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

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

Neoadjuvant chemotherapy is associated with suppression of the B cell-centered immune landscape in pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is typically diagnosed at advanced stages and associated with early distant metastasis and poor survival. Besides clinical factors, the tumor microenvironment (TME) emerged as a crucial determinant of patient survival and therapy response in many tumors, including PDAC. Thus, the presence of tumor-infiltrating lymphocytes and the formation of tertiary lymphoid structures (TLS) is associated with longer survival in PDAC. Although neoadjuvant therapy (NeoTx) has improved the management of locally advanced tumors, detailed insight into its effect on various TME components is limited. While a remodeling towards a proinflammatory state was reported for PDAC-infiltrating T cells, the effect of NeoTx on B cell subsets, including plasma cells, and TLS formation is widely unclear. We thus investigated the frequency, composition, and spatial distribution of PDAC-infiltrating B cells in primary resected (PR) versus neoadjuvant-treated patients using a novel multiplex immunohistochemistry panel. The NeoTx group displayed significantly lower frequencies of pan B cells, GC B cells, plasmablasts, and plasma cells, accompanied by a reduced abundance of TLS. This finding was supported by bulk RNA-sequencing analysis of an independent fresh frozen tissue cohort, which revealed that major B cell pathways were downregulated in the NeoTx group. We further observed that plasma cells frequently formed aggregates that localized close to TLS and that TLS+ patients displayed significantly higher plasma cell frequencies compared to TLS- patients in the PR group. Additionally, high densities of CD20+ intratumoral B cells were significantly associated with longer overall survival in the PR group. While CD20+ B cells held no prognostic value for NeoTx patients, an increased frequency of proliferating CD20+Ki67+ B cells emerged as an independent prognostic factor for longer survival in the NeoTx group. These results indicate that NeoTx differentially affects PDAC-infiltrating immune cells and may have detrimental effects on the existing B cell landscape and the formation of TLS. Gaining further insight into the underlying molecular mechanisms is crucial to overcome the intrinsic immunotherapy resistance of PDAC and develop novel strategies to improve the long-term outcome of PDAC patients.

Lymph node examination and survival in resected pancreatic ductal adenocarcinoma: retrospective study.

BACKGROUND: The minimum number of examined lymph nodes (ELN) required for adequate staging and best prediction of survival has not been established in pancreatic ductal adenocarcinoma (PDAC). The aim of the study was to investigate the influence of ELN on staging and survival in PDAC. METHODS: Patients undergoing partial or total pancreatectomy for PDAC at two European university hospitals between 2007 and 2018 were retrospectively reviewed. Multivariate Cox regression model and survival analyses were performed to verify adequate staging. RESULTS: Overall 341 (73 per cent) patients showed lymph node metastasis (N1/N2), whereas 125 (27 per cent) patients had no lymph node involvement (N0). With increasing number of ELN, the proportion of positive lymph nodes increased. The minimum number of ELN needed to detect lymph node involvement was 21. In multivariate analysis, examination of <21 lymph nodes was a significant negative predictor for survival. Examination of ≥21 ELN reversed this effect and ruled out possible misclassification. CONCLUSION: The number of ELN affects survival in PDAC. Possible misclassification was identified when <21 lymph nodes were examined. Therefore, at least 21 lymph nodes must be examined to avoid false lymph node classification in all types of resection.

Phenotype screens of murine pancreatic cancer identify a Tgf-α-Ccl2-paxillin axis driving human-like neural invasion.

Solid cancers like pancreatic ductal adenocarcinoma (PDAC), a type of pancreatic cancer, frequently exploit nerves for rapid dissemination. This neural invasion (NI) is an independent prognostic factor in PDAC, but insufficiently modeled in genetically engineered mouse models (GEMM) of PDAC. Here, we systematically screened for human-like NI in Europe's largest repository of GEMM of PDAC, comprising 295 different genotypes. This phenotype screen uncovered 2 GEMMs of PDAC with human-like NI, which are both characterized by pancreas-specific overexpression of transforming growth factor α (TGF-α) and conditional depletion of p53. Mechanistically, cancer-cell-derived TGF-α upregulated CCL2 secretion from sensory neurons, which induced hyperphosphorylation of the cytoskeletal protein paxillin via CCR4 on cancer cells. This activated the cancer migration machinery and filopodia formation toward neurons. Disrupting CCR4 or paxillin activity limited NI and dampened tumor size and tumor innervation. In human PDAC, phospho-paxillin and TGF-α-expression constituted strong prognostic factors. Therefore, we believe that the TGF-α-CCL2-CCR4-p-paxillin axis is a clinically actionable target for constraining NI and tumor progression in PDAC.

Oncolytic virotherapy for metastatic breast cancer - a case report.

Background: Breast cancer is one of the most common malignancies worldwide and remains incurable after metastasis, with a 3-year overall survival rate of <40%. Case presentation: A 40-year-old, Caucasian patient with a grade-3 estrogen receptor-, progesterone receptor-, Her2-positive breast tumor and two lung nodules was treated with intramuscular targeted immunotherapy with trastuzumab and oral tamoxifen hormone therapy, together with customized intra-tumoral oncolytic virotherapy (IT-OV) over a 17-month period. PET/CT imaging at 3 and 6 months showed increased primary tumor size and metabolic glucose uptake in the primary tumor, axillary lymph nodes and lung nodules, which were paralleled by a hyperimmune reaction in the bones, liver, and spleen. Thereafter, there was a steady decline in both tumor size and metabolic activity until no radiographic evidence of disease was observed. The treatment regimen was well tolerated and good quality of life was maintained throughout. Conclusion: Integration of IT-OV immunotherapy in standard treatment protocols presents an attractive modality for late-stage primary tumors with an abscopal effect on metastases.

Image processing improvements afford second-generation handheld optoacoustic imaging of breast cancer patients.

Background: Since the initial breast transillumination almost a century ago, breast cancer imaging using light has been considered in different implementations aiming to improve diagnostics, minimize the number of available biopsies, or monitor treatment. However, due to strong photon scattering, conventional optical imaging yields low resolution images, challenging quantification and interpretation. Optoacoustic imaging addresses the scattering limitation and yields high-resolution visualization of optical contrast, offering great potential value for breast cancer imaging. Nevertheless, the image quality of experimental systems remains limited due to a number of factors, including signal attenuation with depth and partial view angle and motion effects, particularly in multi-wavelength measurements. Methods: We developed data analytics methods to improve the accuracy of handheld optoacoustic breast cancer imaging, yielding second-generation optoacoustic imaging performance operating in tandem with ultrasonography. Results: We produced the most advanced images yet with handheld optoacoustic examinations of the human breast and breast cancer, in terms of resolution and contrast. Using these advances, we examined optoacoustic markers of malignancy, including vasculature abnormalities, hypoxia, and inflammation, on images obtained from breast cancer patients. Conclusions: We achieved a new level of quality for optoacoustic images from a handheld examination of the human breast, advancing the diagnostic and theranostic potential of the hybrid optoacoustic-ultrasound (OPUS) examination over routine ultrasonography.

Generation of ductal organoids from normal mammary luminal cells reveals invasive potential.

Here we present an experimental model for human luminal progenitor cells that enables single, primary cells isolated from normal tissue to generate complex branched structures resembling the ductal morphology of low-grade carcinoma of no special type. Thereby, we find that ductal structures are generated through invasive branching morphogenesis via matrix remodeling and identify reduced actomyosin contractility as a prerequisite for invasion. In addition, we show that knockout of E-cadherin causes a dissolution of duct formation as observed in invasive lobular carcinoma, a subtype of invasive carcinomas where E-cadherin function is frequently lost. Thus, our model shows that invasive capacity can be elicited from normal luminal cells in specific environments, which results in low-grade no special type morphology. This assay offers a platform to investigate the dynamics of luminal cell invasion and unravel the impact of genetic and non-genetic aberrations on invasive morphology. © 2021 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.

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

PURPOSE: In this prospective exploratory study, we evaluated the feasibility of [18F]fluorodeoxyglucose ([18F]FDG) PET/MRI-based chemotherapy response prediction in pancreatic ductal adenocarcinoma at two weeks upon therapy onset. MATERIAL AND METHODS: In a mixed cohort, seventeen patients treated with chemotherapy in neoadjuvant or palliative intent were enrolled. All patients were imaged by [18F]FDG PET/MRI before and two weeks after onset of chemotherapy. Response per RECIST1.1 was then assessed at 3 months [18F]FDG PET/MRI-derived parameters (MTV50%, TLG50%, MTV2.5, TLG2.5, SUVmax, SUVpeak, ADCmax, ADCmean and ADCmin) were assessed, using multiple t-test, Man-Whitney-U test and Fisher's exact test for binary features. RESULTS: At 72 ± 43 days, twelve patients were classified as responders and five patients as non-responders. An increase in ∆MTV50% and ∆ADC (≥ 20% and 15%, respectively) and a decrease in ∆TLG50% (≤ 20%) at 2 weeks after chemotherapy onset enabled prediction of responders and non-responders, respectively. Parameter combinations (∆TLG50% and ∆ADCmax or ∆MTV50% and ∆ADCmax) further improved discrimination. CONCLUSION: Multiparametric [18F]FDG PET/MRI-derived parameters, in particular indicators of a change in tumor glycolysis and cellularity, may enable very early chemotherapy response prediction. Further prospective studies in larger patient cohorts are recommended to their clinical impact.

Whole Exome Sequencing of Biliary Tubulopapillary Neoplasms Reveals Common Mutations in Chromatin Remodeling Genes.

The molecular carcinogenesis of intraductal tubulopapillary neoplasms (ITPN), recently described as rare neoplasms in the pancreato-biliary tract with a favorable prognosis despite a high incidence of associated pancreato-biliary adenocarcinoma, is still poorly understood. To identify driver genes, chromosomal gains and losses, mutational signatures, key signaling pathways, and potential therapeutic targets, the molecular profile of 11 biliary and 6 pancreatic ITPNs, associated with invasive adenocarcinoma in 14/17 cases, are studied by whole exome sequencing (WES). The WES of 17 ITPNs reveals common copy number variants (CNVs) broadly distributed across the genome, with recurrent chromosomal deletions primarily in 1p36 and 9p21 affecting the tumor suppressors CHD5 and CDKN2A, respectively, and gains in 1q affecting the prominent oncogene AKT3. The identified somatic nucleotide variants (SNVs) involve few core signaling pathways despite high genetic heterogeneity with diverse mutational spectra: Chromatin remodeling, the cell cycle, and DNA damage/repair. An OncoKB search identifies putative actionable genomic targets in 35% of the cases (6/17), including recurrent missense mutations of the FGFR2 gene in biliary ITPNs (2/11, 18%). Our results show that somatic SNV in classical cancer genes, typically associated with pancreato-biliary carcinogenesis, were absent (KRAS, IDH1/2, GNAS, and others) to rare (TP53 and SMAD4, 6%, respectively) in ITPNs. Mutational signature pattern analysis reveals a predominance of an age-related pattern. Our findings highlight that biliary ITPN and classical cholangiocarcinoma display commonalities, in particular mutations in genes of the chromatin remodeling pathway, and appear, therefore, more closely related than pancreatic ITPN and classical pancreatic ductal adenocarcinoma.

Elevated levels of both microRNA 378 (miR-378) and kallikrein-related peptidase 4 (KLK4) mRNA are associated with an unfavorable prognosis in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) patients have the worst outcome among all breast cancer subtypes. In oral squamous carcinoma cells, miR-378 was reported to target the mRNA of kallikrein-related peptidase 4 (KLK4), resulting in inhibition of cell proliferation, migration and invasion, induction of apoptosis, and reduction of tumor growth in vivo. Similarly, a miR-378/KLK4 axis has been proposed in prostate cancer. Here, we analyzed the correlation between miR-378 and KLK4 mRNA expression and determined the prognostic impact of both factors in TNBC. miR-378 and KLK4 mRNA expression levels were determined by quantitative PCR in tumor tissue of TNBC patients (n=103) and correlated with clinical parameters and patients' survival. There was no significant correlation between miR-378 and KLK4 mRNA expression. In univariate Cox regression analysis, elevated miR-378 expression was significantly associated with shortened disease-free survival (DFS, P=0.047) and overall survival (OS, P=0.031), high KLK4 mRNA levels were linked to a worse DFS (P=0.033). Combination of KLK4 mRNA and miR-378 (KLK4+miR-378, low/low versus high and/or high) allowed even better discrimination between favorable and unfavorable prognosis (DFS, P=0.008; OS, P=0.025). In multivariable analysis, miR-378 and KLK4+miR-378 expression remained independent predictive factors for DFS (P=0.014, P=0.010, respectively) and OS (P=0.016, P=0.049, respectively), while KLK4 mRNA only showed a trend towards significance for DFS (P=0.061). Our findings suggest that in TNBC there is no significant impact of miR-378 on KLK4 expression. Both factors, miR-378 and, to a lesser extent, KLK4 mRNA represent unfavorable prognostic markers in TNBC patients.

Bcl3 Couples Cancer Stem Cell Enrichment With Pancreatic Cancer Molecular Subtypes.

BACKGROUND & AIMS: The existence of different subtypes of pancreatic ductal adenocarcinoma (PDAC) and their correlation with patient outcome have shifted the emphasis on patient classification for better decision-making algorithms and personalized therapy. The contribution of mechanisms regulating the cancer stem cell (CSC) population in different subtypes remains unknown. METHODS: Using RNA-seq, we identified B-cell CLL/lymphoma 3 (BCL3), an atypical nf-κb signaling member, as differing in pancreatic CSCs. To determine the biological consequences of BCL3 silencing in vivo and in vitro, we generated bcl3-deficient preclinical mouse models as well as murine cell lines and correlated our findings with human cell lines, PDX models, and 2 independent patient cohorts. We assessed the correlation of bcl3 expression pattern with clinical parameters and subtypes. RESULTS: Bcl3 was significantly down-regulated in human CSCs. Recapitulating this phenotype in preclinical mouse models of PDAC via BCL3 genetic knockout enhanced tumor burden, metastasis, epithelial to mesenchymal transition, and reduced overall survival. Fluorescence-activated cell sorting analyses, together with oxygen consumption, sphere formation, and tumorigenicity assays, all indicated that BCL3 loss resulted in CSC compartment expansion promoting cellular dedifferentiation. Overexpression of BCL3 in human PDXs diminished tumor growth by significantly reducing the CSC population and promoting differentiation. Human PDACs with low BCL3 expression correlated with increased metastasis, and BCL3-negative tumors correlated with lower survival and nonclassical subtypes. CONCLUSIONS: We demonstrate that bcl3 impacts pancreatic carcinogenesis by restraining CSC expansion and by curtailing an aggressive and metastatic tumor burden in PDAC across species. Levels of BCL3 expression are a useful stratification marker for predicting subtype characterization in PDAC, thereby allowing for personalized therapeutic approaches.

PALLD mutation in a European family conveys a stromal predisposition for familial pancreatic cancer.

BACKGROUNDPancreatic cancer is one of the deadliest cancers, with low long-term survival rates. Despite recent advances in treatment, it is important to identify and screen high-risk individuals for cancer prevention. Familial pancreatic cancer (FPC) accounts for 4%-10% of pancreatic cancers. Several germline mutations are related to an increased risk and might offer screening and therapy options. In this study, we aimed to identity of a susceptibility gene in a family with FPC.METHODSWhole exome sequencing and PCR confirmation was performed on the surgical specimen and peripheral blood of an index patient and her sister in a family with high incidence of pancreatic cancer, to identify somatic and germline mutations associated with familial pancreatic cancer. Compartment-specific gene expression data and immunohistochemistry were also queried.RESULTSThe identical germline mutation of the PALLD gene (NM_001166108.1:c.G154A:p.D52N) was detected in the index patient with pancreatic cancer and the tumor tissue of her sister. Whole genome sequencing showed similar somatic mutation patterns between the 2 sisters. Apart from the PALLD mutation, commonly mutated genes that characterize pancreatic ductal adenocarcinoma were found in both tumor samples. However, the 2 patients harbored different somatic KRAS mutations (G12D and G12V). Healthy siblings did not have the PALLD mutation, indicating a disease-specific impact. Compartment-specific gene expression data and IHC showed expression in cancer-associated fibroblasts (CAFs).CONCLUSIONWe identified a germline mutation of the palladin (PALLD) gene in 2 siblings in Europe, affected by familial pancreatic cancer, with a significant overexpression in CAFs, suggesting that stromal palladin could play a role in the development, maintenance, and/or progression of pancreatic cancer.FUNDINGDFG SFB 1321.

Aggressive PDACs Show Hypomethylation of Repetitive Elements and the Execution of an Intrinsic IFN Program Linked to a Ductal Cell of Origin.

Pancreatic ductal adenocarcinoma (PDAC) is characterized by extensive desmoplasia, which challenges the molecular analyses of bulk tumor samples. Here we FACS-purified epithelial cells from human PDAC and normal pancreas and derived their genome-wide transcriptome and DNA methylome landscapes. Clustering based on DNA methylation revealed two distinct PDAC groups displaying different methylation patterns at regions encoding repeat elements. Methylationlow tumors are characterized by higher expression of endogenous retroviral transcripts and double-stranded RNA sensors, which lead to a cell-intrinsic activation of an interferon signature (IFNsign). This results in a protumorigenic microenvironment and poor patient outcome. Methylationlow/IFNsignhigh and Methylationhigh/IFNsignlow PDAC cells preserve lineage traits, respective of normal ductal or acinar pancreatic cells. Moreover, ductal-derived Kras G12D/Trp53 -/- mouse PDACs show higher expression of IFNsign compared with acinar-derived counterparts. Collectively, our data point to two different origins and etiologies of human PDACs, with the aggressive Methylationlow/IFNsignhigh subtype potentially targetable by agents blocking intrinsic IFN signaling. SIGNIFICANCE: The mutational landscapes of PDAC alone cannot explain the observed interpatient heterogeneity. We identified two PDAC subtypes characterized by differential DNA methylation, preserving traits from normal ductal/acinar cells associated with IFN signaling. Our work suggests that epigenetic traits and the cell of origin contribute to PDAC heterogeneity.This article is highlighted in the In This Issue feature, p. 521.

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

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

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

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

Image-Based Molecular Phenotyping of Pancreatic Ductal Adenocarcinoma.

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

Prognostic value of kallikrein-related peptidase 12 (KLK12) mRNA expression in triple-negative breast cancer patients.

BACKGROUND: The serine protease KLK12 belongs to the human fifteen-member family of kallikrein-related peptidases. Differential expression accompanied by either increased or decreased enzymatic activity has been linked to several diseases including cancer. Triple-negative breast cancer (TNBC) represents a very aggressive subgroup of breast cancer with high tumor recurrence rates and poor patient prognosis. Here, we quantified the KLK12 mRNA expression levels in tumor tissue of TNBC patients and analyzed their prognostic value. METHODS: In the present study, KLK12 mRNA expression in tumor tissue of TNBC patients (n = 116) was determined by quantitative real-time PCR assay. The association of KLK12 mRNA levels with clinical parameters, and patients' outcome was analyzed using Chi-square tests, Cox regression models and Kaplan-Meier survival analysis. RESULTS: Positive, but low KLK12 mRNA levels were detected in about half of the cases (54 out of 116; 47%), the other samples were negative for KLK12 mRNA expression. No significant association was observed between KLK12 mRNA levels and clinicopathological variables (age, lymph node status, tumor size, and histological grade). In univariate Cox analyses, positive KLK12 mRNA expression was significantly associated with shortened disease-free survival (DFS; hazard ratio [HR] = 2.12, 95% CI = 1.19-3.78, p = 0.010) as well as overall survival (OS; HR = 1.91, 95% CI = 1.04-3.50, p = 0.037). In multivariable Cox analysis, including all clinical parameters plus KLK12 mRNA, the latter - together with age - remained an independent unfavorable predictive marker for DFS (HR = 2.33, 95% CI = 1.28-4.24, p = 0.006) and showed a trend towards significance in case of OS (HR = 1.80, 95% CI = 0.96-3.38, p = 0.066). CONCLUSIONS: Positive KLK12 expression is remarkably associated with shortened DFS and OS, suggesting that KLK12 plays a tumor-supporting role in TNBC.

SUMO pathway inhibition targets an aggressive pancreatic cancer subtype.

OBJECTIVE: Pancreatic ductal adenocarcinoma (PDAC) still carries a dismal prognosis with an overall 5-year survival rate of 9%. Conventional combination chemotherapies are a clear advance in the treatment of PDAC; however, subtypes of the disease exist, which exhibit extensive resistance to such therapies. Genomic MYC amplifications represent a distinct subset of PDAC with an aggressive tumour biology. It is clear that hyperactivation of MYC generates dependencies that can be exploited therapeutically. The aim of the study was to find and to target MYC-associated dependencies. DESIGN: We analysed human PDAC gene expression datasets. Results were corroborated by the analysis of the small ubiquitin-like modifier (SUMO) pathway in a large PDAC cohort using immunohistochemistry. A SUMO inhibitor was used and characterised using human and murine two-dimensional, organoid and in vivo models of PDAC. RESULTS: We observed that MYC is connected to the SUMOylation machinery in PDAC. Components of the SUMO pathway characterise a PDAC subtype with a dismal prognosis and we provide evidence that hyperactivation of MYC is connected to an increased sensitivity to pharmacological SUMO inhibition. CONCLUSION: SUMO inhibitor-based therapies should be further developed for an aggressive PDAC subtype.

Neoadjuvant Therapy Remodels the Pancreatic Cancer Microenvironment via Depletion of Protumorigenic Immune Cells.

PURPOSE: Neoadjuvant therapy (neoTx) has dramatically improved the prognosis of patients with locally advanced and borderline resectable pancreatic ductal adenocarcinoma, yet its mechanisms of action on tumor cells and the tumor microenvironment are still unknown. Here, we aimed to characterize the multiple facets of neoTx-induced alterations in the pancreatic cancer microenvironment. EXPERIMENTAL DESIGN: We performed the currently most comprehensive histopathologic analysis of desmoplasia, angiogenesis, neural invasion, and immune cell infiltration at the tumor-host interface of pancreatic cancer after neoTx (n = 37) versus after primary resection (n = 37) through quantitative IHC and double immunofluorescence using automated and software-based quantification algorithms. RESULTS: We demonstrate that, independently of the applied pretreatment, neoadjuvant regimes are able to reverse the immunosuppressive behavior of malignant cells on pancreatic cancer microenvironment. Here, neoTx-driven selective depletion of regulatory T cells and myeloid-derived suppressor cells was associated with enrichment of antitumor immune cells in the peritumoral niche, decreased stromal activation, and less neural invasion. Importantly, the degree of this antitumor immune remodeling correlates to the degree of histopathologic response to neoTx. Survival analysis revealed that the tumor proliferation rate together with the activation of the stroma and the intratumoral infiltration with CD4+ T cells and natural killer cells constitute as independent prognostic factors for neoadjuvantly treated pancreatic cancer. CONCLUSIONS: NeoTx is not only cytotoxic but has pleiotropic, beneficial effects on all cellular and noncellular components of pancreatic cancer. Combinational approaches including immunotherapy may unleash long-term and more effective antitumor responses and improve prognosis of pancreatic cancer.

A machine learning algorithm predicts molecular subtypes in pancreatic ductal adenocarcinoma with differential response to gemcitabine-based versus FOLFIRINOX chemotherapy.

PURPOSE: Development of a supervised machine-learning model capable of predicting clinically relevant molecular subtypes of pancreatic ductal adenocarcinoma (PDAC) from diffusion-weighted-imaging-derived radiomic features. METHODS: The retrospective observational study assessed 55 surgical PDAC patients. Molecular subtypes were defined by immunohistochemical staining of KRT81. Tumors were manually segmented and 1606 radiomic features were extracted with PyRadiomics. A gradient-boosted-tree algorithm was trained on 70% of the patients (N = 28) and tested on 30% (N = 17) to predict KRT81+ vs. KRT81- tumor subtypes. A gradient-boosted survival regression model was fit to the disease-free and overall survival data. Chemotherapy response and survival were assessed stratified by subtype and radiomic signature. Radiomic feature importance was ranked. RESULTS: The mean±STDEV sensitivity, specificity and ROC-AUC were 0.90±0.07, 0.92±0.11, and 0.93±0.07, respectively. The mean±STDEV concordance indices between the disease-free and overall survival predicted by the model based on the radiomic parameters and actual patient survival were 0.76±0.05 and 0.71±0.06, respectively. Patients with a KRT81+ subtype experienced significantly diminished median overall survival compared to KRT81- patients (7.0 vs. 22.6 months, HR 4.03, log-rank-test P = <0.001) and a significantly improved response to gemcitabine-based chemotherapy over FOLFIRINOX (10.14 vs. 3.8 months median overall survival, HR 2.33, P = 0.037) compared to KRT81- patients, who responded significantly better to FOLFIRINOX over gemcitabine-based treatment (30.8 vs. 13.4 months median overall survival, HR 2.41, P = 0.027). Entropy was ranked as the most important radiomic feature. CONCLUSIONS: The machine-learning based analysis of radiomic features enables the prediction of subtypes of PDAC, which are highly relevant for disease-free and overall patient survival and response to chemotherapy.