Using CellMiner 1.6 for Systems Pharmacology and Genomic Analysis of the NCI-60

HIF-2α-dependent TGFBI promotes ovarian cancer chemoresistance by activating PI3K/Akt pathway to inhibit apoptosis and facilitate DNA repair process

Hypoxia-mediated chemoresistance plays a crucial role in the development of ovarian cancer (OC). However, the roles of hypoxia-related genes (HRGs) in chemoresistance and prognosis prediction and theirs underlying mechanisms remain to be further elucidated. We intended to identify and validate classifiers of hub HRGs for chemoresistance, diagnosis, prognosis as well as immune microenvironment of OC, and to explore the function of the most crucial HRG in the development of the malignant phenotypes. The RNA expression and clinical data of HRGs were systematically evaluated in OC training group. Univariate and multivariate Cox regression analysis were applied to construct hub HRGs classifiers for prognosis and diagnosis assessment. The relationship between classifiers and chemotherapy response and underlying pathways were detected by GSEA, CellMiner and CIBERSORT algorithm, respectively. OC cells were cultured under hypoxia or transfected with HIF-1α or HIF-2α plasmids, and the transcription levels of TGFBI were assessed by quantitative PCR. TGFBI was knocked down by siRNAs in OC cells, CCK8 and in vitro migration and invasion assays were performed to examine the changes in cell proliferation, motility and metastasis. The difference in TGFBI expression was examined between cisplatin-sensitive and -resistant cells, and the effects of TGFBI interference on cell apoptosis, DNA repair and key signaling molecules of cisplatin-resistant OC cells were explored. A total of 179 candidate HRGs were extracted and enrolled into univariate and multivariate Cox regression analysis. Six hub genes (TGFBI, CDKN1B, AKAP12, GPC1, TGM2 and ANGPTL4) were selected to create a HRGs prognosis classifier and four genes (TGFBI, AKAP12, GPC1 and TGM2) were selected to construct diagnosis classifiers. The HRGs prognosis classifier could precisely distinguish OC patients into high-risk and low-risk groups and estimate their clinical outcomes. Furthermore, the high-risk group had higher percentage of Macrophages M2 and exhibited higher expression of immunecheckpoints such as PD-L2. Additionally, the diagnosis classifiers could accurately distinguish OC from normal samples. TGFBI was further verified as a specific key target and demonstrated that its high expression was closely correlated with poor prognosis and chemoresistance of OC. Hypoxia upregulated the expression level of TGFBI. The hypoxia-induced factor HIF-2α but not HIF-1α could directly bind to the promoter region of TGFBI, and facilitate its transcription level. TGFBI was upregulated in cisplatin-sensitive and resistant ovarian cancer cells in a cisplatin time-dependent manner. TGFBI interference downregulated DNA repair-related markers (p-p95/NBS1, RAD51, p-DNA-PKcs, DNA Ligase IV and Artemis), apoptosis-related marker (BCL2) and PI3K/Akt pathway-related markers (PI3K-p110 and p-Akt) in cisplatin-resistant OC cells. In summary, the HRGs prognosis risk classifier could be served as a predictor for OC prognosis and efficacy evaluation. TGFBI, upregulated by HIF-2α as an HRG, promoted OC chemoresistance through activating PI3K/Akt pathway to reduce apoptosis and enhance DNA damage repair pathway.

Current advances in comprehensive omics data mining for oncology and cancer research

The availability of a large amount of multiomics data enables data-driven discovery studies on cancers. High-throughput data on mutations, gene/protein expression, immune scores (tumor-infiltrating cells), drug screening, and RNAi (shRNAs and CRISPRs) screening are major integrated components of patient samples and cell line datasets. Improvements in data access and user interfaces make it easy for general scientists to carry out their data mining practices on integrated multiomics data platforms without computational expertise. Here, we summarize the extent of data integration and functionality of several portals and software that provide integrated multiomics data mining platforms for all cancer studies. Recent progress includes programming interfaces (APIs) for customized data mining. Precalculated datasets assist noncomputational users in quickly browsing data associations. Furthermore, stand-alone software provides fast calculations and smart functions, guiding optimal sampling and filtering options for the easy discovery of significant data associations. These efforts improve the utility of cancer omics big data for noncomputational users at all levels of cancer research. In the present review, we aim to provide analytical information guiding general scientists to find and utilize data mining tools for their research.

A pan-cancer analysis of anti-proliferative protein family genes for therapeutic targets in cancer

The recently discovered APRO (anti-proliferative protein) family encodes a group of trans-membrane glycoproteins and includes 6 members: TOB1, TOB2, BTG1, BTG2, BTG3 and BTG4. The APRO family is reportedly associated with the initiation and progression of cancers. This study aims to undertake a comprehensive investigation of the APRO family of proteins as a prognostic biomarker in various human tumors. We performed a pan-cancer analysis of the APRO family based on The Cancer Genome Atlas (TCGA). With the bioinformatics methods, we explored the prognostic value of the APRO family and the correlation between APRO family expression and tumor mutation burden (TMB), microsatellite instability (MSI), drug sensitivity, and immunotherapy in numerous cancers. Our results show that the APRO family was primarily down-regulated in cancer samples. The expression of APRO family members was linked with patient prognosis. In addition, APRO family genes showed significant association with immune infiltrate subtypes, tumor microenvironment, and tumor cell stemness. Finally, our study also demonstrated the relationship between APRO family genes and drug sensitivity. This study provides comprehensive information to understand the APRO family's role as an oncogene and predictor of survival in some tumor types.

Identification of TMEM178 as a Potential Prognostic Biomarker and Therapeutic Target for Breast Cancer

Background

The transmembrane protein (TMEM) family plays important roles in cancer. However, the expression pattern and biological roles of TMEM178, a member of TMEM family, remains unclear in breast cancer (BRCA).

Methods

Methylation and RNA-seq data were obtained to explore methylation level. Expression of TMEM178, methylation inhibitor 5-Aza-CdR was used to verify the effect of methylation status on the expression of TMEM178. We comprehensively investigated the prognostic outcomes, biological functions and effects on immune cell infiltration of the TMEM178 in BRCA using multiple bioinformatics methods.

Results

The expression of TMEM178 was downregulated and negatively correlated with the level of DNA methylation and DNA methyltransferase (DNMT1, DNMT3A, and DNMT3B) in BRCA. Consistently, TMEM178 mRNA were confirmed to be downregulated, while upregulated in response to treatment with methylation inhibitor 5-Aza-CdR by RT-qPCR. Patients with high expression of TMEM178 have better prognosis and are more sensitive to targeted drug Pazopanib. Immune infiltration analysis showed that the infiltration levels of CD4+ T cell subsets were reduced in BRAC tissues with high TMEM178 expression, and immunosuppressive molecules of T-cell exhaustion were lower expression level.

Conclusion

Hypermethylation of the TMEM178 promoter region was a contributing factor to the downregulation of its expression, and TMEM178 may reflect a prognostic and immunosuppressive situation in BRCA.

Establishment of a novel indicator of pyroptosis regulated gene transcription level and its application in pan-cancer

Pyroptosis is a type of programmed cell death and plays a dual role in distinct cancers. It is elusive to evaluate the activation level of pyroptosis and to appraise the involvement of pyroptosis in the occurrence and development of diverse tumors. Accordingly, we herein established an indicator to evaluate pyroptosis related gene transcription levels based on the expression level of genes involved in pyroptosis and tried to elaborated on the association between pyroptosis and tumors across diverse tumor types. We found that pyroptosis related gene transcription levels could predict the prognosis of patients, which could act as either a favorable or a dreadful factor in diverse cancers. According to signaling pathway analyses we observed that pyroptosis played a significant role in immune regulation and tumorigenesis and had strong links with other forms of cell death. We also performed analysis on the crosstalk between pyroptosis and immune status and further investigated the predictive potential of pyroptosis level for the efficacy of immunotherapy. Lastly, we manifested that pyroptosis status could serve as a biomarker to the efficacy of chemotherapy across various cancers. In summary, this study established a quantitative indicator to evaluate pyroptosis related gene transcription levels, systematically explored the role of pyroptosis in pan-cancer. These results could provide potential research directions targeting pyroptosis, and highlighted that pyroptosis may be used to develop a novel strategy for the treatment of cancer.

Preclinical Efficacy of LP-184, a Tumor Site Activated Synthetic Lethal Therapeutic, in Glioblastoma

PURPOSE

Glioblastoma (GBM) is the most common brain malignancy with median survival <2 years. Standard-of-care temozolomide has marginal efficacy in approximately 70% of patients due to MGMT expression. LP-184 is an acylfulvene-derived prodrug activated by the oxidoreductase PTGR1 that alkylates at N3-adenine, not reported to be repaired by MGMT. This article examines LP-184 efficacy against preclinical GBM models and identifies molecular predictors of LP-184 efficacy in clinical GBM.

EXPERIMENTAL DESIGN

LP-184 effects on GBM cell viability and DNA damage were determined using cell lines, primary PDX-derived cells and patient-derived neurospheres. GBM cell sensitivities to LP-184 relative to temozolomide and MGMT expression were examined. Pharmacokinetics and CNS bioavailability were evaluated in mice with GBM xenografts. LP-184 effects on GBM xenograft growth and animal survival were determined. Machine learning, bioinformatic tools, and clinical databases identified molecular predictors of GBM cells and tumors to LP-184 responsiveness.

RESULTS

LP-184 inhibited viability of multiple GBM cell isolates including temozolomide-resistant and MGMT-expressing cells at IC50 = approximately 22-310 nmol/L. Pharmacokinetics showed favorable AUCbrain/plasma and AUCtumor/plasma ratios of 0.11 (brain Cmax = 839 nmol/L) and 0.2 (tumor Cmax = 2,530 nmol/L), respectively. LP-184 induced regression of GBM xenografts and prolonged survival of mice bearing orthotopic xenografts. Bioinformatic analyses identified PTGR1 elevation in clinical GBM subtypes and associated LP-184 sensitivity with EGFR signaling, low nucleotide excision repair (NER), and low ERCC3 expression. Spironolactone, which induces ERCC3 degradation, decreased LP-184 IC50 3 to 6 fold and enhanced GBM xenograft antitumor responses.

CONCLUSIONS

These results establish LP-184 as a promising chemotherapeutic for GBM with enhanced efficacy in intrinsic or spironolactone-induced TC-NER-deficient tumors.

Identification and characterization of topoisomerase III beta poisons

We designed and carried out a high-throughput screen for compounds that trap topoisomerase III beta (TOP3B poisons) by developing a Comparative Cellular Cytotoxicity Screen. We found a bisacridine compound NSC690634 and a thiacyanine compound NSC96932 that preferentially sensitize cell lines expressing TOP3B, indicating that they target TOP3B. These compounds trap TOP3B cleavage complex (TOP3Bcc) in cells and in vitro and predominately act on RNA, leading to high levels of RNA-TOP3Bccs. NSC690634 also leads to enhanced R-loops in a TOP3B-dependent manner. Preliminary structural activity studies show that the lengths of linkers between the two aromatic moieties in each compound are critical; altering the linker length completely abolishes the trapping of TOP3Bccs. Both of our lead compounds share a similar structural motif, which can serve as a base for further modification. They may also serve in anticancer, antiviral, and/or basic research applications.

CellMinerCDB: NCATS Is a Web-Based Portal Integrating Public Cancer Cell Line Databases for Pharmacogenomic Explorations

Major advances have been made in the field of precision medicine for treating cancer. However, many open questions remain that need to be answered to realize the goal of matching every patient with cancer to the most efficacious therapy. To facilitate these efforts, we have developed CellMinerCDB: National Center for Advancing Translational Sciences (NCATS; https://discover.nci.nih.gov/rsconnect/cellminercdb_ncats/), which makes available activity information for 2,675 drugs and compounds, including multiple nononcology drugs and 1,866 drugs and compounds unique to the NCATS. CellMinerCDB: NCATS comprises 183 cancer cell lines, with 72 unique to NCATS, including some from previously understudied tissues of origin. Multiple forms of data from different institutes are integrated, including single and combination drug activity, DNA copy number, methylation and mutation, transcriptome, protein levels, histone acetylation and methylation, metabolites, CRISPR, and miscellaneous signatures. Curation of cell lines and drug names enables cross-database (CDB) analyses. Comparison of the datasets is made possible by the overlap between cell lines and drugs across databases. Multiple univariate and multivariate analysis tools are built-in, including linear regression and LASSO. Examples have been presented here for the clinical topoisomerase I (TOP1) inhibitors topotecan and irinotecan/SN-38. This web application provides both substantial new data and significant pharmacogenomic integration, allowing exploration of interrelationships.

SIGNIFICANCE

CellMinerCDB: NCATS provides activity information for 2,675 drugs in 183 cancer cell lines and analysis tools to facilitate pharmacogenomic research and to identify determinants of response.

Gene S-phase kinase associated protein 2 is a novel prognostic marker in human neoplasms

BACKGROUND

Neoplasms are a series of diseases affecting human health. Prognostic and tumor status-related markers for various tumors should be identified.

METHODS

Based on 19,515 samples from multiple sources, for the first time, this study provided an overview of gene S-phase kinase associated protein 2 (SKP2) in pan-cancer. Differential SKP2 expression in multiple comparison groups was identified by the Kruskal-Wallis test and Wilcoxon rank-sum test. The prognosis significance of SKP2 in individuals with neoplasm was evaluated through univariate Cox regression analysis and Kaplan-Meier curves. The area under the curve was utilized to detect the accuracy of SKP2 in predicting cancer status. Spearman's rank correlation coefficients were calculated in all correlation analyses. Gene set enrichment analysis was used to identify essential signaling pathways of SKP2 in human neoplasms.

RESULTS

The study disclosed the upregulated SKP2 expression in 15 neoplasms and decreased SKP2 expression in three cancers (p < 0.05). The transcription factor Forkhead Box M1 may contribute to the increased expression levels of SKP2 in certain tumors. Over-expressed SKP2 represented a risk factor for the prognosis of most cancer patients (hazard ratio > 1, p < 0.05). SKP2 expression made it feasible to distinguish neoplasm and control tissues of 21 neoplasms (sensitivity = 0.79, specificity = 0.87, area under the curve = 0.90), implying its potential in screening a series of neoplasms. Further, the research revealed the close association of SKP2 expression with DNA methyltransferases, mismatch repair genes, microsatellite instability, tumor mutational burden, neoantigen count, and immunity.

CONCLUSIONS

SKP2 plays an essential role in multiple neoplasms and may serve as a marker for treating and identifying these neoplasms.

LncRNA WAC-AS1 expression in human tumors correlates with immune infiltration and affects prognosis

BACKGROUND

WAC-antisense RNA1 (WAC-AS1) is a newly identified long non-coding RNA (lncRNA) implicated in the prognosis and development of a few types of tumors. However, the correlations of WAC-AS1 with immune infiltration and patient prognosis in pan-cancer remain unclear. In the present study, we aimed to investigate the prognostic value and immunological functions of WAC-AS1 across 33 different types of cancers.

METHODS

To investigate the potential oncogenic roles of WAC-AS1, bioinformatics analyses were performed using the Cancer Genome Atlas (TCGA) and Genotype Tissue-Expression (GTEx) datasets. The correlations of WAC-AS1 with prognosis, clinical phenotype, tumor mutational burden (TMB), microsatellite instability (MSI), tumor regulation-related genes, tumor microenvironment, immune cell infiltration, and drug resistance to commonly used chemotherapy drugs in different types of tumors were explored. Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) were performed to explore the biological functions of WAC-AS1 in tumors. In situ hybridization (ISH) was performed in tissue microarray (TMA) to confirm the expression of WAC-AS1 in multiple tumor tissues.

RESULTS

WAC-AS1 showed aberrant expression in most cancers when compared to the normal tissues. It also has prognostic value in multiple types of cancers. Elevated WAC-AS1 expression was associated with poor prognosis and overall survival in adrenocortical carcinoma (ACC), breast invasive carcinoma (BRCA), and liver hepatocellular carcinoma (LIHC). A significant negative correlation between WAC-AS1 expression and overall survival was observed in brain lower-grade glioma (LGG), pancreatic adenocarcinoma (PAAD), and skin cutaneous melanoma (SKCM). The expression of WAC-AS1 also showed a correlation with clinical stage in six types of tumors, and with tumor mutational burden and microsatellite instability in several different types of cancers. The immune scores of those cancers were found to be significant. Additionally, the effectiveness of fluorouracil and four other anticancer drugs was significantly different based on the expression of WAC-AS1 in these cancers. Moreover, the ISH results showed in six types of tumors, the expression of WAC-AS1 was consistent with the Pan-cancer analysis using TCGA and GTEx database.

CONCLUSIONS

These results indicate an intensive involvement of WAC-AS1 in the regulation of immune responses, immune cell infiltration, and malignant properties in various types of cancers, suggesting that WAC-AS1 may serve as a prognostic marker across diverse types of cancers.

A novel mitochondria-related gene signature in esophageal carcinoma: prognostic, immune, and therapeutic features

Esophageal carcinoma (ESCA) is a common and lethal malignant tumor worldwide. The mitochondrial biomarkers were useful in finding significant prognostic gene modules associated with ESCA owing to the role of mitochondria in tumorigenesis and progression. In the present work, we obtained the transcriptome expression profiles and corresponding clinical information of ESCA from The Cancer Genome Atlas (TCGA) database. Differential expressed genes (DEGs) were overlapped with 2030 mitochondria-related genes to get mitochondria-related DEGs. The univariate cox regression, Least Absolute Shrinkage and Selection Operator (LASSO) regression, and multivariate cox regression were sequentially used to define the risk scoring model for mitochondria-related DEGs, and its prognostic value was verified in the external datasets GSE53624. Based on the risk score, ESCA patients were divided into high- and low-risk groups. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) were performed to further investigate the difference between low- and high-risk groups at the gene pathway level. CIBERSORT was used to evaluate immune cell infiltration. The mutation difference between high- and low-risk groups was compared by using the R package "Maftools". Cellminer was used to assess the association between the risk scoring model and drug sensitivity. As the most important outcome of the study, a 6-gene risk scoring model (APOOL, HIGD1A, MAOB, BCAP31, SLC44A2, and CHPT1) was constructed from 306 mitochondria-related DEGs. Pathways including the "hippo signaling pathway" and "cell-cell junction" were enriched in the DEGs between high and low groups. According to CIBERSORT, samples with high-risk scores demonstrated a higher abundance of CD4⁺ T cells, NK cells, M0 and M2 macrophages, and a lower abundance of M1 macrophages. The immune cell marker genes were correlated with the risk score. In mutation analysis, the mutation rate of TP53 was significantly different between the high- and low-risk groups. Drugs with a strong correlation with the risk model were selected. In conclusion, we focused on the role of mitochondria-related genes in cancer development and proposed a prognostic signature for individualized integrative assessment.

Pan-Cancer Analysis of the TRP Family, Especially TRPV4 and TRPC4, and Its Expression Correlated with Prognosis, Tumor Microenvironment, and Treatment Sensitivity

BACKGROUND

Transient receptor potential (TRP) channels are involved in various physiological, pathological, and tumorigenesis-related processes. However, only a few studies have comprehensively analyzed TRP family members and their association with prognosis and tumor microenvironment (TME) in various cancers. Thus, in this study, we focused on TRP channels in pan-cancer and screened two typical TRP channels, TRPV4 and TRPC4, as examples.

METHODS

Based on the latest public databases, we evaluated the expression level and prognostic value of TRP family genes in pan-cancer tissues via various bioinformatic analytical methods, and investigated the relationship between the expression of TRP family genes with TME, stemness score, immune subtype, drug sensitivity, and immunotherapy outcome in pan-cancer tissues.

RESULTS

Pan-cancer analysis revealed that the TRP family genes were differentially expressed in tumor and para-carcinoma tissues. A significant correlation existed between the expression of TRP family genes and prognosis. The expression of TRP family genes was significantly correlated with stromal, immune, RNA stemness, and DNA stemness scores in pan-cancer tissues. Our results indicated that the expression of TRP family genes correlated with the sensitivity to various drugs including PLX-4720, SB-590885, and HYPOTHEMYCIN, immunotherapy outcome, and immune-activation-related genes. Immunohistochemical analysis revealed significant differential expression of TRPV4 in bladder and para-carcinoma tissues.

CONCLUSIONS

Our study elucidated the possible role of TRP family genes in cancer progression and provided insights for further studies on TRP family genes as potential pan-cancer targets to develop diagnostic and therapeutic strategies.

Large inherent variability in data derived from highly standardised cell culture experiments

Cancer drug development is hindered by high clinical attrition rates, which are blamed on weak predictive power by preclinical models and limited replicability of preclinical findings. However, the technically feasible level of replicability remains unknown. To fill this gap, we conducted an analysis of data from the NCI60 cancer cell line screen (2.8 million compound/cell line experiments), which is to our knowledge the largest depository of experiments that have been repeatedly performed over decades. The findings revealed profound intra-laboratory data variability, although all experiments were executed following highly standardised protocols that avoid all known confounders of data quality. All compound/ cell line combinations with > 100 independent biological replicates displayed maximum GI50 (50% growth inhibition) fold changes (highest/ lowest GI50) > 5% and 70.5% displayed maximum fold changes > 1000. The highest maximum fold change was 3.16 × 10¹⁰ (lowest GI50: 7.93 ×10^-10 µM, highest GI50: 25.0 µM). FDA-approved drugs and experimental agents displayed similar variation. Variability remained high after outlier removal, when only considering experiments that tested drugs at the same concentration range, and when only considering NCI60-provided quality-controlled data. In conclusion, high variability is an intrinsic feature of anti-cancer drug testing, even among standardised experiments in a world-leading research environment. Awareness of this inherent variability will support realistic data interpretation and inspire research to improve data robustness. Further research will have to show whether the inclusion of a wider variety of model systems, such as animal and/ or patient-derived models, may improve data robustness.

CLC-Pred 2.0: A Freely Available Web Application for In Silico Prediction of Human Cell Line Cytotoxicity and Molecular Mechanisms of Action for Druglike Compounds

In vitro cell-line cytotoxicity is widely used in the experimental studies of potential antineoplastic agents and evaluation of safety in drug discovery. In silico estimation of cytotoxicity against hundreds of tumor cell lines and dozens of normal cell lines considerably reduces the time and costs of drug development and the assessment of new pharmaceutical agent perspectives. In 2018, we developed the first freely available web application (CLC-Pred) for the qualitative prediction of cytotoxicity against 278 tumor and 27 normal cell lines based on structural formulas of 59,882 compounds. Here, we present a new version of this web application: CLC-Pred 2.0. It also employs the PASS (Prediction of Activity Spectra for Substance) approach based on substructural atom centric MNA descriptors and a Bayesian algorithm. CLC-Pred 2.0 provides three types of qualitative prediction: (1) cytotoxicity against 391 tumor and 47 normal human cell lines based on ChEMBL and PubChem data (128,545 structures) with a mean accuracy of prediction (AUC), calculated by the leave-one-out (LOO CV) and the 20-fold cross-validation (20F CV) procedures, of 0.925 and 0.923, respectively; (2) cytotoxicity against an NCI60 tumor cell-line panel based on the Developmental Therapeutics Program's NCI60 data (22,726 structures) with different thresholds of IG₅₀ data (100, 10 and 1 nM) and a mean accuracy of prediction from 0.870 to 0.945 (LOO CV) and from 0.869 to 0.942 (20F CV), respectively; (3) 2170 molecular mechanisms of actions based on ChEMBL and PubChem data (656,011 structures) with a mean accuracy of prediction 0.979 (LOO CV) and 0.978 (20F CV). Therefore, CLC-Pred 2.0 is a significant extension of the capabilities of the initial web application.

SARS-CoV-2-correlated ASGR1 is a novel potential marker for the treatment and identification of multiple human cancers

OBJECTIVES

Cancer patients are reported to be more susceptible to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and the COVID-19 (the Corona Virus Disease 2019) patients with cancer suffer from certain serious complications. ASGR1 has been recently identified as a novel receptor of SARS-CoV-2 in human cells; however, there are limited studies on ASGR1 in various human cancers.

METHODS

This study utilized a comprehensive analysis of COVID-19-related ASGR1 in multiple human cancers based on 18,589 multi-center samples. Using Wilcoxon rank-sum analysis, a difference in ASGR1 expression between cancer and control tissues was detected. Cox regression analysis, Kaplan-Meier curves, and receiver operating characteristic curves were utilized to determine the correlation between ASGR1 expression and the clinical parameters of cancer patients. The immune relevance and potential mechanisms of ASGR1 in various cancers were also investigated.

RESULTS

Abnormal ASGR1 mRNA expression was observed in 16 of 20 different cancers (e.g., it was upregulated in colon adenocarcinoma but downregulated in cholangiocarcinoma; P < 0.05). ASGR1 was related to prognosis, e.g., overall survival, in 14 cancers (P < 0.05), such as adrenocortical carcinoma. The gene was also found to be a potential marker that can be utilized to distinguish eleven cancers from controls with moderate to high accuracy (e.g., the area under the curve for cholangiocarcinoma = 1.000). ASGR1 expression was related to DNA methyltransferases, mismatch repair genes, immune checkpoints, levels of tumor mutational burden, microsatellite instability, neoantigen count, and immune infiltration levels in certain cancers (P < 0.05). The gene plays a role in multiple cancers by affecting four signaling pathways, such as cytokine-cytokine receptor interaction. Cancer patients with high ASGR1 expression are sensitive to 25 drugs, including ulixertinib.

CONCLUSIONS

SARS-CoV-2-correlated ASGR1 is a novel marker that can be used for treating and identifying multiple human cancers.

SLC17A9-PTHLH-EMT axis promotes proliferation and invasion of clear renal cell carcinoma

SLC17A9 is a vesicular ATP transport protein that plays an important role in determining cell functions and the onset and progression of different diseases. In this study, SLC17A9 was initially identified as a potential diagnostic and prognostic risk biomarker for clear cell renal cell carcinoma (ccRCC). Then, the aberrant expression levels of SLC17A9 were confirmed in both the cell lines and clinical tissues. Mechanistically, SLC17A9 could upregulate the expression of PTHLH, thus promoting epithelial-mesenchymal transition (EMT) in ccRCC. Functionally, SLC17A9 knockdown inhibited the proliferation, migration, and invasion activity of renal cancer cells, whereas its overexpression led to stronger cell viability and more malignant phenotype in vitro. The overexpression of SLC17A9 in vivo could significantly contribute to the growth of tumors. Finally, we found that SLC17A9 might be related to the drug resistance of vorinostat. Cumulatively, this study demonstrated that the SLC17A9-PTHLH-EMT axis could promote the progression of ccRCC.

Regulation, genomics, and clinical characteristics of cuproptosis regulators in pan-cancer

Background

Cuproptosis, a copper-dependent controlled cell death, is a novel form of cell death that differs from known cell death mechanisms; however, its overall regulation in cancer remains elusive.

Methods

Multiple open-source bioinformatic platforms were used to comprehensively elucidate the expression levels, prognostic efficiency, potential biological functions, genomic and epigenetic characteristics, immune microenvironment, and drug sensitivity of cuproptosis regulators (ATP7A, ATP7B, DLAT, DLD, FDX1, GLS, LIAS, LIPT1, MTF1, NLRP3, PDHA1, PDHB, and SLC31A1) in pan-cancer.

Results

Cuproptosis-related genes (CRGs) were upregulated in most cancers tested. In KIRC, KIRP, LGG, MESO, and PCPG, most highly expressed CRGs predicted a better prognosis but poorer prognosis in patients with ACC, LIHC, and UCEC. Pathway analysis confirmed that cuproptosis regulators were associated with the metabolism-related pathways. The expression of MTF1, NLRP3, and SLC31A1 was positively related with ImmuneScore, StromalScore, and ESTIMATEScore in almost all types of tumor, whereas ATP7B, DLAT, DLD, LIAS, PDHA1, and PDHB were significantly negatively correlated with the scores. In addition, CRGs were significantly correlated with RNA stemness score, DNA stemness score, microsatellite instability, and tumor mutational burden. The expression of ATP7A, ATP7B, LIAS, and DLAT was significantly positively correlated with the drug sensitivity of Docetaxel. ATP7A, LIAS, and FDX1 were significantly negatively correlated with the drug sensitivity of UNC0638, XMD13−2, YM201636, and KIN001−260.

Conclusions

The altered genomic and clinical characteristics of cuproptosis regulators were comprehensively elucidated, providing a preliminary basis for understanding the functions of cuproptosis in pan-cancer.

A novel 10-gene ferroptosis-related prognostic signature in acute myeloid leukemia

Acute myeloid leukemia (AML) is one of the most common hematopoietic malignancies and exhibits a high rate of relapse and unfavorable outcomes. Ferroptosis, a relatively recently described type of cell death, has been reported to be involved in cancer development. However, the prognostic value of ferroptosis-related genes (FRGs) in AML remains unclear. In this study, we found 54 differentially expressed ferroptosis-related genes (DEFRGs) between AML and normal marrow tissues. 18 of 54 DEFRGs were correlated with overall survival (OS) (P<0.05). Using the least absolute shrinkage and selection operator (LASSO) Cox regression analysis, we selected 10 DEFRGs that were associated with OS to build a prognostic signature. Data from AML patients from the International Cancer Genome Consortium (ICGC) cohort as well as the First Affiliated Hospital of Wenzhou Medical University (FAHWMU) cohort were used for validation. Notably, the prognostic survival analyses of this signature passed with a significant margin, and the riskscore was identified as an independent prognostic marker using Cox regression analyses. Then we used a machine learning method (SHAP) to judge the importance of each feature in this 10-gene signature. Riskscore was shown to have the highest correlation with this 10-gene signature compared with each gene in this signature. Further studies showed that AML was significantly associated with immune cell infiltration. In addition, drug-sensitive analysis showed that 8 drugs may be beneficial for treatment of AML. Finally, the expressions of 10 genes in this signature were verified by real-time quantitative polymerase chain reaction. In conclusion, our study establishes a novel 10-gene prognostic risk signature based on ferroptosis-related genes for AML patients and FRGs may be novel therapeutic targets for AML.

Multiomics surface receptor profiling of the NCI-60 tumor cell panel uncovers novel theranostics for cancer immunotherapy

BACKGROUND

Immunotherapy with immune checkpoint inhibitors (ICI) has revolutionized cancer therapy. However, therapeutic targeting of inhibitory T cell receptors such as PD-1 not only initiates a broad immune response against tumors, but also causes severe adverse effects. An ideal future stratified immunotherapy would interfere with cancer-specific cell surface receptors only.

METHODS

To identify such candidates, we profiled the surface receptors of the NCI-60 tumor cell panel via flow cytometry. The resulting surface receptor expression data were integrated into proteomic and transcriptomic NCI-60 datasets applying a sophisticated multiomics multiple co-inertia analysis (MCIA). This allowed us to identify surface profiles for skin, brain, colon, kidney, and bone marrow derived cell lines and cancer entity-specific cell surface receptor biomarkers for colon and renal cancer.

RESULTS

For colon cancer, identified biomarkers are CD15, CD104, CD324, CD326, CD49f, and for renal cancer, CD24, CD26, CD106 (VCAM1), EGFR, SSEA-3 (B3GALT5), SSEA-4 (TMCC1), TIM1 (HAVCR1), and TRA-1-60R (PODXL). Further data mining revealed that CD106 (VCAM1) in particular is a promising novel immunotherapeutic target for the treatment of renal cancer.

CONCLUSION

Altogether, our innovative multiomics analysis of the NCI-60 panel represents a highly valuable resource for uncovering surface receptors that could be further exploited for diagnostic and therapeutic purposes in the context of cancer immunotherapy.

The m6A-Related Long Noncoding RNA Signature Predicts Prognosis and Indicates Tumor Immune Infiltration in Ovarian Cancer

Background: OV is the most lethal gynecological malignancy. M6A and lncRNAs have a great impact on OV development and patient immunotherapy response. In this paper, we decided to establish a reliable signature of mRLs. Method: The lncRNAs associated with m6A in OV were analyzed and obtained by co-expression analysis of the TCGA-OV database. Univariate, LASSO and multivariate Cox regression analyses were employed to establish the model of mRLs. K-M analysis, PCA, GSEA and nomogram based on the TCGA-OV and GEO database were conducted to prove the predictive value and independence of the model. The underlying relationship between the model and TME and cancer stemness properties were further investigated through immune feature comparison, consensus clustering analysis and pan-cancer analysis. Results: A prognostic signature comprising four mRLs, WAC-AS1, LINC00997, DNM3OS and FOXN3-AS1, was constructed and verified for OV according to the TCGA and GEO database. The expressions of the four mRLs were confirmed by qRT-PCR in clinical samples. Applying this signature, one can identify patients more effectively. The samples were divided into two clusters, and the clusters had different overall survival rates, clinical features and tumor microenvironments. Finally, pan-cancer analysis further demonstrated that the four mRLs were significantly related to immune infiltration, TME and cancer stemness properties in various cancer types. Conclusions: This study provided an accurate prognostic signature for patients with OV and elucidated the potential mechanism of the mRLs in immune modulation and treatment response, giving new insights into identifying new therapeutic targets.

Construction and validation of a novel ten miRNA-pair based signature for the prognosis of clear cell renal cell carcinoma

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is the most predominate pathological subtype of renal cell carcinoma, causing a recurrence or metastasis rate as high as 20% to 40% after operation, for which effective prognostic signature is urgently needed.

METHODS

The mRNA and miRNA profiles of ccRCC specimens were collected from the Cancer Genome Atlas. MiRNA-pair risk score (miPRS) for each miRNA pair was generated as a signature and validated by univariate and multivariate Cox proportional hazards regression analysis. Functional enrichment was performed, and immune cells infiltration, as well as tumor mutation burden (TMB), and immunophenoscore (IPS) were evaluated between high and low miPRS groups. Target gene-prediction and differentially expressed gene-analysis were performed based on databases of miRDB, miRTarBase, and TargetScan. Multivariate Cox proportional hazards regression analysis was adopted to establish the prognostic model and Kaplan-Meier survival analysis was performed.

FINDINGS

A novel 10 miRNA-pair based signature was established. Area under the time-dependent receiver operating curve proved the performance of the signature in the training, validation, and testing cohorts. Higher TMB, as well as the higher CTLA4-negative PD1-negative IPS, were discovered in high miPRS patients. A prognostic model was built based on miPRS (1 year-, 5 year-, 10 year- ROC-AUC=0.92, 0.84, 0.82, respectively).

INTERPRETATION

The model based on miPRS is a novel and valid tool for predicting the prognosis of ccRCC.

FUNDING

This study was supported by research grants from the China National Natural Scientific Foundation (81903972, 82002018, and 82170752) and Shanghai Sailing Program (19YF1406700 and 20YF1406000).

Bladder cancer-derived exosomal KRT6B promotes invasion and metastasis by inducing EMT and regulating the immune microenvironment

Background

Tumour-derived exosomes have recently been shown to participate in the formation and progression of different cancer processes, including tumour microenvironment remodelling, angiogenesis, invasion, metastasis, and drug resistance. However, the function and mechanism of exosome-encapsulated nucleic acids and proteins in bladder cancer remain unclear. This study aimed to investigate the effects of tumour-derived exosomes on the tumorigenesis and development of bladder cancer.

Methods

In this study, gene expression profiles and clinical information were collected from The Cancer Genome Atlas (TCGA) database and two independent Gene Expression Omnibus (GEO) datasets. The nucleic acids and proteins encapsulated in bladder cancer-derived exosomes were obtained from the ExoCarta database. Based on these databases, the expression patterns of exosomal mRNAs and proteins and the matched clinicopathological characteristics were analysed. Furthermore, we carried out a series of experiments to verify the relevant findings.

Results

A total of 7280 differentially expressed mRNAs were found in TCGA data, of which 52 mRNAs were shown to be encapsulated in bladder cancer-derived exosomes. Survival analysis based on the UALCAN database showed that among the top 10 upregulated and the top 10 downregulated exosomal genes, only the expression of KRT6B had a statistically significant effect on the survival of bladder cancer patients. Additionally, clinical correlation analysis showed that the elevated level of KRT6B was highly associated with bladder cancer stage, grade, and metastasis status. GSEA revealed that KRT6B was involved not only in epithelial–mesenchymal transition-related pathways but also in the immune response in bladder cancer. Ultimately, our experimental results were also consistent with the bioinformatic analysis.

Conclusion

KRT6B, which can be detected in bladder cancer-derived exosomes, plays an important role in the epithelial–mesenchymal transition and immune responses in bladder cancer. Further research will enable its potentially prognostic marker and therapeutic target for bladder cancer.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03508-2.

Pan-Cancer Analysis, Reveals COVID-19-Related BSG as a Novel Marker for Treatment and Identification of Multiple Human Cancers

Background: Coronavirus disease 2019 (COVID-19) has been a public threat and healthcare concern caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. During the period of the pandemic of COVID-19, cancer patients should be paid more attention as more severe events are found in cancer patients infected with SARS-CoV-2. Basigin (BSG) is an essential factor for the infection and progression of COVID-19 and tumorigenesis of multiple tumors, which may serve as a novel target for the effective treatment against COVID-19 and multiple human cancers.

Methods: A total of 19,020 samples from multiple centers were included in our research for the comprehensive investigation of the differences in BSG expression among human organs, cancer cells, cancer tissues, and normal tissues. Cox regression analysis and Kaplan–Meier curves were utilized to explore the prognosis factor of BSG in cancers. Correlation analyses were used to determine associations of BSG expression with tumor mutational burden, the immune microenvironment, etc. Gene set enrichment analysis was applied to explore the underlying mechanisms of BSG in cancers.

Results: Compared with normal tissues, BSG expression was high in 13 types of cancers (cholangiocarcinoma, etc.) and low in colon adenocarcinoma and rectum adenocarcinoma. BSG expression was related to the prognosis of eight cancers (e.g., invasive breast carcinoma) (p &lt; 0.05). The gene also demonstrated a pronounced effect in identifying 12 cancers (cholangiocarcinoma, etc.) from their control samples (AUC &gt;0.7). The BSG expression was associated with DNA methyltransferases, mismatch repair genes, immune infiltration levels, tumor mutational burden, microsatellite instability, neoantigen, and immune checkpoints, suggesting the potential of BSG as an exciting target for cancer treatment. BSG may play its role in several cancers by affecting several signaling pathways such as drug cytochrome metabolism P450 and JAK-STAT.

Conclusion:BSG may be a novel biomarker for treating and identifying multiple human cancers.

Robust Validation and Comprehensive Analysis of a Novel Signature Derived from Crucial Metabolic Pathways of Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is a malignant tumor with a dismal prognosis. PDAC have extensively reprogrammed metabolic characteristics influenced by interactions with normal cells, the effects of the tumor microenvironment and oncogene-mediated cell-autonomous pathways. In this study, we found that among all cancer hallmarks, metabolism played an important role in PDAC. Subsequently, a 16-gene prognostic signature was established with genes derived from crucial metabolic pathways, including glycolysis, bile acid metabolism, cholesterol homeostasis and xenobiotic metabolism (gbcx). The signature was used to distinguish overall survival in multiple cohorts from public datasets as well as a validation cohort followed up by us at Shanghai Cancer Center. Notably, the gbcx-related risk score (gbcxMRS) also accurately predicted poor PDAC subtypes, such as pure-basal-like and squamous types. At the same time, it also predicted PDAC recurrence. The gbcxMRS was also associated with immune cells, especially CD8 T cells, Treg cells. Furthermore, a high gbcxMRS may indicate high drug sensitivity to irinotecan and docetaxel and CTLA4 inhibitor immunotherapy. Taken together, these results indicate a robust and reproducible metabolic-related signature based on analysis of the overall pathogenesis of pancreatic cancer, which may have excellent prognostic and therapeutic implications for PDAC.

Metagenomic Analyses Reveal Distinct Gut Microbiota Signature for Predicting the Neoadjuvant Chemotherapy Responsiveness in Breast Cancer Patients

Background

Growing evidence supports the modulatory role of human gut microbiome on neoadjuvant chemotherapy (NAC) efficacy. However, the relationships among the gut microbiome, tumor-infiltrating lymphocytes (TILs), and NAC response for breast cancer (BC) patients remain unclear. We thus proposed this preliminary study to investigate the relationship between gut microbiome and BC patients’ responses to NAC treatment as well as underlying mechanisms.

Methods

Prior to receiving NAC, the fecal metagenome collected from 23 patients with invasive BC was analyzed. Patients were subsequently assigned to the NAC non-effectual group and the NAC effectual group based on their response to NAC. The peripheral T lymphocyte subset counts were examined by flow cytometry methods. CellMinor analysis was employed to explore the relationship between CD4 mRNA expression and the reaction of tumor cells to NAC drugs.

Results

The gut microbiomes of the NAC non-effectual group showed characteristics of low diversity with low abundances, distinct metagenomic composition with decreased butyrate-producing and indolepropionic acid-producing bacteria, and increased potential pathobionts compared with the NAC effectual group. The combination of Coprococcus, Dorea, and uncultured Ruminococcus sp. serves as signature bacteria for distinguishing NAC non-effectual group patients from the NAC effectual group. The absolute numbers of CD4⁺ and CD8⁺ TIL infiltration in tumors in the NAC non-effectual group were significantly lower than those in the effectual group. Similar findings were reported for the CD4⁺ T lymphocytes in the peripheral blood (p’s < 0.05). NAC effectual-related signature bacteria were proportional to these patients’ CD4⁺ T lymphocyte counts in peripheral blood and tumors (p’s < 0.05). CellMinor analysis showed that the CD4 mRNA expression level dramatically climbed with increased sensitivity of tumor cells to NAC drugs such as cyclophosphamide, cisplatin, and carboplatin (p’s < 0.05).

Conclusions

The composition of the gut microbial community differs between BC patients for whom NAC is effective to those that are treatment resistant. The modulation of the gut microbiota on host CD4⁺ T lymphocytes may be one critical mechanism underlying chemosensitivity and NAC pathologic response. Taken together, gut microbiota may serve as a potential biomarker for NAC response, which sheds light on novel intervention targets in the treatment of NAC non-effectual BC patients.

Comprehensive Analysis of the Prognosis and Drug Sensitivity of Differentiation-Related lncRNAs in Papillary Thyroid Cancer

Simple Summary

Merging evidence has indicated that dedifferentiation is the main concern associated with radioactive iodine (RAI) refractoriness in patients with papillary thyroid cancer (PTC), and the underlying mechanisms of PTC dedifferentiation remain unclear. This study systematically delineated the expression pattern, tumor immune microenvironment, drug sensitivity, and prognostic value of differentiation-related lncRNAs. It also demonstrated that DPH6-DT could be considered as a novel signature to indicate differentiation and promote TC progression via activating the PI3K-AKT signaling pathway.

Abstract

Dedifferentiation is the main concern associated with radioactive iodine (RAI) refractoriness in patients with papillary thyroid cancer (PTC), and the underlying mechanisms of PTC dedifferentiation remain unclear. The present work aimed to identify a useful signature to indicate dedifferentiation and further explore its role in prognosis and susceptibility to chemotherapy drugs. A total of five prognostic-related DR-lncRNAs were selected to establish a prognostic-predicting model, and corresponding risk scores were closely associated with the infiltration of immune cells and immune checkpoint blockade. Moreover, we built an integrated nomogram based on DR-lncRNAs and age that showed a strong ability to predict the 3- and 5-year overall survival. Interestingly, drug sensitivity analysis revealed that the low-risk group was more sensitive to Bendamustine and TAS-6417 than the high-risk group. In addition, knockdown of DR-lncRNAs (DPH6-DT) strongly promoted cell proliferation, invasion, and migration via PI3K-AKT signal pathway in vitro. Furthermore, DPH6-DT downregulation also increased the expression of vimentin and N-cadherin during epithelial-mesenchymal transition. This study firstly confirms that DR-lncRNAs play a vital role in the prognosis and immune cells infiltration in patients with PTC, as well as a predictor of the drugs’ chemosensitivity. Based on our results, DR-lncRNAs can serve as a promising prognostic biomarkers and treatment targets.

Schlafens Can Put Viruses to Sleep

The Schlafen gene family encodes for proteins involved in various biological tasks, including cell proliferation, differentiation, and T cell development. Schlafens were initially discovered in mice, and have been studied in the context of cancer biology, as well as their role in protecting cells during viral infection. This protein family provides antiviral barriers via direct and indirect effects on virus infection. Schlafens can inhibit the replication of viruses with both RNA and DNA genomes. In this review, we summarize the cellular functions and the emerging relationship between Schlafens and innate immunity. We also discuss the functions and distinctions of this emerging family of proteins as host restriction factors against viral infection. Further research into Schlafen protein function will provide insight into their mechanisms that contribute to intrinsic and innate host immunity.

Tribbles Gene Expression Profiles in Colorectal Cancer

Colorectal cancer (CRC) is the third most common cancer and the second leading cause of death due to cancer in the world. Therefore, the identification of novel druggable targets is urgently needed. Tribbles proteins belong to a pseudokinase family, previously recognized in CRC as oncogenes and potential therapeutic targets. Here, we analyzed the expression of TRIB1, TRIB2, and TRIB3 simultaneously in 33 data sets from CRC based on available GEO profiles. We show that all three Tribbles genes are overrepresented in CRC cell lines and primary tumors, though depending on specific features of the CRC samples. Higher expression of TRIB2 in the tumor microenvironment and TRIB3 overexpression in an early stage of CRC development, unveil a potential and unexplored role for these proteins in the context of CRC. Differential Tribbles expression was also explored in diverse cellular experimental conditions where either genetic or pharmacological approaches were used, providing novel hints for future research. This comprehensive bioinformatic analysis provides new insights into Tribbles gene expression and transcript regulation in CRC.

Tribbles Gene Expression Profiles in Colorectal Cancer

Colorectal cancer (CRC) is the third most common cancer and the second leading cause of death due to cancer in the world. Therefore, the identification of novel druggable targets is urgently needed. Tribbles proteins belong to a pseudokinase family, previously recognized in CRC as oncogenes and potential therapeutic targets. Here, we analyzed the expression of TRIB1, TRIB2, and TRIB3 simultaneously in 33 data sets from CRC based on available GEO profiles. We show that all three Tribbles genes are overrepresented in CRC cell lines and primary tumors, though depending on specific features of the CRC samples. Higher expression of TRIB2 in the tumor microenvironment and TRIB3 overexpression in an early stage of CRC development, unveil a potential and unexplored role for these proteins in the context of CRC. Differential Tribbles expression was also explored in diverse cellular experimental conditions where either genetic or pharmacological approaches were used, providing novel hints for future research. This comprehensive bioinformatic analysis provides new insights into Tribbles gene expression and transcript regulation in CRC.

Schlafen 11 expression in human acute leukemia cells with gain-of-function mutations in the interferon-JAK signaling pathway

Schlafen11 (SLFN11) is referred to as interferon (IFN)-inducible. Based on cancer genomic databases, we identified human acute myeloid and lymphoblastic leukemia cells with gain-of-function mutations in the Janus kinase (JAK) family as exhibiting high SLFN11 expression. In these cells, the clinical JAK inhibitors cerdulatinib, ruxolitinib, and tofacitinib reduced SLFN11 expression, but IFN did not further induce SLFN11 despite phosphorylated STAT1. We provide evidence that suppression of SLFN11 by JAK inhibitors is caused by inactivation of the non-canonical IFN pathway controlled by AKT and ERK. Accordingly, the AKT and ERK inhibitors MK-2206 and SCH77284 suppressed SLFN11 expression. Both also suppressed the E26 transformation-specific (ETS)-family genes ETS-1 and FLI-1 that act as transcription factors for SLFN11. Moreover, SLFN11 expression was inhibited by the ETS inhibitor TK216. Our study reveals that SLFN11 expression is regulated via the JAK, AKT and ERK, and ETS axis. Pharmacological suppression of SLFN11 warrants future studies.

Combination of tumor mutation burden and immune infiltrates for the prognosis of lung adenocarcinoma

BACKGROUND

Tumor mutation burden (TMB) levels are associated with immune infiltrates in the tumor microenvironment and can modulate the responses to immune checkpoint inhibitors (ICIs) in lung adenocarcinoma (LUAD) patients. This study aimed at exploring the potential role of a signature of genes associated with TMB and immune infiltrates and the relevant nomogram in the prognosis of LUAD.

MATERIALS AND METHODS

The TMB levels in LUAD patients in the Cancer Genome Atlas (TCGA) were analyzed. The differentially expressed genes (DEGs) between the higher- and lower-TMB subgroups were functionally analyzed. The immune-related DEGs and their relationship with immune infiltrates in the tumor environment between two subgroups were analyzed. Nine immune-related DEGs were used to generate a TMB-related immune signature. The sensitivity to immunotherapy in TCGA-LUAD patients was analyzed by immunophenotypic scores (IPS). Subsequently, a nomogram was generated using tumor-related parameters and the signature score. The signature or nomogram values in predicting overall survival (OS) were evaluated and validated in LUAD patients in the GSE30219 and GSE72094.

RESULT

There were 468 DEGs between the higher and lower-TMB subgroups of LUAD patients. The TMB levels were associated positively with the number of immune infiltrates in LUAD patients. Nine DEGs were related to immune infiltrates in the tumor environment. The higher signature scores (high-risk) were associated with poor prognosis of LUAD in the TCGA, which was validated in LUAD patients of the GSE30219 and GSE72094 datasets. Interestingly, the patients in the high-risk group had higher PD-L1 expression in their tumors and the risk scores in LUAD patients. The IPS of LUAD patients in the high-risk group were predicted to benefit from immunotherapy. Finally, the nomogram had high AUC values in predicting the OS of LUAD patients.

CONCLUSION

The TMB-related immune signature or nomogram is valuable for the prognosis of LUAD patients and evaluating their responses to ICIs. These relevant genes may participate into the pathogenesis, ICIs, and drug resistance of LUAD.

R-Loop-Mediated ssDNA Breaks Accumulate Following Short-Term Exposure to the HDAC Inhibitor Romidepsin

Histone deacetylase inhibitors (HDACi) induce hyperacetylation of histones by blocking HDAC catalytic sites. Despite regulatory approvals in hematological malignancies, limited solid tumor clinical activity has constrained their potential, arguing for better understanding of mechanisms of action (MOA). Multiple activities of HDACis have been demonstrated, dependent on cell context, beyond the canonical induction of gene expression. Here, using a clinically relevant exposure duration, we established DNA damage as the dominant signature using the NCI-60 cell line database and then focused on the mechanism by which hyperacetylation induces DNA damage. We identified accumulation of DNA-RNA hybrids (R-loops) following romidepsin-induced histone hyperacetylation, with single-stranded DNA (ssDNA) breaks detected by single-cell electrophoresis. Our data suggest that transcription-coupled base excision repair (BER) is involved in resolving ssDNA breaks that, when overwhelmed, evolve to lethal dsDNA breaks. We show that inhibition of BER proteins such as PARP will increase dsDNA breaks in this context. These studies establish accumulation of R-loops as a consequence of romidepsin-mediated histone hyperacetylation. We believe that the insights provided will inform design of more effective combination therapy with HDACis for treatment of solid tumors. IMPLICATIONS: Key HDAC inhibitor mechanisms of action remain unknown; we identify accumulation of DNA-RNA hybrids (R-loops) due to chromatin hyperacetylation that provokes single-stranded DNA damage as a first step toward cell death.

Identification of biological targets through the correlation between cell line chemosensitivity and protein expression pattern

Matching biological data sequences is one of the most interesting ways to discover new bioactive compounds. In particular, matching cell chemosensitivity with a protein expression profile can be a useful approach to predict the activity of compounds against definite biological targets. In this review, we discuss this correlation. First, we analyze case studies in which some known drugs, acting on known targets, show a good correlation between their antiproliferative activities and protein expression when a large panel of tumor cells is considered. Then, we highlight how the application of in silico methods based on the correlation between cell line chemosensitivity and gene/protein expression patterns might be a quick, cheap, and interesting approach to predict the biological activity of investigated molecules.

Bioinformatic analysis linking genomic defects to chemosensitivity and mechanism of action

A joint analysis of the NCI60 small molecule screening data, their genetically defective genes, and mechanisms of action (MOA) of FDA approved cancer drugs screened in the NCI60 is proposed for identifying links between chemosensitivity, genomic defects and MOA. Self-Organizing-Maps (SOMs) are used to organize the chemosensitivity data. Student’s t-tests are used to identify SOM clusters with enhanced chemosensitivity for tumor cell lines with versus without genetically defective genes. Fisher’s exact and chi-square tests are used to reveal instances where defective gene to chemosensitivity associations have enriched MOAs. The results of this analysis find a relatively small set of defective genes, inclusive of ABL1, AXL, BRAF, CDC25A, CDKN2A, IGF1R, KRAS, MECOM, MMP1, MYC, NOTCH1, NRAS, PIK3CG, PTK2, RPTOR, SPTBN1, STAT2, TNKS and ZHX2, as possible candidates for roles in chemosensitivity for compound MOAs that target primarily, but not exclusively, kinases, nucleic acid synthesis, protein synthesis, apoptosis and tubulin. These results find exploitable instances of enhanced chemosensitivity of compound MOA’s for selected defective genes. Collectively these findings will advance the interpretation of pre-clinical screening data as well as contribute towards the goals of cancer drug discovery, development decision making, and explanation of drug mechanisms.

Chromatin Remodeling and Immediate Early Gene Activation by SLFN11 in Response to Replication Stress

Schlafen 11 (SLFN11) was recently discovered as a cellular restriction factor against replication stress. Here, we show that SLFN11 increases chromatin accessibility genome wide, prominently at active promoters in response to replication stress induced by the checkpoint kinase 1 (CHK1) inhibitor prexasertib or the topoisomerase I (TOP1) inhibitor camptothecin. Concomitantly, SLFN11 selectively activates cellular stress response pathways by inducing the transcription of the immediate early genes (IEGs), including JUN, FOS, EGR1, NFKB2, and ATF3, together with the cell cycle arrest genes CDKN1A (p21^WAF1) and GADD45. Both chromatin remodeling and IEG activation require the putative ATPase and helicase activity of SLFN11, whereas canonical extrinsic IEG activation is SLFN11 independent. SLFN11-dependent IEG activation by camptothecin is also observed across 55 non-isogenic NCI-60 cell lines. We conclude that SLFN11 acts as a global regulator of chromatin structure and an intrinsic IEG activator with the potential to engage the innate immune activation in response to replicative stress.

A pan-cancer analysis of the HER family gene and their association with prognosis, tumor microenvironment, and therapeutic targets

AIMS

The human epidermal growth factor receptor (HER) family gene is involved in a wide range of biological functions in human cancers. Nevertheless, there is little research that comprehensively analysis the correlation between HER family members and prognosis, tumor microenvironment (TME) in different cancers.

MATERIALS AND METHODS

Based on updated public databases and integrated several bioinformatics analysis methods, we evaluated expression level, prognostic values of HER family gene and explore the association between expression of HER family gene and TME, Stemness score, immune subtype, drug sensitivity in pan-cancer.

KEY FINDINGS

EGFR, ERBB2, ERBB3, and ERBB4 were higher expressed in four cancers, five cancers, ten cancers, and two cancers, respectively. HER family gene expression is related to the prognosis in several cancers from TCGA and has a significant correlation with stromal and immune scores in pan-cancer also has a significant correlation with RNA stemness score and DNA stemness score in pan-cancer. Expression level of HER family gene is associated with immune subtype in head and neck squamous cell carcinoma and kidney renal clear cell carcinoma. EGFR expression was negatively associated with drug sensitivity of Pipamperone, Tamoxifen, Bafetinib and positively related to drug sensitivity of Dasatinib and Staurosporine. ERBB2 expression was negatively related to drug sensitivity of Ifosfamide, Imexon, and Oxaliplatin. ERBB4 expression was positively related to drug sensitivity of E-7820.

SIGNIFICANCE

These findings may elucidate the roles played by HER family gene in cancer progression and providing insights for further investigation of the HER family gene as potential targets in pan-cancer.

Aberrant methylation modifications reflect specific drug responses in small cell lung cancer

In the study, Methylated DNA immunoprecipitation sequencing, RNA sequencing, and whole-exome sequencing were employed to clinical small cell lung cancer (SCLC) patients. Then, we verified the therapeutic predictive effects of differentially methylated genes (DMGs) in 62 SCLC cell lines. Of 4552 DMGs between chemo-sensitive and chemo-insensitive group, coding genes constituted the largest percentage (85.08%), followed by lncRNAs (10.52%) and miRNAs (3.56%). Both two groups demonstrated two methylation peaks near transcription start site and transcription end site. Two lncRNA-miRNA-mRNA networks suggested the extensive genome connection between chemotherapy efficacy-related non-coding RNAs (ncRNAs) and mRNAs. Combing miRNAs and lncRNAs could effectively predict chemotherapy response in SCLC. In addition, we also verified the predictive values of mutated genes in SCLC cell lines. This study was the first to evaluate multiple drugs efficacy-related ncRNAs and mRNAs which were modified by methylation in SCLC. DMGs identified in our research might serve as promising therapeutic targets to reverse drugs-insensitivity by complex lncRNA-miRNA-mRNA mechanisms in SCLC.

Jinfukang regulates integrin/Src pathway and anoikis mediating circulating lung cancer cells migration

ETHNOPHARMACOLOGICAL RELEVANCE

Metastasis is the main cause of death in lung cancer patients. Circulating tumor cells (CTCs) may be an important target of metastasis intervention. Previous studies have shown that Jinfukang could prevent the recurrence and metastasis of lung cancer, and we have established a circulating lung tumor cell line CTC-TJH-01. However, whether Jinfukang inhibition of lung cancer metastasis is related to CTCs is still unknown.

AIM OF THE STUDY

To further explore the mechanism of Jinfukang in anti-metastasis of lung cancer from the perspective of intervention of CTCs.

MATERIALS AND METHODS

CTC-TJH-01 and H1975 cells were treated with Jinfukang. Cell viability was detected by CCK8, and the cell apoptosis was detected by flow cytometry. Transwell was used to detected cell migration and invasion. Cell anoikis was detected by anoikis detection kit. Protein expression was analysis by Western blot.

RESULTS

Jinfukang could inhibit the proliferation, migration and invasion of CTC-TJH-01 and H1975 cells. Besides, Jinfukang could also induce anoikis in CTC-TJH-01 and H1975 cells. Analysis of the mRNA expression profile showed ECM-receptor interaction and focal adhesion were regulated by Jinfukang. Moreover, it was also find that Jinfukang significantly inhibited integrin/Src pathway in CTC-TJH-01 and H1975 cells. When suppress the expression of integrin with ATN-161, it could promote Jinfukang to inhibit migration and induce anoikis in CTC-TJH-01 and H1975 cells.

CONCLUSIONS

Our results indicate that the migration and invasion of CTCs are inhibited by Jinfukang, and the mechanism may involve the suppression of integrin/Src axis to induce anoikis. These data suggest that Jinfukang exerts anti-metastatic effects in lung cancer may through anoikis.

Transketolase regulates sensitivity to APR-246 in p53-null cells independently of oxidative stress modulation

The prevalence and dire implications of mutations in the tumour suppressor, p53, highlight its appeal as a chemotherapeutic target. We recently showed that impairing cellular antioxidant systems via inhibition of SLC7A11, a component of the system x_c^- cystine-glutamate antiporter, enhances sensitivity to mutant-p53 targeted therapy, APR-246. We investigated whether this synergy extends to other genes, such as those encoding enzymes of the pentose phosphate pathway (PPP). TKT, one of the major enzymes of the PPP, is allegedly regulated by NRF2, which is in turn impaired by accumulated mutant-p53 protein. Therefore, we investigated the relationship between mutant-p53, TKT and sensitivity to APR-246. We found that mutant-p53 does not alter expression of TKT, nor is TKT modulated directly by NRF2, suggesting a more complex mechanism at play. Furthermore, we found that in p53null cells, knockdown of TKT increased sensitivity to APR-246, whilst TKT overexpression conferred resistance to the drug. However, neither permutation elicited any effect on cells overexpressing mutant-p53 protein, despite mediating oxidative stress levels in a similar fashion to that in p53-null cells. In sum, this study has unveiled TKT expression as a determinant for sensitivity to APR-246 in p53-null cells.

A novel prognostic mRNA/miRNA signature for esophageal cancer and its immune landscape in cancer progression

Mounting evidence shows that MicroRNAs (miRNAs) and their target genes are aberrantly expressed in many cancers and are linked to tumor occurrence and progression, especially in esophageal cancer (EC). This study purposed to explore new biomarkers related to the prognosis of EC and to uncover their potential mechanisms in promoting tumor progression. We identified 162 differentially expressed miRNAs and 4555 differentially expressed mRNAs in EC. Then, a risk model involving three miRNAs (miR‐4521, miR‐3682‐3p, and miR‐1269a) was designed to predict prognosis in EC patients. Furthermore, 7 target genes (Rho GTPase‐activating protein 24, Chromobox 3, Contactin‐associated protein 2, ELOVL fatty acid elongase 5, LIF receptor subunit alpha, transmembrane protein 44, and transmembrane protein 67) were selected for Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses to reveal their potential mechanisms in promoting EC progression. After a series of correlation analyses, miRNA target genes were found to be significantly positively or negatively associated with immune infiltration, tumor microenvironment, cancer stemness properties, and tumor mutation burden at different degrees in EC. To further elucidate the role of miRNA signature in cancer progression, we performed a pan‐cancer analysis to determine whether these genes exert similar effects on other tumors. Interestingly, the miRNA target genes altered expression on tumor immunity; however, pan‐cancer progression was the same as that of EC. Thus, we explored the immune landscape of the miRNA signature and its target genes in EC and pan‐cancer. These findings demonstrated the versatility and effectiveness of our model in various cancers and provided a new direction for cancer management.

CellMiner Cross-Database (CellMinerCDB) version 1.2: Exploration of patient-derived cancer cell line pharmacogenomics

CellMiner Cross-Database (CellMinerCDB, discover.nci.nih.gov/cellminercdb) allows integration and analysis of molecular and pharmacological data within and across cancer cell line datasets from the National Cancer Institute (NCI), Broad Institute, Sanger/MGH and MD Anderson Cancer Center (MDACC). We present CellMinerCDB 1.2 with updates to datasets from NCI-60, Broad Cancer Cell Line Encyclopedia and Sanger/MGH, and the addition of new datasets, including NCI-ALMANAC drug combination, MDACC Cell Line Project proteomic, NCI-SCLC DNA copy number and methylation data, and Broad methylation, genetic dependency and metabolomic datasets. CellMinerCDB (v1.2) includes several improvements over the previously published version: (i) new and updated datasets; (ii) support for pattern comparisons and multivariate analyses across data sources; (iii) updated annotations with drug mechanism of action information and biologically relevant multigene signatures; (iv) analysis speedups via caching; (v) a new dataset download feature; (vi) improved visualization of subsets of multiple tissue types; (vii) breakdown of univariate associations by tissue type; and (viii) enhanced help information. The curation and common annotations (e.g. tissues of origin and identifiers) provided here across pharmacogenomic datasets increase the utility of the individual datasets to address multiple researcher question types, including data reproducibility, biomarker discovery and multivariate analysis of drug activity.

Integrative analysis of the common genetic characteristics in ovarian cancer stem cells sorted by multiple approaches

BACKGROUND

Ovarian cancer is the second fatal malignancy of the female reproductive system. Based on the cancer stem cell (CSC) theory, its poor prognosis of ovarian cancer attributed to tumor recurrence caused by CSCs. A variety of cell surface-specific markers have been employed to identify ovarian cancer stem cells (OCSCs). In this study, we attempted to explore the common feature in ovarian cancer stem cells sorted by multiple approaches.

METHODS

We collected the gene expression profiles of OCSCs were from 5 public cohorts and employed R software and Bioconductor packages to establish differently expressed genes (DEGs) between OCSCs and parental cells. We extracted the integrated DEGs by protein-protein interaction (PPI) network construction and explored potential treatment by the Cellminer database.

RESULTS

We identified and integrated the DEGs of OCSCs sorted by multiple isolation approaches. Besides, we identified OCSCs share characteristics in the lipid metabolism and extracellular matrix changes. Moreover, we obtained 16 co-expressed core genes, such as FOXQ1, MMP7, AQP5, RBM47, ETV4, NPW, SUSD2, SFRP2, IDO1, ANPEP, CXCR4, SCNN1A, SPP1 and IFI27 (upregulated) and SERPINE1, DUSP1, CD40, and IL6 (downregulated). Through correlation analysis, we screened out ten potential drugs to target the core genes.

CONCLUSION

Based on the comprehensive analysis of the genomic datasets with different sorting methods of OCSCs, we figured out the common driving genes to regulating OCSC and obtained ten new potential therapies for eliminating ovarian cancer stem cells. Hence, the findings of our study might have potential clinical significance.

Mining Drug-Target Associations in Cancer: Analysis of Gene Expression and Drug Activity Correlations

Cancer is a complex disease affecting millions of people worldwide, with over a hundred clinically approved drugs available. In order to improve therapy, treatment, and response, it is essential to draw better maps of the targets of cancer drugs and possible side interactors. This study presents a large-scale screening method to find associations of cancer drugs with human genes. The analysis is focused on the current collection of Food and Drug Administration (FDA)-approved drugs (which includes about one hundred chemicals). The approach integrates global gene-expression transcriptomic profiles with drug-activity profiles of a set of 60 human cell lines obtained for a collection of chemical compounds (small bioactive molecules). Using a standardized expression for each gene versus standardized activity for each drug, Pearson and Spearman correlations were calculated for all possible pairwise gene-drug combinations. These correlations were used to build a global bipartite network that includes 1007 gene-drug significant associations. The data are integrated into an open web-tool called GEDA (Gene Expression and Drug Activity) which includes a relational view of cancer drugs and genes, disclosing the putative indirect interactions found for FDA-approved drugs as well as the known targets of these drugs. The results also provide insight into the complex action of pharmaceuticals, presenting an alternative view to address predicted pleiotropic effects of the drugs.

Sensitivity of Mesothelioma Cells to PARP Inhibitors Is Not Dependent on BAP1 but Is Enhanced by Temozolomide in Cells With High-Schlafen 11 and Low-O6-methylguanine-DNA Methyltransferase Expression

INTRODUCTION

BRCA1-associated protein-1 (BAP1), a nuclear deubiquitinase thought to be involved in DNA double-strand break repair, is frequently mutated in mesothelioma. Because poly(adenosine diphosphate-ribose) polymerase inhibitors (PARPIs) induce synthetic lethality in BRCA1/2 mutant cancers, we evaluated whether BAP1 inactivating mutations confer sensitivity to PARPIs in mesothelioma and if combination therapy with temozolomide (TMZ) would be beneficial.

METHODS

A total of 10 patient-derived mesothelioma cell lines were generated and characterized for BAP1 mutation status, protein expression, nuclear localization, and sensitivity to the PARPIs, olaparib, and talazoparib, alone or in combination with TMZ. BAP1 deubiquitinase (DUB) activity was evaluated by ubiquitin with 7-amido-4-methylcoumarin assay. BAP1 knockout mesothelioma cell lines were generated by CRISPR-Cas9. Because Schlafen 11 (SLFN11) and O⁶-methylguanine-DNA methyltransferase also drive response to TMZ and PARPIs, we tested their expression and relationship with drug response.

RESULTS

BAP1 mutations or copy-number alterations, or both were present in all 10 cell lines. Nonetheless, four cell lines exhibited intact DUB activity and two had nuclear BAP1 localization. Half maximal-inhibitory concentrations of olaparib and talazoparib ranged from 4.8 μM to greater than 50 μM and 0.039 μM to greater than 5 μM, respectively, classifying them into sensitive (two) or resistant (seven) cells, independent of their BAP1 status. Cell lines with BAP1 knockout resulted in the loss of BAP1 DUB activity but did not increase sensitivity to talazoparib. Response to PARPI tended to be associated with high SLFN11 expression, and combination with temozolomide increased sensitivity of cells with low or no MGMT expression.

CONCLUSIONS

BAP1 status does not determine sensitivity to PARPIs in patient-derived mesothelioma cell lines. Combination of PARPI with TMZ may be beneficial for patients whose tumors have high SLFN11 and low or no MGMT expression.

The antitumor activity of CYB-L10, a human topoisomerase IB catalytic inhibitor

DNA topoisomerase IB (TOP1) is a validated target for discovery and development of antitumor agents. Four TOP1 poisons are clinically used for tumor treatment now. In spite of their effectiveness in solid tumors, these camptothecin (CPT) poisons suffer from many shortcomings. Therefore, many investigations have focused on the discoveries of non-CPT poisons and catalytic inhibitors. Herein, we systematically study the antitumor activity of CYB-L10, a novel indolizinoquinolinedione TOP1 catalytic inhibitor discovered in our laboratory. The results indicated that CYB-L10 mainly acts on TOP1 in cancer cells and is not a substrate of the P-glycoprotein. In addition, CYB-L10 can induce apoptosis of HCT116 cells, shows high cytotoxicity against 60 human clinical cancer cell lines (NCI60) with the mean-graph midpoint for growth inhibition of all cancer cell lines of 0.050 µM concentration and obvious antitumor efficiency in vivo in the HCT116 xenograft model.

A novel assay to screen siRNA libraries identifies protein kinases required for chromosome transmission

One of the hallmarks of cancer is chromosome instability (CIN), which leads to aneuploidy, translocations, and other chromosome aberrations. However, in the vast majority of human tumors the molecular basis of CIN remains unknown, partly because not all genes controlling chromosome transmission have yet been identified. To address this question, we developed an experimental high-throughput imaging (HTI) siRNA assay that allows the identification of novel CIN genes. Our method uses a human artificial chromosome (HAC) expressing the GFP transgene. When this assay was applied to screen an siRNA library of protein kinases, we identified PINK1, TRIO, IRAK1, PNCK, and TAOK1 as potential novel genes whose knockdown induces various mitotic abnormalities and results in chromosome loss. The HAC-based assay can be applied for screening different siRNA libraries (cell cycle regulation, DNA damage response, epigenetics, and transcription factors) to identify additional genes involved in CIN. Identification of the complete spectrum of CIN genes will reveal new insights into mechanisms of chromosome segregation and may expedite the development of novel therapeutic strategies to target the CIN phenotype in cancer cells.

Tyrosyl-DNA Phosphodiesterase 1 and Topoisomerase I Activities as Predictive Indicators for Glioblastoma Susceptibility to Genotoxic Agents

Glioblastoma (GBM) patients have an estimated survival of ~15 months with treatment, and the standard of care only modestly enhances patient survival. Identifying biomarkers representing vulnerabilities may allow for the selection of efficacious chemotherapy options to address personalized variations in GBM tumors. Irinotecan targets topoisomerase I (TOP1) by forming a ternary DNA-TOP1 cleavage complex (TOP1cc), inducing apoptosis. Tyrosyl-DNA phosphodiesterase 1 (TDP1) is a crucial repair enzyme that may reduce the effectiveness of irinotecan. We treated GBM cell lines with increasing concentrations of irinotecan and compared the IC₅₀ values. We found that the TDP1/TOP1 activity ratio had the strongest correlation (Pearson correlation coefficient R = 0.972, based on the average from three sets of experiments) with IC₅₀ values following irinotecan treatment. Increasing the TDP1/TOP1 activity ratio by the ectopic expression of wild-type TDP1 increased in irinotecan IC₅₀, while the expression of the TDP1 catalytic-null mutant did not alter the susceptibility to irinotecan. The TDP1/TOP1 activity ratio may be a new predictive indicator for GBM vulnerability to irinotecan, allowing for the selection of individual patients for irinotecan treatment based on risk-benefit. Moreover, TDP1 inhibitors may be a novel combination treatment with irinotecan to improve GBM patient responsiveness to genotoxic chemotherapies.

Schlafen 11 (SLFN11), a restriction factor for replicative stress induced by DNA-targeting anti-cancer therapies

Schlafen 11 (SLFN11) sensitizes cells to a broad range of anti-cancer drugs including platinum derivatives (cisplatin and carboplatin), inhibitors of topoisomerases (irinotecan, topotecan, doxorubicin, daunorubicin, mitoxantrone and etoposide), DNA synthesis inhibitors (gemcitabine, cytarabine, hydroxyurea and nucleoside analogues), and poly(ADPribose) polymerase (PARP) inhibitors (olaparib, rucaparib, niraparib and talazoparib). In spite of their different primary mechanisms of action, all these drugs damage DNA during S-phase, activate the intra-S-phase checkpoint and induce replication fork slowing and stalling with single-stranded DNA segments coated with replication protein A. Such situation with abnormal replication forks is known as replication stress. SLFN11 irreversibly blocks replication in cells under replication stress, explaining why SLFN11-positive cells are markedly more efficiently killed by DNA-targeting drugs than SLFN11-negative cells. SLFN11 is inactivated in ~50% of cancer cell lines and in a large fraction of tumors, and is linked with the native immune, interferon and T-cells responses, implying the translational relevance of measuring SLFN11 expression as a predictive biomarker of response and resistance in patients. SLFN11 is also a plausible epigenetic target for reactivation by inhibitors of histone deacetylases (HDAC), DNA methyltransferases (DNMT) and EZH2 histone methyltransferase and for combination of these epigenetic inhibitors with DNA-targeting drugs in cells lacking SLFN11 expression. In addition, resistance due to lack of SLFN11 expression in tumors is a potential indication for cell-cycle checkpoint inhibitors in combination with DNA-targeting therapies.

GDA, a web-based tool for Genomics and Drugs integrated analysis

Several major screenings of genetic profiling and drug testing in cancer cell lines proved that the integration of genomic portraits and compound activities is effective in discovering new genetic markers of drug sensitivity and clinically relevant anticancer compounds. Despite most genetic and drug response data are publicly available, the availability of user-friendly tools for their integrative analysis remains limited, thus hampering an effective exploitation of this information. Here, we present GDA, a web-based tool for Genomics and Drugs integrated Analysis that combines drug response data for >50 800 compounds with mutations and gene expression profiles across 73 cancer cell lines. Genomic and pharmacological data are integrated through a modular architecture that allows users to identify compounds active towards cancer cell lines bearing a specific genomic background and, conversely, the mutational or transcriptional status of cells responding or not-responding to a specific compound. Results are presented through intuitive graphical representations and supplemented with information obtained from public repositories. As both personalized targeted therapies and drug-repurposing are gaining increasing attention, GDA represents a resource to formulate hypotheses on the interplay between genomic traits and drug response in cancer. GDA is freely available at http://gda.unimore.it/.

Synthesis and biological evaluation of 5-aminoethyl benzophenanthridone derivatives as DNA topoisomerase IB inhibitors

DNA topoisomerase IB (TOP1) regulates DNA topological structure in many cellular metabolic processes and is a validated target for development of antitumor agents. Our previous study revealed that the benzophenanthridone scaffold is a novel chemotype for the discovery of TOP1 inhibitors. In this work, a series of novel 5-aminoethyl substituted benzophenanthridone derivatives have been synthesized and evaluated for TOP1 inhibition and cytotoxicity. Compound 12 exhibits the most potent TOP1 inhibition (+++) and cytotoxicity in human cancer cell lines with GI₅₀ values at nanomolar concentration range. 12 induces the cellular TOP1cc formation and DNA damage, resulting in HCT116 cell apoptosis. The pharmacokinetics, acute toxicity and antitumor efficiency in vivo of 12 were also studied.