Connectivity mapping-based identification of pharmacological inhibitor targeting HDAC6 in aggressive pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) remains highly lethal due to limited therapeutic options and expensive/burdensome drug discovery processes. Utilizing genomic-data-driven Connectivity Mapping (CMAP) to identify a drug closer to real-world PC targeting may improve pancreatic cancer (PC) patient outcomes. Initially, we mapped CMAP data to gene expression from 106 PC patients, identifying nine negatively connected drugs. These drugs were further narrowed down using a similar analysis for PC cell lines, human tumoroids, and patient-derived xenografts datasets, where ISOX emerged as the most potent agent to target PC. We used human and mouse syngeneic PC cells, human and mouse tumoroids, and in vivo mice to assess the ability of ISOX alone and in combination with 5FU to inhibit tumor growth. Global transcriptomic and pathway analysis of the ISOX-LINCS signature identified HDAC 6/cMyc as the target axis for ISOX. Specifically, we discovered that genetic and pharmacological targeting of HDAC 6 affected non-histone protein cMyc acetylation, leading to cMyc instability, thereby disrupting PC growth and metastasis by affecting cancer stemness. Finally, KrasG12D harboring tumoroids and mice responded effectively against ISOX and 5FU treatment by enhancing survival and controlling metastasis incidence. Overall, our data validate ISOX as a new drug to treat advanced PC patients without toxicity to normal cells. Our study supports the clinical utility of ISOX along with 5FU in future PC clinical trials.

Radiation therapy for pineal parenchymal tumor of intermediate differentiation: A case series and literature review.

Pineal parenchymal tumor of intermediate differentiation (PPTID) is a rare, primary tumor of the pineal gland. Due to its rarity, there is no consensus on optimal therapeutic strategies or standard characterization of the tumor's behavior. Here, we report 2 new cases of PPTID and an extensive review of the literature involving the use and extent of radiation therapy. Patient 1 is a 54-year-old male who presented with PPTID and drop metastases in the spinal cord, received cranial spinal irradiation (CSI), and experienced recurrence 3.5 years after treatment. Stereotactic body radiation therapy (SBRT) helped the patient into remission for 9 months. Patient 2 is a 32-year-old male with a local PPTID at presentation who went on to receive surgical resection followed by focused adjuvant radiation therapy to the pineal tumor bed. He then presented 6 years after treatment with extensive disseminated recurrence and died due to leptomeningeal disease (LMD) about 4 years after recurrence. The available literature on PPTID is limited and reported cases of LMD with ongoing follow-up in PPTID are scarce. Our report adds to the current known PPTID cases, contributing to the information available regarding prognosis and treatment response. Although an optimal therapeutic strategy for PPTID still cannot be determined, data from the literature suggest that utilizing radiation therapy in patients with low-risk disease and gross total resections as well as the use of upfront CSI have the potential to improve patient progression and survival outcomes.

Substituent Effects Impact Surface Charge and Aggregation of Thiophenol-Labeled Gold Nanoparticles for SERS Biosensors.

SERS immunoassay biosensors hold immense potential for clinical diagnostics due to their high sensitivity and growing interest in multi-marker panels. However, their development has been hindered by difficulties in designing compatible extrinsic Raman labels. Prior studies have largely focused on spectroscopic characteristics in selecting Raman reporter molecules (RRMs) for multiplexing since the presence of well-differentiated spectra is essential for simultaneous detection. However, these candidates often induce aggregation of the gold nanoparticles used as SERS nanotags despite their similarity to other effective RRMs. Thus, an improved understanding of factors affecting the aggregation of RRM-coated gold nanoparticles is needed. Substituent electronic effects on particle stability were investigated using various para-substituted thiophenols. The inductive and resonant effects of functional group modifications were strongly correlated with nanoparticle surface charge and hence their stability. Treatment with thiophenols diminished the negative surface charge of citrate-stabilized gold nanoparticles, but electron-withdrawing substituents limited the magnitude of this diminishment. It is proposed that this phenomenon arises by affecting the interplay of competing sulfur binding modes. This has wide-reaching implications for the design of biosensors using thiol-modified gold surfaces. A proof-of-concept multiplexed SERS biosensor was designed according to these findings using the two thiophenol compounds with the most electron-withdrawing substitutions: NO2 and CN.

Disruption of FDPS/Rac1 axis radiosensitizes pancreatic ductal adenocarcinoma by attenuating DNA damage response and immunosuppressive signalling.

BACKGROUND: Radiation therapy (RT) has a suboptimal effect in patients with pancreatic ductal adenocarcinoma (PDAC) due to intrinsic and acquired radioresistance (RR). Comprehensive bioinformatics and microarray analysis revealed that cholesterol biosynthesis (CBS) is involved in the RR of PDAC. We now tested the inhibition of the CBS pathway enzyme, farnesyl diphosphate synthase (FDPS), by zoledronic acid (Zol) to enhance radiation and activate immune cells. METHODS: We investigated the role of FDPS in PDAC RR using the following methods: in vitro cell-based assay, immunohistochemistry, immunofluorescence, immunoblot, cell-based cholesterol assay, RNA sequencing, tumouroids (KPC-murine and PDAC patient-derived), orthotopic models, and PDAC patient's clinical study. FINDINGS: FDPS overexpression in PDAC tissues and cells (P < 0.01 and P < 0.05) is associated with poor RT response and survival (P = 0.024). CRISPR/Cas9 and pharmacological inhibition (Zol) of FDPS in human and mouse syngeneic PDAC cells in conjunction with RT conferred higher PDAC radiosensitivity in vitro (P < 0.05, P < 0.01, and P < 0.001) and in vivo (P < 0.05). Interestingly, murine (P = 0.01) and human (P = 0.0159) tumouroids treated with Zol+RT showed a significant growth reduction. Mechanistically, RNA-Seq analysis of the PDAC xenografts and patients-PBMCs revealed that Zol exerts radiosensitization by affecting Rac1 and Rho prenylation, thereby modulating DNA damage and radiation response signalling along with improved systemic immune cells activation. An ongoing phase I/II trial (NCT03073785) showed improved failure-free survival (FFS), enhanced immune cell activation, and decreased microenvironment-related genes upon Zol+RT treatment. INTERPRETATION: Our findings suggest that FDPS is a novel radiosensitization target for PDAC therapy. This study also provides a rationale to utilize Zol as a potential radiosensitizer and as an immunomodulator in PDAC and other cancers. FUNDING: National Institutes of Health (P50, P01, and R01).

Contribution of Lipid Oxidation and Ferroptosis to Radiotherapy Efficacy.

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.

ST6GalNAc-I promotes lung cancer metastasis by altering MUC5AC sialylation.

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.

Correlation of dosimetric factors with the development of symptomatic radiation pneumonitis in stereotactic body radiotherapy.

BACKGROUND: The development of radiation pneumonitis (RP) after Stereotactic Body Radiotherapy (SBRT) is known to be associated with many different factors, although historical analyses of RP have commonly utilized heterogeneous fractionation schemes and methods of reporting. This study aims to correlate dosimetric values and their association with the development of Symptomatic RP according to recent reporting standards as recommended by the American Association of Physicists in Medicine. METHODS: We performed a single-institution retrospective review for patients who received SBRT to the lung from 2010 to 2017. Inclusion criteria required near-homogeneous tumoricidal (α/ß = 10 Gy) biological effective dose (BED10) of 100-105 Gy (e.g., 50/5, 48/4, 60/8), one or two synchronously treated lesions, and at least 6 months of follow up or documented evidence of pneumonitis. Symptomatic RP was determined clinically by treating radiation oncologists, requiring radiographic evidence and the administration of steroids. Dosimetric parameters and patient factors were recorded. Lung volumes subtracted gross tumor volume(s). Wilcoxon Rank Sums tests were used for nonparametric comparison of dosimetric data between patients with and without RP; p-values were Bonferroni adjusted when applicable. Logistic regressions were conducted to predict probabilities of symptomatic RP using univariable models for each radiation dosimetric parameter. RESULTS: The final cohort included 103 treated lesions in 93 patients, eight of whom developed symptomatic RP (n = 8; 8.6%). The use of total mean lung dose (MLD) > 6 Gy alone captured five of the eight patients who developed symptomatic RP, while V20 > 10% captured two patients, both of whom demonstrated a MLD > 6 Gy. The remaining three patients who developed symptomatic RP without exceeding either metric were noted to have imaging evidence of moderate interstitial lung disease, inflammation of the lungs from recent concurrent chemoradiation therapy to the contralateral lung, or unique peri-tumoral inflammatory appearance at baseline before treatment. CONCLUSIONS: This study is the largest dosimetric analysis of symptomatic RP in the literature, of which we are aware, that utilizes near-homogenous tumoricidal BED fractionation schemes. Mean lung dose and V20 are the most consistently reported of the various dosimetric parameters associated with symptomatic RP. MLD should be considered alongside V20 in the treatment planning process. TRIAL REGISTRATION: Retrospectively registered on IRB 398-17-EP.

Presence and structure-activity relationship of intrinsically disordered regions across mucins.

Many members of the mucin family are evolutionarily conserved and are often aberrantly expressed and glycosylated in various benign and malignant pathologies leading to tumor invasion, metastasis, and immune evasion. The large size and extensive glycosylation present challenges to study the mucin structure using traditional methods, including crystallography. We offer the hypothesis that the functional versatility of mucins may be attributed to the presence of intrinsically disordered regions (IDRs) that provide dynamism and flexibility and that the IDRs offer potential therapeutic targets. Herein, we examined the links between the mucin structure and function based on IDRs, posttranslational modifications (PTMs), and potential impact on their interactome. Using sequence-based bioinformatics tools, we observed that mucins are predicted to be moderately (20%-40%) to highly (>40%) disordered and many conserved mucin domains could be disordered. Phosphorylation sites overlap with IDRs throughout the mucin sequences. Additionally, the majority of predicted O- and N- glycosylation sites in the tandem repeat regions occur within IDRs and these IDRs contain a large number of functional motifs, that is, molecular recognition features (MoRFs), which directly influence protein-protein interactions (PPIs). This investigation provides a novel perspective and offers an insight into the complexity and dynamic nature of mucins.

Radiomics in stratification of pancreatic cystic lesions: Machine learning in action.

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 network 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.

Elevating pancreatic cystic lesion stratification: Current and future pancreatic cancer biomarker(s).

Pancreatic ductal adenocarcinoma (PDAC) is an incredibly deadly disease with a 5-year survival rate of 9%. The presence of pancreatic cystic lesions (PCLs) confers an increased likelihood of future pancreatic cancer in patients placing them in a high-risk category. Discerning concurrent malignancy and risk of future PCL progression to cancer must be carefully and accurately determined to improve survival outcomes and avoid unnecessary morbidity of pancreatic resection. Unfortunately, current image-based guidelines are inadequate to distinguish benign from malignant lesions. There continues to be a need for accurate molecular and imaging biomarker(s) capable of identifying malignant PCLs and predicting the malignant potential of PCLs to enable risk stratification and effective intervention management. This review provides an update on the current status of biomarkers from pancreatic cystic fluid, pancreatic juice, and seromic molecular analyses and discusses the potential of radiomics for differentiating PCLs harboring cancer from those that do not.

Trefoil factor(s) and CA19.9: A promising panel for early detection of pancreatic cancer.

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.

Systems Biology Approach to Identify Novel Genomic Determinants for Pancreatic Cancer Pathogenesis.

Pancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy with a 5-year survival rate of <8%. Its dismal prognosis stems from inefficient therapeutic modalities owing to the lack of understanding about pancreatic cancer pathogenesis. Considering the molecular complexity and heterogeneity of PDAC, identification of novel molecular contributors involved in PDAC onset and progression using global "omics" analysis will pave the way to improved strategies for disease prevention and therapeutic targeting. Meta-analysis of multiple miRNA microarray datasets containing healthy controls (HC), chronic pancreatitis (CP) and PDAC cases, identified 13 miRNAs involved in the progression of PDAC. These miRNAs showed dysregulation in both tissue as well as blood samples, along with progressive decrease in expression from HC to CP to PDAC. Gene-miRNA interaction analysis further elucidated 5 miRNAs (29a/b, 27a, 130b and 148a) that are significantly downregulated in conjunction with concomitant upregulation of their target genes throughout PDAC progression. Among these, miRNA-29a/b targeted genes were found to be most significantly altered in comparative profiling of HC, CP and PDAC, indicating its involvement in malignant evolution. Further, pathway analysis suggested direct involvement of miRNA-29a/b in downregulating the key pathways associated with PDAC development and metastasis including focal adhesion signaling and extracellular matrix organization. Our systems biology data analysis, in combination with real-time PCR validation indicates direct functional involvement of miRNA-29a in PDAC progression and is a potential prognostic marker and therapeutic candidate for patients with progressive disease.

Label-free characterization of exosome via surface enhanced Raman spectroscopy for the early detection of pancreatic cancer.

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.