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Lung cancer (LC) is the leading cause of cancer‐related mortality. However, the molecular mechanisms associated with the development of metastasis are poorly understood. Understanding the biology of LC metastasis is critical to unveil the molecular mechanisms for designing targeted therapies. We developed two genetically engineered LC mouse models KrasG12D/+; Trp53R172H/+; Ad‐Cre (KPA) and KrasG12D/+; Ad‐Cre (KA). Survival analysis showed significantly (P = 0.0049) shorter survival in KPA tumor‐bearing mice as compared to KA, suggesting the aggressiveness of the model. Our transcriptomic data showed high expression of N‐acetylgalactosaminide alpha‐2, 6‐sialyltransferase 1 (St6galnac‐I) in KPA compared to KA tumors. ST6GalNAc‐I is an O‐glycosyltransferase, which catalyzes the addition of sialic acid to the initiating GalNAc residues forming sialyl Tn (STn) on glycoproteins, such as mucins. Ectopic expression of species‐specific p53 mutants in the syngeneic mouse and human LC cells led to increased cell migration and high expression of ST6GalNAc‐I, STn, and MUC5AC. Immunoprecipitation of MUC5AC in the ectopically expressing p53R175H cells exhibited higher affinity toward STn. In addition, ST6GalNAc‐I knockout (KO) cells also showed decreased migration, possibly due to reduced glycosylation of MUC5AC as observed by low STn on the glycoprotein. Interestingly, ST6GalNAc‐I KO cells injected mice developed less liver metastasis (P = 0.01) compared to controls, while colocalization of MUC5AC and STn was observed in the liver metastatic tissues of control mice. Collectively, our findings support the hypothesis that mutant p53R175H mediates ST6GalNAc‐I expression, leading to the sialyation of MUC5AC, and thus contribute to LC liver metastasis., In the presence of mutant p53R175H, ST6GalNAc‐I mediates MUC5AC sialylation that increases the aggressiveness of lung adenocarcinoma (LUAD). MUC5AC sialylation is required for integrin β4 interaction that induces angiogenesis and liver metastasis. Hence, targeting the ST6GalNAc‐I/MUC5AC could prevent LUAD metastasis.

Radiotherapy promotes tumor cell death and senescence through the induction of oxidative damage. Recent work has highlighted the importance of lipid peroxidation for radiotherapy efficacy. Excessive lipid peroxidation can promote ferroptosis, a regulated form of cell death. In this review, we address the evidence supporting a role of ferroptosis in response to radiotherapy and discuss the molecular regulators that underlie this interaction. Finally, we postulate on the clinical implications for the intersection of ferroptosis and radiotherapy.

Pancreatic cancer is a highly lethal malignancy. Lack of early diagnostic markers makes timely detection of pancreatic cancer a highly challenging endeavor. Exosomes have emerged as information-rich cancer specific biomarkers. However, characterization of tumor-specific exosomes has been challenging. This study investigated the proof of principle that exosomes could be used for the detection of pancreatic cancer. Label-free analysis of exosomes purified from normal and pancreatic cancer cell lines was performed using surface enhanced Raman Spectroscopy (SERS) and principal component differential function analysis (PC-DFA), to identify tumor-specific spectral signatures. This method differentiated exosomes originating from pancreatic cancer or normal pancreatic epithelial cell lines with 90% accuracy. The cell line trained PC-DFA algorithm was next applied to SERS spectra of serum-purified exosomes. This method exhibited up to 87% and 90% predictive accuracy for HC and EPC individual samples, respectively. Overall, our study identified utility of SERS spectral signature for deciphering exosomal surface signature.

Pancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy with a 5-year survival rate of

Pancreatic cystic lesions (PCLs) are well-known precursors of pancreatic cancer. Their diagnosis can be challenging as their behavior varies from benign to malignant disease. Precise and timely management of malignant pancreatic cysts might prevent transformation to pancreatic cancer. However, the current consensus guidelines, which rely on standard imaging features to predict cyst malignancy potential, are conflicting and unclear. This has led to an increased interest in radiomics, a high-throughput extraction of comprehensible data from standard-of-care images. Radiomics can be used as a diagnostic and prognostic tool in personalized medicine. It utilizes quantitative image analysis to extract features in conjunction with machine learning and artificial intelligence (AI) methods like support vector machines, random forest, and convolutional neural networks for feature selection and classification. Selected features can then serve as imaging biomarkers to predict high-risk PCLs. Radiomics studies conducted heretofore on PCLs have shown promising results. This cost-effective approach would help us to differentiate benign PCLs from malignant ones and potentially guide clinical decision-making leading to better utilization of healthcare resources. In this review, we discuss the process of radiomics, its myriad applications such as diagnosis, prognosis, and prediction of therapy response. We also discuss the outcomes of studies involving radiomic analysis of PCLs and pancreatic cancer, and challenges associated with this novel field along with possible solutions. Although these studies highlight the potential benefit of radiomics in the prevention and optimal treatment of pancreatic cancer, further studies are warranted before incorporating radiomics into the clinical decision support system.

Background Trefoil factors (TFF1, TFF2, and TFF3) are small secretory molecules that recently have gained significant attention in multiple studies as an integral component of pancreatic cancer (PC) subtype-specific gene signature. Here, we comprehensively investigated the diagnostic potential of all the member of trefoil family, i.e., TFF1, TFF2, and TFF3 in combination with CA19.9 for detection of PC. Methods Trefoil factors (TFFs) gene expression was analyzed in publicly available cancer genome datasets, followed by assessment of their expression in genetically engineered spontaneous mouse model (GEM) of PC (KrasG12D; Pdx1-Cre (KC)) and in human tissue microarray consisting of normal pancreas adjacent to tumor (NAT), precursor lesions (PanIN), and various pathological grades of PC by immunohistochemistry (IHC). Serum TFFs and CA19.9 levels were evaluated via ELISA in comprehensive sample set (n = 362) comprised of independent training and validation sets each containing benign controls (BC), chronic pancreatitis (CP), and various stages of PC. Univariate and multivariate logistic regression and receiver operating characteristic curves (ROC) were used to examine their diagnostic potential both alone and in combination with CA19.9. Findings The publicly available datasets and expression analysis revealed significant increased expression of TFF1, TFF2, and TFF3 in human PanINs and PC tissues. Assessment of KC mouse model also suggested upregulated expression of TFFs in PanIN lesions and early stage of PC. In serum analyses studies, TFF1 and TFF2 were significantly elevated in early stages of PC in comparison to benign and CP control group while significant elevation in TFF3 levels were observed in CP group with no further elevation in its level in early stage PC group. In receiver operating curve (ROC) analyses, combination of TFFs with CA19.9 emerged as promising panel for discriminating early stage of PC (EPC) from BC (AUCTFF1+TFF2+TFF3+CA19.9 = 0.93) as well as CP (AUCTFF1+TFF2+TFF3+CA19.9 = 0.93). Notably, at 90% specificity (desired for blood-based biomarker panel), TFFs combination improved CA19.9 sensitivity by 10% and 25% to differentiate EPC from BC and CP respectively. In an independent blinded validation set, the combination of TFFs and CA19.9 (AUCTFF1+TFF2+TFF3+CA19.9 = 0.82) also improved the overall efficacy of CA19.9 (AUCCA19.9 = 0.66) to differentiate EPC from CP proving unique biomarker capabilities of TFFs to distinguish early stage of this deadly lethal disease. Interpretation In silico, tissue and serum analyses validated significantly increased level of all TFFs in precursor lesions and early stages of PC. The combination of TFFs enhanced sensitivity and specificity of CA19.9 to discriminate early stage of PC from benign control and chronic pancreatitis groups.

Metastasis of breast cancer (BC) is the leading cause of mortality in American women. In particular, brain metastasis is a significant clinical problem present in 30-40% of triple receptor negative (TN) and epidermal growth factor receptor 2 (HER2) positive BC patients. These patients also have the worst prognosis of all breast cancers in women. Due to advances in clinical management at both the diagnostic and therapeutic levels, the lifespan or overall survival of these patients has increased, but the manifestation of brain metastasis at later stages of the disease remains an unfortunate burden for these patients. In addition, the blood-brain barrier (BBB) poses an additional hurdle for treatment of BC brain metastases, because the majority of chemotherapeutic drugs fail to cross the BBB. Furthermore, there is no single targeted therapy available for TNBC patients with brain metastasis, and thus there is an urgent requirement to discover novel biomarkers and therapeutics to address BC brain metastasis. In this regard, using a bioinformatics approach, we observed that several mucins, including MUC5AC, are significantly up-regulated in brain metastases of BC compared to primary tumors. However, we found the secretory mucin MUC5AC protein to be substantially high in brain-seeking BC (BSBC) cell lines and metastatic brain tissues. We also observed that knockdown of MUC5AC reduced proliferation and metastatic potential in these cell lines. Furthermore, we observed that MUC5AC colocalizes with activated MET receptor. MUC5AC knockdown in BSBC cell lines reduced MET activation and its downstream targets FAK and paxillin. Interestingly, MET and FAK inhibition using pharmacological inhibitors led to substantial decrease in MUC5AC expression. Overall, these studies suggest that MUC5AC-MET axis may regulate breast cancer brain metastasis. Understanding the MUC5AC-MET axis could be a novel approach for the development of better prognosis and prevention of life-threatening and treatment-resistant breast cancer brain metastasis. Citation Format: Mohd W. Nasser, Shailendra K. Gautam, Ranjana Kanchan, Pranita Atri, Jawed Siddiqui, Rakesh Bhatia, Joseph Carmicheal, Dario Ghersi, Sukhwinder Kaur, Siddharth Mahapatra, Maneesh Jain, Surinder K. Batra. Elucidating the role of MUC5AC-MET axis in breast cancer brain metastasis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 50.

Background and Aims Pancreatic Cancer (PC) is often discovered in late stages, which contributes to its extreme lethality. Early detection is key to improved curative response and increased survival. This study explored the potential of secretory mucin MUC5AC and its glycosylation (Sialyl-Lewis A and Disialyl-Lewis A) states in combination with carbohydrate antigen CA19.9 for early diagnosis of PC. Methods Sandwich ELISA and radioimmunoassay were utilized to measure patient serum for levels of MUC5AC and CA19.9, respectively. A blinded reference set was obtained from the NCI’s Early Detection Research Network Program (n=242): healthy control (HC, N=50), chronic pancreatitis (CP, N=59), acute biliary obstruction (ABO, N= 30), stage IA/IB/IIA (N=52), and stage IIB PC (N=41), to assess the diagnostic performance of MUC5AC. Further, glycans on MUC5AC (Disialyl Lewis A, Lewis A, Blood group H (BGH) antigen) were measured via Surface Enhanced Raman Spectroscopy (SERS). Results MUC5AC levels were significantly increased in patients with stage IA/IB/IIA/IIB PC in comparison to HC, ABO and CP. MUC5AC efficiently differentiated stage IA/IB/IIA PC from healthy controls [AUC- 0.707], ABO [AUC- 0.662], and CP [AUC- 0.745]. CA19.9 differentiated stage IA/IB/IIA PC from healthy controls [AUC- 0.727], ABO [AUC-0.537] and CP [AUC- 0.675]. The MUC5AC combination with CA19.9 significantly improved the performance of CA19.9 alone: healthy controls [AUC- 0.761], ABO [AUC-0 .679], and CP [AUC- 0.753]. Further, PC serum was shown to express MUC5AC with greater Sialyl-Lewis A glycosylation in comparison to Disialyl-Lewis A glycosylation. Further, the reverse trend for these glycosylation was observed in CP and BC group. Conclusions MUC5AC is an early-stage PC biomarker that offers improved performance with CA19.9 for the detection of PC. Also, measurement of MUC5AC glycan modification will aid in the better differentiation of PC from healthy controls and high risk groups (CP, ABO). Further, the ratio of disialyl to CA19.9 glycosylation of MUC5AC is a novel way to differentiate between PC and benign conditions. Citation Format: Chihiro Hayashi, Joseph Carmicheal, Alexey Krasnoslobodtsev, Ying Haung, Randall E. Brand,, Surinder K. Batra, Sukhwinder Kaur. Implication of secretory mucin MUC5AC and its glycan modification for detection of pancreatic cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr LB-244. doi:10.1158/1538-7445.AM2017-LB-244