Mechanisms of PDAC subtype heterogeneity and therapy response

Integrating intratumoral and peritumoral radiomics with clinical risk factors for prognostic prediction in pancreatic ductal adenocarcinoma patients undergoing combined chemotherapy and HIFU ablation

OBJECTIVE

A radiomics nomogram will be created utilizing MRI data from intratumoral and peritumoral areas to forecast survival outcomes in patients who have had treatment for pancreatic ductal adenocarcinoma (PDAC).

METHODS

A total of 87 individuals diagnosed with PDAC were included in the study, with 60 patients in the training cohort and 27 patients in the validation cohort. A grand total of 2395 radiomics characteristics were extracted from the tumor region and the peritumoral region. The least absolute shrinkage and selection operator (LASSO) method was used to select features and create a radiomics score, also known as the Rad-score. A multivariate regression analysis was then conducted to build the radiomics nomogram. The evaluation of the nomogram included discrimination, calibration, and clinical utility assessments.

RESULTS

Based on the conclusions derived from the multivariate Cox model, Rad-Score, jaundice, and tumor size were identified as independent risk factors for overall survival (OS). The inclusion of the Rad-score in the radiomics nomogram led to improved accuracy in predicting survival compared to the clinical model. Patients were categorized into high-risk and low-risk groups based on their Rad-Score. Kaplan-Meier analysis revealed a statistically significant difference between the two groups (p < 0.05). Furthermore, the radiomics nomogram demonstrated excellent ability to differentiate, calibrate, and provide clinical utility in both the training and validation groups.

CONCLUSIONS

The MRI-based intratumoral and peritumoral radiomics nomogram, integrating the Rad-score and clinical data, provided better prognostic prediction for PDAC patients after HIFU treatment, which may hold great potential for guiding personalized care for these patients.

Identification of Gαi3 as a promising molecular oncotarget of pancreatic cancer

The increasing mortality rate of pancreatic cancer globally necessitates the urgent identification for novel therapeutic targets. This study investigated the expression, functions, and mechanistic insight of G protein inhibitory subunit 3 (Gαi3) in pancreatic cancer. Bioinformatics analyses reveal that Gαi3 is overexpressed in human pancreatic cancer, correlating with poor prognosis, higher tumor grade, and advanced classification. Elevated Gαi3 levels are also confirmed in human pancreatic cancer tissues and primary/immortalized cancer cells. Gαi3 shRNA or knockout (KO) significantly reduced cell viability, proliferation, cell cycle progression, and mobility in primary/immortalized pancreatic cancer cells. Conversely, Gαi3 overexpression enhanced pancreatic cancer cell growth. RNA-sequencing and bioinformatics analyses of Gαi3-depleted cells indicated Gαi3's role in modulating the Akt-mTOR and PKA-Hippo-YAP pathways. Akt-S6 phosphorylation was decreased in Gαi3-depleted cells, but was increased with Gαi3 overexpression. Additionally, Gαi3 depletion elevated PKA activity and activated the Hippo pathway kinase LATS1/2, leading to YAP/TAZ inactivation, while Gαi3 overexpression exerted the opposite effects. There is an increased binding between Gαi3 promoter and the transcription factor TCF7L2 in pancreatic cancer tissues and cells. Gαi3 expression was significantly decreased following TCF7L2 silencing, but increased with TCF7L2 overexpression. In vivo, intratumoral injection of Gαi3 shRNA-expressing adeno-associated virus significantly inhibited subcutaneous pancreatic cancer xenografts growth in nude mice. A significant growth reduction was also observed in xenografts from Gαi3 knockout pancreatic cancer cells. Akt-mTOR inactivation and increased PKA activity coupled with YAP/TAZ inactivation were also detected in xenograft tumors upon Gαi3 depletion. Furthermore, bioinformatic analysis and multiplex immunohistochemistry (mIHC) staining on pancreatic cancer tissue microarrays showed a reduced proportion of M1-type macrophages and an increase in PD-L1 positive cells in Gαi3-high pancreatic cancer tissues. Collectively, these findings highlight Gαi3's critical role in promoting pancreatic cancer cell growth, potentially through the modulation of the Akt-mTOR and PKA-Hippo-YAP pathways and its influence on the immune landscape.

The xenobiotic transporter ABCC4/MRP4 promotes epithelial mesenchymal transition in pancreatic cancer

The xenobiotic transporter ABCC4/MRP4 is highly expressed in pancreatic ductal adenocarcinoma (PDAC) and correlates with a more aggressive phenotype and metastatic propensity. Here, we show that ABCC4 promotes epithelial-mesenchymal transition (EMT) in PDAC, a hallmark process involving the acquisition of mesenchymal traits by epithelial cells, enhanced cell motility, and chemoresistance. Modulation of ABCC4 levels in PANC-1 and BxPC-3 cell lines resulted in the dysregulation of genes present in the EMT signature. Bioinformatic analysis on several cohorts including tumor samples, primary patient-derived cultured cells, patient-derived xenografts, and cell lines, revealed a positive correlation between ABCC4 expression and EMT markers. We also characterized the ABCC4 cistrome and identified four candidate clusters in the distal promoter and intron one that showed differential binding of pro-epithelial FOXA1 and pro-mesenchymal GATA2 transcription factors in low ABCC4-expressing HPAF-II and high ABCC4-expressing PANC-1 xenografts. HPAF-II xenografts showed exclusive binding of FOXA1, and PANC-1 xenografts exclusive binding of GATA2, at ABCC4 clusters, consistent with their low and high EMT phenotype respectively. Our results underscore ABCC4/MRP4 as a valuable prognostic marker and a potential therapeutic target to treat PDAC subtypes with prominent EMT features, such as the basal-like/squamous subtype, characterized by worse prognosis and no effective therapies.

Artificial Intelligence in Pancreatic Image Analysis: A Review

Pancreatic cancer is a highly lethal disease with a poor prognosis. Its early diagnosis and accurate treatment mainly rely on medical imaging, so accurate medical image analysis is especially vital for pancreatic cancer patients. However, medical image analysis of pancreatic cancer is facing challenges due to ambiguous symptoms, high misdiagnosis rates, and significant financial costs. Artificial intelligence (AI) offers a promising solution by relieving medical personnel's workload, improving clinical decision-making, and reducing patient costs. This study focuses on AI applications such as segmentation, classification, object detection, and prognosis prediction across five types of medical imaging: CT, MRI, EUS, PET, and pathological images, as well as integrating these imaging modalities to boost diagnostic accuracy and treatment efficiency. In addition, this study discusses current hot topics and future directions aimed at overcoming the challenges in AI-enabled automated pancreatic cancer diagnosis algorithms.

Generation of a biliary tract cancer cell line atlas reveals molecular subtypes and therapeutic targets

Biliary tract cancers (BTCs) are a group of deadly malignancies encompassing intrahepatic and extrahepatic cholangiocarcinoma, gallbladder carcinoma, and ampullary carcinoma. Here, we present the integrative analysis of 63 BTC cell lines via multi-omics clustering and genome- scale CRISPR screens, providing a platform to illuminate BTC biology and inform therapeutic development. We identify dependencies broadly enriched in BTC compared to other cancers as well as dependencies selective to the anatomic subtypes. Notably, cholangiocarcinoma cell lines are stratified into distinct lineage subtypes based on biliary or dual biliary/hepatocyte marker signatures, associated with dependency on specific lineage survival factors. Transcriptional analysis of patient specimens demonstrates the prognostic significance of these lineage subtypes. Additionally, we delineate strategies to enhance targeted therapies or to overcome resistance in cell lines with key driver gene mutations. Furthermore, clustering based on dependencies and proteomics data elucidates unexpected functional relationships, including a BTC subgroup with partial squamous differentiation. Thus, this cell line atlas reveals potential therapeutic targets in molecularly defined BTCs, unveils biologically distinct disease subtypes, and offers a vital resource for BTC research.

An alternative splicing signature defines the basal-like phenotype and predicts worse clinical outcome in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is characterized by extremely poor prognosis. PDAC presents with molecularly distinct subtypes, with the basal-like one being associated with enhanced chemoresistance. Splicing dysregulation contributes to PDAC; however, its involvement in subtype specification remains elusive. Herein, we uncover a subtype-specific splicing signature associated with prognosis in PDAC and the splicing factor Quaking (QKI) as a determinant of the basal-like signature. Single-cell sequencing analyses highlight QKI as a marker of the basal-like phenotype. QKI represses splicing events associated with the classical subtype while promoting basal-like events associated with shorter survival. QKI favors a plastic, quasi-mesenchymal phenotype that supports migration and chemoresistance in PDAC organoids and cell lines, and its expression is elevated in high-grade primary tumors and metastatic lesions. These studies identify a splicing signature that defines PDAC subtypes and indicate that QKI promotes an undifferentiated, plastic phenotype, which renders PDAC cells chemoresistant and adaptable to environmental changes.

Innate and adaptive immune-directed tumour microenvironment in pancreatic ductal adenocarcinoma

One of the most deadly and aggressive cancers in the world, pancreatic ductal adenocarcinoma (PDAC), typically manifests at an advanced stage. PDAC is becoming more common, and by the year 2030, it is expected to overtake lung cancer as the second greatest cause of cancer-related death. The poor prognosis can be attributed to a number of factors, including difficulties in early identification, a poor probability of curative radical resection, limited response to chemotherapy and radiotherapy, and its immunotherapy resistance. Furthermore, an extensive desmoplastic stroma that surrounds PDAC forms a mechanical barrier that prevents vascularization and promotes poor immune cell penetration. Phenotypic heterogeneity, drug resistance, and immunosuppressive tumor microenvironment are the main causes of PDAC aggressiveness. There is a complex and dynamic interaction between tumor cells in PDAC with stromal cells within the tumour immune microenvironment. The immune suppressive microenvironment that promotes PDAC aggressiveness is contributed by a range of cellular and humoral factors, which itself are modulated by the cancer. In this review, we describe the role of innate and adaptive immune cells, complex tumor microenvironment in PDAC, humoral factors, innate immune-mediated therapeutic advances, and recent clinical trials in PDAC.

[Histopathologic diagnosis of solid and cystic pancreatic lesions with a focus on ductal adenocarcinoma : A vademecum for daily practice]

Pancreas pathology is constantly evolving and can present various challenges for pathologists. This paper is focused on providing helpful hints for daily routine diagnostics. During histopathological analysis of pancreas biopsies, pancreatic ductal adenocarcinoma must be distinguished not only from other solid neoplasms, but especially from its mimicker, autoimmune pancreatitis. This can be achieved by a systematic workup following clear diagnostic criteria. When analyzing samples from cystic pancreatic lesions, mucin-producing neoplasms must be detected due to their role as pancreatic cancer precursors; molecular analyses can help considerably with their detection and distinction. During frozen section examination, evaluation of the pancreatic neck margin and analysis of unclear lesions of the liver are two important tasks, which are explained further in this article. A special challenge is the evaluation of neoadjuvant treated pancreatic cancer, which requires a detailed macroscopic and microscopic workup. Finally, current advances in precision oncology and emerging approaches for pancreatic cancer within this field are discussed. With the advancement of technical possibilities and their increasingly broad implementation, the classification systems in pancreatic pathology will continue to gain in complexity, but also in accuracy.

TRPA1 Contributes to FGFR2c Signaling and to Its Oncogenic Outcomes in Pancreatic Ductal Adenocarcinoma-Derived Cell Lines

Fibroblast growth factor receptor (FGFR) signaling is a key modulator of cellular processes dysregulated in cancer. We recently found that the high expression of the mesenchymal FGFR2c variant in human pancreatic ductal adenocarcinoma (PDAC)-derived cells triggers the PKCε-mediated improvement of EMT and of MCL-1/SRC-dependent cell invasion. Since other membrane proteins can affect the receptor tyrosine kinase signaling, including transient receptor potential channels (TRPs), in this work, we investigated the role of TRPs in the FGFR2c/PKCε oncogenic axis. Our results highlighted that either the FGFR2c/PKCε axis shut-off obtained by shRNA or its sustained activation via ligand stimulation induces TRPA1 downregulation, suggesting a channel/receptor dependence. Indeed, biochemical molecular and immunofluorescence approaches demonstrated that the transient depletion of TRPA1 by siRNA was sufficient to attenuate FGFR2c downstream signaling pathways, as well as the consequent enhancement of EMT. Moreover, the biochemical check of MCL1/SRC signaling and the in vitro assay of cellular motility suggested that TRPA1 also contributes to the FGFR2c-induced enhancement of PDAC cell invasiveness. Finally, the use of a selective channel antagonist indicated that the contribution of TRPA1 to the FGFR2c oncogenic potential is independent of its pore function. Thus, TRPA1 could represent a putative candidate for future target therapies in PDAC.

Roles of microbiota in pancreatic cancer development and treatment

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive disease with poor prognosis. This is due to the fact that most cases are only diagnosed at an advanced and palliative disease stage, and there is a high incidence of therapy resistance. Despite ongoing efforts, to date, the mechanisms underlying PDAC oncogenesis and its poor responses to treatment are still largely unclear. As the study of the microbiome in cancer progresses, growing evidence suggests that bacteria or fungi might be key players both in PDAC oncogenesis as well as in its resistance to chemo- and immunotherapy, for instance through modulation of the tumor microenvironment and reshaping of the host immune response. Here, we review how the microbiota exerts these effects directly or indirectly via microbial-derived metabolites. Finally, we further discuss the potential of modulating the microbiota composition as a therapy in PDAC.

Cancer-associated fibroblasts in neoadjuvant setting for solid cancers

Therapeutic approaches for cancer have become increasingly diverse in recent times. A comprehensive understanding of the tumor microenvironment (TME) holds great potential for enhancing the precision of tumor therapies. Neoadjuvant therapy offers the possibility of alleviating patient symptoms and improving overall quality of life. Additionally, it may facilitate the reduction of inoperable tumors and prevent potential preoperative micrometastases. Within the TME, cancer-associated fibroblasts (CAFs) play a prominent role as they generate various elements that contribute to tumor progression. Particularly, extracellular matrix (ECM) produced by CAFs prevents immune cell infiltration into the TME, hampers drug penetration, and diminishes therapeutic efficacy. Therefore, this review provides a summary of the heterogeneity and interactions of CAFs within the TME, with a specific focus on the influence of neoadjuvant therapy on the microenvironment, particularly CAFs. Finally, we propose several potential and promising therapeutic strategies targeting CAFs, which may efficiently eliminate CAFs to decrease stroma density and impair their functions.

Pancreatic Cancer-Secreted Proteins: Targeting Their Functions in Tumor Microenvironment

Pancreatic Ductal Adenocarcinoma (PDAC) is a ravaging disease with a poor prognosis, requiring a more detailed understanding of its biology to foster the development of effective therapies. The unsatisfactory results of treatments targeting cell proliferation and its related mechanisms suggest a shift in focus towards the inflammatory tumor microenvironment (TME). Here, we discuss the role of cancer-secreted proteins in the complex TME tumor-stroma crosstalk, shedding lights on druggable molecular targets for the development of innovative, safer and more efficient therapeutic strategies.

A protein-based machine learning approach to the identification of inflammatory subtypes in pancreatic ductal adenocarcinoma

BACKGROUND/OBJECTIVES

The inherently immunosuppressive tumor microenvironment along with the heterogeneity of pancreatic ductal adenocarcinoma (PDAC) limits the effectiveness of available treatment options and contributes to the disease lethality. Using a machine learning algorithm, we hypothesized that PDAC may be categorized based on its microenvironment inflammatory milieu.

METHODS

Fifty-nine tumor samples from patients naïve to treatment were homogenized and probed for 41 unique inflammatory proteins using a multiplex assay. Subtype clustering was determined using t-distributed stochastic neighbor embedding (t-SNE) machine learning analysis of cytokine/chemokine levels. Statistics were performed using Wilcoxon rank sum test and Kaplan-Meier survival analysis.

RESULTS

t-SNE analysis of tumor cytokines/chemokines revealed two distinct clusters, immunomodulating and immunostimulating. In pancreatic head tumors, patients in the immunostimulating group (N = 26) were more likely to be diabetic (p = 0.027), but experienced less intraoperative blood loss (p = 0.0008). Though there were no significant differences in survival (p = 0.161), the immunostimulating group trended toward longer median survival by 9.205 months (11.28 vs. 20.48 months).

CONCLUSION

A machine learning algorithm identified two distinct subtypes within the PDAC inflammatory milieu, which may influence diabetes status as well as intraoperative blood loss. Opportunity exists to further explore how these inflammatory subtypes may influence treatment response, potentially elucidating targetable mechanisms of PDAC's immunosuppressive tumor microenvironment.

Desmoplastic stroma restricts T cell extravasation and mediates immune exclusion and immunosuppression in solid tumors

The desmoplastic stroma in solid tumors presents a formidable challenge to immunotherapies that rely on endogenous or adoptively transferred T cells, however, the mechanisms are poorly understood. To define mechanisms involved, here we treat established desmoplastic pancreatic tumors with CAR T cells directed to fibroblast activation protein (FAP), an enzyme highly overexpressed on a subset of cancer-associated fibroblasts (CAFs). Depletion of FAP+ CAFs results in loss of the structural integrity of desmoplastic matrix. This renders these highly treatment-resistant cancers susceptible to subsequent treatment with a tumor antigen (mesothelin)-targeted CAR T cells and to anti-PD-1 antibody therapy. Mechanisms include overcoming stroma-dependent restriction of T cell extravasation and/or perivascular invasion, reversing immune exclusion, relieving T cell suppression, and altering the immune landscape by reducing myeloid cell accumulation and increasing endogenous CD8+ T cell and NK cell infiltration. These data provide strong rationale for combining tumor stroma- and malignant cell-targeted therapies to be tested in clinical trials.

Desmoplastic stroma restricts T cell extravasation and mediates immune exclusion and immunosuppression in solid tumors

The desmoplastic stroma in solid tumors presents a formidable challenge to immunotherapies that rely on endogenous or adoptively transferred T cells, however, the mechanisms are poorly understood. To define mechanisms involved, we treat established desmoplastic pancreatic tumors with CAR T cells directed to fibroblast activation protein (FAP), an enzyme highly overexpressed on a subset of cancer-associated fibroblasts (CAFs). Depletion of FAP+CAFs results in loss of the structural integrity of desmoplastic matrix. This renders these highly treatment-resistant cancers susceptible to subsequent treatment with a tumor antigen (mesothelin)-targeted CAR and to anti-PD1 antibody therapy. Mechanisms include overcoming stroma-dependent restriction of T cell extravasation and/or perivascular invasion, reversing immune exclusion, relieving T cell suppression, and altering the immune landscape by reducing myeloid cell accumulation and increasing endogenous CD8+ T cell and NK cell infiltration. These data provide strong rationale for combining tumor stroma- and malignant cell-targeted therapies to be tested in clinical trials.

PDAC, the Influencer Cancer: Cross-Talk with Tumor Microenvironment and Connected Potential Therapy Strategies

Pancreatic ductal adenocarcinoma (PDAC) is among the leading causes of death by cancer in the world. What makes this pathological condition particularly lethal is a combination of clinical and molecular heterogeneity, lack of early diagnostic indexes, and underwhelming results from current therapeutic protocols. A major cause of PDAC chemoresistance seems to lie in the ability of cancer cells to spread out and fill the pancreatic parenchyma, exchanging nutrients, substrates, and even genetic material with cells from the surrounding tumor microenvironment (TME). Several components can be found in the TME ultrastructure, including collagen fibers, cancer-associated fibroblasts, macrophages, neutrophils, mast cells, and lymphocytes. Cross-talk between PDAC and TME cells results in the latter being converted into cancer-favoring phenotypes; this behavior could be compared to an influencer guiding followers into supporting his activity. Moreover, TME could be a potential target for some of the newest therapeutic strategies; these include the use of pegvorhyaluronidase-α and CAR-T lymphocytes against HER2, FAP, CEA, MLSN, PSCA, and CD133. Other experimental therapy options are being currently studied, aiming to interfere with the KRAS pathway, DNA-repairing proteins, and apoptosis resistance in PDAC cells. Hopefully these new approaches will grant better clinical outcomes in future patients.

Prognostic value of human leukocyte antigen G expression in solid tumors: a systematic review and meta-analysis

Introduction

Identification of modulators of the immune response with inhibitory properties that could be susceptible for therapeutic intervention is a key goal in cancer research. An example is the human leukocyte antigen G (HLA-G), a nonclassical major histocompatibility complex (MHC) class I molecule, involved in cancer progression.

Methods

In this article we performed a systematic review and meta-analysis on the association between HLA-G expression and outcome in solid tumors. This study was performed in accordance with PRISMA guidelines and registered in PROSPERO.

Results

A total of 25 studies met the inclusion criteria. These studies comprised data from 4871 patients reporting overall survival (OS), and 961 patients, reporting disease free survival (DFS). HLA-G expression was associated with worse OS (HR 2.09, 95% CI = 1.67 to 2.63; P < .001), that was higher in gastric (HR = 3.40; 95% CI = 1.64 to 7.03), pancreatic (HR = 1.72; 95% CI = 0.79 to 3.74) and colorectal (HR = 1.55; 95% CI = 1.16 to 2.07) cancer. No significant differences were observed between the most commonly utilized antibody (4H84) and other methods of detection. HLA-G expression was associated with DFS which approached but did not meet statistical significance.

Discussion

In summary, we describe the first meta-analysis associating HLA-G expression and worse survival in a variety of solid tumors.

Systematic Review Registration

https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42022311973.

Irbesartan overcomes gemcitabine resistance in pancreatic cancer by suppressing stemness and iron metabolism via inhibition of the Hippo/YAP1/c-Jun axis

BACKGROUND

Chemoresistance is the main reason for the poor prognosis of pancreatic ductal adenocarcinoma (PDAC). Thus, there is an urgent need to screen out new targets and compounds to reverse chemotherapeutic resistance.

METHODS

We established a bio-bank of human PDAC organoid models, covering a representative range of PDAC tumor subtypes. We screened a library of 1304 FDA-approved compounds to identify candidates efficiently overcoming chemotherapy resistance. The effects of the compounds were evaluated with a CellTiter-Glo-3D assay, organoid apoptosis assay and in vivo patient-derived xenograft (PDX), patient-derived organoid (PDO) and LSL-KrasG12D/+; LSL-Trp53R172H/+; Pdx1-Cre (KPC) genetically engineered mouse models. RNA-sequencing, genome editing, sphere formation assays, iron assays and luciferase assays were conducted to elucidate the mechanism.

RESULTS

High-throughput drug screening of chemotherapy-resistant PDOs identified irbesartan, an angiotensin ‖ type 1 (AT1) receptor antagonist, which could synergistically enhance the ability of chemotherapy to kill PDAC cells. In vitro and in vivo validation using PDO, PDX and KPC mouse models showed that irbesartan efficiently sensitized PDAC tumors to chemotherapy. Mechanistically, we found that irbesartan decreased c-Jun expression by inhibiting the Hippo/YAP1 pathway and further overcame chemotherapy resistance in PDAC. We also explored c-Jun, a potential target of irbesartan, which can transcriptionally upregulate the expression of key genes involved in stemness maintenance (SOX9/SOX2/OCT4) and iron metabolism (FTH1/FTL/TFRC). More importantly, we observed that PDAC patients with high levels of c-Jun expression demonstrated poor responses to the current standard chemotherapy regimen (gemcitabine plus nab-paclitaxel). Moreover, patients with PDAC had significant survival benefits from treatment with irbesartan plus a standard chemotherapy regimen in two-center retrospective clinical cohorts and patients with high c-Jun expression exhibited a better response to combination chemotherapy.

CONCLUSIONS

Irbesartan could be used in combination with chemotherapy to improve the therapeutic efficacy in PDAC patients with high levels of c-Jun expression. Irbesartan effectively inhibited chemotherapy resistance by suppressing the Hippo/YAP1/c-Jun/stemness/iron metabolism axis. Based on our findings, we are designing an investigator-initiated phase II clinical trial on the efficacy and safety of irbesartan plus a standard gemcitabine/nab-paclitaxel regimen in the treatment of patients with advanced III/IV staged PDAC and are hopeful that we will observe patient benefits.

Development of a Novel Anti-CD44 Variant 5 Monoclonal Antibody C44Mab-3 for Multiple Applications against Pancreatic Carcinomas

Pancreatic cancer exhibits a poor prognosis due to the lack of early diagnostic biomarkers and the resistance to conventional chemotherapy. CD44 has been known as a cancer stem cell marker and plays tumor promotion and drug resistance roles in various cancers. In particular, the splicing variants are overexpressed in many carcinomas and play essential roles in the cancer stemness, invasiveness or metastasis, and resistance to treatments. Therefore, the understanding of each CD44 variant's (CD44v) function and distribution in carcinomas is essential for the establishment of CD44-targeting tumor therapy. In this study, we immunized mice with CD44v3-10-overexpressed Chinese hamster ovary (CHO)-K1 cells and established various anti-CD44 monoclonal antibodies (mAbs). One of the established clones (C₄₄Mab-3; IgG₁, kappa) recognized peptides of the variant-5-encoded region, indicating that C₄₄Mab-3 is a specific mAb for CD44v5. Moreover, C₄₄Mab-3 reacted with CHO/CD44v3-10 cells or pancreatic cancer cell lines (PK-1 and PK-8) by flow cytometry. The apparent K_D of C₄₄Mab-3 for CHO/CD44v3-10 and PK-1 was 1.3 × 10^-9 M and 2.6 × 10^-9 M, respectively. C₄₄Mab-3 could detect the exogenous CD44v3-10 and endogenous CD44v5 in Western blotting and stained the formalin-fixed paraffin-embedded pancreatic cancer cells but not normal pancreatic epithelial cells in immunohistochemistry. These results indicate that C₄₄Mab-3 is useful for detecting CD44v5 in various applications and is expected to be useful for the application of pancreatic cancer diagnosis and therapy.