SIMarker: Cellular similarity detection and its application to diagnosis and prognosis of liver cancer.

BACKGROUND: The emergence of single-cell technology offers a unique opportunity to explore cellular similarity and heterogeneity between precancerous diseases and solid tumors. However, there is lacking a systematic study for identifying and characterizing similarities at single-cell resolution. METHODS: We developed SIMarker, a computational framework to detect cellular similarities between precancerous diseases and solid tumors based on gene expression at single-cell resolution. Taking hepatocellular carcinoma (HCC) as a case study, we quantified the cellular and molecular connections between HCC and cirrhosis. Core analysis modules of SIMarker is publicly available at https://github.com/xmuhuanglab/SIMarker ("SIM" means "similarity" and "Marker" means "biomarkers). RESULTS: We found PGA5+ hepatocytes in HCC showed cirrhosis-like characteristics, including similar transcriptional programs and gene regulatory networks. Consequently, the genes constituting the gene expression program of these cirrhosis-like subpopulations were designated as cirrhosis-like signatures (CLS). Strikingly, our utilization of CLS enabled the development of diagnosis and prognosis biomarkers based on within-sample relative expression orderings of gene pairs. These biomarkers achieved high precision and concordance compared with previous studies. CONCLUSIONS: Our work provides a systematic method to investigate the clinical translational significance of cellular similarities between HCC and cirrhosis, which opens avenues for identifying similar paradigms in other categories of cancers and diseases.

Sex-dependent Prognosis of Patients with Advanced Soft Tissue Sarcoma.

PURPOSE: To examine whether overall survival (OS) differs for male and female patients with advanced soft-tissue sarcoma (STS). EXPERIMENTAL DESIGN: The study included patients from Kaiser Permanente Northern California and Stanford Cancer Center with grade 2 and 3 locally advanced or metastatic STS whose tumor underwent next-generation sequencing. We used Cox regression modeling to examine association of sex and OS adjusting for other important factors. RESULTS: Among 388 eligible patients, 174 had leiomyosarcoma (LMS), 136 had undifferentiated pleomorphic sarcoma (UPS), and 78 had liposarcoma. OS for male versus female patients appeared to be slightly better among the full cohort [HR = 0.89; 95% confidence interval (CI), 0.66-1.20]; this association appeared to be stronger among the subsets of patients with LMS (HR = 0.76; 95% CI, 0.39-1.49) or liposarcoma (HR = 0.74; 95% CI, 0.32-1.70). Better OS for male versus female patients was also observed among all molecular subgroups except mutRB1 and mutATRX, especially among patients whose tumor retained wtTP53 (HR = 0.73; 95% CI, 0.44-1.18), wtCDKN2A (HR = 0.85; 95% CI, 0.59-1.23), wtRB1 (HR = 0.73; 95% CI, 0.51-1.04), and among patients whose tumor had mutPTEN (HR = 0.37; 95% CI, 0.09-1.62). OS also appeared to be better for males in the MSK-IMPACT and TCGA datasets. CONCLUSIONS: A fairly consistent pattern of apparent better OS for males across histologic and molecular subgroups of STS was observed. If confirmed, our results could have implications for clinical practice for prognostic stratification and possibly treatment tailoring as well as for future clinical trials design.

Sex- and Co-Mutation-Dependent Prognosis in Patients with SMARCA4-Mutated Malignancies.

BACKGROUND: Whether sex and co-mutations impact prognosis of patients with SMARCA4-mutated (mutSMARCA4) malignancies is not clear. METHODS: This cohort included patients from Northern California Kaiser Permanente with next-generation sequencing (NGS) performed from August 2020 to October 2022. We used Cox regression modeling to examine the association between sex and overall survival (OS), adjusting for demographics, performance status, Charlson comorbidity index, receipt of treatment, tumor mutation burden (TMB), and TP53, KRAS, CDKN2A, STK11, and Keap1 co-mutations. RESULTS: Out of 9221 cases with NGS performed, 125 cases (1.4%) had a mutSMARCA4. The most common malignancies with a mutSMARCA4 were non-small cell lung cancer (NSCLC, 35.2%), esophageal and stomach adenocarcinoma (12.8%), and cancer of unknown primary (11.2%). The most common co-mutations were p53 (mutp53, 59.2%), KRAS (mutKRAS, 28.8%), CDKN2A (mutCDKN2A, 31.2%), STK11 (mutSTK11, 12.8%), and Keap1 (mutKeap1, 8.8%) mutations. Male patients had substantially worse OS than female patients both among the entire mutSMARCA4 cohort (HR = 1.71, [95% CI 0.92-3.18]) with a median OS of 3.0 versus 43.3 months (p < 0.001), and among the NSCLC subgroup (HR = 14.2, [95% CI 2.76-73.4]) with a median OS of 2.75 months versus un-estimable (p = 0.02). Among all patients with mutSMARCA4, mutp53 versus wtp53 (HR = 2.12, [95% CI 1.04-4.29]) and mutSTK11 versus wtSTK11 (HR = 2.59, [95% CI 0.87-7.73]) were associated with worse OS. Among the NSCLC subgroup, mutp53 versus wtp53 (HR = 0.35, [0.06-1.97]) and mutKRAS versus wtKRAS (HR = 0.04, [0.003-.45]) were associated with better OS, while mutCDKN2A versus wtCDKN2A (HR = 5.04, [1.12-22.32]), mutSTK11 versus wtSTK11 (HR = 13.10, [95% CI 1.16-148.26]), and mutKeap1 versus wtKeap1 (HR = 5.06, [95% CI 0.89-26.61}) were associated with worse OS. CONCLUSION: In our cohort of patients with mutSMARCA4, males had substantially worse prognosis than females, while mutTP53, mutKRAS, mutCDKN2A, mutSTK11 and mutKeap1were differentially associated with prognosis among all patients and among the NSCLC subgroup. Our results, if confirmed, could suggest potentially unidentified mechanisms that underly this sex and co-mutation-dependent prognostic disparity among patients whose tumor bears a mutSMARCA4.

TP53 Gain-of-Function and Non-Gain-of-Function Mutations Are Associated With Differential Prognosis in Advanced Pancreatic Ductal Adenocarcinoma.

PURPOSE: To examine the impact of TP53 gain-of-function (GOF) and non-GOF mutations on prognosis of advanced pancreatic ductal adenocarcinoma (PDAC) among patients with KRAS, CDKN2A, and SMAD4 comutations. METHODS: This cohort included patients with locally advanced, recurrent, and de novo metastatic PDAC with next-generation sequencing performed from November 2017 to May 2022. We defined R175H, R248W, R248Q, R249S, R273H, R273L, and R282W as GOF and all other p53 mutations (mutp53) as non-GOF. We used Cox regression modeling to examine the association between GOF and non-GOF mutp53 and overall survival (OS), adjusting for demographics, performance status, Charlson comorbidity index, receipt of chemotherapy, and KRAS, CDKN2A, and SMAD4 comutations. RESULTS: Of 893 total eligible patients, 68.5% had tumors with mutp53, 90.1% had KRAS mutations (mutKRAS), 44.7% had CDKN2A mutations (mutCDKN2A), and 17.0% had SMAD4 mutations. Among patients with mutp53, 121 had GOF and 491 had non-GOF. GOF mutp53 was associated with worse OS than non-GOF mutp53 (hazard ratio [HR], 1.27; 95% CI, 1.02 to 1.59) and wild-type p53 (wtp53; HR, 1.24; 95% CI, 0.98 to 1.57), whereas non-GOF was not associated with worse OS than wtp53 (HR, 0.95; 95% CI, 0.80 to 1.13). In addition, mutKRAS was associated with worse OS than wild-type KRAS in patients with mutCDKN2A (HR, 1.57; 95% CI, 0.88 to 2.80) but not in patients with wild-type CDKN2A (HR, 1.03; 95% CI, 0.76 to 1.39). CONCLUSION: GOF and non-GOF mutp53 were associated with differential prognosis in advanced PDAC. The adverse effect of mutKRAS on OS appeared to be primarily driven by patients with mutCDKN2A. Our results provide new insight that could be helpful for prognostic stratification in clinical practice and for aiding future clinical trial designs.

Prioritizing prognostic-associated subpopulations and individualized recurrence risk signatures from single-cell transcriptomes of colorectal cancer.

Colorectal cancer (CRC) is one of the most common gastrointestinal malignancies. There are few recurrence risk signatures for CRC patients. Single-cell RNA-sequencing (scRNA-seq) provides a high-resolution platform for prognostic signature detection. However, scRNA-seq is not practical in large cohorts due to its high cost and most single-cell experiments lack clinical phenotype information. Few studies have been reported to use external bulk transcriptome with survival time to guide the detection of key cell subtypes in scRNA-seq data. We proposed scRankXMBD, a computational framework to prioritize prognostic-associated cell subpopulations based on within-cell relative expression orderings of gene pairs from single-cell transcriptomes. scRankXMBD achieves higher precision and concordance compared with five existing methods. Moreover, we developed single-cell gene pair signatures to predict recurrence risk for patients individually. Our work facilitates the application of the rank-based method in scRNA-seq data for prognostic biomarker discovery and precision oncology. scRankXMBD is available at https://github.com/xmuyulab/scRank-XMBD. (XMBD:Xiamen Big Data, a biomedical open software initiative in the National Institute for Data Science in Health and Medicine, Xiamen University, China.).

Adenylate Kinase Fused to Spidroin as a Catalyst for Decreasing Leakage out of 3D-Bioprinted Hydrogels and for ATP Regeneration.

Numerous metabolic reactions and pathways use adenosine 5'-triphosphate (ATP) as an energy source and as a phosphorous or pyrophosphorous donor. Based on three-dimensional (3D)-printing, enzyme immobilization can be used to improve ATP regeneration and operability and reduce cost. However, due to the relatively large mesh size of 3D-bioprinted hydrogels soaked in a reaction solution, the lower-molecular-weight enzymes cannot avoid leaking out of the hydrogels readily. Here, a chimeric adenylate-kinase-spidroin (ADK-RC) is created, with ADK serving as the N-terminal domain. The chimera is capable of self-assembling to form micellar nanoparticles at a higher molecular scale. Although fused to spidroin (RC), ADK-RC remains relatively consistent and exhibits high activity, thermostability, pH stability, and organic solvent tolerance. Considering different surface-to-volume ratios, three shapes of enzyme hydrogels are designed, 3D bioprinted, and measured. In addition, a continuous enzymatic reaction demonstrates that ADK-RC hydrogels have higher specific activity and substrate affinity but a lower reaction rate and catalytic power compared to free enzymes in solution. With ATP regeneration, the ADK and ADK-RC hydrogels significantly increase the production of d-glucose-6-phosphate and obtain an efficient usage frequency. In conclusion, enzymes fused to spidroin might be an efficient strategy for maintaining activity and reducing leakage in 3D-bioprinted hydrogels under mild conditions.

A secretory system for extracellular production of spider neurotoxin huwentoxin-I in Escherichia coli.

Due to their advantages in structural stability and versatility, cysteine-rich peptides, which are secreted from the venom glands of venomous animals, constitute a naturally occurring pharmaceutical arsenal. However, the correct folding of disulfide bonds is a challenging task in the prokaryotic expression system like Escherichia coli due to the reducing environment. Here, a secretory expression plasmid pSE-G1M5-SUMO-HWTX-I for the spider neurotoxin huwentoxin-I (HWTX-I) with three disulfides as a model of cysteine-rich peptides was constructed. By utilizing the signal peptide G1M5, the fusion protein 6 × His-SUMO-HWTX-I was successfully secreted into extracellular medium of BL21(DE3). After enrichment using cation-exchange chromatography and purification utilizing the Ni-NTA column, 6 × His-SUMO-HWTX-I was digested via Ulp1 kinase to release recombinant HWTX-I (rHWTX-I), which was further purified utilizing RP-HPLC. Finally, both impurities with low and high molecular weights were completely removed. The molecular mass of rHWTX-I was identified as being 3750.8 Da, which was identical to natural HWTX-I with three disulfide bridges. Furthermore, by utilizing whole-cell patch clamp, the sodium currents of hNav1.7 could be inhibited by rHWTX-I and the IC50 value was 419 nmol/L.

Application of individualized differential expression analysis in human cancer proteome.

Liquid chromatography-mass spectrometry-based quantitative proteomics can measure the expression of thousands of proteins from biological samples and has been increasingly applied in cancer research. Identifying differentially expressed proteins (DEPs) between tumors and normal controls is commonly used to investigate carcinogenesis mechanisms. While differential expression analysis (DEA) at an individual level is desired to identify patient-specific molecular defects for better patient stratification, most statistical DEP analysis methods only identify deregulated proteins at the population level. To date, robust individualized DEA algorithms have been proposed for ribonucleic acid data, but their performance on proteomics data is underexplored. Herein, we performed a systematic evaluation on five individualized DEA algorithms for proteins on cancer proteomic datasets from seven cancer types. Results show that the within-sample relative expression orderings (REOs) of protein pairs in normal tissues were highly stable, providing the basis for individualized DEA for proteins using REOs. Moreover, individualized DEA algorithms achieve higher precision in detecting sample-specific deregulated proteins than population-level methods. To facilitate the utilization of individualized DEA algorithms in proteomics for prognostic biomarker discovery and personalized medicine, we provide Individualized DEP Analysis IDEPAXMBD (XMBD: Xiamen Big Data, a biomedical open software initiative in the National Institute for Data Science in Health and Medicine, Xiamen University, China.) (https://github.com/xmuyulab/IDEPA-XMBD), which is a user-friendly and open-source Python toolkit that integrates individualized DEA algorithms for DEP-associated deregulation pattern recognition.

A dynamic and multilocus metabolic regulation strategy using quorum-sensing-controlled bacterial small RNA.

Metabolic regulation strategies have been developed to redirect metabolic fluxes to production pathways. However, it is difficult to screen out target genes that, when repressed, improve yield without affecting cell growth. Here, we report a strategy using a quorum-sensing system to control small RNA transcription, allowing cell-density-dependent repression of target genes. This strategy is shown with convenient operation, dynamic repression, and availability for simultaneous regulation of multiple genes. The parameters Ai, Am, and RA (3-oxohexanoyl-homoserine lactone [AHL] concentrations at which half of the maximum repression and the maximum repression were reached and value of the maximum repression when AHL was added manually, respectively) are defined and introduced to characterize repression curves, and the variant LuxRI58N is identified as the most suitable tuning factor for shake flask culture. Moreover, it is shown that dynamic overexpression of the Hfq chaperone is the key to combinatorial repression without disruptions on cell growth. To show a broad applicability, the production titers of pinene, pentalenene, and psilocybin are improved by 365.3%, 79.5%, and 302.9%, respectively, by applying combinatorial dynamic repression.

Reference genome and annotation updates lead to contradictory prognostic predictions in gene expression signatures: a case study of resected stage I lung adenocarcinoma.

RNA-sequencing enables accurate and low-cost transcriptome-wide detection. However, expression estimates vary as reference genomes and gene annotations are updated, confounding existing expression-based prognostic signatures. Herein, prognostic 9-gene pair signature (GPS) was applied to 197 patients with stage I lung adenocarcinoma derived from previous and latest data from The Cancer Genome Atlas (TCGA) processed with different reference genomes and annotations. For 9-GPS, 6.6% of patients exhibited discordant risk classifications between the two TCGA versions. Similar results were observed for other prognostic signatures, including IRGPI, 15-gene and ORACLE. We found that conflicting annotations for gene length and overlap were the major cause of their discordant risk classification. Therefore, we constructed a prognostic 40-GPS based on stable genes across GENCODE v20-v30 and validated it using public data of 471 stage I samples (log-rank P < 0.0010). Risk classification was still stable in RNA-sequencing data processed with the newest GENCODE v32 versus GENCODE v20-v30. Specifically, 40-GPS could predict survival for 30 stage I samples with formalin-fixed paraffin-embedded tissues (log-rank P = 0.0177). In conclusion, this method overcomes the vulnerability of existing prognostic signatures due to reference genome and annotation updates. 40-GPS may offer individualized clinical applications due to its prognostic accuracy and classification stability.

Identification of a small mutation panel of coding sequences to predict the efficacy of immunotherapy for lung adenocarcinoma.

BACKGROUND: Immune checkpoint inhibitors are effective in some cases of lung adenocarcinoma (LUAD). Whole-exome sequencing has revealed that the tumour mutation burden (TMB) is associated with clinical benefits among patients from immune checkpoint inhibitors. Several commercial mutation panels have been developed for estimating the TMB regardless of the cancer type. However, different cancer types have different mutational landscapes; hence, this study aimed to develop a small cancer-type-specific mutation panel for high-accuracy estimation of the TMB of LUAD patients. METHODS: We developed a small cancer-type-specific mutation panel based on coding sequences (CDSs) rather than genes, for LUAD patients. Using somatic CDSs mutation data from 486 LUAD patients in The Cancer Genome Atlas (TCGA) database, we pre-selected a set of CDSs with mutation states significantly correlated with the TMB, from which we selected a CDS mutation panel with a panel-score most significantly correlated with the TMB, using a genetic algorithm. RESULTS: A mutation panel containing 106 CDSs of 100 genes with only 0.34 Mb was developed, whose length was much shorter than current commercial mutation panels of 0.80-0.92 Mb. The correlation of this panel with the TMB was validated in two independent LUAD datasets with progression-free survival data for patients treated with nivolumab plus ipilimumab and pembrolizumab immunotherapies, respectively. In both test datasets, survival analyses revealed that patients with a high TMB predicted via the 106-CDS mutation panel with a cut-point of 6.20 mutations per megabase, median panel score in the training dataset, had a significantly longer progression-free survival than those with a low predicted TMB (log-rank p = 0.0018, HR = 3.35, 95% CI 1.51-7.42; log-rank p = 0.0020, HR = 5.06, 95% CI 1.63-15.69). This small panel better predicted the efficacy of immunotherapy than current commercial mutation panels. CONCLUSIONS: The small-CDS mutation panel of only 0.34 Mb is superior to current commercial mutation panels and can better predict the efficacy of immunotherapy for LUAD patients, and its low cost and time-intensiveness make it more suitable for clinical applications.

Single-cell RNA sequencing reveals compartmental remodeling of tumor-infiltrating immune cells induced by anti-CD47 targeting in pancreatic cancer.

BACKGROUND: Human pancreatic ductal adenocarcinoma (PDAC) responds poorly to immune checkpoint inhibitor (ICPi). While the mechanism is not completely clear, it has been recognized that tumor microenvironment (TME) plays key roles. We investigated if targeting CD47 with a monoclonal antibody could enhance the response of PDAC to ICPi by altering the TME. METHODS: Using immunohistochemistry, we examined tumor-infiltrating CD68+ pan-macrophages (CD68+ M) and CD163+ M2 macrophages (CD163+ M2) and tumor expression of CD47 and PD-L1 proteins in 106 cases of PDAC. The efficacy of CD47 blockade was examined in xenograft models. CD45+ immune cells from syngeneic tumor models were subjected to single-cell RNA-sequencing (scRNA-seq) by using the 10x Genomics pipeline. RESULTS: We found that CD47 expression correlated with the level of CD68+ M but not CD163+ M2. High levels of tumor-infiltrating CD68+ M, CD163+ M2, and CD47 expression were significantly associated with worse survival. CD47high/CD68+ Mhigh and CD47high/CD163+ M2high correlated significantly with shorter survival, whereas CD47low/CD68+ Mlow and CD47low/CD163+ M2low correlated with longer survival. Intriguingly, CD47 blockade decreased the tumor burden in the Panc02 but not in the MPC-83 syngeneic mouse model. Using scRNA-seq, we showed that anti-CD47 treatment significantly remodeled the intratumoral lymphocyte and macrophage compartments in Panc02 tumor-bearing mice by increasing the pro-inflammatory macrophages that exhibit anti-tumor function, while reducing the anti-inflammatory macrophages. Moreover, CD47 blockade not only increased the number of intratumoral CD8+ T cells, but also remodeled the T cell cluster toward a more activated one. Further, combination therapy targeting both CD47 and PD-L1 resulted in synergistic inhibition of PDAC growth in the MPC-83 but not in Panc02 model. MPC-83 but not Panc02 mice treated with both anti-CD47 and anti-PD-L1 showed increased number of PD-1+CD8+ T cells and enhanced expression of key immune activating genes. CONCLUSION: Our data indicate that CD47 targeting induces compartmental remodeling of tumor-infiltrating immune cells of the TME in PDAC. Different PDAC mouse models exhibited differential response to the anti-CD47 and anti-PD-L1 blockade due to the differential effect of this combination treatment on the infiltrating immune cells and key immune activating genes in the TME established by the different PDAC cell lines.

A qualitative transcriptional signature for the histological reclassification of lung squamous cell carcinomas and adenocarcinomas.

BACKGROUND: Targeted therapy for non-small cell lung cancer is histology dependent. However, histological classification by routine pathological assessment with hematoxylin-eosin staining and immunostaining for poorly differentiated tumors, particularly those from small biopsies, is still challenging. Additionally, the effectiveness of immunomarkers is limited by technical inconsistencies of immunostaining and lack of standardization for staining interpretation. RESULTS: Using gene expression profiles of pathologically-determined lung adenocarcinomas and squamous cell carcinomas, denoted as pADC and pSCC respectively, we developed a qualitative transcriptional signature, based on the within-sample relative gene expression orderings (REOs) of gene pairs, to distinguish ADC from SCC. The signature consists of two genes, KRT5 and AGR2, which has the stable REO pattern of KRT5 > AGR2 in pSCC and KRT5 < AGR2 in pADC. In the two test datasets with relative unambiguous NSCLC types, the apparent accuracy of the signature were 94.44 and 98.41%, respectively. In the other integrated dataset for frozen tissues, the signature reclassified 4.22% of the 805 pADC patients as SCC and 12% of the 125 pSCC patients as ADC. Similar results were observed in the clinical challenging cases, including FFPE specimens, mixed tumors, small biopsy specimens and poorly differentiated specimens. The survival analyses showed that the pADC patients reclassified as SCC had significantly shorter overall survival than the signature-confirmed pADC patients (log-rank p = 0.0123, HR = 1.89), consisting with the knowledge that SCC patients suffer poor prognoses than ADC patients. The proliferative activity, subtype-specific marker genes and consensus clustering analyses also supported the correctness of our signature. CONCLUSIONS: The non-subjective qualitative REOs signature could effectively distinguish ADC from SCC, which would be an auxiliary test for the pathological assessment of the ambiguous cases.

A Qualitative Transcriptional Signature for Predicting Recurrence Risk for High-Grade Serous Ovarian Cancer Patients Treated With Platinum-Taxane Adjuvant Chemotherapy.

Resistance to platinum and taxane adjuvant chemotherapy (ACT) is the main cause of the recurrence and poor prognosis of high-grade serous ovarian cancer (HGS-OvCa) patients receiving platinum-taxane ACT after surgery. However, currently reported quantitative transcriptional signatures, which are commonly based on risk scores summarized from gene expression, are unsuitable for clinical application because of their high sensitivity to experimental batch effects and quality uncertainties of clinical samples. Using 226 samples of HGS-OvCa patients receiving platinum-taxane ACT in TCGA, we developed a qualitative transcriptional signature, consisting of four gene pairs whose within-samples relative expression orderings could robustly predict patient recurrence-free survival (RFS). In two independent test datasets, the predicted non-responders had significantly shorter RFS than the predicted responders (log-rank p < 0.05). In a test dataset containing data for patient pathological response state, the signature reclassified 12 out of 22 pathological complete response patients as non-responders and two out of 16 pathological non-complete response patients as responders. Notably, the 12 predicted non-responders in the pathological complete response group had significantly shorter RFS than the predicted responders (log-rank p = 0.0122). This qualitative transcriptional signature, which is insensitive to experimental batch effects and quality uncertainties of clinical samples, can individually identify HGS-OvCa patients who are more likely to benefit from platinum-taxane adjuvant chemotherapy.

Synergistic inhibition of pancreatic cancer with anti-PD-L1 and c-Myc inhibitor JQ1.

Human pancreatic ductal adenocarcinoma (PDAC) exhibits marginal responses to anti-PD-1/PD-L1 immunotherapy and its mechanism remains poorly understood. We have investigated the effect of anti-PD-L1 and c-Myc inhibition in PDAC. Using 87 patients with PDAC from our hospital database we found a significant correlation between the expression of PD-L1 and c-Myc. Moreover, the expression of both PD-L1 and c-Myc was associated with poor overall survival. In addition, we confirmed this finding with the PDAC patients in the TCGA database. Using several PDAC cell lines we demonstrated a significant correlation between the expression of PD-L1 and c-Myc. We also found that expression of PD-L1 correlated with high-grade histology. JQ1, an inhibitor of c-Myc inhibited PD-L1 expression and tumor growth. Using xenograft models, we demonstrated that the combination of JQ1 and anti-PD-L1 antibody exerted synergistic inhibition of PDAC growth. Our data demonstrated that the expression of PD-L1 and c-Myc may be helpful prognostic biomarkers, and their inhibition may potentially serve as an effective treatment for PDAC.

WIPF1 antagonizes the tumor suppressive effect of miR-141/200c and is associated with poor survival in patients with PDAC.

BACKGROUND: Aberrant expression of Wiskott-Aldrich syndrome protein interacting protein family member 1 (WIPF1) contributes to the invasion and metastasis of several malignancies. However, the role of WIPF1 in human pancreatic ductal adenocarcinoma (PDAC) remains poorly understood. METHODS: Human pancreatic cancer samples from PDAC patients were collected for methylation analysis. Bioinformatic prediction program and luciferase reporter assay were used to identify microRNAs regulating WIPF1 expression. The association between WIPF1 expression and the overall survival (OS) of patients with PDAC was evaluated by using The Cancer Genome Atlas (TCGA) database. The roles of miR-141/200c and WIPF1 on the invasion and metastasis of PDAC cells were investigated both in vitro and in vivo. RESULTS: We found that compared to the surrounding non-cancerous tissues, there was significantly increased methylation of miR-200c and miR-141 in human PDAC tissues that resulted in their silencing, whereas the members of the other cluster of miR-200 family including miR-200a, miR-200b and miR-429 were hypomethylated. Our data show that forced expression of miR-141 or miR-200c suppressed invasion and metastasis of PDAC cells both in vitro and in xenograft and identified WIPF1 as a direct target of miR-141 and miR-200c. Both miR-141 and miR-200c inhibit WIPF1 by directly interacting with its 3'-untranslated region. Remarkably, silencing of WIPF1 blocked PDAC growth and metastasis both in vitro and in vivo, whereas forced WIPF1 overexpression antagonized the tumor suppressive effect of miR-141/200c. Additionally, by using TCGA database we showed that high expression of WIPF1 correlated with poor survival in patients with PDAC. Moreover, we show that miR-141 and miR-200c blocked YAP/TAZ expression by suppressing WIPF1. CONCLUSIONS: We have identified WIPF1 as an oncoprotein in PDAC and a direct target of miR-141/miR-200c. We have also defined the miR-141/200c-WIPF1-YAP/TAZ as a novel signaling pathway that is involved in the regulation of the invasion and metastasis of human PDAC cells.