure. The cut-off value for M-RDR was determined using Youden's index. We further evaluated the predictive values of M-RDR on prognosis and adjuvant chemotherapy stratification. The primary outcome was 3-year disease-free survival (DFS), and cox model performance was assessed using AUCs and 95 % confidence intervals.

RESULTS

M-RDR demonstrated a high accuracy in DR classification with AUCs of 0.778 and 0.798 in the training and internal validation datasets. Multivariable analysis confirmed M-RDR as an independent prognostic factor after adjusting for clinicopathological factors.The combined model incorporating M-RDR and clinicopathological factors showed good performance in predicting 3-year DFS, with AUCs of 0.923, 0.908, and 0.891 in the training, internal validation and external validation datasets, respectively. Additionally, patients in the M-RDR-high group who received adjuvant chemotherapy had significantly better DFS compared with those who did not (P < 0.05).

CONCLUSION

The MRI-based multiregional radiomics model could effectively improve non-invasive DR classification, and was able to enhance postoperative risk stratification and treatment decision-making in stage II RC patients.

Extracellular Volume Derived from Equilibrium CT for the Prediction of Survival Outcomes in Patients with Pancreatic Ductal Adenocarcinoma

ObjectiveTo assess the efficiency of extracellular volume (ECV) derived from equilibrium computed tomography (CT) in predicting recurrence-free survival (RFS) and overall survival (OS) after R0 resection of pancreatic ductal adenocarcinoma (PDAC).MethodsThis retrospective study included 83 patients who underwent CT and R0 resection between January 2016 and September 2023. The pattern of tumor recurrence and prognosis were recorded for each patient. Tumor recurrence was classified into three groups: isolated local recurrence group, distant recurrence group and censored group. The associations between the CT-ECV and clinicopathological features and recurrence pattern of PDAC were evaluated by chi-squared test. Multivariable Cox proportional-hazards models were conducted to evaluate the effects of clinical factors, CT features and CT-ECV on RFS and OS.ResultsThe median RFS and OS were 10.7 and 17.1 months, respectively. On multivariate analysis, the CT-ECV and adjacent organ invasion were found to be associated with RFS (HR, 0.968, P = .017; HR, 0.453; P = .006), and only the CT-ECV was an independent prognostic factor for OS (HR, 0.968; P = .022). Low CT-ECV group was significantly associated with elevated CA19-9, larger tumor size, G3 (tumor grade) and II/III (AJCC tumor stage) (P < .05). In the recurrence pattern analysis, the CT-ECV did not exhibit an association between local recurrence and non-local recurrence groups (P = .455), while patients in the low CT-ECV group were more inclined to experience distant recurrence after curative surgery (P = .037).ConclusionsCT-ECV determined by equilibrium contrast-enhanced CT was a useful imaging biomarker for predicting distant recurrence and survival in resectable PDAC patients, which may facilitate further risk stratification and personalized care.

Embedded Bioprinting of Tumor-Scale Pancreatic Cancer-Stroma 3D Models for Preclinical Drug Screening

The establishment of organotypic preclinical models that accurately resemble the native tumor microenvironment at an anatomic human scale is highly desirable to level up in vitro platforms potential for screening candidate therapies. The bioengineering of anatomic-scaled three-dimensional (3D) models that emulate native tumor scale while recapitulating their cellular and matrix components remains, however, to be fully realized. In this focus, herein, we leveraged embedded 3D bioprinting for biofabricating pancreatic ductal adenocarcinoma (PDAC) in vitro models combining gelatin-methacryloyl and hyaluronic acid methacrylate extracellular matrix (ECM)-mimetic biomaterials with human pancreatic cancer cells and cancer-associated fibroblasts to generate in vitro models capable of emulating native tumor size (∼6 mm) and stromal elements. By using a viscoelastic continuous polymeric supporting bath, tumor-scale 3D models were rapidly generated (∼50 constructs/h) and easily recovered following in-bath visible light photocrosslinking. As a proof-of-concept, tissue-scale constructs displaying physiomimetic designs were biofabricated. These models also encompass the incorporation of a stromal compartment to better emulate the cellular components of the PDAC native tumor microenvironment (TME) and its stratified spatial organization. Cell-laden tumor-size constructs remained viable for up to 14 days and were responsive to Gemcitabine in a dose-dependent mode. Cancer-stroma models also exhibited increased drug resistance compared to their monotypic counterparts, highlighting the key role of stromal cells in chemotherapeutic resistance. Overall, we report for the first time the freeform biofabrication of PDAC models exhibiting anatomic scale, different structural complexities, and engineered cancer-stromal compartments, being highly valuable for preclinical screening of therapeutics.

MUC16 Retention after Neoadjuvant Chemotherapy in Pancreatic Ductal Adenocarcinoma

Background/Objectives: Pancreatic ductal adenocarcinoma (PDAC) has a poor prognosis. Currently, surgical resection is the only potentially curative treatment. Unfortunately, less than 20% of PDAC patients are eligible for surgical resection at diagnosis. In the past few decades, neoadjuvant chemotherapy treatment (NCT) has been investigated as a way to downstage PDAC tumors for surgical resection. Fluorescence-guided surgery (FGS) is a technique that can aid in increasing complete resection rates by enhancing the tumor through passive or active targeting of a contrast agent. In active targeting, a probe (e.g., antibody) binds a protein differentially upregulated in the tumor compared to normal tissue. Mucin 16 (MUC16), a transmembrane glycoprotein, has recently been explored as an FGS target in preclinical tumor models. However, the impact of chemotherapy on MUC16 expression is unknown. Methods: To investigate this issue, immunohistochemistry was performed on PDAC patient samples. Results: We found that MUC16 expression was retained after NCT in patient samples (mean expression = 5.7) with minimal change in expression between the matched diagnostic (mean expression = 3.66) and PDAC NCT patient samples (mean expression = 4.5). Conclusions: This study suggests that MUC16 is a promising target for FGS and other targeted therapies in PDAC patients treated with NCT.

Tumour evolution and microenvironment interactions in 2D and 3D space

To study the spatial interactions among cancer and non-cancer cells1, we here examined a cohort of 131 tumour sections from 78 cases across 6 cancer types by Visium spatial transcriptomics (ST). This was combined with 48 matched single-nucleus RNA sequencing samples and 22 matched co-detection by indexing (CODEX) samples. To describe tumour structures and habitats, we defined 'tumour microregions' as spatially distinct cancer cell clusters separated by stromal components. They varied in size and density among cancer types, with the largest microregions observed in metastatic samples. We further grouped microregions with shared genetic alterations into 'spatial subclones'. Thirty five tumour sections exhibited subclonal structures. Spatial subclones with distinct copy number variations and mutations displayed differential oncogenic activities. We identified increased metabolic activity at the centre and increased antigen presentation along the leading edges of microregions. We also observed variable T cell infiltrations within microregions and macrophages predominantly residing at tumour boundaries. We reconstructed 3D tumour structures by co-registering 48 serial ST sections from 16 samples, which provided insights into the spatial organization and heterogeneity of tumours. Additionally, using an unsupervised deep-learning algorithm and integrating ST and CODEX data, we identified both immune hot and cold neighbourhoods and enhanced immune exhaustion markers surrounding the 3D subclones. These findings contribute to the understanding of spatial tumour evolution through interactions with the local microenvironment in 2D and 3D space, providing valuable insights into tumour biology.

Revealing a cancer-associated fibroblast-based risk signature for pancreatic adenocarcinoma through single-cell and bulk RNA-seq analysis

PURPOSE

Proliferation of stromal connective tissue is a hallmark of pancreatic adenocarcinoma (PAAD). The engagement of activated cancer-associated fibroblasts (CAFs) contributes to the progression of PAAD through their involvement in tumor fibrogenesis. However, the prognostic significance of CAF-based risk signature in PAAD has not been explored.

METHODS

The single-cell RNA sequencing (scRNA-seq) data sourced from GSE155698 within the Gene Expression Omnibus (GEO) database was supplemented by bulk RNA sequencing data from The Cancer Genome Atlas (TCGA) and microarray data retrieved from the GEO database. The scRNA-seq data underwent processing via the Seurat package to identify distinct CAF clusters utilizing specific CAF markers. Differential gene expression analysis between normal and tumor samples was conducted within the TCGA-PAAD cohort. Univariate Cox regression analysis pinpointed genes associated with CAF clusters, identifying prognostic CAF-related genes. These genes were utilized in LASSO regression to craft a predictive risk signature. Subsequently, integrating clinicopathological traits and the risk signature, a nomogram model was constructed.

RESULTS

Our scRNA-seq analysis unveiled four distinct CAF clusters in PAAD, with two linked to PAAD prognosis. Among 207 identified DEGs, 148 exhibited significant correlation with these CAF clusters, forming the basis of a seven-gene risk signature. This signature emerged as an independent predictor in multivariate analysis for PAAD and demonstrated predictive efficacy in immunotherapeutic outcomes. Additionally, a novel nomogram, integrating age and the CAF-based risk signature, exhibited robust predictability and reliability in prognosticating PAAD. Moreover, the risk signature displayed substantial correlations with stromal and immune scores, as well as specific immune cell types.

CONCLUSIONS

The prognosis of PAAD can be accurately predicted using the CAF-based risk signature, and a thorough analysis of the PAAD CAF signature may aid in deciphering the patient's immunotherapy response and presenting fresh cancer treatment options.

Heterodimerization of T cell engaging bispecific antibodies to enhance specificity against pancreatic ductal adenocarcinoma

BACKGROUND

EGFR and/or HER2 expression in pancreatic cancers is correlated with poor prognoses. We generated homodimeric (EGFRxEGFR or HER2xHER2) and heterodimeric (EGFRxHER2) T cell-engaging bispecific antibodies (T-BsAbs) to direct polyclonal T cells to these antigens on pancreatic tumors.

METHODS

EGFR and HER2 T-BsAbs were constructed using the 2 + 2 IgG-[L]-scFv T-BsAbs format bearing two anti-CD3 scFvs attached to the light chains of an IgG to engage T cells while retaining bivalent binding to tumor antigens with both Fab arms. A Fab arm exchange strategy was used to generate EGFRxHER2 heterodimeric T-BsAb carrying one Fab specific for EGFR and one for HER2. EGFR and HER2 T-BsAbs were also heterodimerized with a CD33 control T-BsAb to generate 'tumor-monovalent' EGFRxCD33 and HER2xCD33 T-BsAbs. T-BsAb avidity for tumor cells was studied by flow cytometry, cytotoxicity by T-cell mediated 51Chromium release, and in vivo efficacy against cell line-derived xenografts (CDX) or patient-derived xenografts (PDX). Tumor infiltration by T cells transduced with luciferase reporter was quantified by bioluminescence.

RESULTS

The EGFRxEGFR, HER2xHER2, and EGFRxHER2 T-BsAbs demonstrated high avidity and T cell-mediated cytotoxicity against human pancreatic ductal adenocarcinoma (PDAC) cell lines in vitro with EC50s in the picomolar range (0.17pM to 18pM). They were highly efficient in driving human polyclonal T cells into subcutaneous PDAC xenografts and mediated potent T cell-mediated anti-tumor effects. Both EGFRxCD33 and HER2xCD33 tumor-monovalent T-BsAbs displayed substantially reduced avidity by SPR when compared to homodimeric EGFRxEGFR or HER2xHER2 T-BsAbs (∼150-fold and ∼6000-fold respectively), tumor binding by FACS (8.0-fold and 63.6-fold), and T-cell mediated cytotoxicity (7.7-fold and 47.2-fold), while showing no efficacy against CDX or PDX. However, if either EGFR or HER2 was removed from SW1990 by CRISPR-mediated knockout, the in vivo efficacy of heterodimeric EGFRxHER2 T-BsAb was lost.

CONCLUSION

EGFR and HER2 were useful targets for driving T cell infiltration and tumor ablation. Two arm Fab binding to either one or both targets was critical for robust anti-tumor effect in vivo. By engaging both targets, EGFRxHER2 heterodimeric T-BsAb exhibited potent anti-tumor effects if CDX or PDX were EGFR+HER2+ double-positive with the potential to spare single-positive normal tissue.

High-dimensional deconstruction of pancreatic cancer identifies tumor microenvironmental and developmental stemness features that predict survival

Numerous cell states are known to comprise the pancreatic ductal adenocarcinoma (PDAC) tumor microenvironment (TME). However, the developmental stemness and co-occurrence of these cell states remain poorly defined. Here, we performed single-cell RNA sequencing (scRNA-seq) on a cohort of treatment-naive PDAC time-of-diagnosis endoscopic ultrasound-guided fine needle biopsy (EUS-FNB) samples (n = 25). We then combined these samples with surgical resection (n = 6) and publicly available samples to increase statistical power (n = 80). Following annotation into 25 distinct cell states, cells were scored for developmental stemness, and a customized version of the Ecotyper tool was used to identify communities of co-occurring cell states in bulk RNA-seq samples (n = 268). We discovered a tumor microenvironmental community comprised of aggressive basal-like malignant cells, tumor-promoting SPP1+ macrophages, and myofibroblastic cancer-associated fibroblasts associated with especially poor prognosis. We also found a developmental stemness continuum with implications for survival that is present in both malignant cells and cancer-associated fibroblasts (CAFs). We further demonstrated that high-dimensional analyses predictive of survival are feasible using standard-of-care, time-of-diagnosis EUS-FNB specimens. In summary, we identified tumor microenvironmental and developmental stemness characteristics from a high-dimensional gene expression analysis of PDAC using human tissue specimens, including time-of-diagnosis EUS-FNB samples. These reveal new connections between tumor microenvironmental composition, CAF and malignant cell stemness, and patient survival that could lead to better upfront risk stratification and more personalized upfront clinical decision-making.

Mucins as contrast agent targets for fluorescence-guided surgery of pancreatic cancer

Pancreatic cancer is difficult to resect due to its unique challenges, often leading to incomplete tumor resections. Fluorescence-guided surgery (FGS), also known as intraoperative molecular imaging and optical surgical navigation, is an intraoperative tool that can aid surgeons in complete tumor resection through an increased ability to detect the tumor. To target the tumor, FGS contrast agents rely on biomarkers aberrantly expressed in malignant tissue compared to normal tissue. These biomarkers allow clinicians to identify the tumor and its stage before surgical resection and provide a contrast agent target for intraoperative imaging. Mucins, a family of glycoproteins, are upregulated in malignant tissue compared to normal tissue. Therefore, these proteins may serve as biomarkers for surgical resection. Intraoperative imaging of mucin expression in pancreatic cancer can potentially increase the number of complete resections. While some mucins have been studied for FGS, the potential ability to function as a biomarker target extends to the entire mucin family. Therefore, mucins are attractive proteins to investigate more broadly as FGS biomarkers. This review summarizes the biomarker traits of mucins and their potential use in FGS for pancreatic cancer.

Tumor-Associated Fibrosis Impairs the Response to Immunotherapy

Previously, impaired responses to immunotherapy in cancer had been attributed mainly to inherent tumor characteristics (tumor cell intrinsic factors) such as low immunogenicity, (low) mutational burden, weak host immune system, etc. However, mapping the responses of immunotherapeutic regimes in clinical trials for different types of cancer has pointed towards an obvious commonality - that tumors with a rich fibrotic stroma respond poorly or not at all. This has prompted a harder look on tumor cell extrinsic factors such as the surrounding tumor microenvironment (TME), and specifically, the fibrotic stroma as a potential enabler of immunotherapy failure. Indeed, the role of cancer-associated fibrosis in impeding efficacy of immunotherapy is now well-established. In fact, recent studies reveal a complex interconnection between fibrosis and treatment efficacy. Accordingly, in this review we provide a general overview of what a tumor associated fibrotic reaction is and how it interacts with the members of immune system that are frequently seen to be modulated in a failed immunotherapeutic regime.

Spatial genomics reveals a high number and specific location of B cells in the pancreatic ductal adenocarcinoma microenvironment of long-term survivors

Background and aim

Only 10% of pancreatic ductal adenocarcinoma (PDAC) patients survive longer than five years. Factors underlining long-term survivorship in PDAC are not well understood. Therefore, we aimed to identify the key players in the tumor immune microenvironment (TIME) associated with long-term survivorship in PDAC patients.

Methods

The immune-related gene expression profiles of resected PDAC tumors of patients who survived and remained recurrence-free of disease for ≥36 months (long-term survivors, n=10) were compared to patients who had survived ≤6 months (short-term survivors, n=10) due to tumor recurrence. Validation was performed by the spatial protein expression profile of immune cells using the GeoMx™ Digital Spatial Profiler. An independent cohort of samples consisting of 12 long-term survivors and 10 short-term survivors, was used for additional validation. The independent validation was performed by combining qualitative immunohistochemistry and quantitative protein expression profiling.

Results

B cells were found to be significantly increased in the TIME of long-term survivors by gene expression profiling (p=0.018). The high tumor infiltration of B cells was confirmed by spatial protein profiling in the discovery and the validation cohorts (p=0.002 and p=0.01, respectively). The higher number of infiltrated B cells was found mainly in the stromal compartments of PDAC samples and was exclusively found within tumor cells in long-term survivors.

Conclusion

This is the first comprehensive study that connects the immune landscape of gene expression profiles and protein spatial infiltration with the survivorship of PDAC patients. We found a higher number and a specific location of B cells in TIME of long-term survivors which emphasizes the importance of B cells and B cell-based therapy for future personalized immunotherapy in PDAC patients.

The novel subclusters based on cancer-associated fibroblast for pancreatic adenocarcinoma

Introduction

Pancreatic adenocarcinoma (PAAD) is a fatal disease characterized by promoting connective tissue proliferation in the stroma. Activated cancer-associated fibroblasts (CAFs) play a key role in fibrogenesis in PAAD. CAF-based tumor typing of PAAD has not been explored.

Methods

We extracted single-cell sequence transcriptomic data from GSE154778 and CRA001160 datasets from Gene Expression Omnibus or Tumor Immune Single-cell Hub to collect CAFs in PAAD. On the basis of Seurat packages and new algorithms in machine learning, CAF-related subtypes and their top genes for PAAD were analyzed and visualized. We used CellChat package to perform cell-cell communication analysis. In addition, we carried out functional enrichment analysis based on clusterProfiler package. Finally, we explored the prognostic and immunotherapeutic value of these CAF-related subtypes for PAAD.

Results

CAFs were divided into five new subclusters (CAF-C0, CAF-C1, CAF-C2, CAF-C3, and CAF-C4) based on their marker genes. The five CAF subclusters exhibited distinct signaling patterns, immune status, metabolism features, and enrichment pathways and validated in the pan-cancer datasets. In addition, we found that both CAF-C2 and CAF-C4 subgroups were negatively correlated with prognosis. With their top genes of each subclusters, the sub-CAF2 had significantly relations to immunotherapy response in the patients with pan-cancer and immunotherapy.

Discussion

We explored the heterogeneity of five subclusters based on CAF in signaling patterns, immune status, metabolism features, enrichment pathways, and prognosis for PAAD.

The Desmoplastic Stroma of Pancreatic Cancer: Multilayered Levels of Heterogeneity, Clinical Significance, and Therapeutic Opportunities

Simple Summary

Pancreatic cancer is a highly malignant disease with treatment resistance to standardized chemotherapies. In addition, only a small fraction of patients with pancreatic cancer has, to date, actionable genetic aberrations, leading to a narrow therapeutic window for molecularly targeted therapies or immunotherapies. A lot of preclinical and translational studies are ongoing to discover potential vulnerabilities to treat pancreatic cancer. Histologically, human pancreatic cancer is characterized by abundant cancer-associated fibrotic stroma, called “desmoplastic stroma”. Recent technological advances have revealed that desmoplastic stroma in pancreatic cancer is much more complicated than previously thought, playing pleiotropic roles in manipulating tumor cell fate and anti-tumor immunity. Moreover, real-world specimen-based analyses of pancreatic cancer stroma have also uncovered spatial heterogeneity and an intertumoral variety associated with molecular alterations, clinicopathological factors, and patient outcomes. This review describes an overview of the current efforts in the field of pancreatic cancer stromal biology and discusses treatment opportunities of stroma-modifying therapies against this hard-to-treat cancer.

Abstract

Pancreatic cancer remains one of the most lethal malignancies and is becoming a dramatically increasing cause of cancer-related mortality worldwide. Abundant desmoplastic stroma is a histological hallmark of pancreatic ductal adenocarcinoma. Emerging evidence suggests a promising therapeutic effect of several stroma-modifying therapies that target desmoplastic stromal elements in the pancreatic cancer microenvironment. The evidence also unveils multifaceted roles of cancer-associated fibroblasts (CAFs) in manipulating pancreatic cancer progression, immunity, and chemotherapeutic response. Current state-of-the-art technologies, including single-cell transcriptomics and multiplexed tissue imaging techniques, have provided a more profound knowledge of CAF heterogeneity in real-world specimens from pancreatic cancer patients, as well as in genetically engineered mouse models. In this review, we describe recent advances in the understanding of the molecular pathology bases of pancreatic cancer desmoplastic stroma at multilayered levels of heterogeneity, namely, (1) variations in cellular and non-cellular members, including CAF subtypes and extracellular matrix (ECM) proteins; (2) geographical heterogeneity in relation to cell–cell interactions and signaling pathways at niche levels and spatial heterogeneity at locoregional levels or organ levels; and (3) intertumoral stromal heterogeneity at individual levels. This review further discusses the clinicopathological significance of desmoplastic stroma and the potential opportunities for stroma-targeted therapies against this lethal malignancy.

Programmable Living Units for Emulating Pancreatic Tumor-Stroma Interplay

Bioengineering close-to-native in vitro models that emulate tumors bioarchitecture and microenvironment is highly appreciable for improving disease modeling toolboxes. Herein, pancreatic cancer living units-so termed cancer-on-a-bead models-are generated. Such user-programmable in vitro platforms exhibit biomimetic multicompartmentalization and tunable integration of cancer associated stromal elements. These stratified units can be rapidly assembled in-air, exhibit reproducible morphological features, tunable size, and recapitulate spatially resolved tumor-stroma extracellular matrix (ECM) niches. Compartmentalization of pancreatic cancer and stromal cells in well-defined ECM microenvironments stimulates the secretion of key biomolecular effectors including transforming growth factor β and Interleukin 1-β, closely emulating the signatures of human pancreatic tumors. Cancer-on-a-bead models also display increased drug resistance to chemotherapeutics when compared to their reductionistic counterparts, reinforcing the importance to differentially model ECM components inclusion and their spatial stratification as observed in vivo. Beyond providing a universal technology that enables spatial modularity in tumor-stroma elements bioengineering, a scalable, in-air fabrication of ECM-tunable 3D platforms that can be leveraged for recapitulating differential matrix composition occurring in other human neoplasias is provided here.

Targeting Tumor-Stromal Interactions in Pancreatic Cancer: Impact of Collagens and Mechanical Traits

Pancreatic ductal adenocarcinoma (PDAC) has one of the worst outcomes among cancers with a 5-years survival rate of below 10%. This is a result of late diagnosis and the lack of effective treatments. The tumor is characterized by a highly fibrotic stroma containing distinct cellular components, embedded within an extracellular matrix (ECM). This ECM-abundant tumor microenvironment (TME) in PDAC plays a pivotal role in tumor progression and resistance to treatment. Cancer-associated fibroblasts (CAFs), being a dominant cell type of the stroma, are in fact functionally heterogeneous populations of cells within the TME. Certain subtypes of CAFs are the main producer of the ECM components of the stroma, with the most abundant one being the collagen family of proteins. Collagens are large macromolecules that upon deposition into the ECM form supramolecular fibrillar structures which provide a mechanical framework to the TME. They not only bring structure to the tissue by being the main structural proteins but also contain binding domains that interact with surface receptors on the cancer cells. These interactions can induce various responses in the cancer cells and activate signaling pathways leading to epithelial-to-mesenchymal transition (EMT) and ultimately metastasis. In addition, collagens are one of the main contributors to building up mechanical forces in the tumor. These forces influence the signaling pathways that are involved in cell motility and tumor progression and affect tumor microstructure and tissue stiffness by exerting solid stress and interstitial fluid pressure on the cells. Taken together, the TME is subjected to various types of mechanical forces and interactions that affect tumor progression, metastasis, and drug response. In this review article, we aim to summarize and contextualize the recent knowledge of components of the PDAC stroma, especially the role of different collagens and mechanical traits on tumor progression. We furthermore discuss different experimental models available for studying tumor-stromal interactions and finally discuss potential therapeutic targets within the stroma.

Pancreatic Cancer Microenvironment and Cellular Composition: Current Understandings and Therapeutic Approaches

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal human solid tumors, despite great efforts in improving therapeutics over the past few decades. In PDAC, the distinct characteristic of the tumor microenvironment (TME) is the main barrier for developing effective treatments. PDAC TME is characterized by a dense stroma, cancer-associated fibroblasts, and immune cells populations that crosstalk to the subpopulations of neoplastic cells that include cancer stem cells (CSCs). The heterogeneity in TME is also exhibited in the diversity and dynamics of acellular components, including the Extracellular matrix (ECM), cytokines, growth factors, and secreted ligands to signaling pathways. These contribute to drug resistance, metastasis, and relapse in PDAC. However, clinical trials targeting TME components have often reported unexpected results and still have not benefited patients. The failures in those trials and various efforts to understand the PDAC biology demonstrate the highly heterogeneous and multi-faceted TME compositions and the complexity of their interplay within TME. Hence, further functional and mechanistic insight is needed. In this review, we will present a current understanding of PDAC biology with a focus on the heterogeneity in TME and crosstalk among its components. We also discuss clinical challenges and the arising therapeutic opportunities in PDAC research.

Cancer: a mirrored room between tumor bulk and tumor microenvironment

It has been well documented that the tumor microenvironment (TME) plays a key role in the promotion of drug resistance, the support of tumor progression, invasiveness, metastasis, and even the maintenance of a cancer stem-like phenotype. Here, we reviewed TME formation presenting it as a reflection of a tumor’s own organization during the different stages of tumor development. Interestingly, functionally different groups of stromal cells seem to have specific spatial distributions within the TME that change as the tumor evolves into advanced stage progression which correlates with the fact that cancer stem-like cells (CSCs) are located in the edges of solid tumor masses in advanced tumors.

We also focus on the continuos feedback that is established between a tumor and its surroundings. The “talk” between tumor mass cells and TME stromal cells, marks the evolution of both interlocuting cell types. For instance, the metabolic and functional transformations that stromal cells undergo due to tumor corrupting activity.

Moreover, the molecular basis of metastatic spread is also approached, making special emphasis on the site-specific pre-metastatic niche formation as another reflection of the primary tumor molecular signature.

Finally, several therapeutic approaches targeting primary TME and pre-metastatic niche are suggested. For instance, a systematic analysis of the TME just adjacent to the tumor mass to establish the proportion of myofibroblasts-like cancer-associated fibroblasts (CAFs) which may in turn correspond to stemness and metastases-promotion. Or the implementation of “re-education” therapies consisting of switching tumor-supportive stromal cells into tumor-suppressive ones. In summary, to improve our clinical management of cancer, it is crucial to understand and learn how to manage the close interaction between TME and metastasis.

Large-duct pattern invasive adenocarcinoma of the pancreas-a variant mimicking pancreatic cystic neoplasms: A minireview

Pancreatic cancer currently has no subtypes that inform clinical decisions; hence, there exists an opportunity to rearrange the morphological and molecular taxonomy that guides a better understanding of tumor characteristics. Nonetheless, accumulating studies to date have revealed the large-duct type variant, a unique subtype of pancreatic ductal adenocarcinoma (PDA) with cystic features. This subtype often radiographically mimics intraductal papillary mucinous neoplasms (IPMNs) and involves multiple small cysts occasionally associated with solid masses. The "bunch-of-grapes" sign, an imaging characteristic of IPMNs, is absent in large-duct PDA. Large-duct PDA defines the mucin profile, and genetic alterations are useful in distinguishing large-duct PDA from IPMNs. Histologically, neoplastic ducts measure over 0.5 mm, forming large ductal elements. Similar to classic PDAs, this subtype is frequently accompanied by perineural invasion and abundant desmoplastic reactions, and KRAS mutations in codon 12 are nearly ubiquitous. Despite such morphological similarities with IPMNs, the prognosis of large-duct PDA is equivalent to that of classic PDA. Differential diagnosis is therefore essential.

Metastasis: crosstalk between tissue mechanics and tumour cell plasticity

Despite the fact that different genetic programmes drive metastasis of solid tumours, the ultimate outcome is the same: tumour cells are empowered to pass a series of physical hurdles to escape the primary tumour and disseminate to other organs. Epithelial-to-mesenchymal transition (EMT) has been proposed to drive the detachment of individual cells from primary tumour masses and facilitate the subsequent establishment of metastases in distant organs. However, this concept has been challenged by observations from pathologists and from studies in animal models, in which partial and transient acquisition of mesenchymal traits is seen but tumour cells travel collectively rather than as individuals. In this review, we discuss how crosstalk between a hybrid E/M state and variations in the mechanical aspects of the tumour microenvironment can provide tumour cells with the plasticity required for strategies to navigate surrounding tissues en route to dissemination. Targeting such plasticity provides therapeutic opportunities to combat metastasis.

Beyond just a tight fortress: contribution of stroma to epithelial-mesenchymal transition in pancreatic cancer

Novel effective treatment is direly needed for patients with pancreatic ductal adenocarcinoma (PDAC). Therapeutics that target the driver mutations, especially the KRAS oncoprotein and its effector cascades, have been ineffective. It is increasing clear that the extensive fibro-inflammatory stroma (or desmoplasia) of PDAC plays an active role in the progression and therapeutic resistance of PDAC. The desmoplastic stroma is composed of dense extracellular matrix (ECM) deposited mainly by the cancer-associated-fibroblasts (CAFs) and infiltrated with various types of immune cells. The dense ECM functions as a physical barrier that limits tumor vasculatures and distribution of therapeutics to PDAC cells. In addition, mounting evidence have demonstrated that both CAFs and ECM promote PDAC cells aggressiveness through multiple mechanisms, particularly engagement of the epithelial-mesenchymal transition (EMT) program. Acquisition of a mesenchymal-like phenotype renders PDAC cells more invasive and resistant to therapy-induced apoptosis. Here, we critically review seminal and recent articles on the signaling mechanisms by which each stromal element promotes EMT in PDAC. We discussed the experimental models that are currently employed and best suited to study EMT in PDAC, which are instrumental in increasing the chance of successful clinical translation.

Pros and Cons: High Proportion of Stromal Component Indicates Better Prognosis in Patients With Pancreatic Ductal Adenocarcinoma-A Research Based on the Evaluation of Whole-Mount Histological Slides

The study aimed to investigate the potential of tumor–stroma ratio (TSR) on digitalized whole-mount histopathology to predict prognosis in patients with pancreatic ductal adenocarcinoma (PDAC). The effectiveness were evaluated through internal validation. Data were retrospectively collected from consecutive patients who underwent primary pancreatic resection from December 2016 to August 2017 (developing cohort) and from September 2017 to April 2018 (validation cohort). Digitalized whole-mount slide images were used to evaluate TSR by both pathologists and a computerized model based on Conditional Generative Adversarial Model (cGAN), respectively. TSR>1 and ≤ 1 denoted low and high stromal component. Logistic regression analysis revealed intratumoral necrosis and R1 independently associated with low stromal component in the developing cohort. Cox regression analysis revealed tumor–node–metastasis (TNM) stage [II vs. I: hazard ratio (HR), 2.584; 95% CI, 1.386–4.819; P = 0.003; III vs. I: HR, 4.384; 95% CI, 2.285–8.411; P < 0.001], stromal component (low vs. high: HR, 1.876; 95% CI, 1.227–2.870; P = 0.004), tumor grade (G3 vs. G1/2: HR, 2.124; 95% CI, 1.419–3.179; P < 0.001), and perineural invasion (with vs. without: HR, 2.147; 95% CI, 1.187–3.883; P = 0.011) were independent prognostic factors in the developing cohort. Stromal component categories could classify patients into subgroups within TNM stages I, II, and III based on over survival. All results were validated in the validation cohort. The weighted kappa value for categorical assessments between pathologists' evaluation and computer-aided evaluation was 0.804 (95% CI, 0.573–0.951). TSR represents a simple and reliable metric for combining the prognostic value of TNM stage in patients with PDAC.