Transport properties of pancreatic cancer describe gemcitabine delivery and response

PanIN or IPMN? Redefining Lesion Size in 3 Dimensions

Pancreatic ductal adenocarcinoma (PDAC) develops from 2 known precursor lesions: a majority (∼85%) develops from pancreatic intraepithelial neoplasia (PanIN), and a minority develops from intraductal papillary mucinous neoplasms (IPMNs). Clinical classification of PanIN and IPMN relies on a combination of low-resolution, 3-dimensional (D) imaging (computed tomography, CT), and high-resolution, 2D imaging (histology). The definitions of PanIN and IPMN currently rely heavily on size. IPMNs are defined as macroscopic: generally >1.0 cm and visible in CT, and PanINs are defined as microscopic: generally <0.5 cm and not identifiable in CT. As 2D evaluation fails to take into account 3D structures, we hypothesized that this classification would fail in evaluation of high-resolution, 3D images. To characterize the size and prevalence of PanINs in 3D, 47 thick slabs of pancreas were harvested from grossly normal areas of pancreatic resections, excluding samples from individuals with a diagnosis of an IPMN. All patients but one underwent preoperative CT scans. Through construction of cellular resolution 3D maps, we identified >1400 ductal precursor lesions that met the 2D histologic size criteria of PanINs. We show that, when 3D space is considered, 25 of these lesions can be digitally sectioned to meet the 2D histologic size criterion of IPMN. Re-evaluation of the preoperative CT images of individuals found to possess these large precursor lesions showed that nearly half are visible on imaging. These findings demonstrate that the clinical classification of PanIN and IPMN fails in evaluation of high-resolution, 3D images, emphasizing the need for re-evaluation of classification guidelines that place significant weight on 2D assessment of 3D structures.

Cancer and Cardiovascular Disease: The Conjoined Twins

Cancer and cardiovascular disease are the two most common causes of death worldwide. As the fields of cardiovascular medicine and oncology continue to expand, the area of overlap is becoming more prominent demanding dedicated attention and individualized patient care. We have come to realize that both fields are inextricably intertwined in several aspects, so much so that the mere presence of one, with its resultant downstream implications, has an impact on the other. Nonetheless, cardiovascular disease and cancer are generally approached independently. The focus that is granted to the predominant pathological entity (either cardiovascular disease or cancer), does not allow for optimal medical care for the other. As a result, ample opportunities for improvement in overall health care are being overlooked. Herein, we hope to shed light on the interconnected relationship between cardiovascular disease and cancer and uncover some of the unintentionally neglected intricacies of common cardiovascular therapeutics from an oncologic standpoint.

Double-Balloon Catheter-Mediated Transarterial Chemotherapy Delivery in a Swine Model: A Mechanism Recruiting the Vasa Vasorum for Localized Therapies

PURPOSE

Treatment of hypovascular tumors, such as pancreatic adenocarcinoma, is challenging owing to inefficient drug delivery. This report examines the potential mechanism of localized drug delivery via transarterial microperfusion (TAMP) using a proprietary adjustable double-balloon occlusion catheter in a porcine model.

MATERIALS AND METHODS

Adult Yorkshire swine (N = 21) were used in the Institutional Animal Care & Use Committee-approved protocols. The RC-120 catheter (RenovoRx, Los Altos, California) was positioned into visceral, femoral, and pulmonary arteries with infusion of methylene blue dye, gemcitabine, or gold nanoparticles. Transmural delivery was compared under double-balloon occlusion with and without side-branch exclusion, single-balloon occlusion, and intravenous delivery. Intra-arterial pressure and vascular histologic changes were assessed.

RESULTS

Infusion with double-balloon occlusion and side-branch exclusion provided increased intra-arterial pressure in the isolated segment and enhanced perivascular infusate penetration with minimal vascular injury. Infusates were predominantly found in the vasa vasorum by electron microscopy.

CONCLUSIONS

TAMP enhanced transmural passage mediated by localized increase in arterial pressure via vasa vasorum.

Deletion of the mRNA stability factor ELAVL1 (HuR) in pancreatic cancer cells disrupts the tumor microenvironment integrity

Stromal cells promote extensive fibrosis in pancreatic ductal adenocarcinoma (PDAC), which is associated with poor prognosis and therapeutic resistance. We report here for the first time that loss of the RNA-binding protein human antigen R (HuR, ELAVL1) in PDAC cells leads to reprogramming of the tumor microenvironment. In multiple in vivo models, CRISPR deletion of ELAVL1 in PDAC cells resulted in a decrease of collagen deposition, accompanied by a decrease of stromal markers (i.e. podoplanin, α-smooth muscle actin, desmin). RNA-sequencing data showed that HuR plays a role in cell-cell communication. Accordingly, cytokine arrays identified that HuR regulates the secretion of signaling molecules involved in stromal activation and extracellular matrix organization [i.e. platelet-derived growth factor AA (PDGFAA) and pentraxin 3]. Ribonucleoprotein immunoprecipitation analysis and transcription inhibition studies validated PDGFA mRNA as a novel HuR target. These data suggest that tumor-intrinsic HuR supports extrinsic activation of the stroma to produce collagen and desmoplasia through regulating signaling molecules (e.g. PDGFAA). HuR-deficient PDAC in vivo tumors with an altered tumor microenvironment are more sensitive to the standard of care gemcitabine, as compared to HuR-proficient tumors. Taken together, we identified a novel role of tumor-intrinsic HuR in its ability to modify the surrounding tumor microenvironment and regulate PDGFAA.

Molecular mechanisms of microRNA-301a during tumor progression and metastasis

Cancer is known as one of the leading causes of human deaths globally. Late diagnosis is considered as one of the main reasons for the high mortality rate among cancer patients. Therefore, the introduction of early diagnostic tumor markers can improve the efficiency of therapeutic modalities. MicroRNAs (miRNAs) have a key role in regulation of cell proliferation and apoptosis. MiRNAs deregulation has been frequently reported during tumor progressions. Since, miRNAs have a high stability in body fluids; they can be used as the reliable non-invasive tumor markers. Here, we discussed the role of miR-301a during tumor progressions. MiR-301a mainly functions as an oncogene via the modulation of transcription factors, autophagy, epithelial-mesenchymal transition (EMT), and signaling pathways. This review paves the way to suggest miR-301a as a non-invasive marker for the early tumor diagnosis. MiR-301a can also be suggested as an effective target in cancer therapy.

Angiotensin receptor blockers retard the progression and fibrosis via inhibiting the viability of AGTR1+ CAFs in intrahepatic cholangiocarcinoma

BACKGROUND

Intrahepatic cholangiocarcinoma (iCCA) is a highly lethal malignancy characterized by massive fibrosis and has ineffective adjuvant therapies. Here, we demonstrate the potential of angiotensin receptor blockers (ARBs) in targeting iCCA.

METHODS

Masson's trichrome staining was used to assess the effect of ARBs in iCCA specimens, CCK8 and gel contraction assays in vitro and in xenograft models in vivo. RNA-seq and ATAC-seq were used for mechanistic investigations.

RESULTS

Patients with iCCA who were administered ARBs had a better prognosis and a lower proportion of tumour stroma, indicating alleviated fibrosis. The presence of AGTR1, the ARBs receptor, is associated with a poor prognosis of iCCA and is highly expressed in tumour tissues and cancer-associated fibroblasts (CAFs). The ARBs strongly attenuated the viability of AGTR1+ CAFs in vitro and retarded tumour progression and fibrosis in xenograft models of co-cultured CAFs and iCCA cells. Still, they did not have a significant effect on AGTR1- CAFs. Moreover, ARBs decreased the secretion of AGTR1+ CAF-derived MFAP5 via the Hippo pathway, weakened the interaction between CAFs and iCCA cells, and impaired the aggressiveness of iCCA cells by attenuating the activation of the Notch1 pathway in iCCA cells.

CONCLUSIONS

ARBs exhibit anti-fibrotic function by inhibiting the viability of AGTR1+ CAFs. These findings support using ARBs as a novel therapeutic option for targeting iCCA.

Use of time‑density curves of dynamic contrast‑enhanced computed tomography for determination of the histological therapeutic effects of neoadjuvant chemotherapy for pancreatic ductal adenocarcinoma

The present study aimed to investigate the histological changes caused by neoadjuvant chemotherapy (NAC) for pancreatic ductal adenocarcinoma (PDAC), and to demonstrate the use of time‑density curves (TDCs) of dynamic contrast‑enhanced computed tomography (CECT) for determination of the histological therapeutic effects of NAC for PDAC. A total of 96 patients with PDAC were examined; 46 underwent NAC (NAC group) and 50 did not undergo NAC (non‑NAC group). Based on histological therapeutic effect and using the area of residual tumor (ART) grading system, the NAC group was divided into low‑responders and high‑responders. Histological analysis was used to evaluate the densities of cancer cells, cancer‑associated fibroblasts (CAFs), microvessels and stromal collagen fibers in the NAC and non‑NAC groups. Radiological analysis was used to evaluate the TDCs of three slopes of the NAC group, namely slopes between the non‑contrast and arterial phases (δ1 and δ1'), between the arterial and portal phases (δ2 and δ2'), and between the portal and equilibrium phases (δ3 and δ3'). δ1‑δ3 were before NAC, whereas δ1'‑δ3' were after NAC. Changes in δ1, δ2 and δ3 before and after NAC were denoted as δδ1 (=δ1'‑δ1), δδ2 (=δ2'‑δ2) and δδ3 (=δ3'‑δ3). ART grading system, histological examination and radiological examination data were also statistically analyzed. Histological examination revealed a significant decrease in cancer cells and CAFs, and a significant increase in stromal collagen fibers due to NAC (P<0.01). Radiological examination revealed that δ1' was significantly higher than δ1 in low‑responders (P<0.05), whereas δ2' was significantly lower than δ2 in high‑responders (P<0.01). δδ2 was significantly lower and δδ3 was significantly higher in high‑responders than in low‑responders (P<0.01 and P<0.05, respectively). Receiver operating characteristic curve showed that δδ2 and δδ3 were effective indicators of the histological therapeutic effect of NAC. In conclusion, the TDC of dynamic CECT may be useful for determining the histological therapeutic effect of NAC for PDAC.

Emerging Challenges to Cellular Therapy of Cancer

ABSTRACT

Cellular immunotherapy of cancer in the form of chimeric antigen receptor-modified T-cell therapy has become a standard treatment for lymphoid and more recently plasma cell malignancies. Although their successes in these cancers represent a breakthrough for adoptive cell therapy, there are several challenges to their continued growth in the field of cancer medicine. In this review, we discuss the progress made thus far toward achieving "off-the-shelf" accessibility of cell therapies that has the potential to greatly offset the costs associated with the current practice of making patient-specific products. We also review the innovations under investigation that attempt to make cellular therapy applicable to solid tumors as well.

Endothelin-axis antagonism enhances tumor perfusion in pancreatic cancer

Delivery of therapeutic agents in pancreatic cancer (PC) is impaired due to its hypovascular and desmoplastic tumor microenvironment. The Endothelin (ET)-axis is the major regulator of vasomotor tone under physiological conditions and is highly upregulated in multiple cancers. We investigated the effect of dual endothelin receptor antagonist bosentan on perfusion and macromolecular transport in a PC cell-fibroblast co-implantation tumor model using Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI). Following bosentan treatment, the contrast enhancement ratio and wash-in rates in tumors were two- and nine times higher, respectively, compared to the controls, whereas the time to peak was significantly shorter (7.29 ± 1.29 min v/s 22.08 ± 5.88 min; p = 0.04). Importantly, these effects were tumor selective as the magnitudes of change for these parameters were much lower in muscles. Bosentan treatment also reduced desmoplasia and improved intratumoral distribution of high molecular weight FITC-dextran. Overall, these findings support that targeting the ET-axis can serve as a potential strategy to selectively enhance tumor perfusion and improve the delivery of therapeutic agents in pancreatic tumors.

An EGFR/HER2-targeted conjugate sensitizes gemcitabine-sensitive and resistant pancreatic cancer through different SMAD4-mediated mechanisms

Chemoresistance limits its clinical implementation for pancreatic ductal adenocarcinoma (PDAC). We previously generated an EGFR/HER2 targeted conjugate, dual-targeting ligand-based lidamycin (DTLL), which shows a highly potent antitumor effect. To overcome chemoresistance in PDAC, we aim to study DTLL efficacy when combined with gemcitabine and explore its mechanisms of action. DTLL in combination with gemcitabine show a superior inhibitory effect on the growth of gemcitabine-resistant/sensitive tumors. DTLL sensitizes gemcitabine efficacy via distinct action mechanisms mediated by mothers against decapentaplegic homolog 4 (SMAD4). It not only prevents neoplastic proliferation via ATK/mTOR blockade and NF-κB impaired function in SMAD4-sufficient PDACs, but also restores SMAD4 bioactivity to trigger downstream NF-κB-regulated signaling in SMAD4-deficient tumors and to overcome chemoresistance. DTLL seems to act as a SMAD4 module that normalizes its function in PDAC, having a synergistic effect in combination with gemcitabine. Our findings provide insight into a rational SMAD4-directed precision therapy in PDAC.

Chemoresistance is a main limitation for the treatment of pancreatic ductal adenocarcinoma (PDAC). Here, the authors show that an antibody drug conjugate-like compound targeting both EGFR and HER2 overcomes gemcitabine resistance in PDAC preclinical models by mechanisms involving the tumour suppressor SMAD4.

Sustained degradation of hyaluronic acid using an in situ forming implant

In pancreatic cancer, excessive hyaluronic acid (HA) in the tumor microenvironment creates a viscous stroma, which reduces systemic drug transport into the tumor and correlates with poor patient prognosis. HA can be degraded through both enzymatic and nonenzymatic methods to improve mass transport properties. Here, we use an in situ forming implant to provide sustained degradation of HA directly at a local, targeted site. We formulated and characterized an implant capable of sustained release of hyaluronidase (HAase) using 15 kDa poly(lactic-co-glycolic) acid and bovine testicular HAase. The implant releases bioactive HAase to degrade the HA through enzymatic hydrolysis at early timepoints. In the first 24 h, 17.9% of the HAase is released, which can reduce the viscosity of a 10 mg/mL HA solution by 94.1% and deplete the HA content within primary human pancreatic tumor samples and ex vivo murine tumors. At later timepoints, as lower quantities of HAase are released (51.4% released in total over 21 d), the degradation of HA is supplemented by the acidic by-products that accumulate as a result of implant degradation. Acidic conditions degrade HA through nonenzymatic methods. This formulation has potential as an intratumoral injection to allow sustained degradation of HA at the pancreatic tumor site.

Functional biomarkers derived from computed tomography and magnetic resonance imaging differentiate PDAC subgroups and reveal gemcitabine-induced hypo-vascularization

PURPOSE

Pancreatic ductal adenocarcinoma (PDAC) is a molecularly heterogeneous tumor entity with no clinically established imaging biomarkers. We hypothesize that tumor morphology and physiology, including vascularity and perfusion, show variations that can be detected by differences in contrast agent (CA) accumulation measured non-invasively. This work seeks to establish imaging biomarkers for tumor stratification and therapy response monitoring in PDAC, based on this hypothesis.

METHODS AND MATERIALS

Regional CA accumulation in PDAC was correlated with tumor vascularization, stroma content, and tumor cellularity in murine and human subjects. Changes in CA distribution in response to gemcitabine (GEM) were monitored longitudinally with computed tomography (CT) Hounsfield Units ratio (HUr) of tumor to the aorta or with magnetic resonance imaging (MRI) ΔR₁ area under the curve at 60 s tumor-to-muscle ratio (AUC60r). Tissue analyses were performed on co-registered samples, including endothelial cell proliferation and cisplatin tissue deposition as a surrogate of chemotherapy delivery.

RESULTS

Tumor cell poor, stroma-rich regions exhibited high CA accumulation both in human (meanHUr 0.64 vs. 0.34, p < 0.001) and mouse PDAC (meanAUC60r 2.0 vs. 1.1, p < 0.001). Compared to the baseline, in vivo CA accumulation decreased specifically in response to GEM treatment in a subset of human (HUr -18%) and mouse (AUC60r -36%) tumors. Ex vivo analyses of mPDAC showed reduced cisplatin delivery (GEM: 0.92 ± 0.5 mg/g, vs. vehicle: 3.1 ± 1.5 mg/g, p = 0.004) and diminished endothelial cell proliferation (GEM: 22.3% vs. vehicle: 30.9%, p = 0.002) upon GEM administration.

CONCLUSION

In PDAC, CA accumulation, which is related to tumor vascularization and perfusion, inversely correlates with tumor cellularity. The standard of care GEM treatment results in decreased CA accumulation, which impedes drug delivery. Further investigation is warranted into potentially detrimental effects of GEM in combinatorial therapy regimens.

Mass Transport Model of Radiation Response: Calibration and Application to Chemoradiation for Pancreatic Cancer

PURPOSE

The benefit of radiation therapy for pancreatic ductal adenocarcinoma (PDAC) remains unclear. We hypothesized that a new mechanistic mathematical model of chemotherapy and radiation response could predict clinical outcomes a priori, using a previously described baseline measurement of perfusion from computed tomography scans, normalized area under the enhancement curve (nAUC).

METHODS AND MATERIALS

We simplified an existing mass transport model that predicted cancer cell death by replacing previously unknown variables with averaged direct measurements from randomly selected pathologic sections of untreated PDAC. This allowed using nAUC as the sole model input to approximate tumor perfusion. We then compared the predicted cancer cell death to the actual cell death measured from corresponding resected tumors treated with neoadjuvant chemoradiation in a calibration cohort (n = 80) and prospective cohort (n = 25). After calibration, we applied the model to 2 separate cohorts for pathologic and clinical associations: targeted therapy cohort (n = 101), cetuximab/bevacizumab + radiosensitizing chemotherapy, and standard chemoradiation cohort (n = 81), radiosensitizing chemotherapy to 50.4 Gy in 28 fractions.

RESULTS

We established the relationship between pretreatment computed v nAUC to pathologically verified blood volume fraction of the tumor (r = 0.65; P = .009) and fractional tumor cell death (r = 0.97-0.99; P < .0001) in the calibration and prospective cohorts. On multivariate analyses, accounting for traditional covariates, nAUC independently associated with overall survival in all cohorts (mean hazard ratios, 0.14-0.31). Receiver operator characteristic analyses revealed discrimination of good and bad prognostic groups in the cohorts with area under the curve values of 0.64 to 0.71.

CONCLUSIONS

This work presents a new mathematical modeling approach to predict clinical response from chemotherapy and radiation for PDAC. Our findings indicate that oxygen/drug diffusion strongly influences clinical responses and that nAUC is a potential tool to select patients with PDAC for radiation therapy.

Contrast-enhanced harmonic endoscopic ultrasonography for predicting the efficacy of first-line gemcitabine and nab-paclitaxel chemotherapy in pancreatic cancer

BACKGROUND AND AIMS

The purpose of this study was to assess prognosis with different intratumoral vascularity on contrast-enhanced endoscopic harmonic ultrasonography (CH-EUS) in pancreatic cancer patients receiving chemotherapy.

METHODS

Patients with unresectable pancreatic cancer who underwent CH-EUS before first-line gemcitabine and nab-paclitaxel (GEM and nab-PTX) therapy were classified into four groups according to vascularity on the early and late phases of contrast enhancement: "Group A″, poor on both phases; "Group B″, rich and poor on the early and late phases, respectively; "Group C″, poor and rich on the early and late phases; "Group D″, rich on both phases. Subgroups were compared in terms of progression-free survival (PFS) and overall survival (OS). We also assessed whether the results with CH-EUS correlate with those of contrast-enhanced computed tomography (CE-CT).

RESULTS

On CH-EUS, 57, 64, 0, and 24 patients were classified into Groups A, B, C, and D, respectively. The median PFS of patients in groups A, B, and D was 3.9, 7.6, and 10.8 months, respectively, and the median OS were 9.5, 13.1, and 18.6 months, respectively. Both PFS and OS were longest in Group D (p < 0.001 and p < 0.001, respectively). The results of CE-CT were consistent with those of CH-EUS, and there was a correlation between CE-CT and CH-EUS.

CONCLUSIONS

Evaluation of intratumoral vascularity by CH-EUS may be useful for predicting the efficacy of chemotherapy in patients with pancreatic cancer. A better response to GEM and nab-PTX can be expected in patients showing rich vascularity at both the early and late phases.

Baseline CT-based Radiomic Features Aid Prediction of Nodal Positivity after Neoadjuvant Therapy in Pancreatic Cancer

Purpose To study the association between CT-derived textural features of pancreatic cancer and patient outcome. Materials and Methods This retrospective study evaluated 54 patients (median age, 62 years [range, 40-88 years]; 32 men) with pancreatic cancer who underwent chemoradiation followed by surgical resection and lymph node dissection from May 2012 to June 2016. Three-dimensional segmentation of the pancreatic tumor was performed on baseline dual-energy CT images: 70-keV pancreatic parenchymal phase (PPP) images and iodine material density images. Then, 15 and 19 radiomic features were extracted from each phase, respectively. Logistic regression with elastic net regularization was used to select textural features associated with outcome, and receiver operating characteristic analysis evaluated feature performance. Survival curves were generated using the Kaplan-Meier method. Results The feature of integral total (∫ T), representing the mean intensity in Hounsfield units times the contour volume in milliliters of PPP imaging (hereafter, "∫ T (HU·mL) (PPP)"), is inversely associated with posttherapy pathologic lymph node (ypN) category. A threshold ∫ T (HU·mL) (PPP) less than 507.85 predicted ypN1-2 classification with 96% sensitivity, 34% specificity, and area under the curve of 0.61. Patients with an ∫ T (HU·mL) (PPP) of less than 507.85 had decreased overall survival (median, 2.8 years) compared with patients with an ∫ T (HU·mL) (PPP) of 507.85 or greater (one event at 3.4 years) (P = .006). Patients with an ∫ T (HU·mL) (PPP) of less than 507.85 had decreased progression-free survival (median, 1.5 years) compared with patients with an ∫ T (HU·mL) (PPP) of 507.85 or greater (median, 2.7 years) (P = .001). Conclusion A CT-based radiomic signature may help predict ypN category in patients with pancreatic cancer. Keywords: CT-Dual Energy, Abdomen/GI, Pancreas, Tumor Response, Outcomes Analysis © RSNA, 2022 Supplemental material is available for this article.

Molecular tests for prediction of tumor sensitivity to cytotoxic drugs

Chemotherapy constitutes the backbone of cancer treatment. Several predictive assays assist personalized administration of cytotoxic drugs and are recommended for use in a clinical setting. The deficiency of DNA repair by homologous recombination (HRD), which is caused by inactivation of BRCA1/2 genes or other genetic events, is associated with high tumor responsiveness to platinum compounds, bifunctional alkylating agents and topoisomerase II poisons. Low activity of MGMT predicts the efficacy of nitrosoureas and tetrazines. Some clinically established pharmacogenetic tests allow for the adjustment of drug dosage, for example, the analysis of DPYD allelic variants for administration of fluoropyrimidines and UGT1A1 genotyping for the use of irinotecan. While there are promising molecular predictors of tumor sensitivity to pemetrexed, gemcitabine and taxanes, they remain in the investigational stage and require additional validation. Comprehensive molecular analysis of tumors obtained from drug responders and non-responders is likely to reveal new clinically useful predictive markers for cytotoxic therapy.

PIONEER-Panc: a platform trial for phase II randomized investigations of new and emerging therapies for localized pancreatic cancer

Background

Personalized and effective treatments for pancreatic ductal adenocarcinoma (PDAC) continue to remain elusive. Novel clinical trial designs that enable continual and rapid evaluation of novel therapeutics are needed. Here, we describe a platform clinical trial to address this unmet need.

Methods

This is a phase II study using a Bayesian platform design to evaluate multiple experimental arms against a control arm in patients with PDAC. We first separate patients into three clinical stage groups of localized PDAC (resectable, borderline resectable, and locally advanced disease), and further divide each stage group based on treatment history (treatment naïve or previously treated). The clinical stage and treatment history therefore define 6 different cohorts, and each cohort has one control arm but may have one or more experimental arms running simultaneously. Within each cohort, adaptive randomization rules are applied and patients will be randomized to either an experimental arm or the control arm accordingly. The experimental arm(s) of each cohort are only compared to the applicable cohort specific control arm. Experimental arms may be added independently to one or more cohorts during the study. Multiple correlative studies for tissue, blood, and imaging are also incorporated.

Discussion

To date, PDAC has been treated as a single disease, despite knowledge that there is substantial heterogeneity in disease presentation and biology. It is recognized that the current approach of single arm phase II trials and traditional phase III randomized studies are not well-suited for more personalized treatment strategies in PDAC. The PIONEER Panc platform clinical trial is designed to overcome these challenges and help advance our treatment strategies for this deadly disease.

Trial registration

This study is approved by the Institutional Review Board (IRB) of MD Anderson Cancer Center, IRB-approved protocol 2020-0075. The PIONEER trial is registered at the US National Institutes of Health (ClinicalTrials.gov) NCT04481204.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-09095-7.

Pre-operative radiomics model for prognostication in resectable pancreatic adenocarcinoma with external validation

OBJECTIVES

In resectable pancreatic ductal adenocarcinoma (PDAC), few pre-operative prognostic biomarkers are available. Radiomics has demonstrated potential but lacks external validation. We aimed to develop and externally validate a pre-operative clinical-radiomic prognostic model.

METHODS

Retrospective international, multi-center study in resectable PDAC. The training cohort included 352 patients (pre-operative CTs from five Canadian hospitals). Cox models incorporated (a) pre-operative clinical variables (clinical), (b) clinical plus CT-radiomics, and (c) post-operative TNM model, which served as the reference. Outcomes were overall (OS)/disease-free survival (DFS). Models were assessed in the validation cohort from Ireland (n = 215, CTs from 34 hospitals), using C-statistic, calibration, and decision curve analyses.

RESULTS

The radiomic signature was predictive of OS/DFS in the validation cohort, with adjusted hazard ratios (HR) 2.87 (95% CI: 1.40-5.87, p < 0.001)/5.28 (95% CI 2.35-11.86, p < 0.001), respectively, along with age 1.02 (1.01-1.04, p = 0.01)/1.02 (1.00-1.04, p = 0.03). In the validation cohort, median OS was 22.9/37 months (p = 0.0092) and DFS 14.2/29.8 (p = 0.0023) for high-/low-risk groups and calibration was moderate (mean absolute errors 7%/13% for OS at 3/5 years). The clinical-radiomic model discrimination (C = 0.545, 95%: 0.543-0.546) was higher than the clinical model alone (C = 0.497, 95% CI 0.496-0.499, p < 0.001) or TNM (C = 0.525, 95% CI: 0.524-0.526, p < 0.001). Despite superior net benefit compared to the clinical model, the clinical-radiomic model was not clinically useful for most threshold probabilities.

CONCLUSION

A multi-institutional pre-operative clinical-radiomic model for resectable PDAC prognostication demonstrated superior net benefit compared to a clinical model but limited clinical utility at external validation. This reflects inherent limitations of radiomics for PDAC prognostication, when deployed in real-world settings.

KEY POINTS

• At external validation, a pre-operative clinical-radiomics prognostic model for pancreatic ductal adenocarcinoma (PDAC) outperformed pre-operative clinical variables alone or pathological TNM staging. • Discrimination and clinical utility of the clinical-radiomic model for treatment decisions remained low, likely due to heterogeneity of CT acquisition parameters. • Despite small improvements, prognosis in PDAC using state-of-the-art radiomics methodology remains challenging, mostly owing to its low discriminative ability. Future research should focus on standardization of CT protocols and acquisition parameters.

Early prediction of clinical response to checkpoint inhibitor therapy in human solid tumors through mathematical modeling

Background:

Checkpoint inhibitor therapy of cancer has led to markedly improved survival of a subset of patients in multiple solid malignant tumor types, yet the factors driving these clinical responses or lack thereof are not known. We have developed a mechanistic mathematical model for better understanding these factors and their relations in order to predict treatment outcome and optimize personal treatment strategies.

Methods:

Here, we present a translational mathematical model dependent on three key parameters for describing efficacy of checkpoint inhibitors in human cancer: tumor growth rate (α), tumor-immune infiltration (Λ), and immunotherapy-mediated amplification of anti-tumor response (µ). The model was calibrated by fitting it to a compiled clinical tumor response dataset (n = 189 patients) obtained from published anti-PD-1 and anti-PD-L1 clinical trials, and then validated on an additional validation cohort (n = 64 patients) obtained from our in-house clinical trials.

Results:

The derived parameters Λ and µ were both significantly different between responding versus nonresponding patients. Of note, our model appropriately classified response in 81.4% of patients by using only tumor volume measurements and within 2 months of treatment initiation in a retrospective analysis. The model reliably predicted clinical response to the PD-1/PD-L1 class of checkpoint inhibitors across multiple solid malignant tumor types. Comparison of model parameters to immunohistochemical measurement of PD-L1 and CD8+ T cells confirmed robust relationships between model parameters and their underlying biology.

Conclusions:

These results have demonstrated reliable methods to inform model parameters directly from biopsy samples, which are conveniently obtainable as early as the start of treatment. Together, these suggest that the model parameters may serve as early and robust biomarkers of the efficacy of checkpoint inhibitor therapy on an individualized per-patient basis.

Funding:

We gratefully acknowledge support from the Andrew Sabin Family Fellowship, Center for Radiation Oncology Research, Sheikh Ahmed Center for Pancreatic Cancer Research, GE Healthcare, Philips Healthcare, and institutional funds from the University of Texas M.D. Anderson Cancer Center. We have also received Cancer Center Support Grants from the National Cancer Institute (P30CA016672 to the University of Texas M.D. Anderson Cancer Center and P30CA072720 the Rutgers Cancer Institute of New Jersey). This research has also been supported in part by grants from the National Science Foundation Grant DMS-1930583 (ZW, VC), the National Institutes of Health (NIH) 1R01CA253865 (ZW, VC), 1U01CA196403 (ZW, VC), 1U01CA213759 (ZW, VC), 1R01CA226537 (ZW, RP, WA, VC), 1R01CA222007 (ZW, VC), U54CA210181 (ZW, VC), and the University of Texas System STARS Award (VC). BC acknowledges support through the SER Cymru II Programme, funded by the European Commission through the Horizon 2020 Marie Skłodowska-Curie Actions (MSCA) COFUND scheme and the Welsh European Funding Office (WEFO) under the European Regional Development Fund (ERDF). EK has also received support from the Project Purple, NIH (U54CA210181, U01CA200468, and U01CA196403), and the Pancreatic Cancer Action Network (16-65-SING). MF was supported through NIH/NCI center grant U54CA210181, R01CA222959, DoD Breast Cancer Research Breakthrough Level IV Award W81XWH-17-1-0389, and the Ernest Cockrell Jr. Presidential Distinguished Chair at Houston Methodist Research Institute. RP and WA received serial research awards from AngelWorks, the Gillson-Longenbaugh Foundation, and the Marcus Foundation. This work was also supported in part by grants from the National Cancer Institute to SHC (R01CA109322, R01CA127483, R01CA208703, and U54CA210181 CITO pilot grant) and to PYP (R01CA140243, R01CA188610, and U54CA210181 CITO pilot grant). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Starvation induced autophagy promotes the progression of bladder cancer by LDHA mediated metabolic reprogramming

Background

Aberrant autophagy and preternatural elevated glycolysis are prevalent in bladder cancer (BLCA) and are both related to malignant progression. However, the regulatory relationship between autophagy and glycolytic metabolism remains largely unknown. We imitated starvation conditions in the tumour microenvironment and found significantly increased levels of autophagy and aerobic glycolysis, which both regulated the progression of BLCA cells. We further explored the regulatory relationships and mechanisms between them.

Methods

We used immunoblotting, immunofluorescence and transmission electron microscopy to detect autophagy levels in BLCA cells under different treatments. Lactate and glucose concentration detection demonstrated changes in glycolysis. The expression of lactate dehydrogenase A (LDHA) was detected at the transcriptional and translational levels and was also silenced by small interfering RNA, and the effects on malignant progression were further tested. The underlying mechanisms of signalling pathways were evaluated by western blot, immunofluorescence and immunoprecipitation assays.

Results

Starvation induced autophagy, regulated glycolysis by upregulating the expression of LDHA and caused progressive changes in BLCA cells. Mechanistically, after starvation, the ubiquitination modification of Axin1 increased, and Axin1 combined with P62 was further degraded by the autophagy–lysosome pathway. Liberated β-catenin nuclear translocation increased, binding with LEF1/TCF4 and promoting LDHA transcriptional expression. Additionally, high expression of LDHA was observed in cancer tissues and was positively related to progression.

Conclusion

Our study demonstrated that starvation-induced autophagy modulates glucose metabolic reprogramming by enhancing Axin1 degradation and β-catenin nuclear translocation in BLCA, which promotes the transcriptional expression of LDHA and further malignant progression.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02303-1.

Radiomic analysis to predict local response in locally advanced pancreatic cancer treated with stereotactic body radiation therapy

PURPOSE

Aim of this study is to assess the ability of contrast-enhanced CT image-based radiomic analysis to predict local response (LR) in a retrospective cohort of patients affected by pancreatic cancer and treated with stereotactic body radiation therapy (SBRT). Secondary aim is to evaluate progression free survival (PFS) and overall survival (OS) at long-term follow-up.

METHODS

Contrast-enhanced-CT images of 37 patients who underwent SBRT were analyzed. Two clinical variables (BED, CTV volume), 27 radiomic features were included. LR was used as the outcome variable to build the predictive model. The Kaplan-Meier method was used to evaluate PFS and OS.

RESULTS

Three variables were statistically correlated with the LR in the univariate analysis: Intensity Histogram (StdValue feature), Gray Level Cooccurrence Matrix (GLCM25_Correlation feature) and Neighbor Intensity Difference (NID25_Busyness feature). Multivariate model showed GLCM25_Correlation (P = 0.007) and NID25_Busyness (P = 0.03) as 2 independent predictive variables for LR. The odds ratio values of GLCM25_Correlation and NID25_Busyness were 0.07 (95%CI 0.01-0.49) and 8.10 (95%CI 1.20-54.40), respectively. The area under the curve for the multivariate logistic regressive model was 0.851 (95%CI 0.724-0.978). At a median follow-up of 30 months, median PFS was 7 months (95%CI 6-NA); median OS was 11 months (95%CI 10-22 months).

CONCLUSIONS

This analysis identified a radiomic signature that correlates with LR. To confirm these results, prospective studies could identify patient sub-groups with different rates of radiation dose-response to define a more personalized SBRT approach.

Ferroptosis: At the Crossroad of Gemcitabine Resistance and Tumorigenesis in Pancreatic Cancer

The overall five-year survival rate of pancreatic cancer has hardly changed in the past few decades (less than 10%) because of resistance to all known therapies, including chemotherapeutic drugs. In the past few decades, gemcitabine has been at the forefront of treatment for pancreatic ductal adenocarcinoma, but more strategies to combat drug resistance need to be explored. One promising possibility is ferroptosis, a form of a nonapoptotic cell death that depends on intracellular iron and occurs through the accumulation of lipid reactive oxygen species, which are significant in drug resistance. In this article, we reviewed gemcitabine-resistance mechanisms; assessed the relationship among ferroptosis, tumorigenesis and gemcitabine resistance, and explored a new treatment method for pancreatic cancer.

A Novel Local Tumor Progression Prediction Method for Multimode Ablation Treatment

OBJECTIVE

The multimode ablation of liver cancer, which uses radio-frequency heating after a pre-freezing process to treat the tumor, has shown significantly improved therapeutic effects and enhanced anti-tumor immune response. Unlike open surgery, the ablated lesions remain in the body after treatment, so it is critical to assess the immediate outcome and to monitor disease status over time. Here we propose a novel tumor progression prediction method for simultaneous postoperative evaluation and prognosis analysis.

METHODS

We propose to leverage the intraoperative therapeutic information extracted from thermal dose distribution. For tumors with specific sensitivity reflected in medical images, different thermal doses implicitly indicate the degree of instant damage and long-term inhibition excited under specific ablation energy. We further propose a survival analysis framework for the multimode ablation treatment. It extracts carefully designed features from clinical, preoperative, intraoperative, and postoperative data, then uses random survival forest for feature selection and deep neural networks for survival prediction.

RESULTS

We evaluated the proposed methods using clinical data. The results show that our method outperforms the state-of-the-art survival analysis methods with a C-index of 0.8550.090. The thermal dose information contributes significantly to the prediction accuracy by taking up 21.7% of the overall feature importance.

CONCLUSION

The proposed methods have been demonstrated to be a powerful tool in tumor progression prediction of multimode ablation therapy.

SIGNIFICANCE

This kind of data-driven prognosis analysis may benefit personalized medicine and simplify the follow-up process.

Drug Repurposing, an Attractive Strategy in Pancreatic Cancer Treatment: Preclinical and Clinical Updates

Pancreatic cancer (PC) is one of the deadliest malignancies worldwide, since patients rarely display symptoms until an advanced and unresectable stage of the disease. Current chemotherapy options are unsatisfactory and there is an urgent need for more effective and less toxic drugs to improve the dismal PC therapy. Repurposing of non-oncology drugs in PC treatment represents a very promising therapeutic option and different compounds are currently being considered as candidates for repurposing in the treatment of this tumor. In this review, we provide an update on some of the most promising FDA-approved, non-oncology, repurposed drug candidates that show prominent clinical and preclinical data in pancreatic cancer. We also focus on proposed mechanisms of action and known molecular targets that they modulate in PC. Furthermore, we provide an explorative bioinformatic analysis, which suggests that some of the PC repurposed drug candidates have additional, unexplored, oncology-relevant targets. Finally, we discuss recent developments regarding the immunomodulatory role displayed by some of these drugs, which may expand their potential application in synergy with approved anticancer immunomodulatory agents that are mostly ineffective as single agents in PC.

Digital twinning of Cellular Capsule Technology: Emerging outcomes from the perspective of porous media mechanics

Spheroids encapsulated within alginate capsules are emerging as suitable in vitro tools to investigate the impact of mechanical forces on tumor growth since the internal tumor pressure can be retrieved from the deformation of the capsule. Here we focus on the particular case of Cellular Capsule Technology (CCT). We show in this contribution that a modeling approach accounting for the triphasic nature of the spheroid (extracellular matrix, tumor cells and interstitial fluid) offers a new perspective of analysis revealing that the pressure retrieved experimentally cannot be interpreted as a direct picture of the pressure sustained by the tumor cells and, as such, cannot therefore be used to quantify the critical pressure which induces stress-induced phenotype switch in tumor cells. The proposed multiphase reactive poro-mechanical model was cross-validated. Parameter sensitivity analyses on the digital twin revealed that the main parameters determining the encapsulated growth configuration are different from those driving growth in free condition, confirming that radically different phenomena are at play. Results reported in this contribution support the idea that multiphase reactive poro-mechanics is an exceptional theoretical framework to attain an in-depth understanding of CCT experiments, to confirm their hypotheses and to further improve their design.

A novel gene signature for prognosis prediction and chemotherapy response in patients with pancreatic cancer

Pancreatic cancer is a lethal disease. Chemoresistance is one of the characteristics of pancreatic cancer and leads to a poor prognosis. This study built an effective predictive model for personalized treatment and explored the molecular mechanism of chemoresistance. A four-gene signature, including serine peptidase inhibitor Kazal type 1 (SPINK1), anoctamin 1 (ANO1), desmoglein 3 (DSG3) and GTPase, IMAP family member 1 (GIMAP1) was identified and associated with prognosis and chemoresistance in the training group. An internal testing dataset and the external dataset, GSE57495, were used for validation and showed a good performance of the gene signature. The high-risk group was enriched with multiple oncological pathways related to immunosuppression and was correlated with epidermal growth factor receptor (EGFR) expression, a target molecule of Erlotinib. In conclusion, this study identified a four-gene signature and established two nomograms for predicting prognosis and chemotherapy responses in patients with pancreatic cancer. The clinical value of the nomogram was evaluated by decision curve analysis (DCA). It showed that these may be helpful for clinical treatment decision-making and the discovery of the potential molecular mechanism and therapy targets for pancreatic cancer.

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.

Seed- and Soil-Dependent Differences in Murine Breast Tumor Microenvironments Dictate Anti-PD-L1 IgG Delivery and Therapeutic Efficacy

We sought to determine if Stephen Paget’s “seed and soil” hypothesis of organ-preference patterns of cancer metastasis can explain the development of heterogeneity in a tumor microenvironment (TME) as well as immunotherapeutic delivery and efficacy. We established single-cell-derived clones (clones 1 and 16) from parental 4T1 murine breast cancer cells to create orthotopic primary and liver metastasis models to deconvolute polyclonal complexity cancer cells and the difference in TME-derived heterogeneities. Tumor-bearing mice were treated with anti-PD-L1 IgG or a control antibody, and immunofluorescent imaging and quantification were then performed to evaluate the therapeutic efficacy on tumor growth, the delivery of therapy to tumors, the development of blood vessels, the expression of PD-L1, the accumulation of immune cells, and the amount of coagulation inside tumors. The quantification showed an inverse correlation between the amount of delivered therapy and therapeutic efficacy in parental-cell-derived tumors. In contrast, tumors originating from clone 16 cells accumulated a significantly greater amount of therapy and responded better than clone-1-derived tumors. This difference was greater when tumors grew in the liver than the primary site. A similar trend was found in PD-L1 expression and immune cell accumulation. However, the change in the number of blood vessels was not significant. In addition, the amount of coagulation was more abundant in clone-1-derived tumors when compared to others. Thus, our findings reconfirmed the seed- and soil-dependent differences in PD-L1 expression, therapeutic delivery, immune cell accumulation, and tumor coagulation, which can constitute a heterogeneous delivery and response of immunotherapy in polyclonal tumors growing in different organs.

Stellate Cells Aid Growth-Permissive Metabolic Reprogramming and Promote Gemcitabine Chemoresistance in Pancreatic Cancer

Simple Summary

The great majority, more than 90%, of patients with pancreatic ductal adenocarcinoma (PDAC) die within less than five years after detection of the disease, despite recent treatment advances. The poor prognosis is related to late diagnosis, aggressive disease progression, and tumor resistance to conventional chemotherapy. PDAC tumor tissue is characterized by dense fibrosis and poor nutrient availability. A large portion of the tumor is made up of stromal fibroblasts, the pancreatic stellate cells (PSCs), which are known to contribute to tumor progression in several ways. PSCs have been shown to act as an alternate energy source, induce drug resistance, and inhibit drug availability in tumor cells, however, the underlying exact molecular mechanisms remain unknown. In this literature review, we discuss recent available knowledge about the contributions of PSCs to the overall progression of PDAC via changes in tumor metabolism and how this is linked to therapy resistance.

Abstract

Pancreatic ductal adenocarcinoma (PDAC), also known as pancreatic cancer (PC), is characterized by an overall poor prognosis and a five-year survival that is less than 10%. Characteristic features of the tumor are the presence of a prominent desmoplastic stromal response, an altered metabolism, and profound resistance to cancer drugs including gemcitabine, the backbone of PDAC chemotherapy. The pancreatic stellate cells (PSCs) constitute the major cellular component of PDAC stroma. PSCs are essential for extracellular matrix assembly and form a supportive niche for tumor growth. Various cytokines and growth factors induce activation of PSCs through autocrine and paracrine mechanisms, which in turn promote overall tumor growth and metastasis and induce chemoresistance. To maintain growth and survival in the nutrient-poor, hypoxic environment of PDAC, tumor cells fulfill their high energy demands via several unconventional ways, a process generally referred to as metabolic reprogramming. Accumulating evidence indicates that activated PSCs not only contribute to the therapy-resistant phenotype of PDAC but also act as a nutrient supplier for the tumor cells. However, the precise molecular links between metabolic reprogramming and an acquired therapy resistance in PDAC remain elusive. This review highlights recent findings indicating the importance of PSCs in aiding growth-permissive metabolic reprogramming and gemcitabine chemoresistance in PDAC.

A Mathematical Model to Estimate Chemotherapy Concentration at the Tumor-Site and Predict Therapy Response in Colorectal Cancer Patients with Liver Metastases

Simple Summary

It is known that drug transport barriers in the tumor determine drug concentration at the tumor site, causing disparity from the systemic (plasma) drug concentration. However, current clinical standard of care still bases dosage and treatment optimization on the systemic concentration of drugs. Here, we present a proof of concept observational cohort study to accurately estimate drug concentration at the tumor site from mathematical modeling using biologic, clinical, and imaging/perfusion data, and correlate it with outcome in colorectal cancer liver metastases. We demonstrate that drug concentration at the tumor site, not in systemic circulation, can be used as a credible biomarker for predicting chemotherapy outcome, and thus our mathematical modeling approach can be applied prospectively in the clinic to personalize treatment design to optimize outcome.

Abstract

Chemotherapy remains a primary treatment for metastatic cancer, with tumor response being the benchmark outcome marker. However, therapeutic response in cancer is unpredictable due to heterogeneity in drug delivery from systemic circulation to solid tumors. In this proof-of-concept study, we evaluated chemotherapy concentration at the tumor-site and its association with therapy response by applying a mathematical model. By using pre-treatment imaging, clinical and biologic variables, and chemotherapy regimen to inform the model, we estimated tumor-site chemotherapy concentration in patients with colorectal cancer liver metastases, who received treatment prior to surgical hepatic resection with curative-intent. The differential response to therapy in resected specimens, measured with the gold-standard Tumor Regression Grade (TRG; from 1, complete response to 5, no response) was examined, relative to the model predicted systemic and tumor-site chemotherapy concentrations. We found that the average calculated plasma concentration of the cytotoxic drug was essentially equivalent across patients exhibiting different TRGs, while the estimated tumor-site chemotherapeutic concentration (eTSCC) showed a quadratic decline from TRG = 1 to TRG = 5 (p < 0.001). The eTSCC was significantly lower than the observed plasma concentration and dropped by a factor of ~5 between patients with complete response (TRG = 1) and those with no response (TRG = 5), while the plasma concentration remained stable across TRG groups. TRG variations were driven and predicted by differences in tumor perfusion and eTSCC. If confirmed in carefully planned prospective studies, these findings will form the basis of a paradigm shift in the care of patients with potentially curable colorectal cancer and liver metastases.

ncRNA therapy with miRNA-22-3p suppresses the growth of triple-negative breast cancer

Deregulation of noncoding RNAs, including microRNAs (miRs), is implicated in the pathogenesis of many human cancers, including breast cancer. Through extensive analysis of The Cancer Genome Atlas, we found that expression of miR-22-3p is markedly lower in triple-negative breast cancer (TNBC) than in normal breast tissue. The restoration of miR-22-3p expression led to significant inhibition of TNBC cell proliferation, colony formation, migration, and invasion. We demonstrated that miR-22-3p reduces eukaryotic elongation factor 2 kinase (eEF2K) expression by directly binding to the 3' untranslated region of eEF2K mRNA. Inhibition of EF2K expression recapitulated the effects of miR-22-3p on TNBC cell proliferation, motility, invasion, and suppression of phosphatidylinositol 3-kinase/Akt and Src signaling. Systemic administration of miR-22-3p in single-lipid nanoparticles significantly suppressed tumor growth in orthotopic MDA-MB-231 and MDA-MB-436 TNBC models. Evaluation of the tumor response, following miR-22-3p therapy in these models using a novel mathematical model factoring in various in vivo parameters, demonstrated that the therapy is highly effective against TNBC. These findings suggest that miR-22-3p functions as a tumor suppressor by targeting clinically significant oncogenic pathways and that miR-22-3p loss contributes to TNBC growth and progression. The restoration of miR-22-3p expression is a potential novel noncoding RNA-based therapy for TNBC.

A mathematical model for the quantification of a patient's sensitivity to checkpoint inhibitors and long-term tumour burden

A large proportion of patients with cancer are unresponsive to treatment with immune checkpoint blockade and other immunotherapies. Here, we report a mathematical model of the time-course of tumour responses to immune-checkpoint inhibitors. The model takes into account intrinsic tumour-growth rates, the rates of immune activation and of tumour–immune-cell interactions, and the efficacy of immune-mediated tumour killing. For 124 patients, four cancer types and two immunotherapy agents, the model reliably described the immune responses and final tumour burden across all different cancers and drug combinations examined. In validation cohorts from four clinical trials of checkpoint inhibitors (with a total of 177 patients), the model accurately stratified the patients according to reduced or increased long-term tumour burden. We also provide model-derived quantitative measures of treatment sensitivity for specific drug–cancer combinations. The model can be used to predict responses to therapy and to quantify specific drug–cancer sensitivities in individual patients.

Clinicopathological correlation of radiologic measurement of post-therapy tumor size and tumor volume for pancreatic ductal adenocarcinoma

OBJECTIVES

Tumor size measurement is critical for accurate tumor staging in patients with pancreatic ductal adenocarcinoma (PDAC). However, accurate tumor size measurement is challenging in patients who received neoadjuvant therapy before resection, due to treatment-induced fibrosis and tumor invasion beyond the grossly identified tumor area. In this study, we evaluated the correlation between the tumor size and tumor volume measured on post-therapy computed tomography (CT) scans and the pathological measurement. Also, we investigated the correlation between these measurements and clinicopathological parameters and survival.

MATERIALS AND METHODS

Retrospectively, we evaluated 343 patients with PDAC who received neoadjuvant therapy, followed by pancreaticoduodenectomy and had pre-operative pancreatic protocol CT imaging. We measured the longest tumor diameter (RadL) and the radiological tumor volume (RadV) on the post-therapy CT scan, then we categorized RadL into four radiologic tumor stages (RTS) based on the current AJCC staging (8th edition) protocol and RadV based on the median. Pearson correlation or Spearman's coefficient (δ), T-test and ANOVA was used to test the correlation between the radiological and pathological measurement. Chi-square analysis was used to test the correlation with the tumor pathological response, lymph-node metastasis and margin status and Kaplan-Meier and Cox-proportional hazard for survival analysis. P-value < 0.05 was considered significant.

RESULTS

As a continuous variable, RadL showed a positive linear correlation with the post-therapy pathologic tumor size in the overall patient population (Pearson correlation coefficient: 0.72, P < 0.001) and RadV (δ: 0.63, p < 0.0001). However, there was no correlation between RadL and pathologic tumor size in patients with ypT0 and those with pathologic tumor size of ≤1.0 cm. Post-therapy RTS and RadV group correlated with ypT stage, tumor response grades using either CAP or MDA grading system, distance of superior mesenteric artery margin and tumor recurrence/metastasis.

CONCLUSION

Although RadL tends to understage ypT in PDAC patients who had no radiologically detectable tumor or small tumors (RTS0 or RTS1), radiologic measurement of post-therapy tumor size may be used as a marker for the pathologic tumor staging and tumor response to neoadjuvant therapy.

Extracellular Matrix Composition Modulates the Responsiveness of Differentiated and Stem Pancreatic Cancer Cells to Lipophilic Derivate of Gemcitabine

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal disease. Gemcitabine (GEM) is used as the gold standard drug in PDAC treatment. However, due to its poor efficacy, it remains urgent to identify novel strategies to overcome resistance issues. In this context, an intense stroma reaction and the presence of cancer stem cells (CSCs) have been shown to influence PDAC aggressiveness, metastatic potential, and chemoresistance.

METHODS

We used three-dimensional (3D) organotypic cultures grown on an extracellular matrix composed of Matrigel or collagen I to test the effect of the new potential therapeutic prodrug 4-(N)-stearoyl-GEM, called C18GEM. We analyzed C18GEM cytotoxic activity, intracellular uptake, apoptosis, necrosis, and autophagy induction in both Panc1 cell line (P) and their derived CSCs.

RESULTS

PDAC CSCs show higher sensitivity to C18GEM treatment when cultured in both two-dimensional (2D) and 3D conditions, especially on collagen I, in comparison to GEM. The intracellular uptake mechanisms of C18GEM are mainly due to membrane nucleoside transporters' expression and fatty acid translocase CD36 in Panc1 P cells and to clathrin-mediated endocytosis and CD36 in Panc1 CSCs. Furthermore, C18GEM induces an increase in cell death compared to GEM in both cell lines grown on 2D and 3D cultures. Finally, C18GEM stimulated protective autophagy in Panc1 P and CSCs cultured on 3D conditions.

CONCLUSION

We propose C18GEM together with autophagy inhibitors as a valid alternative therapeutic approach in PDAC treatment.

Predictive Modeling for Voxel-Based Quantification of Imaging-Based Subtypes of Pancreatic Ductal Adenocarcinoma (PDAC): A Multi-Institutional Study

Previously, we characterized qualitative imaging-based subtypes of pancreatic ductal adenocarcinoma (PDAC) on computed tomography (CT) scans. Conspicuous (high delta) PDAC tumors are more likely to have aggressive biology and poorer clinical outcomes compared to inconspicuous (low delta) tumors. Here, we developed a quantitative classification of this imaging-based subtype (quantitative delta; q-delta). Retrospectively, baseline pancreatic protocol CT scans of three cohorts (cohort#1 = 101, cohort#2 = 90 and cohort#3 = 16 [external validation]) of patients with PDAC were qualitatively classified into high and low delta. We used a voxel-based method to volumetrically quantify tumor enhancement while referencing normal-pancreatic-parenchyma and used machine learning-based analysis to build a predictive model. In addition, we quantified the stromal content using hematoxylin- and eosin-stained treatment-naïve PDAC sections. Analyses revealed that PDAC quantitative enhancement values are predictive of the qualitative delta scoring and were used to build a classification model (q-delta). Compared to high q-delta, low q-delta tumors were associated with improved outcomes, and the q-delta class was an independent prognostic factor for survival. In addition, low q-delta tumors had higher stromal content and lower cellularity compared to high q-delta tumors. Our results suggest that q-delta classification provides a clinically and biologically relevant tool that may be integrated into ongoing and future clinical trials.

Imaging-Based Subtypes of Pancreatic Ductal Adenocarcinoma Exhibit Differential Growth and Metabolic Patterns in the Pre-Diagnostic Period: Implications for Early Detection

BACKGROUND

Previously, we characterized subtypes of pancreatic ductal adenocarcinoma (PDAC) on computed-tomography (CT) scans, whereby conspicuous (high delta) PDAC tumors are more likely to have aggressive biology and poorer clinical outcomes compared to inconspicuous (low delta) tumors. Here, we hypothesized that these imaging-based subtypes would exhibit different growth-rates and distinctive metabolic effects in the period prior to PDAC diagnosis.

MATERIALS AND METHODS

Retrospectively, we evaluated 55 patients who developed PDAC as a second primary cancer and underwent serial pre-diagnostic (T0) and diagnostic (T1) CT-scans. We scored the PDAC tumors into high and low delta on T1 and, serially, obtained the biaxial measurements of the pancreatic lesions (T0-T1). We used the Gompertz-function to model the growth-kinetics and estimate the tumor growth-rate constant (α) which was used for tumor binary classification, followed by cross-validation of the classifier accuracy. We used maximum-likelihood estimation to estimate initiation-time from a single cell (10^-6 mm³) to a 10 mm³ tumor mass. Finally, we serially quantified the subcutaneous-abdominal-fat (SAF), visceral-abdominal-fat (VAF), and muscles volumes (cm³) on CT-scans, and recorded the change in blood glucose (BG) levels. T-test, likelihood-ratio, Cox proportional-hazards, and Kaplan-Meier were used for statistical analysis and p-value <0.05 was considered significant.

RESULTS

Compared to high delta tumors, low delta tumors had significantly slower average growth-rate constants (0.024 month^-1 vs. 0.088 month^-1, p<0.0001) and longer average initiation-times (14 years vs. 5 years, p<0.0001). α demonstrated high accuracy (area under the curve (AUC)=0.85) in classifying the tumors into high and low delta, with an optimal cut-off of 0.034 month^-1. Leave-one-out-cross-validation showed 80% accuracy in predicting the delta-class (AUC=0.84). High delta tumors exhibited accelerated SAF, VAF, and muscle wasting (p <0.001), and BG disturbance (p<0.01) compared to low delta tumors. Patients with low delta tumors had better PDAC-specific progression-free survival (log-rank, p<0.0001), earlier stage tumors (p=0.005), and higher likelihood to receive resection after PDAC diagnosis (p=0.008), compared to those with high delta tumors.

CONCLUSION

Imaging-based subtypes of PDAC exhibit distinct growth, metabolic, and clinical profiles during the pre-diagnostic period. Our results suggest that heterogeneous disease biology may be an important consideration in early detection strategies for PDAC.

Pressure-Enabled Drug Delivery Approach in the Pancreas with Retrograde Venous Infusion of Lipiodol with Ex Vivo Analysis

Purpose

To determine the safety and feasibility of pancreatic retrograde venous infusion (PRVI) utilizing a microvalvular infusion system (MVI) to deliver ethiodized oil (lipiodol) by means of the Pressure-Enabled Drug Delivery (PEDD) approach.

Methods

Utilizing transhepatic access, mapping of the pancreatic body and head venous anatomy was performed in 10 swine. PEDD was performed by cannulation of veins in the head (n = 4) and body (n = 10) of the pancreas with a MVI (Surefire® Infusion System (SIS), Surefire Medical, Inc (DBA TriSalus™ Life Sciences)) followed by infusion with lipiodol. Sets of animals were killed either immediately (n = 8) or at 4 days post-PRVI (n = 2). All pancreata were harvested and studied with micro-CT and histology. We also performed three-dimensional volumetric/multiplanar imaging to assess the vascular distribution of lipiodol within the glands.

Results

A total of 14 pancreatic veins were successfully infused with an average of 1.7 (0.5–2.0) mL of lipiodol. No notable change in serum chemistries was seen at 4 days. The signal-to-noise ratio (SNR) of lipiodol deposition was statistically increased both within the organ in target relative to non-target pancreatic tissue and compared to extra pancreatic tissue (p < 0.05). Histological evaluation demonstrated no evidence of pancreatic edema or ischemia.

Conclusions

PEDD using the RVI approach for targeted pancreatic infusions is technically feasible and did not result in organ damage in this pilot animal study.

Multiparametric MRI for prediction of treatment response to neoadjuvant FOLFIRINOX therapy in borderline resectable or locally advanced pancreatic cancer

OBJECTIVES

To identify multiparametric MRI biomarkers to predict the tumor response to neoadjuvant FOLFIRINOX therapy in patients with borderline resectable (BR) or locally advanced (LA) pancreatic ductal adenocarcinoma (PDAC).

METHODS

From May 2016 to March 2018, adult patients with BR or LA PDAC were prospectively enrolled in this study. They received eight cycles of FOLFIRINOX therapy and underwent multiparametric MRI twice (at baseline and after the second cycle). MRI evaluations included dynamic contrast-enhanced MRI, intravoxel incoherent motion diffusion-weighted imaging, and assessment of T2* relaxivity (R2*) and the change in T1 relaxivity (ΔR1, equilibrium phase R1 minus non-enhanced R1) of the tumors. Factors to predict the responders determined by the best overall response during FOLFIRINOX therapy and those to predict progression-free survival (PFS) and overall survival (OS) were evaluated using multivariable logistic regression and the Cox proportional hazard model.

RESULTS

Forty-one patients (mean age, 60.3 years ± 9.3; 24 men) were included. Among the clinical and MRI factors, the baseline ΔR1 (adjusted odds ratio, 31.07; p = 0.008) was the only independent predictor for tumor response. The baseline ΔR1 was also an independent predictor for PFS (adjusted hazard ratio, 0.40; p = 0.033) along with R0 resection. The use of a cutoff ΔR1 value of ≥ 1.31 s^-1 enabled prognostic stratification (median PFS, 16.0 months vs.10.0 months; p = 0.029; median OS, 34.9 months vs. 16.6 months; p = 0 .023, respectively).

CONCLUSIONS

The baseline tumor ΔR1 value may be useful to predict tumor response and survival in patients with BR or LA PDAC receiving FOLFIRINOX neoadjuvant therapy.

KEY POINTS

• Baseline ΔR1 was an independent predictor for tumor response (adjusted odds ratio, 31.07; p = 0.008) and progression-free survival (adjusted hazard ratio, 0.40; p = 0.033) in patients with borderline resectable or locally advanced pancreatic ductal adenocarcinoma receiving neoadjuvant FOLFIRINOX therapy. • The criterion of baseline ΔR1 value ≥ 1.31 s^-1 allowed for the prediction of favorable tumor response and survival outcome after neoadjuvant FOLFIRINOX therapy.

Pancreatic Ductal Adenocarcinoma: Interface Enhancement Gradient Measured on Dual-Energy CT Images Improves Prognostic Evaluation

Purpose

To investigate the prognostic value of differential enhancement on baseline dual-energy CT images in patients with treatment-naive pancreatic ductal adenocarcinoma (PDAC), with a focus on tumor-host interface characterization.

Materials and Methods

This was a retrospective, institutional review board-approved, Health Insurance Portability and Accountability Act-compliant study of 158 consecutive adult patients (mean age, 68 years; age range, 40.9-88.9 years; 50% women) with histopathologically proven, treatment-naive PDAC, who had undergone multiphasic pancreatic dual-energy CT from December 2011 to March 2017. Regions of interest in tumor core, tumor border, pancreas border with tumor, nontumoral pancreas, and aorta were recorded on pancreatic parenchymal phase (PPP) dual-energy CT 70-keV, 52-keV, and iodine material density (MD) images, plus portal venous phase (PVP) conventional CT images. Enhancement gradient (delta) across the tumor-pancreas interface was calculated. Delta was evaluated combining the dual-energy CT values with the PVP values and as individual predictors. Receiver operating characteristic analysis with logistic regression was used to determine the optimal cut point for each dual-energy CT delta to predict disease outcome based on highest Youden index. Survival curves were generated using Kaplan-Meier method, and comparison between two independent groups (high and low delta) was evaluated with log-rank test. Clinical outcomes included overall survival and distant metastasis-free survival. Three independent blinded radiologists visually scored tumor conspicuity (subjective delta score) on a 1-5 scale, and agreement was evaluated with κ statistic.

Results

Ninety-three patients had advanced stage (50 locally advanced and 43 metastatic) and 65 had lower stage (48 resectable and 17 borderline resectable) tumors. Patients with high delta tumors (≥ 40 HU) on either 70-keV PPP images or conventional PVP images had significantly shorter overall survival compared with those with low delta tumors (< 40 HU) in both early stage PDAC (13.5 months vs 23.3 months; hazard ratio [HR], 1.87; 95% confidence interval [CI]: 1.01, 3.5; P = .04) and advanced stage PDAC (10.8 months vs 18.0 months; HR, 2.1; 95% CI: 1.28, 3.6; P = .003). Qualitative visual scoring of tumor conspicuity also showed shorter overall survival in patients with more conspicuous tumors. Highest interreader agreement for subjective delta score was 0.73 and 0.60 using iodine MD and 52-keV images, respectively.

Conclusion

Increased quantitative and qualitative border conspicuity (high delta) is associated with shorter survival in patients with PDAC. Agreement on the subjective qualitative characterization of PDAC borders is best achieved using iodine MD and lower-energy simulated monoenergetic images at pancreatic protocol dual-energy CT.Keywords: Abdomen/GI, CT, CT-Dual Energy, CT-Quantitative, PancreasSupplemental material is available for this article.© RSNA, 2020.

Early detection of pancreatic cancer

Pancreatic ductal adenocarcinoma is most frequently detected at an advanced stage. Such late detection restricts treatment options and contributes to a dismal 5-year survival rate of 3-15%. Pancreatic ductal adenocarcinoma is relatively uncommon and screening of the asymptomatic adult population is not feasible or recommended with current modalities. However, screening of individuals in high-risk groups is recommended. Here, we review groups at high risk for pancreatic ductal adenocarcinoma, including individuals with inherited predisposition and patients with pancreatic cystic lesions. We discuss studies aimed at finding ways of identifying pancreatic ductal adenocarcinoma in high-risk groups, such as among individuals with new-onset diabetes mellitus and people attending primary and secondary care practices with symptoms that suggest this cancer. We review early detection biomarkers, explore the potential of using social media for detection, appraise prediction models developed using electronic health records and research data, and examine the application of artificial intelligence to medical imaging for the purposes of early detection.

Pressure-enabled delivery of gemcitabine in an orthotopic pancreatic cancer mouse model

BACKGROUND

We describe the use of pancreatic retrograde venous infusion in an orthotopic murine model of pancreatic ductal adenocarcinoma and hypothesize that pancreatic retrograde venous infusion delivery of gemcitabine will increase concentrations of gemcitabine in the tumor and the subsequent tumor response to treatment.

METHODS

Murine pancreatic ductal adenocarcinoma (KPC4580P) was transplanted onto the pancreatic tail of C57BL/6J mice. Groups (n = 15) of mice were assigned to sham laparotomy and 100 mg/kg intraperitoneal infusion of gemcitabine (systemic gemcitabine), pancreatic venous isolation with pancreatic retrograde venous infusion of 100 mg/kg gemcitabine, or pancreatic retrograde venous infusion with saline infusion. Tumor pressures were recorded during pancreatic retrograde venous infusion. Mice were killed at 1 hour or 7 days after infusion.

RESULTS

Baseline tumor pressures were 45 ± 8 mm Hg, and pancreatic retrograde venous infusion increased tumor pressures by 29 ± 6 mm Hg (P < .01). Pancreatic retrograde venous infusion gemcitabine mice had greater tumor gemcitabine concentrations compared with systemic gemcitabine (127 vs 19 ng/mg; P < .01) and lesser tumor volumes compared with both systemic gem and pancreatic retrograde venous infusion with saline (274 vs 857 vs 629 mm³; P < .01).

CONCLUSION

Pancreatic retrograde venous infusion increased tumor pressures greater than baseline, improved gemcitabine delivery, and increased the treatment response. These findings suggest that pressurized, regional delivery overcomes the increased pressure barrier in pancreatic ductal adenocarcinoma. Additional preclinical studies with cytotoxic and immunotherapeutic agents and clinical trials using pressure-enabled drug delivery with pancreatic retrograde venous infusion devices are underway.

Radiomic analysis identifies tumor subtypes associated with distinct molecular and microenvironmental factors in head and neck squamous cell carcinoma

PURPOSE

To identify whether radiomic features from pre-treatment computed tomography (CT) scans can predict molecular differences between head and neck squamous cell carcinoma (HNSCC) using The Cancer Imaging Archive (TCIA) and The Cancer Genome Atlas (TCGA).

METHODS

77 patients from the TCIA with HNSCC had imaging suitable for analysis. Radiomic features were extracted and unsupervised consensus clustering was performed to identify subtypes. Genomic data was extracted from the matched patients in the TCGA database. We explored relationships between radiomic features and molecular profiles of tumors, including the tumor immune microenvironment. A machine learning method was used to build a model predictive of CD8 + T-cells. An independent cohort of 83 HNSCC patients was used to validate the radiomic clusters.

RESULTS

We initially extracted 104 two-dimensional radiomic features, and after feature stability tests and removal of volume dependent features, reduced this to 67 features for subsequent analysis. Consensus clustering based on these features resulted in two distinct clusters. The radiomic clusters differed by primary tumor subsite (p = 0.0096), HPV status (p = 0.0127), methylation-based clustering results (p = 0.0025), and tumor immune microenvironment. A random forest model using radiomic features predicted CD8 + T-cells independent of HPV status with R² = 0.30 (p < 0.0001) on cross validation. Consensus clustering on the validation cohort resulted in two distinct clusters that differ in tumor subsite (p = 1.3 × 10^-7) and HPV status (p = 4.0 × 10^-7).

CONCLUSION

Radiomic analysis can identify biologic features of tumors such as HPV status and T-cell infiltration and may be able to provide other information in the near future to help with patient stratification.

Mathematical prediction of clinical outcomes in advanced cancer patients treated with checkpoint inhibitor immunotherapy

We present a mechanistic mathematical model of immune checkpoint inhibitor therapy to address the oncological need for early, broadly applicable readouts (biomarkers) of patient response to immunotherapy. The model is built upon the complex biological and physical interactions between the immune system and cancer, and is informed using only standard-of-care CT. We have retrospectively applied the model to 245 patients from multiple clinical trials treated with anti-CTLA-4 or anti-PD-1/PD-L1 antibodies. We found that model parameters distinctly identified patients with common (n = 18) and rare (n = 10) malignancy types who benefited and did not benefit from these monotherapies with accuracy as high as 88% at first restaging (median 53 days). Further, the parameters successfully differentiated pseudo-progression from true progression, providing previously unidentified insights into the unique biophysical characteristics of pseudo-progression. Our mathematical model offers a clinically relevant tool for personalized oncology and for engineering immunotherapy regimens.

Upregulation of DUSP14 Affects Proliferation, Invasion and Metastasis, Potentially via Epithelial-Mesenchymal Transition and Is Associated with Poor Prognosis in Pancreatic Cancer

Background

There is a growing number of evidence which report the relationship of the dual-specificity phosphatases 14 (DUSP14) with physiological and pathological mechanisms in the human body. However, it is still not known what if any role DUSP14 plays in pancreatic cancer.

Materials and Methods

The study evaluates the levels of DUSP14 in the pancreatic cancer tissues and cell lines using Western blotting and qRT-PCR to assess the levels of the DUSP14 and epithelial–mesenchymal transition (EMT) biomarkers. After the DUSP14 was blocked, the following assays were performed: colony formation, assessments of scratch wound and transwell to examine the effects of DUSP14 on the proliferation, migration and invasion of the pancreatic cancer.

Results

Results showed that there was a significant increase in the level of DUSP14 expression both in the pancreatic cancer tissues and cell lines. Experimental downregulation of DUSP14 induced the inhibition of the capacity of proliferation, migration and invasion of the pancreatic cancer cells. Western blotting analyses showed changes in the levels of expression of the EMT biomarkers, which helped to determine the function of DUSP14 in EMT.

Conclusion

In conclusion, we suggest that DUSP14 is a novel molecular target that can be used for the treatment of pancreatic cancer.

Ultrasound- and Microbubble-Assisted Gemcitabine Delivery to Pancreatic Cancer Cells

Pancreatic ductal adenocarcinoma (PDAC) is a major cause of cancer death worldwide. Poor drug delivery to tumours is thought to limit chemotherapeutic treatment efficacy. Sonoporation combines ultrasound (US) and microbubbles to increase the permeability of cell membranes. We assessed gemcitabine uptake combined with sonoporation in vitro in three PDAC cell lines (BxPC-3, MIA PaCa-2 and PANC-1). Cells were cultured in hypoxic bioreactors, while gemcitabine incubation ± sonoporation was conducted in cells with operational or inhibited nucleoside membrane transporters. Intracellular active metabolite (dFdCTP), extracellular gemcitabine, and inactive metabolite (dFdU) concentrations were measured with liquid chromatography tandem mass spectrometry. Sonoporation with increasing US intensities resulted in decreasing extracellular gemcitabine concentrations in all three cell lines with inhibited membrane transporters. In cells with inhibited membrane transporters, without sonoporation, dFdCTP concentrations were reduced down to 10% of baseline. Sonoporation partially restored gemcitabine uptake in these cells, as indicated by a moderate increase in dFdCTP concentrations (up to 37% of baseline) in MIA PaCa-2 and PANC-1. In BxPC-3, gemcitabine was effectively inactivated to dFdU, which might represent a protective mechanism against dFdCTP accumulation in these cells. Intracellular dFdCTP concentrations did not change significantly following sonoporation in any of the cell lines with operational membrane transporters, indicating that the gemcitabine activation pathway may have been saturated with the drug. Sonoporation allowed a moderate increase in gemcitabine transmembrane uptake in all three cell lines, but pre-existing nucleoside transporters were the major determinants of gemcitabine uptake and retention.

ZIP4 Increases Expression of Transcription Factor ZEB1 to Promote Integrin α3β1 Signaling and Inhibit Expression of the Gemcitabine Transporter ENT1 in Pancreatic Cancer Cells

BACKGROUND & AIMS

Pancreatic tumors undergo rapid growth and progression, become resistant to chemotherapy, and recur after surgery. We studied the functions of the solute carrier family 39 member 4 (SLC39A4, also called ZIP4), which regulates concentrations of intracellular zinc and is increased in pancreatic cancer cells, in cell lines and mice.

METHODS

We obtained 93 pancreatic cancer specimens (tumor and adjacent nontumor tissues) from patients who underwent surgery and gemcitabine chemotherapy and analyzed them by immunohistochemistry. ZIP4 and/or ITGA3 or ITGB1 were overexpressed or knocked down with short hairpin RNAs in AsPC-1 and MIA PaCa-2 pancreatic cancer cells lines, and in pancreatic cells from KPC and KPC-ZEB1-knockout mice, and pancreatic spheroids were established; cells and spheroids were analyzed by immunoblots, reverse transcription polymerase chain reaction, and liquid chromatography tandem mass spectrometry. We studied transcriptional regulation of ZEB1, ITGA3, ITGB1, JNK, and ENT1 by ZIP4 using chromatin precipitation and luciferase reporter assays. Nude mice were given injections of genetically manipulated AsPC-1 and MIA PaCa-2 cells, and growth of xenograft tumors and metastases was measured.

RESULTS

In pancreatic cancer specimens from patients, increased levels of ZIP4 were associated with shorter survival times. MIA PaCa-2 cells that overexpressed ZIP4 had increased resistance to gemcitabine, 5-fluorouracil, and cisplatin, whereas AsPC-1 cells with ZIP4 knockdown had increased sensitivity to these drugs. In mice, xenograft tumors grown from AsPC-1 cells with ZIP4 knockdown were smaller and more sensitive to gemcitabine. ZIP4 overexpression significantly reduced accumulation of gemcitabine in pancreatic cancer cells, increased growth of xenograft tumors in mice, and increased expression of the integrin subunits ITGA3 and ITGB1; expression levels of ITGA3 and ITGB1 were reduced in cells with ZIP4 knockdown. Pancreatic cancer cells with ITGA3 or ITGB1 knockdown had reduced proliferation and formed smaller tumors in mice, despite overexpression of ZIP4; spheroids established from these cells had increased sensitivity to gemcitabine. We found ZIP4 to activate STAT3 to induce expression of ZEB1, which induced expression of ITGA3 and ITGB1 in KPC cells. Increased ITGA3 and ITGB1 expression and subsequent integrin α3β1 signaling, via c-Jun-N-terminal kinase (JNK), inhibited expression of the gemcitabine transporter ENT1, which reduced gemcitabine uptake by pancreatic cancer cells. ZEB1-knockdown cells had increased sensitivity to gemcitabine.

CONCLUSIONS

In studies of pancreatic cancer cell lines and mice, we found that ZIP4 increases expression of the transcription factor ZEB1, which activates expression of ITGA3 and ITGB1. The subsequent increase in integrin α3β1 signaling, via JNK, inhibits expression of the gemcitabine transporter ENT1, so that cells take up smaller amounts of the drug. Activation of this pathway might help mediate resistance of pancreatic tumors to chemotherapeutic agents.

Diffusion-weighted MRI predicts the histologic response for neoadjuvant therapy in patients with pancreatic cancer: a prospective study (DIFFERENT trial)

PURPOSE

Pre-operative prediction of histological response to neoadjuvant therapy aids decisions regarding surgical management of borderline resectable pancreatic cancer (BRPC). We elucidate correlation between pre-/post-treatment whole-tumor apparent diffusion coefficient (ADC) value and rate of tumor cell destruction. We newly verify whether post-treatment ADC value at the site of vascular contact predicts R0 resectability of BRPC.

METHODS

We prospectively reviewed 28 patients with BRPC who underwent diffusion-weighted magnetic resonance imaging before neoadjuvant chemotherapy and surgery. Correlation between the percentage of tumor cell destruction and various parameters was analyzed. Strong parameters were assessed for their ability to predict therapeutic histological response and R0 resectability.

RESULTS

Pre-/post-treatment whole-tumor ADC value correlated with tumor cell destruction rate by all parameters (R = 0.630/0.714, P < 0.001/< 0.0001). The post-treatment cutoff value of ADC at the site of vascular contact for discriminating histological response of tumor destruction of ≤ 50% and tumor destruction of > 50% was determined at 1.42 × 10^-3 mm²/s. It predicts R0 with 88% sensitivity, 50% specificity, and 61% accuracy. For histological response, the post-treatment whole-tumor ADC cutoff value for discriminating between tumor destruction of ≤ 50% and tumor destruction of > 50% was determined at 1.40 × 10^-3 mm²/s. It predicts histological response with 100% sensitivity, 81% specificity, and 89% accuracy. It predicts R0 with 88% sensitivity, 70% specificity, and 75% accuracy.

CONCLUSIONS

Post-treatment whole-tumor ADC value may be a predictor of R0 resectability in patients with BRPC. Tumor cell destruction rate is indicated by the difference between pre-/post-treatment ADC values. This difference is strongly affected by the pre-treatment ADC value. The cutoff value of ADC at the site of vascular contact could not discriminate R0 resectability.

Spatial heterogeneity of nanomedicine investigated by multiscale imaging of the drug, the nanoparticle and the tumour environment

Genetic and phenotypic tumour heterogeneity is an important cause of therapy resistance. Moreover, non-uniform spatial drug distribution in cancer treatment may cause pseudo-resistance, meaning that a treatment is ineffective because the drug does not reach its target at sufficient concentrations. Together with tumour heterogeneity, non-uniform drug distribution causes “therapy heterogeneity”: a spatially heterogeneous treatment effect. Spatial heterogeneity in drug distribution occurs on all scales ranging from interpatient differences to intratumour differences on tissue or cellular scale. Nanomedicine aims to improve the balance between efficacy and safety of drugs by targeting drug-loaded nanoparticles specifically to tumours. Spatial heterogeneity in nanoparticle and payload distribution could be an important factor that limits their efficacy in patients. Therefore, imaging spatial nanoparticle distribution and imaging the tumour environment giving rise to this distribution could help understand (lack of) clinical success of nanomedicine. Imaging the nanoparticle, drug and tumour environment can lead to improvements of new nanotherapies, increase understanding of underlying mechanisms of heterogeneous distribution, facilitate patient selection for nanotherapies and help assess the effect of treatments that aim to reduce heterogeneity in nanoparticle distribution.

In this review, we discuss three groups of imaging modalities applied in nanomedicine research: non-invasive clinical imaging methods (nuclear imaging, MRI, CT, ultrasound), optical imaging and mass spectrometry imaging. Because each imaging modality provides information at a different scale and has its own strengths and weaknesses, choosing wisely and combining modalities will lead to a wealth of information that will help bring nanomedicine forward.

Mathematical Modeling to Address Challenges in Pancreatic Cancer

Pancreatic Ductal Adenocarcinoma (PDAC) is regarded as one of the most lethal cancer types for its challenges associated with early diagnosis and resistance to standard chemotherapeutic agents, thereby leading to a poor five-year survival rate. The complexity of the disease calls for a multidisciplinary approach to better manage the disease and improve the status quo in PDAC diagnosis, prognosis, and treatment. To this end, the application of quantitative tools can help improve the understanding of disease mechanisms, develop biomarkers for early diagnosis, and design patient-specific treatment strategies to improve therapeutic outcomes. However, such approaches have only been minimally applied towards the investigation of PDAC, and we review the current status of mathematical modeling works in this field.

Enhancement pattern mapping technique for improving contrast-to-noise ratios and detectability of hepatobiliary tumors on multiphase computed tomography

PURPOSE

Currently, radiologists use tumor-to-normal tissue contrast across multiphase computed tomography (MPCT) for lesion detection. Here, we developed a novel voxel-based enhancement pattern mapping (EPM) technique and investigated its ability to improve contrast-to-noise ratios (CNRs) in a phantom study and in patients with hepatobiliary cancers.

METHODS

The EPM algorithm is based on the root mean square deviation between each voxel and a normal liver enhancement model using patient-specific (EPM-PA) or population data (EPM-PO). We created a phantom consisting of liver tissue and tumors with distinct enhancement signals under varying tumor sizes, motion, and noise. We also retrospectively evaluated 89 patients with hepatobiliary cancers who underwent active breath-hold MPCT between 2016 and 2017. MPCT phases were registered using a three-dimensional deformable image registration algorithm. For the patient study, CNRs of tumor to adjacent tissue across MPCT phases, EPM-PA and EPM-PO were measured and compared.

RESULTS

EPM resulted in statistically significant CNR improvement (P < 0.05) for tumor sizes down to 3 mm, but the CNR improvement was significantly affected by tumor motion and image noise. Eighty-two of 89 hepatobiliary cases showed CNR improvement with EPM (PA or PO) over grayscale MPCT, by an average factor of 1.4, 1.6, and 1.5 for cholangiocarcinoma, hepatocellular carcinoma, and colorectal liver metastasis, respectively (P < 0.05 for all).

CONCLUSIONS

EPM increases CNR compared with grayscale MPCT for primary and secondary hepatobiliary cancers. This new visualization method derived from MPCT datasets may have applications for early cancer detection, radiomic characterization, tumor treatment response, and segmentation.

IMPLICATIONS FOR PATIENT CARE

We developed a voxel-wise enhancement pattern mapping (EPM) technique to improve the contrast-to-noise ratio (CNR) of multiphase CT. The improvement in CNR was observed in datasets of patients with cholangiocarcinoma, hepatocellular carcinoma, and colorectal liver metastasis. EPM has the potential to be clinically useful for cancers with regard to early detection, radiomic characterization, response, and segmentation.