Functional linkage of gene fusions to cancer cell fitness assessed by pharmacological and CRISPR-Cas9 screening

Novel WRN Helicase Inhibitors Selectively Target Microsatellite-Unstable Cancer Cells

Microsatellite-unstable (MSI) cancers require WRN helicase to resolve replication stress due to expanded DNA (TA)n dinucleotide repeats. WRN is a promising synthetic lethal target for MSI tumors, and WRN inhibitors are in development. In this study, we used CRISPR-Cas9 base editing to map WRN residues critical for MSI cells, validating the helicase domain as the primary drug target. Fragment-based screening led to the development of potent and highly selective WRN helicase covalent inhibitors. These compounds selectively suppressed MSI model growth in vitro and in vivo by mimicking WRN loss, inducing DNA double-strand breaks at expanded TA repeats and DNA damage. Assessment of biomarkers in preclinical models linked TA-repeat expansions and mismatch repair alterations to compound activity. Efficacy was confirmed in immunotherapy-resistant organoids and patient-derived xenograft models. The discovery of potent, selective covalent WRN inhibitors provides proof of concept for synthetic lethal targeting of WRN in MSI cancer and tools to dissect WRN biology. Significance: We report the discovery and characterization of potent, selective WRN helicase inhibitors for MSI cancer treatment, with biomarker analysis and evaluation of efficacy in vivo and in immunotherapy-refractory preclinical models. These findings pave the way to translate WRN inhibition into MSI cancer therapies and provide tools to investigate WRN biology. See related commentary by Wainberg, p. 1369.

Mechanism of Action of KL-50, a Candidate Imidazotetrazine for the Treatment of Drug-Resistant Brain Cancers

Aberrant DNA repair is a hallmark of cancer, and many tumors display reduced DNA repair capacities that sensitize them to genotoxins. Here, we demonstrate that the differential DNA repair capacities of healthy and transformed tissue may be exploited to obtain highly selective chemotherapies. We show that the novel N3-(2-fluoroethyl)imidazotetrazine "KL-50" is a selective toxin toward tumors that lack the DNA repair protein O6-methylguanine-DNA-methyltransferase (MGMT), which reverses the formation of O6-alkylguanine lesions. We establish that KL-50 generates DNA interstrand cross-links (ICLs) by a multistep process comprising DNA alkylation to generate an O6-(2-fluoroethyl)guanine (O6FEtG) lesion, slow unimolecular displacement of fluoride to form an N1,O6-ethanoguanine (N1,O6EtG) intermediate, and ring-opening by the adjacent cytidine. The slow rate of N1,O6EtG formation allows healthy cells expressing MGMT to reverse the initial O6FEtG lesion before it evolves to N1,O6EtG, thereby suppressing the formation of toxic DNA-MGMT cross-links and reducing the amount of DNA ICLs generated in healthy cells. In contrast, O6-(2-chloroethyl)guanine lesions produced by agents such as lomustine and the N3-(2-chloroethyl)imidazotetrazine mitozolomide rapidly evolve to N1,O6EtG, resulting in the formation of DNA-MGMT cross-links and DNA ICLs in healthy tissue. These studies suggest that careful consideration of the rates of chemical DNA modification and biochemical DNA repair may lead to the identification of other tumor-specific genotoxic agents.

Crosstalk between CAFs and tumour cells in head and neck cancer

Head and neck squamous cell carcinomas (HNSCCs) are amongst the most aggressive, complex, and heterogeneous malignancies. The standard of care treatments for HNC patients include surgery, radiotherapy, chemotherapy, or their combination. However, around 50% do not benefit while suffering severe toxic side effects, costing the individuals and society. Decades have been spent to improve HNSCC treatment outcomes with only limited success. Much of the research in HNSCC treatment has focused on understanding the genetics of the HNSCC malignant cells, but it has become clear that tumour microenvironment (TME) plays an important role in the progression as well as treatment response in HNSCC. Understanding the crosstalk between cancer cells and TME is crucial for inhibiting progression and treatment resistance. Cancer-associated fibroblasts (CAFs), the predominant component of stroma in HNSCC, serve as the primary source of extra-cellular matrix (ECM) and various pro-tumoral composites in TME. The activation of CAFs in HNSCC is primarily driven by cancer cell-secreted molecules, which in turn induce phenotypic changes, elevated secretive status, and altered ECM production profile. Concurrently, CAFs play a pivotal role in modulating the cell cycle, stemness, epithelial-mesenchymal transition (EMT), and resistance to targeted and chemoradiotherapy in HNSCC cells. This modulation occurs through interactions with secreted molecules or direct contact with the ECM or CAF. Co-culture and 3D models of tumour cells and other TME cell types allows to mimic the HNSCC tumour milieu and enable modulating tumour hypoxia and reprograming cancer stem cells (CSC). This review aims to provide an update on the development of HNSCC tumour models comprising CAFs to obtain better understanding of the interaction between CAFs and tumour cells, and for providing preclinical testing platforms of current and combination with emerging therapeutics.

Computational repurposing of oncology drugs through off-target drug binding interactions from pharmacological databases

PURPOSE

Systematic repurposing of approved medicines for another indication may accelerate drug development in oncology. We present a strategy combining biomarker testing with drug repurposing to identify new treatments for patients with advanced cancer.

METHODS

Tumours were sequenced with the Illumina TruSight Oncology 500 (TSO-500) platform or the FoundationOne CDx panel. Mutations were screened by two medical oncologists and pathogenic mutations were categorised referencing literature. Variants of unknown significance were classified as potentially pathogenic using plausible mechanisms and computational prediction of pathogenicity. Gain of function (GOF) mutations were evaluated through repurposing databases Probe Miner (PM), Broad Institute Drug Repurposing Hub (Broad Institute DRH) and TOPOGRAPH. GOF mutations were repurposing events if identified in PM, not indexed in TOPOGRAPH and excluding mutations with a known Food and Drug Administration (FDA)-approved biomarker. The computational repurposing approach was validated by evaluating its ability to identify FDA-approved biomarkers. The total repurposable genome was identified by evaluating all possible gene-FDA drug-approved combinations in the PM dataset.

RESULTS

The computational repurposing approach was accurate at identifying FDA therapies with known biomarkers (94%). Using next-generation sequencing molecular reports (n = 94), a meaningful percentage of patients (14%) could have an off-label therapeutic identified. The frequency of theoretical drug repurposing events in The Cancer Genome Atlas pan-cancer dataset was 73% of the samples in the cohort.

CONCLUSION

A computational drug repurposing approach may assist in identifying novel repurposing events in cancer patients with no access to standard therapies. Further validation is needed to confirm a precision oncology approach using drug repurposing.

Auranofin repurposing for lung and pancreatic cancer: low CA12 expression as a marker of sensitivity in patient-derived organoids, with potentiated efficacy by AKT inhibition

BACKGROUND

This study explores the repurposing of Auranofin (AF), an anti-rheumatic drug, for treating non-small cell lung cancer (NSCLC) adenocarcinoma and pancreatic ductal adenocarcinoma (PDAC). Drug repurposing in oncology offers a cost-effective and time-efficient approach to developing new cancer therapies. Our research focuses on evaluating AF's selective cytotoxicity against cancer cells, identifying RNAseq-based biomarkers to predict AF response, and finding the most effective co-therapeutic agents for combination with AF.

METHODS

Our investigation employed a comprehensive drug screening of AF in combination with eleven anticancer agents in cancerous PDAC and NSCLC patient-derived organoids (n = 7), and non-cancerous pulmonary organoids (n = 2). Additionally, we conducted RNA sequencing to identify potential biomarkers for AF sensitivity and experimented with various drug combinations to optimize AF's therapeutic efficacy.

RESULTS

The results revealed that AF demonstrates a preferential cytotoxic effect on NSCLC and PDAC cancer cells at clinically relevant concentrations below 1 µM, sparing normal epithelial cells. We identified Carbonic Anhydrase 12 (CA12) as a significant RNAseq-based biomarker, closely associated with the NF-κB survival signaling pathway, which is crucial in cancer cell response to oxidative stress. Our findings suggest that cancer cells with low CA12 expression are more susceptible to AF treatment. Furthermore, the combination of AF with the AKT inhibitor MK2206 was found to be particularly effective, exhibiting potent and selective cytotoxic synergy, especially in tumor organoid models classified as intermediate responders to AF, without adverse effects on healthy organoids.

CONCLUSION

Our research offers valuable insights into the use of AF for treating NSCLC and PDAC. It highlights AF's cancer cell selectivity, establishes CA12 as a predictive biomarker for AF sensitivity, and underscores the enhanced efficacy of AF when combined with MK2206 and other therapeutics. These findings pave the way for further exploration of AF in cancer treatment, particularly in identifying patient populations most likely to benefit from its use and in optimizing combination therapies for improved patient outcomes.

Investigating the mechanisms underlying resistance to chemoterapy and to CRISPR-Cas9 in cancer cell lines

Cancer is one of the major causes of death worldwide and the development of multidrug resistance (MDR) in cancer cells is the principal cause of chemotherapy failure. To gain insights into the specific mechanisms of MDR in cancer cell lines, we developed a novel method for the combined analysis of recently published datasets on drug sensitivity and CRISPR loss-of-function screens for the same set of cancer cell lines. For our analysis, we first selected cell lines that consistently exhibit drug resistance across several classes of compounds. We then identified putative resistance genes for each class of compound and used inferred gene regulatory networks (GRNs) to study possible mechanisms underlying the development of MDR in the identified cancer cell lines. We show that the same method of analysis can also be used to identify cell lines that consistently exhibit resistance to the gene knockout effect of the CRISPR-Cas9 technique and to study the possible underlying mechanisms. In the GRN associated to the drug resistant cell lines, we identify genes previously associated with resistance (UHMK1, RALYL, MGST3, USP9X, and ESRG), genes for which an indirect association can be identified (SPINK13, LINC00664, MRPL38, and EMILIN3), and genes that are found to be overexpressed in non-resistant cancer cell lines (MRPL38, EMILIN3 and RALYL). In the GRNs associated to the CRISPR-Cas9 resistance mechanism, none of the identified genes has been previously reported in the admittedly sparse literature on the subject. However, some of these genes have a common role: APBB2, RUNX1T1, ZBTB7C, and ISX regulate transcription, while APBB2, BTG3, ZBTB7C, SZRD1 and LEF1 have a function in regulating proliferation, suggesting a role for these two pathways. While our results are specific for the lung cancer cell lines we selected for this work, our method of analysis can be applied to cell lines from other tissues and for which the required data is available.

Anthracyclines induce cardiotoxicity through a shared gene expression response signature

TOP2 inhibitors (TOP2i) are effective drugs for breast cancer treatment. However, they can cause cardiotoxicity in some women. The most widely used TOP2i include anthracyclines (AC) Doxorubicin (DOX), Daunorubicin (DNR), Epirubicin (EPI), and the anthraquinone Mitoxantrone (MTX). It is unclear whether women would experience the same adverse effects from all drugs in this class, or if specific drugs would be preferable for certain individuals based on their cardiotoxicity risk profile. To investigate this, we studied the effects of treatment of DOX, DNR, EPI, MTX, and an unrelated monoclonal antibody Trastuzumab (TRZ) on iPSC-derived cardiomyocytes (iPSC-CMs) from six healthy females. All TOP2i induce cell death at concentrations observed in cancer patient serum, while TRZ does not. A sub-lethal dose of all TOP2i induces limited cellular stress but affects calcium handling, a function critical for cardiomyocyte contraction. TOP2i induce thousands of gene expression changes over time, giving rise to four distinct gene expression response signatures, denoted as TOP2i early-acute, early-sustained, and late response genes, and non-response genes. There is no drug- or AC-specific signature. TOP2i early response genes are enriched in chromatin regulators, which mediate AC sensitivity across breast cancer patients. However, there is increased transcriptional variability between individuals following AC treatments. To investigate potential genetic effects on response variability, we first identified a reported set of expression quantitative trait loci (eQTLs) uncovered following DOX treatment in iPSC-CMs. Indeed, DOX response eQTLs are enriched in genes that respond to all TOP2i. Next, we identified 38 genes in loci associated with AC toxicity by GWAS or TWAS. Two thirds of the genes that respond to at least one TOP2i, respond to all ACs with the same direction of effect. Our data demonstrate that TOP2i induce thousands of shared gene expression changes in cardiomyocytes, including genes near SNPs associated with inter-individual variation in response to DOX treatment and AC-induced cardiotoxicity.

Three-dimensional chromatin landscapes in hepatocellular carcinoma associated with hepatitis B virus

BACKGROUND

Three-dimensional (3D) chromatin architecture frequently altered in cancer. However, its changes during the pathogenesis of hepatocellular carcinoma (HCC) remained elusive.

METHODS

Hi-C and RNA-seq were applied to study the 3D chromatin landscapes and gene expression of HCC and ANHT. Hi-C Pro was used to generate genome-wide raw interaction matrices, which were normalized via iterative correction (ICE). Moreover, the chromosomes were divided into different compartments according to the first principal component (E1). Furthermore, topologically associated domains (TADs) were visualized via WashU Epigenome Browser. Furthermore, differential expression analysis of ANHT and HCC was performed using the DESeq2 R package. Additionally, dysregulated genes associated with 3D genome architecture altered were confirmed using TCGA, qRT-PCR, immunohistochemistry (IHC), etc. RESULTS: First, the intrachromosomal interactions of chr1, chr2, chr5, and chr11 were significantly different, and the interchromosomal interactions of chr4-chr10, chr13-chr21, chr15-chr22, and chr16-chr19 are remarkably different between ANHT and HCC, which resulted in the up-regulation of TP53I3 and ZNF738 and the down-regulation of APOC3 and APOA5 in HCC. Second, 49 compartment regions on 18 chromosomes have significantly switched (A-B or B-A) during HCC tumorigenesis, contributing to up-regulation of RAP2A. Finally, a tumor-specific TAD boundary located on chr5: 6271000-6478000 and enhancer hijacking were identified in HCC tissues, potentially associated with the elevated expression of MED10, whose expression were associated with poor prognosis of HCC patients.

CONCLUSION

This study demonstrates the crucial role of chromosomal structure variation in HCC oncogenesis and potential novel biomarkers of HCC, laying a foundation for cancer precision medicine development.

Gene fusions in poroma, porocarcinoma and related adnexal skin tumours: An update

Poroma is a benign sweat gland tumour showing morphological features recapitulating the superficial portion of the eccrine sweat coil. A subset of poromas may transform into porocarcinoma, its malignant counterpart. Poroma and porocarcinoma are characterised by recurrent gene fusions involving YAP1, a transcriptional co-activator, which is controlled by the Hippo signalling pathway. The fusion genes frequently involve MAML2 and NUTM1, which are also rearranged in other cutaneous and extracutaneous neoplasms. We aimed to review the clinical, morphological and molecular features of this category of adnexal neoplasms with a special focus upon emerging differential diagnoses, and discuss how their systematic molecular characterisation may contribute to a standardisation of diagnosis, more accurate classification and, ultimately, refinement of their prognosis and therapeutic modalities.

The Incidence of Multiple Fusions in a Series of Pediatric Soft Tissue and Bone Tumors

BACKGROUND

Next generation sequencing (NGS) has increased the detection of fusion genes in cancer. NGS has found multiple fusions in single tumor samples; however, the incidence of this in pediatric soft tissue and bone tumors (PSTBTs) is not well documented. The aim of this study is to catalogue the incidence of multiple fusions in a series of PSTBTs, and apply a modified gene fusion classification system to determine clinical relevance.

METHODOLOGY

RNA from 78 bone and soft tissue tumors and 7 external quality assessment samples were sequenced and analyzed using recently-described Metafusion (MF) software and classified using a modification of previously-published schema for fusion classification into 3 tiers: 1, strong clinical significance; 2, potential clinical significance; and 3, unknown clinical significance.

RESULTS

One-hundred forty-five fusions were detected in 85 samples. Fifty-five samples (65%) had a single fusion and 30 (35%) had more than 1 fusion. No samples contained more than 1 tier 1 fusion. There were 40 tier 1 (28%), 36 tier 2 (24%), and 69 (48%) tier 3 fusions.

CONCLUSIONS

A significant percentage of PSTBTs harbor more than 1 fusion, and by applying a modified fusion classification scheme, the potential clinical relevance of such fusions can be determined.

Modeling phenotypic heterogeneity towards evolutionarily inspired osteosarcoma therapy

Osteosarcoma is the most common bone sarcoma in children and young adults. While universally delivered, chemotherapy only benefits roughly half of patients with localized disease. Increasingly, intratumoral heterogeneity is recognized as a source of therapeutic resistance. In this study, we develop and evaluate an in vitro model of osteosarcoma heterogeneity based on phenotype and genotype. Cancer cell populations vary in their environment-specific growth rates and in their sensitivity to chemotherapy. We present the genotypic and phenotypic characterization of an osteosarcoma cell line panel with a focus on co-cultures of the most phenotypically divergent cell lines, 143B and SAOS2. Modest environmental (pH, glutamine) or chemical perturbations dramatically shift the success and composition of cell lines. We demonstrate that in nutrient rich culture conditions 143B outcompetes SAOS2. But, under nutrient deprivation or conventional chemotherapy, SAOS2 growth can be favored in spheroids. Importantly, when the simplest heterogeneity state is evaluated, a two-cell line coculture, perturbations that affect the faster growing cell line have only a modest effect on final spheroid size. Thus the only evaluated therapies to eliminate the spheroids were by switching therapies from a first strike to a second strike. This extensively characterized, widely available system, can be modeled and scaled to allow for improved strategies to anticipate resistance in osteosarcoma due to heterogeneity.

Reassessing pharmacogenomic cell sensitivity with multilevel statistical models

Pharmacogenomic experiments allow for the systematic testing of drugs, at varying dosage concentrations, to study how genomic markers correlate with cell sensitivity to treatment. The first step in the analysis is to quantify the response of cell lines to variable dosage concentrations of the drugs being tested. The signal to noise in these measurements can be low due to biological and experimental variability. However, the increasing availability of pharmacogenomic studies provides replicated data sets that can be leveraged to gain power. To do this, we formulate a hierarchical mixture model to estimate the drug-specific mixture distributions for estimating cell sensitivity and for assessing drug effect type as either broad or targeted effect. We use this formulation to propose a unified approach that can yield posterior probability of a cell being susceptible to a drug conditional on being a targeted effect or relative effect sizes conditioned on the cell being broad. We demonstrate the usefulness of our approach via case studies. First, we assess pairwise agreements for cell lines/drugs within the intersection of two data sets and confirm the moderate pairwise agreement between many publicly available pharmacogenomic data sets. We then present an analysis that identifies sensitivity to the drug crizotinib for cells harboring EML4-ALK or NPM1-ALK gene fusions, as well as significantly down-regulated cell-matrix pathways associated with crizotinib sensitivity.

Partial gene suppression improves identification of cancer vulnerabilities when CRISPR-Cas9 knockout is pan-lethal

BACKGROUND

Hundreds of functional genomic screens have been performed across a diverse set of cancer contexts, as part of efforts such as the Cancer Dependency Map, to identify gene dependencies-genes whose loss of function reduces cell viability or fitness. Recently, large-scale screening efforts have shifted from RNAi to CRISPR-Cas9, due to superior efficacy and specificity. However, many effective oncology drugs only partially inhibit their protein targets, leading us to question whether partial suppression of genes using RNAi could reveal cancer vulnerabilities that are missed by complete knockout using CRISPR-Cas9. Here, we compare CRISPR-Cas9 and RNAi dependency profiles of genes across approximately 400 matched cancer cell lines.

RESULTS

We find that CRISPR screens accurately identify more gene dependencies per cell line, but the majority of each cell line's dependencies are part of a set of 1867 genes that are shared dependencies across the entire collection (pan-lethals). While RNAi knockdown of about 30% of these genes is also pan-lethal, approximately 50% have selective dependency patterns across cell lines, suggesting they could still be cancer vulnerabilities. The accuracy of the unique RNAi selectivity is supported by associations to multi-omics profiles, drug sensitivity, and other expected co-dependencies.

CONCLUSIONS

Incorporating RNAi data for genes that are pan-lethal knockouts facilitates the discovery of a wider range of gene targets than could be detected using the CRISPR dataset alone. This can aid in the interpretation of contrasting results obtained from CRISPR and RNAi screens and reinforce the importance of partial gene suppression methods in building a cancer dependency map.

High-Throughput Drug Screening of Primary Tumor Cells Identifies Therapeutic Strategies for Treating Children with High-Risk Cancer

For one-third of patients with pediatric cancer enrolled in precision medicine programs, molecular profiling does not result in a therapeutic recommendation. To identify potential strategies for treating these high-risk pediatric patients, we performed in vitro screening of 125 patient-derived samples against a library of 126 anticancer drugs. Tumor cell expansion did not influence drug responses, and 82% of the screens on expanded tumor cells were completed while the patients were still under clinical care. High-throughput drug screening (HTS) confirmed known associations between activating genomic alterations in NTRK, BRAF, and ALK and responses to matching targeted drugs. The in vitro results were further validated in patient-derived xenograft models in vivo and were consistent with clinical responses in treated patients. In addition, effective combinations could be predicted by correlating sensitivity profiles between drugs. Furthermore, molecular integration with HTS identified biomarkers of sensitivity to WEE1 and MEK inhibition. Incorporating HTS into precision medicine programs is a powerful tool to accelerate the improved identification of effective biomarker-driven therapeutic strategies for treating high-risk pediatric cancers.

SIGNIFICANCE

Integrating HTS with molecular profiling is a powerful tool for expanding precision medicine to support drug treatment recommendations and broaden the therapeutic options available to high-risk pediatric cancers.

The pharmacoepigenomic landscape of cancer cell lines reveals the epigenetic component of drug sensitivity

Aberrant DNA methylation accompanies genetic alterations during oncogenesis and tumour homeostasis and contributes to the transcriptional deregulation of key signalling pathways in cancer. Despite increasing efforts in DNA methylation profiling of cancer patients, there is still a lack of epigenetic biomarkers to predict treatment efficacy. To address this, we analyse 721 cancer cell lines across 22 cancer types treated with 453 anti-cancer compounds. We systematically detect the predictive component of DNA methylation in the context of transcriptional and mutational patterns, i.e., in total 19 DNA methylation biomarkers across 17 drugs and five cancer types. DNA methylation constitutes drug sensitivity biomarkers by mediating the expression of proximal genes, thereby enhancing biological signals across multi-omics data modalities. Our method reproduces anticipated associations, and in addition, we find that the NEK9 promoter hypermethylation may confer sensitivity to the NEDD8-activating enzyme (NAE) inhibitor pevonedistat in melanoma through downregulation of NEK9. In summary, we envision that epigenomics will refine existing patient stratification, thus empowering the next generation of precision oncology.

Highlights from the 1st European cancer dependency map symposium and workshop

The systematic identification of tumour vulnerabilities through perturbational experiments on cancer models, including genome editing and drug screens, is playing a crucial role in combating cancer. This collective effort is known as the Cancer Dependency Map (DepMap). The 1st European Cancer Dependency Map Symposium (EuroDepMap), held in Milan last May, featured talks, a roundtable discussion, and a poster session, showcasing the latest discoveries and future challenges related to the DepMap. The symposium aimed to facilitate interactions among participants across Europe, encourage idea exchange with leading experts, and present their work and future projects. Importantly, it sparked discussions on future endeavours, such as screening more complex cancer models and accounting for tumour evolution.

Genomics driven precision oncology in advanced biliary tract cancer improves survival

BACKGROUND

Biliary tract cancers (BTCs) including intrahepatic, perihilar, and distal cholangiocarcinoma as well as gallbladder cancer, are rare but aggressive malignancies with few effective standard of care therapies.

METHODS

We implemented integrative clinical sequencing of advanced BTC tumors from 124 consecutive patients who progressed on standard therapies (N=92 with MI-ONCOSEQ and N=32 with commercial gene panels) enrolled between 2011-2020.

RESULTS

Genomic profiling of paired tumor and normal DNA and tumor transcriptome (RNA) sequencing identified actionable somatic and germline genomic alterations in 54 patients (43.5%), and potentially actionable alterations in 79 (63.7%) of the cohort. Of these, patients who received matched targeted therapy (22; 40.7%) had a median overall survival of 28.1 months compared to 13.3 months in those who did not receive matched targeted therapy (32; P < 0.01), or 13.9 months in those without actionable mutations (70; P < 0.01). Additionally, we discovered recurrent activating mutations in FGFR2, and a novel association between KRAS and BRAF mutant tumors with high expression of immune modulatory protein NT5E (CD73) that may represent novel therapeutic avenues.

CONCLUSIONS

Overall, the identification of actionable/ potentially actionable aberrations in a large proportion of cases, and improvement in survival with precision oncology supports molecular analysis and clinical sequencing for all patients with advanced BTC.

Systematic discovery of gene fusions in pediatric cancer by integrating RNA-seq and WGS

BACKGROUND

Gene fusions are important cancer drivers in pediatric cancer and their accurate detection is essential for diagnosis and treatment. Clinical decision-making requires high confidence and precision of detection. Recent developments show RNA sequencing (RNA-seq) is promising for genome-wide detection of fusion products but hindered by many false positives that require extensive manual curation and impede discovery of pathogenic fusions.

METHODS

We developed Fusion-sq to overcome existing disadvantages of detecting gene fusions. Fusion-sq integrates and "fuses" evidence from RNA-seq and whole genome sequencing (WGS) using intron-exon gene structure to identify tumor-specific protein coding gene fusions. Fusion-sq was then applied to the data generated from a pediatric pan-cancer cohort of 128 patients by WGS and RNA sequencing.

RESULTS

In a pediatric pan-cancer cohort of 128 patients, we identified 155 high confidence tumor-specific gene fusions and their underlying structural variants (SVs). This includes all clinically relevant fusions known to be present in this cohort (30 patients). Fusion-sq distinguishes healthy-occurring from tumor-specific fusions and resolves fusions in amplified regions and copy number unstable genomes. A high gene fusion burden is associated with copy number instability. We identified 27 potentially pathogenic fusions involving oncogenes or tumor-suppressor genes characterized by underlying SVs, in some cases leading to expression changes indicative of activating or disruptive effects.

CONCLUSIONS

Our results indicate how clinically relevant and potentially pathogenic gene fusions can be identified and their functional effects investigated by combining WGS and RNA-seq. Integrating RNA fusion predictions with underlying SVs advances fusion detection beyond extensive manual filtering. Taken together, we developed a method for identifying candidate gene fusions that is suitable for precision oncology applications. Our method provides multi-omics evidence for assessing the pathogenicity of tumor-specific gene fusions for future clinical decision making.

A landscape of response to drug combinations in non-small cell lung cancer

Combination of anti-cancer drugs is broadly seen as way to overcome the often-limited efficacy of single agents. The design and testing of combinations are however very challenging. Here we present a uniquely large dataset screening over 5000 targeted agent combinations across 81 non-small cell lung cancer cell lines. Our analysis reveals a profound heterogeneity of response across the tumor models. Notably, combinations very rarely result in a strong gain in efficacy over the range of response observable with single agents. Importantly, gain of activity over single agents is more often seen when co-targeting functionally proximal genes, offering a strategy for designing more efficient combinations. Because combinatorial effect is strongly context specific, tumor specificity should be achievable. The resource provided, together with an additional validation screen sheds light on major challenges and opportunities in building efficacious combinations against cancer and provides an opportunity for training computational models for synergy prediction.

Donafenib and GSK-J4 Synergistically Induce Ferroptosis in Liver Cancer by Upregulating HMOX1 Expression

Hepatocellular carcinoma (HCC) is one of the most lethal cancers worldwide. Donafenib is a multi-receptor tyrosine kinase inhibitor approved for the treatment of patients with advanced HCC, but its clinical effect is very limited. Here, through integrated screening of a small-molecule inhibitor library and a druggable CRISPR library, that GSK-J4 is synthetically lethal with donafenib in liver cancer is shown. This synergistic lethality is validated in multiple HCC models, including xenograft, orthotopically induced HCC, patient-derived xenograft, and organoid models. Furthermore, co-treatment with donafenib and GSK-J4 resulted in cell death mainly via ferroptosis. Mechanistically, through integrated RNA sequencing (RNA-seq) and assay for transposase-accessible chromatin with high throughput sequencing (ATAC-seq) analyses, that donafenib and GSK-J4 synergistically promoted the expression of HMOX1 and increased the intracellular Fe2+ level is found, eventually leading to ferroptosis. Additionally, through cleavage under targets & tagmentation followed by sequencing (CUT&Tag-seq), it is found that the enhancer regions upstream of HMOX1 promoter significantly increased under donafenib and GSK-J4 co-treatment. A chromosome conformation capture assay confirmed that the increased expression of HMOX1 is caused by the significantly enhanced interaction between the promoter and upstream enhancer under dual-drug combination. Taken together, this study elucidates a new synergistic lethal interaction in liver cancer.

Insights into recent findings and clinical application of YAP and TAZ in cancer

Decades of research have mapped out the basic mechanics of the Hippo pathway. The paralogues Yes-associated protein (YAP) and transcriptional co-activator with PDZ-binding motif (TAZ), as the central transcription control module of the Hippo pathway, have long been implicated in the progression of various human cancers. The current literature regarding oncogenic YAP and TAZ activities consists mostly of context-specific mechanisms and treatments of human cancers. Furthermore, a growing number of studies demonstrate tumour-suppressor functions of YAP and TAZ. In this Review we aim to synthesize an integrated perspective of the many disparate findings regarding YAP and TAZ in cancer. We then conclude with the various strategies for targeting and treating YAP- and TAZ-dependent cancers.

Rolling circle transcription and CRISPR/Cas12a-assisted versatile bicyclic cascade amplification assay for sensitive uracil-DNA glycosylase detection

Uracil-DNA glycosylase (UDG) is pivotal in maintaining genome integrity and aberrant expressed UDG is highly relevant to numerous diseases. Sensitive and accurate detecting UDG is critically significant for early clinical diagnosis. In this research, we demonstrated a sensitive UDG fluorescent assay based on rolling circle transcription (RCT)/CRISPR/Cas12a-assisted bicyclic cascade amplification strategy. Target UDG catalyzed to remove uracil base of DNA dumbbell-shape substrate probe (Sub_UDG) to produce an apurinic/apyrimidinic (AP) site, at which Sub_UDG was cleaved by apurinic/apyrimidinic endonuclease (APE1) subsequently. The exposed 5'-PO₄ was ligated with the free 3'-OH terminus to form an enclosed DNA dumbbell-shape substrate probe (E-Sub_UDG). E-Sub_UDG functioned as a template can actuate T7 RNA polymerase-mediated RCT signal amplification, generating multitudes of crRNA repeats. The resultant Cas12a/crRNA/activator ternary complex activated the activity of Cas12a, causing a significantly enhanced fluorescence output. In this bicyclic cascade strategy, target UDG was amplified via RCT and CRISPR/Cas12a, and the whole reaction was completed without complex procedures. This method enabled sensitive and specific monitor UDG down to 0.0005 U/mL, screen corresponding inhibitors, and analyze endogenous UDG in A549 cells at single-cell level. Importantly, this assay can be extended to analyze other DNA glycosylase (hAAG and Fpg) by altering the recognition site in DNA substrates probe rationally, thereby offering a potent tool for DNA glycosylase-associated clinical diagnosis and biomedical research.

Targeting DEAD-box RNA helicases: The emergence of molecular staples

RNA helicases constitute a large family of proteins that play critical roles in mediating RNA function. They have been implicated in all facets of gene expression pathways involving RNA, from transcription to processing, transport and translation, and storage and decay. There is significant interest in developing small molecule inhibitors to RNA helicases as some family members have been documented to be dysregulated in neurological and neurodevelopment disorders, as well as in cancers. Although different functional properties of RNA helicases offer multiple opportunities for small molecule development, molecular staples have recently come to the forefront. These bifunctional molecules interact with both protein and RNA components to lock them together, thereby imparting novel gain-of-function properties to their targets. This article is categorized under: RNA Interactions with Proteins and Other Molecules > Small Molecule-RNA Interactions RNA Interactions with Proteins and Other Molecules > Protein-RNA Interactions: Functional Implications.

CellPalmSeq: A curated RNAseq database of palmitoylating and de-palmitoylating enzyme expression in human cell types and laboratory cell lines

The reversible lipid modification protein S-palmitoylation can dynamically modify the localization, diffusion, function, conformation and physical interactions of substrate proteins. Dysregulated S-palmitoylation is associated with a multitude of human diseases including brain and metabolic disorders, viral infection and cancer. However, the diverse expression patterns of the genes that regulate palmitoylation in the broad range of human cell types are currently unexplored, and their expression in commonly used cell lines that are the workhorse of basic and preclinical research are often overlooked when studying palmitoylation dependent processes. We therefore created CellPalmSeq (https://cellpalmseq.med.ubc.ca), a curated RNAseq database and interactive webtool for visualization of the expression patterns of the genes that regulate palmitoylation across human single cell types, bulk tissue, cancer cell lines and commonly used laboratory non-human cell lines. This resource will allow exploration of these expression patterns, revealing important insights into cellular physiology and disease, and will aid with cell line selection and the interpretation of results when studying important cellular processes that depend on protein S-palmitoylation.

Significance of YAP1-MAML2 rearrangement and GTF2I mutation in the diagnosis and differential diagnosis of metaplastic thymoma

BACKGROUND

Metaplastic thymoma (MT) is a very uncommon thymoma type, with biphasic differentiation as one of its histological characteristics. This histological pattern, however, can also be mistaken for type A thymoma and the A component in type AB thymoma.

METHODS

Postoperative specimens were collected from five MT and four type A thymomas with a retrospective analysis involving immunohistochemistry, fluorescence in situ hybridization (FISH) and next-generation sequencing (NGS).

RESULTS

The histological morphology of the MT overlapped with that of the type A thymoma. With immunostains, the former's spindle cell components expressed vimentin and EMA, but not CD20. In MT, 3/5 cases had the nuclear expression of YAP1. The spindle cell component of the type A thymoma was found to express CD20. In all five cases of MT, FISH detection revealed YAP1-MAML2 fusion, which was not found in any type A thymoma cases. NGS sequencing confirmed YAP1-MAML2 rearrangement in all five cases of MT, and mutations in POLE and HRAS were also found in two cases, respectively. GTF2I c.74146970 T > A mutations were found in all cases of type A thymoma, and HRAS and NRAS mutations were found in two cases, but no YAP1-MAML2 rearrangement was evident.

CONCLUSIONS

For the diagnosis and differential diagnosis of challenging cases, the YAP1-MAML2 rearrangement and GTF2I mutation were both significant molecular events specific to MT and type A thymoma, respectively.

PANACEA: network-based methods for pharmacotherapy prioritization in personalized oncology

MOTIVATION

Identifying appropriate pharmacotherapy options from genomics results is a significant challenge in personalized oncology. However, computational methods for prioritizing drugs are underdeveloped. With the hypothesis that network-based approaches can improve the performance by extending the use of potential drug targets beyond direct interactions, we devised two network-based methods for personalized pharmacotherapy prioritization in cancer.

RESULTS

We developed novel personalized drug prioritization approaches, PANACEA: PersonAlized Network-based Anti-Cancer therapy EvaluAtion. In PANACEA, initially, the protein interaction network is extended with drugs, and a driverness score is assigned to each altered gene. For scoring drugs, either (i) the 'distance-based' method, incorporating the shortest distance between drugs and altered genes, and driverness scores, or (ii) the 'propagation' method involving the propagation of driverness scores via a random walk with restart framework is performed. We evaluated PANACEA using multiple datasets, and demonstrated that (i) the top-ranking drugs are relevant for cancer pharmacotherapy using TCGA data; (ii) drugs that cancer cell lines are sensitive to are identified using GDSC data; and (iii) PANACEA can perform adequately in the clinical setting using cases with known drug responses. We also illustrate that the proposed methods outperform iCAGES and PanDrugs, two previous personalized drug prioritization approaches.

AVAILABILITY AND IMPLEMENTATION

The corresponding R package is available on GitHub. (https://github.com/egeulgen/PANACEA.git).

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Chromosomal instability (CIN) in HAP1 cell lines revealed by multiplex fluorescence in situ hybridisation (M-FISH)

BACKGROUND

HAP1, a near-haploid human leukemic cancer cell line is often used in combination with CRISPR-Cas9 gene editing technology for genetic screens. HAP1 carries the Philadelphia chromosome (Ph) and an additional ~ 30 Mb fragment of chromosome 15 inserted into chromosome 19. The potential use of an in vitro cell line as a model system in biomedical research studies depends on its ability to maintain genome stability. Being a cancer cell line with a near-haploid genome, HAP1 is prone to genetic instability, which is further compounded by its tendency to diploidise in culture spontaneously. Moreover, CRISPR-Cas9 gene editing coupled with prolonged in-vitro cell culturing has the potential to induce unintended 'off-target' cytogenetic mutations. To gain an insight into chromosomal instability (CIN) and karyotype heterogeneity, 19 HAP1 cell lines were cytogenetically characterised, 17 of which were near-haploids and two double-haploids, using multiplex fluorescence in situ hybridisation (M-FISH), at single cell resolution. We focused on novel numerical (N) and structural (S) CIN and discussed the potential causal factors for the observed instability. For each cell line we examined its ploidy, gene editing status and its length of in-vitro cell culturing.

RESULTS

Sixteen of the 19 cell lines had been gene edited with passage numbers ranging from 10 to 35. Diploidisation in 17 near-haploid cell lines ranged from 4 to 35% and percentage of N- and S-CIN in [1n] and [2n] metaphases ranged from 7 to 50% with two cell lines showing no CIN. Percentage of cells with CIN in the two double-haploid cell lines were 96% and 100% respectively. The most common S-CIN observed was deletion followed by translocation of both types, non-reciprocal and Robertsonian. Interestingly, we observed a prevalence of S-CIN associated with chromosome 13 in both near-and double-haploid cell lines, with a high incidence of Robertsonian translocation involving chromosome 13. Furthermore, locus-specific BAC (bacterial artificial chromosome) FISH enabled us to show for the first time that the additional chromosome 15 fragment is inserted into the p-arm rather than the q-arm of chromosome 19 of the HAP1 genome.

CONCLUSION

Our study revealed a high incidence of CIN leading to karyotype heterogeneity in majority of the HAP1 cell lines with the number of chromosomal aberrations varying between cell lines. A noteworthy observation was the high frequency of structural chromosomal aberrations associated with chromosome 13. We showed that CRISPR-Cas9 gene editing technology in combination with spontaneous diploidisation and prolonged in-vitro cell culturing is potentially instrumental in inducing further chromosomal rearrangements in the HAP1 cell lines with existing CIN. We highlight the importance of maintaining cell lines at low passage and the need for regular monitoring to prevent implications in downstream applications. Our study also established that the additional fragment of chromosome 15 in the HAP1 genome is inserted into chromosome 19p rather than 19q.

Single-cell profiling reveals molecular basis of malignant phenotypes and tumor microenvironments in small bowel adenocarcinomas

Small bowel adenocarcinomas (SBAs) are rare malignant tumors with a high mortality rate, and their molecular characteristics are still largely unexplored. Here we performed single-cell RNA sequencing for tumor samples from 12 SBA patients and predicted drug candidates for SBA. We identified four prevalent subtypes of malignant cells with distinct signatures including cell cycle program, mitochondria program, metabolism program and epithelial–mesenchymal transition (EMT) program. The progression relationships of these four subtypes of malignant cells were also revealed, which started from the cell cycle program, through the mitochondria program and then progressing into either the metabolism program or the EMT program. Importantly, ligand–receptor interaction pairs were found to be specifically enriched in pairs of EMT-program malignant cells and highly exhausted CD8+ T cells, suggesting that cancer cell subpopulations with EMT features may contribute most to the exhaustion of T cells. We also showed that the duodenal subtype of SBA exhibited molecular features more similar to gastric cancer whereas jejunal subtype of SBA more similar to colorectal cancer. Especially, we predicted specific drugs for SBA based on differential gene expression signatures between malignant cells and normal epithelial cells of SBA, and verified more potent inhibitory effects of volasertib and tozasertib for SBA cancer cells than conventional drugs of SBA at the same concentration, which provides new clues for treatments of SBA. In summary, our study provides a blueprint of the molecular signatures of both tumor cells and tumor microenvironment cells in SBA and reveals potential targets and drug candidates for its clinical treatments.

Subgroup-Enriched Pathways and Kinase Signatures in Medulloblastoma Patient-Derived Xenografts

Medulloblastoma (MB) is the most common malignant pediatric brain tumor. MB is classified into four primary molecular subgroups: wingless (WNT), sonic hedgehog (SHH), Group 3 (G3), and Group 4 (G4), and further genomic and proteomic subtypes have been reported. Subgroup heterogeneity and few actionable mutations have hindered the development of targeted therapies, especially for G3 MB, which has a particularly poor prognosis. To identify novel therapeutic targets for MB, we performed mass spectrometry-based deep expression proteomics and phosphoproteomics in 20 orthotopic patient-derived xenograft (PDX) models of MB comprising SHH, G3, and G4 subgroups. We found that the proteomic profiles of MB PDX tumors are closely aligned with those of primary human MB tumors illustrating the utility of PDX models. SHH PDXs were enriched for NFκB and p38 MAPK signaling, while G3 PDXs were characterized by MYC activity. Additionally, we found a significant association between actinomycin D sensitivity and increased abundance of MYC and MYC target genes. Our results highlight several candidate pathways that may serve as targets for new MB therapies. Mass spectrometry data are available via ProteomeXchange with identifier PXD035070.

Cancer cell histone density links global histone acetylation, mitochondrial proteome and histone acetylase inhibitor sensitivity

Chromatin metabolism is frequently altered in cancer cells and facilitates cancer development. While cancer cells produce large amounts of histones, the protein component of chromatin packaging, during replication, the potential impact of histone density on cancer biology has not been studied systematically. Here, we show that altered histone density affects global histone acetylation, histone deactylase inhibitor sensitivity and altered mitochondrial proteome composition. We present estimates of nuclear histone densities in 373 cancer cell lines, based on Cancer Cell Line Encyclopedia data, and we show that a known histone regulator, HMGB1, is linked to histone density aberrations in many cancer cell lines. We further identify an E3 ubiquitin ligase interactor, DCAF6, and a mitochondrial respiratory chain assembly factor, CHCHD4, as histone modulators. As systematic characterization of histone density aberrations in cancer cell lines, this study provides approaches and resources to investigate the impact of histone density on cancer biology.

Elevated histone density is associated with global histone acetylation, histone deacetylase inhibitor sensitivity and altered mitochondrial proteome composition, with histone regulator HMGB1 linked to histone density aberrations in many cancer cell lines.

Pan-cancer proteomic map of 949 human cell lines

The proteome provides unique insights into disease biology beyond the genome and transcriptome. A lack of large proteomic datasets has restricted the identification of new cancer biomarkers. Here, proteomes of 949 cancer cell lines across 28 tissue types are analyzed by mass spectrometry. Deploying a workflow to quantify 8,498 proteins, these data capture evidence of cell-type and post-transcriptional modifications. Integrating multi-omics, drug response, and CRISPR-Cas9 gene essentiality screens with a deep learning-based pipeline reveals thousands of protein biomarkers of cancer vulnerabilities that are not significant at the transcript level. The power of the proteome to predict drug response is very similar to that of the transcriptome. Further, random downsampling to only 1,500 proteins has limited impact on predictive power, consistent with protein networks being highly connected and co-regulated. This pan-cancer proteomic map (ProCan-DepMapSanger) is a comprehensive resource available at https://cellmodelpassports.sanger.ac.uk.

Single-Molecule Counting of FTO in Human Breast Tissues Based on a Rolling Circle Transcription Amplification-Driven Clustered Regularly Interspaced Short Palindromic Repeat─Cas12a

N6-methyladenosine modification as an mRNA modification in mammalian cells is dynamically reversible, regulated by RNA demethylase [e.g., fat mass and obesity-associated protein (FTO)]. The abnormal expression of FTO is closely related to numerous diseases (e.g., various cancers and obesity). Herein, we demonstrate the single-molecule counting of FTO in human cancer cells and breast tissues based on a T7 RNA polymerase-mediated rolling circle transcription (RCT) amplification-driven clustered regularly interspaced short palindromic repeat (CRISPR)─Cas12a. When FTO is present, it demethylates the DNA substrate, initiating the DpnII-mediated cleavage reaction. After magnetic separation, the cleaved DNA fragments trigger the T7 RNA polymerase-mediated RCT amplification, activating CRISPR-/Cas12a-mediated cleavage of signal probes and releasing abundant FAM molecules that are simply counted via single-molecule detection. In this assay, only target FTO can generate CRISPR RNAs, efficiently improving detection specificity. Moreover, the integration of single-molecule detection with magnetic separation achieves zero background and effectively enhances detection sensitivity. This method can specifically and sensitively monitor FTO activity with a limit of detection of 1.20 × 10^-13 M, and it may measure FTO at the single-cell level. Furthermore, it may accurately discriminate the FTO expression level in breast tissues between healthy persons and breast cancer patients and screen the FTO inhibitors as well, with great potential in clinical diagnosis and drug discovery.

DUSP4 protects BRAF- and NRAS-mutant melanoma from oncogene overdose through modulation of MITF

MAPK inhibitors (MAPKi) remain an important component of the standard of care for metastatic melanoma. However, acquired resistance to these drugs limits their therapeutic benefit. Tumor cells can become refractory to MAPKi by reactivation of ERK. When this happens, tumors often become sensitive to drug withdrawal. This drug addiction phenotype results from the hyperactivation of the oncogenic pathway, a phenomenon commonly referred to as oncogene overdose. Several feedback mechanisms are involved in regulating ERK signaling. However, the genes that serve as gatekeepers of oncogene overdose in mutant melanoma remain unknown. Here, we demonstrate that depletion of the ERK phosphatase, DUSP4, leads to toxic levels of MAPK activation in both drug-naive and drug-resistant mutant melanoma cells. Importantly, ERK hyperactivation is associated with down-regulation of lineage-defining genes including MITF Our results offer an alternative therapeutic strategy to treat mutant melanoma patients with acquired MAPKi resistance and those unable to tolerate MAPKi.

Computational analysis of cancer genome sequencing data

Distilling biologically meaningful information from cancer genome sequencing data requires comprehensive identification of somatic alterations using rigorous computational methods. As the amount and complexity of sequencing data have increased, so has the number of tools for analysing them. Here, we describe the main steps involved in the bioinformatic analysis of cancer genomes, review key algorithmic developments and highlight popular tools and emerging technologies. These tools include those that identify point mutations, copy number alterations, structural variations and mutational signatures in cancer genomes. We also discuss issues in experimental design, the strengths and limitations of sequencing modalities and methodological challenges for the future.

Predictive and Therapeutic Implications of a Novel PLCγ1/SHP2-Driven Mechanism of Cetuximab Resistance in Metastatic Colorectal Cancer

PURPOSE

Cetuximab is an EGFR-targeted therapy approved for the treatment of RAS wild-type (WT) metastatic colorectal cancer (mCRC). However, about 60% of these patients show innate resistance to cetuximab. To increase cetuximab efficacy, it is crucial to successfully identify responder patients, as well as to develop new therapeutic approaches to overcome cetuximab resistance.

EXPERIMENTAL DESIGN

We evaluated the value of EGFR effector phospholipase C gamma 1 (PLCγ1) in predicting cetuximab responses, by analyzing progression-free survival (PFS) of a multicentric retrospective cohort of 94 treated patients with mCRC (log-rank test and Cox regression model). Furthermore, we used in vitro and zebrafish xenotransplant models to identify and target the mechanism behind PLCγ1-mediated resistance to cetuximab.

RESULTS

In this study, levels of PLCγ1 were found increased in RAS WT tumors and were able to predict cetuximab responses in clinical samples and in vitro and in vivo models. Mechanistically, PLCγ1 expression was found to bypass cetuximab-dependent EGFR inhibition by activating ERK and AKT pathways. This novel resistance mechanism involves a noncatalytic role of PLCγ1 SH2 tandem domains in the propagation of downstream signaling via SH2-containing protein tyrosine phosphatase 2 (SHP2). Accordingly, SHP2 inhibition sensitizes PLCγ1-resistant cells to cetuximab.

CONCLUSIONS

Our discoveries reveal the potential of PLCγ1 as a predictive biomarker for cetuximab responses and suggest an alternative therapeutic approach to circumvent PLCγ1-mediated resistance to cetuximab in patients with RAS WT mCRC. In this way, this work contributes to the development of novel strategies in the medical management and treatment of patients with mCRC.

Systematic illumination of druggable genes in cancer genomes

By combining 6 druggable genome resources, we identify 6,083 genes as potential druggable genes (PDGs). We characterize their expression, recurrent genomic alterations, cancer dependencies, and therapeutic potentials by integrating genome, functionome, and druggome profiles across cancers. 81.5% of PDGs are reliably expressed in major adult cancers, 46.9% show selective expression patterns, and 39.1% exhibit at least one recurrent genomic alteration. We annotate a total of 784 PDGs as dependent genes for cancer cell growth. We further quantify 16 cancer-related features and estimate a PDG cancer drug target score (PCDT score). PDGs with higher PCDT scores are significantly enriched for genes encoding kinases and histone modification enzymes. Importantly, we find that a considerable portion of high PCDT score PDGs are understudied genes, providing unexplored opportunities for drug development in oncology. By integrating the druggable genome and the cancer genome, our study thus generates a comprehensive blueprint of potential druggable genes across cancers.

Jiang et al. generate a comprehensive blueprint of potential druggable genes (PDGs) across cancers by a systematic integration of the druggable genome and the cancer genome. This resource is publicly available to the cancer research community in The Cancer Druggable Gene Atlas (TCDA) through the Functional Cancer Genome data portal.

The Hippo pathway in cancer: YAP/TAZ and TEAD as therapeutic targets in cancer

Tumorigenesis is a highly complex process, involving many interrelated and cross-acting signalling pathways. One such pathway that has garnered much attention in the field of cancer research over the last decade is the Hippo signalling pathway. Consisting of two antagonistic modules, the pathway plays an integral role in both tumour suppressive and oncogenic processes, generally via regulation of a diverse set of genes involved in a range of biological functions. This review discusses the history of the pathway within the context of cancer and explores some of the most recent discoveries as to how this critical transducer of cellular signalling can influence cancer progression. A special focus is on the various recent efforts to therapeutically target the key effectors of the pathway in both preclinical and clinical settings.

PharmacoDB 2.0: improving scalability and transparency of in vitro pharmacogenomics analysis

Cancer pharmacogenomics studies provide valuable insights into disease progression and associations between genomic features and drug response. PharmacoDB integrates multiple cancer pharmacogenomics datasets profiling approved and investigational drugs across cell lines from diverse tissue types. The web-application enables users to efficiently navigate across datasets, view and compare drug dose-response data for a specific drug-cell line pair. In the new version of PharmacoDB (version 2.0, https://pharmacodb.ca/), we present (i) new datasets such as NCI-60, the Profiling Relative Inhibition Simultaneously in Mixtures (PRISM) dataset, as well as updated data from the Genomics of Drug Sensitivity in Cancer (GDSC) and the Genentech Cell Line Screening Initiative (gCSI); (ii) implementation of FAIR data pipelines using ORCESTRA and PharmacoDI; (iii) enhancements to drug-response analysis such as tissue distribution of dose-response metrics and biomarker analysis; and (iv) improved connectivity to drug and cell line databases in the community. The web interface has been rewritten using a modern technology stack to ensure scalability and standardization to accommodate growing pharmacogenomics datasets. PharmacoDB 2.0 is a valuable tool for mining pharmacogenomics datasets, comparing and assessing drug-response phenotypes of cancer models.

A community challenge to evaluate RNA-seq, fusion detection, and isoform quantification methods for cancer discovery

The accurate identification and quantitation of RNA isoforms present in the cancer transcriptome is key for analyses ranging from the inference of the impacts of somatic variants to pathway analysis to biomarker development and subtype discovery. The ICGC-TCGA DREAM Somatic Mutation Calling in RNA (SMC-RNA) challenge was a crowd-sourced effort to benchmark methods for RNA isoform quantification and fusion detection from bulk cancer RNA sequencing (RNA-seq) data. It concluded in 2018 with a comparison of 77 fusion detection entries and 65 isoform quantification entries on 51 synthetic tumors and 32 cell lines with spiked-in fusion constructs. We report the entries used to build this benchmark, the leaderboard results, and the experimental features associated with the accurate prediction of RNA species. This challenge required submissions to be in the form of containerized workflows, meaning each of the entries described is easily reusable through CWL and Docker containers at https://github.com/SMC-RNA-challenge. A record of this paper's transparent peer review process is included in the supplemental information.

Coregulation of pathways in lung cancer patients with EGFR mutation: therapeutic opportunities

Epidermal growth factor receptor (EGFR) mutations in lung adenocarcinoma are a frequent class of driver mutations. Single EGFR tyrosine kinase inhibitor (TKI) provides substantial clinical benefit, but almost nil radiographic complete responses. Patients invariably progress, although survival can reach several years with post-treatment therapies, including EGFR TKIs, chemotherapy or other procedures. Endeavours have been clinically oriented to manage the acquisition of EGFR TKI-resistant mutations; however, basic principles on cancer evolution have not been considered in clinical trials. For years, evidence has displayed rapidly adaptive mechanisms of resistance to selective monotherapy, posing several dilemmas for the practitioner. Strict adherence to non-small cell lung cancer (NSCLC) guidelines is not always practical for addressing the clinical progression that EGFR-mutant lung adenocarcinoma patients suffer. The purpose of this review is to highlight regulatory mechanisms and signalling pathways that cause therapy-induced resistance to EGFR TKIs. It suggests combinatorial therapies that target EGFR, as well as potential mechanisms underlying EGFR-mutant NSCLC, alerting the reader to clinical opportunities that may lead to a deeper and more durable response. Molecular reprogramming contributes to EGFR TKI resistance, and the compiled information is relevant in understanding the development of new combined targeted strategies in EGFR-mutant NSCLC.

Gene Fusions Create Partner and Collateral Dependencies Essential to Cancer Cell Survival

Gene fusions frequently result from rearrangements in cancer genomes. In many instances, gene fusions play an important role in oncogenesis; in other instances, they are thought to be passenger events. Although regulatory element rearrangements and copy number alterations resulting from these structural variants are known to lead to transcriptional dysregulation across cancers, the extent to which these events result in functional dependencies with an impact on cancer cell survival is variable. Here we used CRISPR-Cas9 dependency screens to evaluate the fitness impact of 3,277 fusions across 645 cell lines from the Cancer Dependency Map. We found that 35% of cell lines harbored either a fusion partner dependency or a collateral dependency on a gene within the same topologically associating domain as a fusion partner. Fusion-associated dependencies revealed numerous novel oncogenic drivers and clinically translatable alterations. Broadly, fusions can result in partner and collateral dependencies that have biological and clinical relevance across cancer types. SIGNIFICANCE: This study provides insights into how fusions contribute to fitness in different cancer contexts beyond partner-gene activation events, identifying partner and collateral dependencies that may have direct implications for clinical care.

YAP1-MAML2 Fusion as a Diagnostic Biomarker for Metaplastic Thymoma

BACKGROUND

Metaplastic thymoma is a very rare tumor with only a few case reports documented in literature. Hence, its molecular features have not been well explored.

MATERIAL AND METHODS

Seventeen specimens of metaplastic thymoma were sequenced and retrospectively analyzed by fluorescence in situ hybridization (FISH) and immunohistochemistry in the study. In addition, seven cases of micronodular thymoma with lymphoid stroma and nine cases of type A thymoma were also investigated.

RESULTS

Among these metaplastic thymomas, fifteen cases showed classical histological features, and two cases displayed characteristic micronodular-like growth patterns. DNA and RNA based next-generation sequencing identified and confirmed highly recurrent Yes Associated Protein 1 (YAP1) - Mastermind Like Transcriptional Coactivator 2 (MAML2) translocation (13/17, 76.5%) in metaplastic thymoma but not in micronodular thymoma with lymphoid stroma (0/7, 0%) and type A thymoma (0/9, 0%). In addition, six nonsense mutations were also detected in the metaplastic thymoma. FISH in microdissection specimens indicated that both epithelioid and spindle cell components harbored YAP1-MAML2 gene rearrangements.

CONCLUSIONS

Our study explored the genetic alterations in epithelioid and spindle cell components in metaplastic thymoma. Furthermore, YAP1-MAML2 gene rearrangements emerged as a potential diagnostic biomarker helpful for distinguishing metaplastic thymoma from type A and micronodular thymoma with lymphoid stroma.

Establishment of a Plasticity-Associated Risk Model Based on a SOX2- and SOX9-Related Gene Set in Head and Neck Squamous Cell Carcinoma

Recent studies highlighted SOX2 and SOX9 as key determinants for cancer-cell plasticity and demonstrated that cisplatin-induced adaptation in oral squamous cell carcinoma (SCC) is acquired by an inverse regulation of both transcription factors. However, the association between SOX2/SOX9-related genetic programs with risk factors and genetic or epigenetic alterations in primary head and neck SCC (HNSCC), and their prognostic value is largely unknown.Here, we identified differentially-expressed genes (DEG) related to SOX2 and SOX9 transcription in The Cancer Genome Atlas (TCGA)-HNSC, which enable clustering of patients into groups with distinct clinical features and survival. A prognostic risk model was established by LASSO Cox regression based on expression patterns of DEGs in TCGA-HNSC (training cohort), and was confirmed in independent HNSCC validation cohorts as well as other cancer cohorts from TCGA. Differences in the mutational landscape among risk groups of TCGA-HNSC demonstrated an enrichment of truncating NSD1 mutations for the low-risk group and elucidated DNA methylation as modulator of SOX2 expression. Gene set variation analysis (GSVA) revealed differences in several oncogenic pathways among risk groups, including upregulation of gene sets related to oncogenic KRAS signaling for the high-risk group. Finally, in silico drug screen analysis revealed numerous compounds targeting EGFR signaling with significantly lower efficacy for cancer cell lines with a higher risk phenotype, but also indicated potential vulnerabilities. IMPLICATIONS: The established risk model identifies patients with primary HNSCC, but also other cancers at a higher risk for treatment failure, who might benefit from a therapy targeting SOX2/SOX9-related gene regulatory and signaling networks.

Review of applications of CRISPR-Cas9 gene-editing technology in cancer research

Characterized by multiple complex mutations, including activation by oncogenes and inhibition by tumor suppressors, cancer is one of the leading causes of death. Application of CRISPR-Cas9 gene-editing technology in cancer research has aroused great interest, promoting the exploration of the molecular mechanism of cancer progression and development of precise therapy. CRISPR-Cas9 gene-editing technology provides a solid basis for identifying driver and passenger mutations in cancer genomes, which is of great value in genetic screening and for developing cancer models and treatments. This article reviews the current applications of CRISPR-Cas9 gene-editing technology in various cancer studies, the challenges faced, and the existing solutions, highlighting the potential of this technology for cancer treatment.

CELLector: Genomics-Guided Selection of Cancer In Vitro Models

Selecting appropriate cancer models is a key prerequisite for maximizing translational potential and clinical relevance of in vitro oncology studies. We developed CELLector: an R package and R Shiny application allowing researchers to select the most relevant cancer cell lines in a patient-genomic-guided fashion. CELLector leverages tumor genomics to identify recurrent subtypes with associated genomic signatures. It then evaluates these signatures in cancer cell lines to prioritize their selection. This enables users to choose appropriate in vitro models for inclusion or exclusion in retrospective analyses and future studies. Moreover, this allows bridging outcomes from cancer cell line screens to precisely defined sub-cohorts of primary tumors. Here, we demonstrate the usefulness and applicability of CELLector, showing how it can aid prioritization of in vitro models for future development and unveil patient-derived multivariate prognostic and therapeutic markers. CELLector is freely available at https://ot-cellector.shinyapps.io/CELLector_App/ (code at https://github.com/francescojm/CELLector and https://github.com/francescojm/CELLector_App).

A JAK/STAT-mediated inflammatory signaling cascade drives oncogenesis in AF10-rearranged AML

Leukemias bearing fusions of the AF10/MLLT10 gene are associated with poor prognosis, and therapies targeting these fusion proteins (FPs) are lacking. To understand mechanisms underlying AF10 fusion-mediated leukemogenesis, we generated inducible mouse models of acute myeloid leukemia (AML) driven by the most common AF10 FPs, PICALM/CALM-AF10 and KMT2A/MLL-AF10, and performed comprehensive characterization of the disease using transcriptomic, epigenomic, proteomic, and functional genomic approaches. Our studies provide a detailed map of gene networks and protein interactors associated with key AF10 fusions involved in leukemia. Specifically, we report that AF10 fusions activate a cascade of JAK/STAT-mediated inflammatory signaling through direct recruitment of JAK1 kinase. Inhibition of the JAK/STAT signaling by genetic Jak1 deletion or through pharmacological JAK/STAT inhibition elicited potent antioncogenic effects in mouse and human models of AF10 fusion AML. Collectively, our study identifies JAK1 as a tractable therapeutic target in AF10-rearranged leukemias.

Preclinical models as patients' avatars for precision medicine in colorectal cancer: past and future challenges

Colorectal cancer (CRC) is a complex and heterogeneous disease, characterized by dismal prognosis and low survival rate in the advanced (metastatic) stage. During the last decade, the establishment of novel preclinical models, leading to the generation of translational discovery and validation platforms, has opened up a new scenario for the clinical practice of CRC patients. To bridge the results developed at the bench with the medical decision process, the ideal model should be easily scalable, reliable to predict treatment responses, and flexibly adapted for various applications in the research. As such, the improved benefit of novel therapies being tested initially on valuable and reproducible preclinical models would lie in personalized treatment recommendations based on the biology and genomics of the patient's tumor with the overall aim to avoid overtreatment and unnecessary toxicity. In this review, we summarize different in vitro and in vivo models, which proved efficacy in detection of novel CRC culprits and shed light into the biology and therapy of this complex disease. Even though cell lines and patient-derived xenografts remain the mainstay of colorectal cancer research, the field has been confidently shifting to the use of organoids as the most relevant preclinical model. Prioritization of organoids is supported by increasing body of evidence that these represent excellent tools worth further therapeutic explorations. In addition, novel preclinical models such as zebrafish avatars are emerging as useful tools for pharmacological interrogation. Finally, all available models represent complementary tools that can be utilized for precision medicine applications.

Mutations and Copy Number Abnormalities of Hippo Pathway Components in Human Cancers

The Hippo pathway is highly conserved from Drosophila to mammals. As a key regulator of cell proliferation, the Hippo pathway controls tissue homeostasis and has a major impact on tumorigenesis. The originally defined core components of the Hippo pathway in mammals include STK3/4, LATS1/2, YAP1/TAZ, TEAD, VGLL4, and NF2. However, for most of these genes, mutations and copy number variations are relatively uncommon in human cancer. Several other recently identified upstream and downstream regulators of Hippo signaling, including FAT1, SHANK2, Gq/11, and SWI/SNF complex, are more commonly dysregulated in human cancer at the genomic level. This review will discuss major genomic events in human cancer that enable cancer cells to escape the tumor-suppressive effects of Hippo signaling.

Assessing Consistency Across Functional Screening Datasets in Cancer Cells

Motivation

Many high-throughput screening studies have been carried out in cancer cell lines to identify therapeutic agents and targets. Existing consistency assessment studies only examined two datasets at a time, with conclusions based on a subset of carefully selected features rather than considering global consistency of all the data. However, poor concordance can still be observed for a large part of the data even when selected features are highly consistent.

Results

In this study, we assembled nine compound screening datasets and three functional genomics datasets. We derived direct measures of consistency as well as indirect measures of consistency based on association between functional data and copy number-adjusted gene expression data. These results have been integrated into a web application—the Functional Data Consistency Explorer (FDCE), to allow users to make queries and generate interactive visualizations so that functional data consistency can be assessed for individual features of interest.

Availability and implementation

The FDCE web tool and we have developed and the functional data consistency measures we have generated are available at https://lccl.shinyapps.io/FDCE/.

Supplementary information

Supplementary data are available at Bioinformatics online.