Delineating the role of βIV-Tubulins in pancreatic cancer: βIVb-tubulin inhibition sensitizes pancreatic cancer cells to vinca alkaloids

Pancreatic cancer (PC) is a lethal disease which is characterized by chemoresistance. Components of the cell cytoskeleton are therapeutic targets in cancer. βIV-tubulin is one such component that has two isotypes—βIVa and βIVb. βIVa and βIVb isotypes only differ in two amino acids at their C-terminus. Studies have implicated βIVa-tubulin or βIVb-tubulin expression with chemoresistance in prostate, breast, ovarian and lung cancer. However, no studies have examined the role of βIV-tubulin in PC or attempted to identify isotype specific roles in regulating cancer cell growth and chemosensitivity. We aimed to determine the role of βIVa- or βIVb-tubulin on PC growth and chemosensitivity. PC cells (MiaPaCa-2, HPAF-II, AsPC1) were treated with siRNA (control, βIVa-tubulin or βIVb-tubulin). The ability of PC cells to form colonies in the presence or absence of chemotherapy was measured by clonogenic assays. Inhibition of βIVa-tubulin in PC cells had no effect chemosensitivity. In contrast, inhibition of βIVb-tubulin in PC cells sensitized to vinca alkaloids (Vincristine, Vinorelbine and Vinblastine), which was accompanied by increased apoptosis and enhanced cell cycle arrest. We show for the first time that βIVb-tubulin, but not βIVa-tubulin, plays a role in regulating vinca alkaloid chemosensitivity in PC cells. The results from this study suggest βIVb-tubulin may be a novel therapeutic target and predictor of vinca alkaloid sensitivity for PC and warrants further investigation

Defining the molecular pathology of pancreatic body and tail adenocarcinom

Background: Pancreatic ductal adenocarcinoma (PDAC) remains a dismal disease, with very little improvement in survival over the past 50 years. Recent large-scale genomic studies have improved understanding of the genomic and transcriptomic landscape of the disease, yet very little is known about molecular heterogeneity according to tumour location in the pancreas; body and tail PDACs especially tend to have a significantly worse prognosis. The aim was to investigate the molecular differences between PDAC of the head and those of the body and tail of the pancreas. Methods: Detailed correlative analysis of clinicopathological variables, including tumour location, genomic and transcriptomic data, was performed using the Australian Pancreatic Cancer Genome Initiative (APGI) cohort, part of the International Cancer Genome Consortium study. Results: Clinicopathological data were available for 518 patients recruited to the APGI, of whom 421 underwent genomic analyses; 179 of these patients underwent whole-genome and 96 RNA sequencing. Patients with tumours of the body and tail had significantly worse survival than those with pancreatic head tumours (12·1 versus 22·0 months; P = 0·001). Location in the body and tail was associated with the squamous subtype of PDAC. Body and tail PDACs enriched for gene programmes involved in tumour invasion and epithelial-to-mesenchymal transition, as well as features of poor antitumour immune response. Whether this is due to a molecular predisposition from the outset, or reflects a later time point on the tumour molecular clock, requires further investigation using well designed prospective studies in pancreatic cancer. Conclusion: PDACs of the body and tail demonstrate aggressive tumour biology that may explain worse clinical outcomes

Pancreatic cancer: from genome discovery to PRECISION-Panc

No abstract available

PRECISION-Panc: the next generation therapeutic development platform for pancreatic cancer

No abstract available

Clinical and molecular characterization of HER2 amplified-pancreatic cancer

<p>Background: Pancreatic cancer is one of the most lethal and molecularly diverse malignancies. Repurposing of therapeutics that target specific molecular mechanisms in different disease types offers potential for rapid improvements in outcome. Although HER2 amplification occurs in pancreatic cancer, it is inadequately characterized to exploit the potential of anti-HER2 therapies.</p> <p>Methods: HER2 amplification was detected and further analyzed using multiple genomic sequencing approaches. Standardized reference laboratory assays defined HER2 amplification in a large cohort of patients (n = 469) with pancreatic ductal adenocarcinoma (PDAC).</p> <p>Results: An amplified inversion event (1 MB) was identified at the HER2 locus in a patient with PDAC. Using standardized laboratory assays, we established diagnostic criteria for HER2 amplification in PDAC, and observed a prevalence of 2%. Clinically, HER2- amplified PDAC was characterized by a lack of liver metastases, and a preponderance of lung and brain metastases. Excluding breast and gastric cancer, the incidence of HER2-amplified cancers in the USA is >22,000 per annum.</p> <p>Conclusions: HER2 amplification occurs in 2% of PDAC, and has distinct features with implications for clinical practice. The molecular heterogeneity of PDAC implies that even an incidence of 2% represents an attractive target for anti-HER2 therapies, as options for PDAC are limited. Recruiting patients based on HER2 amplification, rather than organ of origin, could make trials of anti-HER2 therapies feasible in less common cancer types.</p&gt

Expression of LMO4 and outcome in pancreatic ductal adenocarcinoma

Identification of a biomarker of prognosis and response to therapy that can be assessed preoperatively would significantly improve overall outcomes for patients with pancreatic cancer. In this study, patients whose tumours exhibited high LMO4 expression had a significant survival advantage following operative resection, whereas the survival of those patients whose tumours had low or no LMO4 expression was not significantly different when resection was compared with operative biopsy alone

Reshaping preoperative treatment of pancreatic cancer in the era of precision medicine

This review summarises the recent evidence on preoperative therapeutic strategies in pancreatic cancer and discusses the rationale for an imminent need for a personalized therapeutic approach in non-metastatic disease. The molecular diversity of pancreatic cancer and its influence on prognosis and treatment response, combined with the failure of “all-comer” treatments to significantly impact on patient outcomes, requires a paradigm shift towards a genomic-driven approach. This is particularly important in the preoperative, potentially curable setting, where a personalized treatment allocation has the substantial potential to reduce pancreatic cancer mortality

ADAM12 is a circulating marker for stromal activation in pancreatic cancer and predicts response to chemotherapy

Pancreatic ductal adenocarcinoma (PDAC) is characterized by abundant stroma that harbors tumor-promoting properties. No good biomarkers exist to monitor the effect of stromal targeting therapies or to predict response. We set out to identify such non-invasive markers for PDAC stroma and predict response to therapy. Gene expression datasets, co-culture experiments, xenografts, and patient samples were analyzed. Serum samples were measured from a cohort of 58 resected patients, and 87 metastatic or locally advanced PDAC patients. Baseline and follow-up levels were assessed in 372 additional metastatic PDAC patients who received nab-paclitaxel with gemcitabine (n = 184) or gemcitabine monotherapy (n = 188) in the phase III MPACT trial. Increased levels of ADAM12 were found in PDAC patients compared to healthy controls (p < 0.0001, n = 157 and n = 38). High levels of ADAM12 significantly associated with poor outcome in resected PDAC (HR 2.07, p = 0.04). In the MPACT trial survival was significantly longer for patients who received nab-paclitaxel and had undetectable ADAM12 levels before treatment (OS 12.3 m vs 7.9 m p = 0.0046). Consistently undetectable or decreased ADAM12 levels during treatment significantly associated with longer survival as well (OS 14.4 m and 11.2 m, respectively vs 8.3, p = 0.0054). We conclude that ADAM12 is a blood-borne proxy for stromal activation, the levels of which have prognostic significance and correlate with treatment benefit

A deep learning system accurately classifies primary and metastatic cancers using passenger mutation patterns.

In cancer, the primary tumour's organ of origin and histopathology are the strongest determinants of its clinical behaviour, but in 3% of cases a patient presents with a metastatic tumour and no obvious primary. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, we train a deep learning classifier to predict cancer type based on patterns of somatic passenger mutations detected in whole genome sequencing (WGS) of 2606 tumours representing 24 common cancer types produced by the PCAWG Consortium. Our classifier achieves an accuracy of 91% on held-out tumor samples and 88% and 83% respectively on independent primary and metastatic samples, roughly double the accuracy of trained pathologists when presented with a metastatic tumour without knowledge of the primary. Surprisingly, adding information on driver mutations reduced accuracy. Our results have clinical applicability, underscore how patterns of somatic passenger mutations encode the state of the cell of origin, and can inform future strategies to detect the source of circulating tumour DNA