CSNK1E/CTNNB1 are synthetic lethal to TP53 in colorectal cancer and are markers for prognosis

Motif Graph Neural Network

Graphs can model complicated interactions between entities, which naturally emerge in many important applications. These applications can often be cast into standard graph learning tasks, in which a crucial step is to learn low-dimensional graph representations. Graph neural networks (GNNs) are currently the most popular model in graph embedding approaches. However, standard GNNs in the neighborhood aggregation paradigm suffer from limited discriminative power in distinguishing high-order graph structures as opposed to low-order structures. To capture high-order structures, researchers have resorted to motifs and developed motif-based GNNs. However, the existing motif-based GNNs still often suffer from less discriminative power on high-order structures. To overcome the above limitations, we propose motif GNN (MGNN), a novel framework to better capture high-order structures, hinging on our proposed motif redundancy minimization operator and injective motif combination. First, MGNN produces a set of node representations with respect to each motif. The next phase is our proposed redundancy minimization among motifs which compares the motifs with each other and distills the features unique to each motif. Finally, MGNN performs the updating of node representations by combining multiple representations from different motifs. In particular, to enhance the discriminative power, MGNN uses an injective function to combine the representations with respect to different motifs. We further show that our proposed architecture increases the expressive power of GNNs with a theoretical analysis. We demonstrate that MGNN outperforms state-of-the-art methods on seven public benchmarks on both the node classification and graph classification tasks.

Critical residues in the Ku70 von Willebrand A domain mediate Ku interaction with the LigIV-XRCC4 complex in non-homologous end-joining

The Ku heterodimer (Ku70/Ku80) is central to the non-homologous end-joining (NHEJ) pathway. Ku binds to the broken DNA ends and promotes the assembly of the DNA repair complex. The N-terminal Ku70 von Willebrand A (vWA) domain is known to mediate protein-protein interactions important for the repair process. In particular, the D192 and D195 residues within helix 5 of the Ku70 vWA domain were shown to be essential for NHEJ function, although the precise role of these residues was not identified. Here, we set up a miniTurbo screening system to identify Ku70 D192/D195 residue-specific interactors in a conditional, human Ku70-knockout cell line in response to DNA damage. Using fusion protein constructs of Ku70 wild-type and mutant (D192A/D195R) with miniTurbo, we identified a number of candidate proximal interactors in response to DNA damage treatment, including DNA Ligase IV (LigIV), a known and essential NHEJ complex member. Interestingly, LigIV was enriched in our wildtype screen but not the Ku70 D192A/D195R screen, suggesting its interaction is disrupted by the mutation. Validation experiments demonstrated that the DNA damage-induced interaction between Ku70 and LigIV was disrupted by the Ku70 D192A/D195R mutations. Our findings provide greater detail about the interaction surface between the Ku70 vWA domain and LigIV and offer strong evidence that the D192 and D195 residues are important for NHEJ completion through an interaction with LigIV. Altogether, this work reveals novel potential proximal interactors of Ku in response to DNA damage and identifies Ku70 D192/D195 residues as essential for LigIV interaction with Ku during NHEJ.

KinPred-RNA-kinase activity inference and cancer type classification using machine learning on RNA-seq data

Kinases as important enzymes can transfer phosphate groups from high-energy and phosphate-donating molecules to specific substrates and play essential roles in various cellular processes. Existing algorithms for kinase activity from phosphorylated proteomics data are often costly, requiring valuable samples. Moreover, methods to extract kinase activities from bulk RNA sequencing data remain undeveloped. In this study, we propose a computational framework KinPred-RNA to derive kinase activities from bulk RNA-sequencing data in cancer samples. KinPred-RNA framework, using the extreme gradient boosting (XGBoost) regression model, outperforms random forest regression, multiple linear regression, and support vector machine regression models in predicting kinase activities from cancer-related RNA sequencing data. Efficient gene signatures from the LINCS-L1000 dataset were used as inputs for KinPred-RNA. The results highlight its potential to be related to biological function. In conclusion, KinPred RNA constitutes a significant advance in cancer research by potentially facilitating the identification of cancer.

Circadian clock-related genome-wide mendelian randomization identifies putatively genes for ulcerative colitis and its comorbidity

BACKGROUND

Circadian rhythm is crucial to the function of the immune system. Disorders of the circadian rhythm can contribute to inflammatory diseases such as Ulcerative colitis (UC). This Mendelian Randomization (MR) analysis applies genetic tools to represent the aggregated statistical results of exposure to circadian rhythm disorders and UC and its comorbidities, allowing for causal inferences.

METHODS

Summary statistics of protein, DNA methylation and gene expression quantitative trait loci in individuals of European ancestry (pQTL, mQTL, and eQTL, respectively) were used. Genetic variants located within or near 152 circadian clock-related genes and closely related to circadian rhythm disorders were selected as instrumental variables. Causal relationships with UC and its comorbidities were then estimated through employed Summary data-based Mendelian Randomization (SMR) and Inverse-Variance-Weighted MR (IVW-MR).

RESULTS

Through preliminary SMR analysis, we identified a potential causal relationship between circadian clock-related genes and UC along with its comorbidities, which was further confirmed by IVW-MR analysis. Our study identified strong evidence of positive correlation involving seven overlapping genes (CSNK1E, OPRL1, PIWIL2, RORC, MAX, PPP5C, and AANAT) through MWAS and TWAS in UC, four overlapping genes (OPRL1, CHRNB2, FBXL17, and SIRT1) in UC with PSC, and three overlapping genes (ARNTL, USP7, and KRAS) in UC with arthropathy.

CONCLUSIONS

This SMR study demonstrates the causal effect of circadian rhythm disorders in UC and its comorbidities. Furthermore, our investigation pinpointed candidate genes that could potentially serve as drug targets.

CK1δ and CK1ε Signaling Sustains Mitochondrial Metabolism and Cell Survival in Multiple Myeloma

Multiple myeloma remains an incurable malignancy due to acquisition of intrinsic programs that drive therapy resistance. Here we report that casein kinase-1δ (CK1δ) and CK1ε are therapeutic targets in multiple myeloma that are necessary to sustain mitochondrial metabolism. Specifically, the dual CK1δ/CK1ε inhibitor SR-3029 had potent in vivo and ex vivo anti-multiple myeloma activity, including against primary multiple myeloma patient specimens. RNA sequencing (RNA-seq) and metabolic analyses revealed inhibiting CK1δ/CK1ε disables multiple myeloma metabolism by suppressing genes involved in oxidative phosphorylation (OxPhos), reducing citric acid cycle intermediates, and suppressing complexes I and IV of the electron transport chain. Finally, sensitivity of multiple myeloma patient specimens to SR-3029 correlated with elevated expression of mitochondrial genes, and RNA-seq from 687 multiple myeloma patient samples revealed that increased CSNK1D, CSNK1E, and OxPhos genes correlate with disease progression and inferior outcomes. Thus, increases in mitochondrial metabolism are a hallmark of multiple myeloma progression that can be disabled by targeting CK1δ/CK1ε.

SIGNIFICANCE

CK1δ and CK1ε are attractive therapeutic targets in multiple myeloma whose expression increases with disease progression and connote poor outcomes, and that are necessary to sustain expression of genes directing OxPhos.

The role of circadian clock genes in colorectal carcinoma: Novel insights into regulatory mechanism and implications in clinical therapy

Colorectal cancer (CRC) is a lethal malignancy with limited treatment strategies. Accumulating evidence indicates that CRC tumorigenesis, progression and metastasis are intimately associated with circadian clock, an inherent 24-h cycle oscillation of biochemical, physiological functions in almost every eukaryote. In the present review, we summarize the altered expression level of circadian genes in CRC and the prognosis associated with gene abundance switch. We illustrate the function and potential mechanisms of circadian genes in CRC pathogenesis and progression. Moreover, circadian based-therapeutic strategies including chronotherapy, therapeutics targeting potential circadian components, and melatonin treatment in CRC are also highlighted.

Riok1, A Novel Potential Target in MSI-High p53 Mutant Colorectal Cancer Cells

The vulnerabilities of cancer cells constitute a promising strategy for drug therapeutics. This paper integrates proteomics, bioinformatics, and cell genotype together with in vitro cell proliferation assays to identify key biological processes and potential novel kinases that could account, at least in part, for the clinical differences observed in colorectal cancer (CRC) patients. This study started by focusing on CRC cell lines stratified by their microsatellite (MS) state and p53 genotype. It shows that cell-cycle checkpoint, metabolism of proteins and RNA, signal transduction, and WNT signaling processes are significantly more active in MSI-High p53-WT cell lines. Conversely, MSI-High cell lines with a mutant (Mut) p53 gene showed hyperactivation of cell signaling, DNA repair, and immune-system processes. Several kinases were linked to these phenotypes, from which RIOK1 was selected for additional exploration. We also included the KRAS genotype in our analysis. Our results showed that RIOK1's inhibition in CRC MSI-High cell lines was dependent on both the p53 and KRAS genotypes. Explicitly, Nintedanib showed relatively low cytotoxicity in MSI-High with both mutant p53 and KRAS (HCT-15) but no inhibition in p53 and KRAS WT (SW48) MSI-High cells. This trend was flipped in CRC MSI-High bearing opposite p53-KRAS genotypes (e.g., p53-Mut KRAS-WT or p53-WT KRAS-Mut), where observed cytotoxicity was more extensive compared to the p53-KRAS WT-WT or Mut-Mut cells, with HCT 116 (KRAS-Mut and p53-WT) being the most sensitive to RIOK1 inhibition. These results highlight the potential of our in silico computational approach to identify novel kinases in CRC sub-MSI-High populations as well as the importance of clinical genomics in determining drug potency.

Association of β-Catenin, APC, SMAD3/4, Tp53, and Cyclin D1 Genes in Colorectal Cancer: A Systematic Review and Meta-Analysis

Objectives

Accumulating evidence indicates that the expression and/or variants of several genes play an essential role in the progress of colorectal cancer (CRC). The current study is a meta-analysis undertaken to estimate the prognosis and survival associated with CTNNB1/β-catenin, APC, Wnt, SMAD3/4, TP53, and Cyclin D1 genes among CRC patients.

Methods

The authors searched PubMed, EMBASE, and Science Direct for relevant reports published between 2000 and 2020 and analyzed them to determine any relationship between the (immunohistochemically/sequencing-detected) gene expression and variants of the selected genes and the survival of CRC patients.

Results

The analysis included 34,074 patients from 64 studies. To evaluate association, hazard ratios (HRs) were estimated for overall survival (OS) or disease-free survival (DFS), with a 95% confidence interval (CIs). Pooled results showed that β-catenin overexpression, APC mutation, SMAD-3 or 4 loss of expression, TP53 mutations, and Cyclin D1 expression were associated with shorter OS. β-Catenin overexpression (HR: 0.137 (95% CI: 0.131–0.406)), loss of expression of SMAD3 or 4 (HR: 0.449 (95% CI: 0.146–0.753)), the mutations of TP53 (HR: 0.179 (95% CI: 0.126–0.485)), and Cyclin D1 expression (HR: 0.485 (95% CI: 0.772–0.198)) also presented risk for shorter DFS.

Conclusions

The present meta-analysis indicates that overexpression or underexpression and variants of CTNNB1/β-catenin, APC, SMAD3/4, TP53, and Cyclin D1 genes potentially acted as unfavorable biomarkers for the prognosis of CRC. The Wnt gene was not associated with prognosis.

Characterization of Aging-Related Genes to Predict Prognosis and Evaluate the Tumor Immune Microenvironment in Malignant Melanoma

Objective. Malignant melanoma (MM) is one of the most malignant types of skin cancer and its incidence and mortality rates are increasing worldwide. Aging is well recognized as a significant risk factor for cancer. However, few studies have analyzed in depth the association between aging-related genes (AGs) and malignant melanoma prognosis with tumor immune microenvironment. Methods. Here, we downloaded 471 MM patients from The Cancer Genome Atlas (TCGA) with RNA sequence and clinicopathological data. 58 AGs from the TCGA dataset were examined using Cox regression and the LASSO assay. As a result, a gene signature for aging-related genes was created. The time-dependent ROC curve and Kaplan–Meier analysis were calculated to determine its predictive capability. Moreover, we created a nomogram for the clinicopathologic variables and the AGs gene signature to determine overall survival (OS). We also explored the association between three immune checkpoints, immune cell infiltration, and the aging-related gene signature. Results. We established an aging risk model to identify and predict the immune microenvironment in malignant melanoma. Then we developed and validated a prognosis risk model using three AGs (CSNK1E, C1QA, and SOD-2) in the GSE65904 dataset. The aging signature was positively associated with clinical and molecular characteristics and can be used as a prognostic factor for malignant melanoma. The low aging risk score was associated with a poor prognosis and indicated an immunosuppressive microenvironment. Conclusions. To summarize, we established and validated a model of aging risk based on three aging-related genes that acted as an independent prognostic predictor of overall survival. Besides, it also characterized the immune response in the malignant melanoma microenvironment and could provide a potential indicator of individualized immunotherapy in malignant melanoma.

Fanconi Anemia Pathway in Colorectal Cancer: A Novel Opportunity for Diagnosis, Prognosis and Therapy

Colorectal cancer (CRC) is the third most commonly diagnosed malignancy and has the second highest mortality rate globally. Thanks to the advent of next-generation sequencing technologies, several novel candidate genes have been proposed for CRC susceptibility. Germline biallelic mutations in one or more of the 22 currently recognized Fanconi anemia (FA) genes have been associated with Fanconi anemia disease, while germline monoallelic mutations, somatic mutations, or the promoter hypermethylation of some FANC genes increases the risk of cancer development, including CRC. The FA pathway is a substantial part of the DNA damage response system that participates in the repair of DNA inter-strand crosslinks through homologous recombination (HR) and protects genome stability via replication fork stabilization, respectively. Recent studies revealed associations between FA gene/protein tumor expression levels (i.e., FANC genes) and CRC progression and drug resistance. Moreover, the FA pathway represents a potential target in the CRC treatment. In fact, FANC gene characteristics may contribute to chemosensitize tumor cells to DNA crosslinking agents such as oxaliplatin and cisplatin besides exploiting the synthetic lethal approach for selective targeting of tumor cells. Hence, this review summarizes the current knowledge on the function of the FA pathway in DNA repair and genomic integrity with a focus on the FANC genes as potential predisposition factors to CRC. We then introduce recent literature that highlights the importance of FANC genes in CRC as promising prognostic and predictive biomarkers for disease management and treatment. Finally, we represent a brief overview of the current knowledge around the FANC genes as synthetic lethal therapeutic targets for precision cancer medicine.

Harnessing Synthetic Lethal Interactions for Personalized Medicine

Two genes are said to have synthetic lethal (SL) interactions if the simultaneous mutations in a cell lead to lethality, but each individual mutation does not. Targeting SL partners of mutated cancer genes can kill cancer cells but leave normal cells intact. The applicability of translating this concept into clinics has been demonstrated by three drugs that have been approved by the FDA to target PARP for tumors bearing mutations in BRCA1/2. This article reviews applications of the SL concept to translational cancer medicine over the past five years. Topics are (1) exploiting the SL concept for drug combinations to circumvent tumor resistance, (2) using synthetic lethality to identify prognostic and predictive biomarkers, (3) applying SL interactions to stratify patients for targeted and immunotherapy, and (4) discussions on challenges and future directions.

Development and Validation of Tumor Immunogenicity Based Gene Signature for Skin Cancer Risk Stratification

Melanoma is one of the most aggressive types of skin cancer, with significant heterogeneity in overall survival. Currently, tumor-node-metastasis (TNM) staging is insufficient to provide accurate survival prediction and appropriate treatment decision making for several types of tumors, such as those in melanoma patients. Therefore, the identification of more reliable prognosis biomarkers is urgently essential. Recent studies have shown that low immune cells infiltration is significantly associated with unfavorable clinical outcome in melanoma patients. Here we constructed a prognostic-related gene signature for melanoma risk stratification by quantifying the levels of several cancer hallmarks and identify the Wnt/β-catenin activation pathway as a primary risk factor for low tumor immunity. A series of bioinformatics and statistical methods were combined and applied to construct a Wnt-immune-related prognosis gene signature. With this gene signature, we computed risk scores for individual patients that can predict overall survival. To evaluate the robustness of the result, we validated the signature in multiple independent GEO datasets. Finally, an overall survival-related nomogram was established based on the gene signature and clinicopathological features. The Wnt-immune-related prognostic risk score could better predict overall survival compared with standard clinicopathological features. Our results provide a comprehensive map of the oncogene-immune-related gene signature that can serve as valuable biomarkers for better clinical decision making.

Progression Risk Score Estimation Based on Immunostaining Data in Oral Cancer Using Unsupervised Hierarchical Clustering Analysis: A Retrospective Study in Taiwan

This study aimed to investigate whether the progression risk score (PRS) developed from cytoplasmic immunohistochemistry (IHC) biomarkers is available and applicable for assessing risk and prognosis in oral cancer patients. Participants in this retrospective case-control study were diagnosed between 2012 and 2014 and subsequently underwent surgical intervention. The specimens from surgery were stained by IHC for 16 cytoplasmic target markers. We evaluated the results of IHC staining, clinical and pathological features, progression-free survival (PFS), and overall survival (OS) of 102 oral cancer patients using a novel estimation approach with unsupervised hierarchical clustering analysis. Patients were stratified into high-risk (52) and low-risk (50) groups, according to their PRS; a metric consisting of cytoplasmic PLK1, PhosphoMet, SGK2, and SHC1 expression. Moreover, PRS could be extended for use in the Cox proportional hazard regression model to estimate survival outcomes with associated clinical parameters. Our study findings revealed that the high-risk patients had a significantly increased risk in cancer progression compared with low-risk patients (hazard ratio (HR) = 2.20, 95% confidence interval (CI) = 1.10-2.42, p = 0.026). After considering the influences of demographics, risk behaviors, and tumor characteristics, risk estimation with PRS provided distinct PFS groups for patients with oral cancer (p = 0.017, p = 0.019, and p = 0.020). Our findings support that PRS could serve as an ideal biomarker for clinical use in risk stratification and progression assessment in oral cancer.

Application of the Interaction between Tissue Immunohistochemistry Staining and Clinicopathological Factors for Evaluating the Risk of Oral Cancer Progression by Hierarchical Clustering Analysis: A Case-Control Study in a Taiwanese Population

The aim of this single-center case-control study is to investigate the feasibility and accuracy of oral cancer protein risk stratification (OCPRS) to analyze the risk of cancer progression. All patients diagnosed with oral cancer in Taiwan, between 2012 and 2014, and who underwent surgical intervention were selected for the study. The tissue was further processed for immunohistochemistry (IHC) for 21 target proteins. Analyses were performed using the results of IHC staining, clinicopathological characteristics, and survival outcomes. Novel stratifications with a hierarchical clustering approach and combinations were applied using the Cox proportional hazard regression model. Of the 163 participants recruited, 102 patients were analyzed, and OCPRS successfully identified patients with different progression-free survival (PFS) profiles in high-risk (53 subjects) versus low-risk (49 subjects) groups (p = 0.012). OCPRS was composed of cytoplasmic PLK1, phosphoMet, and SGK2 IHC staining. After controlling for the influence of clinicopathological features, high-risk patients were 2.33 times more likely to experience cancer progression than low-risk patients (p = 0.020). In the multivariate model, patients with extranodal extension (HR = 2.66, p = 0.045) demonstrated a significantly increased risk for disease progression. Risk stratification with OCPRS provided distinct PFS groups for patients with oral cancer after surgical intervention. OCPRS appears suitable for routine clinical use for progression and prognosis estimation.

Immunohistochemical Expression of Five Protein Combinations Revealed as Prognostic Markers in Asian Oral Cancer

Oral squamous cell carcinoma (OSCC) has a high mortality rate (∼50%), and the 5-year overall survival rate is not optimal. Cyto- and histopathological examination of cancer tissues is the main strategy for diagnosis and treatment. In the present study, we aimed to uncover immunohistochemical (IHC) markers for prognosis in Asian OSCC. From the collected 742 synthetic lethal gene pairs (of various cancer types), we first filtered genes relevant to OSCC, performed 29 IHC stains at different cellular portions and combined these IHC stains into 398 distinct pairs. Next, we identified novel IHC prognostic markers in OSCC among Taiwanese population, from the single and paired IHC staining by univariate Cox regression analysis. Increased nuclear expression of RB1 [RB1(N)↑], CDH3(C)↑-STK17A(N)↑ and FLNA(C)↑-KRAS(C)↑were associated with survival, but not independent of tumor stage, where C and N denote cytoplasm and nucleus, respectively. Furthermore, multivariate Cox regression analyses revealed that CSNK1E(C)↓-SHC1(N)↓ (P = 5.9 × 10^–5; recommended for clinical use), BRCA1(N)↓-SHC1(N)↓ (P = 0.030), CSNK1E(C)↓-RB1(N)↑ (P = 0.045), [CSNK1E(C)-SHC1(N), FLNA(C)-KRAS(C)] (P = 0.000, rounded to three decimal places) and [BRCA1(N)-SHC1(N), FLNA(C)-KRAS(C)] (P = 0.020) were significant factors of poor prognosis, independent of lymph node metastasis, stage and alcohol consumption. An external dataset from The Cancer Genome Atlas HNSCC cohort confirmed that CDH3↑-STK17A↑ was a significant predictor of poor survival. Our approach identified prognostic markers with components involved in different pathways and revealed IHC marker pairs while neither single IHC was a marker, thus it improved the current state-of-the-art for identification of IHC markers.

Transcriptomic analysis reveals a WNT signaling pathway-based gene signature prognostic for non-small cell carcinoma

The value of combining multiple candidate genes into a panel to improve biomarker performance is increasingly emphasized. Genes associated with WNT signaling are widely-reported to provide prognostic signatures in non-small cell carcinoma (NSCLC). Screening of genes involved in this signaling pathway facilitated selection of an optimal candidate biomarker gene combination and development of an NSCLC prognostic model based on expression of these genes. Risk scores derived from the model performed well in predicting survival; in the training dataset, samples achieving a high risk score exhibit a shorter survival interval (median survival time 34.8 months, 95% CI 31.1-41.0) than did samples achieving a low risk score (median survival time 72.0 months, 95% CI 59.3-87.5, p=2e-11), and exhibited higher oncogene and lower tumor suppressor gene expression. Receiver-operator characteristic curves based on three-year survival demonstrate that the model outperformed clinical prognostic indicators. In addition, the model was validated in four independent cohorts, demonstrating robust NSCLC prognostic value. Correlation analyses reveal that the model offers efficacy independent of other clinical indicators. Gene Set Enrichment Analysis (GSEA) reveals that the model reflects variable tissue functional states relevant to NSCLC biology. In summary, the signature model shows potential as a valuable and robust NSCLC prognostic indicator.

A gene-expression-based signature predicts survival in adults with T-cell lymphoblastic lymphoma: a multicenter study

We aimed to establish a discriminative gene-expression-based classifier to predict survival outcomes of T-cell lymphoblastic lymphoma (T-LBL) patients. After exploring global gene-expression profiles of progressive (n = 22) vs. progression-free (n = 28) T-LBL patients, 43 differentially expressed mRNAs were identified. Then an eleven-gene-based classifier was established using LASSO Cox regression based on NanoString quantification. In the training cohort (n = 169), high-risk patients stratified using the classifier had significantly lower progression-free survival (PFS: hazards ratio 4.123, 95% CI 2.565-6.628; p < 0.001), disease-free survival (DFS: HR 3.148, 95% CI 1.857-5.339; p < 0.001), and overall survival (OS: HR 3.790, 95% CI 2.237-6.423; p < 0.001) compared with low-risk patients. The prognostic accuracy of the classifier was validated in the internal testing (n = 84) and independent validation cohorts (n = 360). A prognostic nomogram consisting of five independent variables including the classifier, lactate dehydrogenase levels, ECOG-PS, central nervous system involvement, and NOTCH1/FBXW7 status showed significantly greater prognostic accuracy than each single variable alone. The addition of a five-miRNA-based signature further enhanced the accuracy of this nomogram. Furthermore, patients with a nomogram score ≥154.2 significantly benefited from the BFM protocol. In conclusion, our nomogram comprising the 11-gene-based classifier may make contributions to individual prognosis prediction and treatment decision-making.

Synthetic lethality: A promising therapeutic strategy for hepatocellular carcinoma

Hepatocellular carcinoma (HCC), the main cause of liver cancer-related death, is one of the main cancers in terms of incidence and mortality. However, HCC is difficult to target and develops strong drug resistance. Therefore, a new treatment strategy is urgently needed. The clinical application of the concept of synthetic lethality in recent years provides a new therapeutic direction for the accurate treatment of HCC. Here, we introduce the concept of synthetic lethality, the screening used to study synthetic lethality, and the identified and potential genetic interactions that induce synthetic lethality in HCC. In addition, we propose opportunities and challenges for translating synthetic lethal interactions to the clinical treatment of HCC.

TP53 mutations in epithelial ovarian cancer

Genomic sequencing analyses of a variety of human cancers have revealed that massive mutations of cancer-relevant genes are the major alterations in cancerous cells, and their mutation frequencies or rates are highly associated with the development, progression, metastasis, and drug resistance of cancers as well as their clinical outcomes and prognosis. One predominant genetic alternation in human epithelial ovarian cancer (EOC) is the mutation of TP53 that encodes the tumor suppressor p53 protein. This essay will review the most recent progress in understanding the role of TP53 mutations in development, progression, and metastasis of EOC, and discuss the potential of TP53 mutations as diagnostic and prognostic biomarkers as well as therapeutic targets for EOC.

Uncovering synthetic lethal interactions for therapeutic targets and predictive markers in lung adenocarcinoma

Two genes are called synthetic lethal (SL) if their simultaneous mutation leads to cell death, but mutation of either individual does not. Targeting SL partners of mutated cancer genes can selectively kill cancer cells, but leave normal cells intact. We present an integrated approach to uncover SL gene pairs as novel therapeutic targets of lung adenocarcinoma (LADC). Of 24 predicted SL pairs, PARP1-TP53 was validated by RNAi knockdown to have synergistic toxicity in H1975 and invasive CL1-5 LADC cells; additionally FEN1-RAD54B, BRCA1-TP53, BRCA2-TP53 and RB1-TP53 were consistent with the literature. While metastasis remains a bottleneck in cancer treatment and inhibitors of PARP1 have been developed, this result may have therapeutic potential for LADC, in which TP53 is commonly mutated. We also demonstrated that silencing PARP1 enhanced the cell death induced by the platinum-based chemotherapy drug carboplatin in lung cancer cells (CL1-5 and H1975). IHC of RAD54B↑, BRCA1↓-RAD54B↑, FEN1(N)↑-RAD54B↑ and PARP1↑-RAD54B↑ were shown to be prognostic markers for 131 Asian LADC patients, and all markers except BRCA1↓-RAD54B↑ were further confirmed by three independent gene expression data sets (a total of 426 patients) including The Cancer Genome Atlas (TCGA) cohort of LADC. Importantly, we identified POLB-TP53 and POLB as predictive markers for the TCGA cohort (230 subjects), independent of age and stage. Thus, POLB and POLB-TP53 may be used to stratify future non-Asian LADC patients for therapeutic strategies.

Genetic Variants in the Wnt/β-Catenin Signaling Pathway as Indicators of Bladder Cancer Risk

PURPOSE

Genetic factors that influence bladder cancer risk remain largely unknown. Previous research has suggested that there is a strong genetic component underlying the risk of bladder cancer. The Wnt/β-catenin signaling pathway is a key modulator of cellular proliferation through its regulation of stem cell homeostasis. Furthermore, variants in the Wnt/β-catenin signaling pathway have been implicated in the development of other cancers, leading us to believe that this pathway may have a vital role in bladder cancer development.

MATERIALS AND METHODS

A total of 230 single nucleotide polymorphisms in 40 genes in the Wnt/β-catenin signaling pathway were genotyped in 803 bladder cancer cases and 803 healthy controls.

RESULTS

A total of 20 single nucleotide polymorphisms were nominally significant for risk. Individuals with 2 variants of LRP6: rs10743980 were associated with a decreased risk of bladder cancer in the recessive model in the initial analysis (OR 0.76, 95% CI 0.58-0.99, p=0.039). This was validated using the bladder genome-wide association study chip (OR 0.51, 95% CI 0.27-1.00, p=0.049 and for combined analysis p=0.007).

CONCLUSIONS

Together these findings implicate variants in the Wnt/β-catenin stem cell pathway as having a role in bladder cancer etiology.

The Overexpression of FEN1 and RAD54B May Act as Independent Prognostic Factors of Lung Adenocarcinoma

Synthetic lethality arises when a combination of mutations in two or more genes leads to cell death. However, the prognostic role of concordant overexpression of synthetic lethality genes in protein level rather than a combination of mutations is not clear. In this study, we explore the prognostic role of combined overexpression of paired genes in lung adenocarcinoma. We used immunohistochemical staining to investigate 24 paired genes in 93 lung adenocarcinoma patients and Kaplan-Meier analysis and Cox proportional hazards models to evaluate their prognostic roles. Among 24 paired genes, only FEN1 (Flap endonuclease 1) and RAD54B (RAD54 homolog B) were overexpressed in lung adenocarcinoma patients with poor prognosis. Patients with expression of both FEN1 and RAD54B were prone to have advanced nodal involvement and significantly poor prognosis (HR = 2.35, P = 0.0230). These results suggest that intensive follow up and targeted therapy might improve clinical outcome for patients who show expression of both FEN1 and RAD54B.

CSNK1A1 and Gli2 as Novel Targets Identified Through an Integrative Analysis of Gene Expression Data, Protein-Protein Interaction and Pathways Networks in Glioblastoma Tumors: Can These Two Be Antagonistic Proteins?

Glioblastoma (GBM) is the malignant form of glioma, and the interplay of different pathways working in concert in GBM development and progression needs to be fully understood. Wnt signaling and sonic hedgehog (SHH) signaling pathways, having basic similarities, are among the major pathways aberrantly activated in GBM, and hence, need to be targeted. It becomes imperative, therefore, to explore the functioning of these pathways in context of each other in GBM. An integrative approach may help provide new biological insights, as well as solve the problem of identifying common drug targets for simultaneous targeting of these pathways. The beauty of this approach is that it can recapitulate several known facts, as well as decipher new emerging patterns, identifying those targets that could be missed when relying on one type of data at a time. This approach can be easily extended to other systems to discover key patterns in the functioning of signaling molecules. Studies were designed to assess the relationship between significant differential expression of genes of the Wnt (Wnt/β-catenin canonical and Wnt non-canonical) and SHH signaling pathways and their connectivity patterns in interaction and signaling networks. Further, the aim was to decipher underlying mechanistic patterns that may be involved in a more specific way and to generate a ranked list of genes that can be used as markers or drug targets. These studies predict that Wnt pathway plays a relatively more pro-active role than the SHH pathway in GBM. Further, CTNNB1, CSNK1A1, and Gli2 proteins may act as key drug targets common to these pathways. While CTNNB1 is a widely studied molecule in the context of GBM, the likely roles of CSNK1A1 and Gli2 are found to be relatively novel. It is surmised that Gli2 may be antagonistic to CSNK1A1, preventing the phosphorylation of CTNNB1 and SMO proteins in Wnt and SHH signaling pathway, respectively, by CSNK1A1, and thereby, aberrant activation. New insights into the possible behavior of these pathway molecules relative to each other in GBM reveal some key interesting patterns.