A genome-wide RNAi screen identifies multiple synthetic lethal interactions with the Ras oncogene

The DNA Damage Response (DDR) landscape of endometrial cancer defines discrete disease subtypes and reveals therapeutic opportunities

Genome maintenance is an enabling characteristic that allows neoplastic cells to tolerate the inherent stresses of tumorigenesis and evade therapy-induced genotoxicity. Neoplastic cells also deploy many mis-expressed germ cell proteins termed Cancer Testes Antigens (CTAs) to promote genome maintenance and survival. Here, we present the first comprehensive characterization of the DNA Damage Response (DDR) and CTA transcriptional landscapes of endometrial cancer in relation to conventional histological and molecular subtypes. We show endometrial serous carcinoma (ESC), an aggressive endometrial cancer subtype, is defined by gene expression signatures comprising members of the Replication Fork Protection Complex (RFPC) and Fanconi Anemia (FA) pathway and CTAs with mitotic functions. DDR and CTA-based profiling also defines a subset of highly aggressive endometrioid endometrial carcinomas (EEC) with poor clinical outcomes that share similar profiles to ESC yet have distinct characteristics based on conventional histological and genomic features. Using an unbiased CRISPR-based genetic screen and a candidate gene approach, we confirm that DDR and CTA genes that constitute the ESC and related EEC gene signatures are required for proliferation and therapy-resistance of cultured endometrial cancer cells. Our study validates the use of DDR and CTA-based tumor classifiers and reveals new vulnerabilities of aggressive endometrial cancer where none currently exist.

MPASL: multi-perspective learning knowledge graph attention network for synthetic lethality prediction in human cancer

Synthetic lethality (SL) is widely used to discover the anti-cancer drug targets. However, the identification of SL interactions through wet experiments is costly and inefficient. Hence, the development of efficient and high-accuracy computational methods for SL interactions prediction is of great significance. In this study, we propose MPASL, a multi-perspective learning knowledge graph attention network to enhance synthetic lethality prediction. MPASL utilizes knowledge graph hierarchy propagation to explore multi-source neighbor nodes related to genes. The knowledge graph ripple propagation expands gene representations through existing gene SL preference sets. MPASL can learn the gene representations from both gene-entity perspective and entity-entity perspective. Specifically, based on the aggregation method, we learn to obtain gene-oriented entity embeddings. Then, the gene representations are refined by comparing the various layer-wise neighborhood features of entities using the discrepancy contrastive technique. Finally, the learned gene representation is applied in SL prediction. Experimental results demonstrated that MPASL outperforms several state-of-the-art methods. Additionally, case studies have validated the effectiveness of MPASL in identifying SL interactions between genes.

Onvansertib in Combination with FOLFIRI and Bevacizumab in Second-Line Treatment of KRAS-Mutant Metastatic Colorectal Cancer: A Phase Ib Clinical Study

PURPOSE

Onvansertib is a highly specific inhibitor of polo-like kinase 1 (PLK1), with demonstrated safety in solid tumors. We evaluated, preclinically and clinically, the potential of onvansertib in combination with chemotherapy as a therapeutic option for KRAS-mutant colorectal cancer.

PATIENTS AND METHODS

Preclinical activity of onvansertib was assessed (i) in vitro in KRAS wild-type and -mutant isogenic colorectal cancer cells and (ii) in vivo, in combination with irinotecan, in a KRAS-mutant xenograft model. Clinically, a phase Ib trial was conducted to investigate onvansertib at doses 12, 15, and 18 mg/m2 (days 1-5 and 14-19 of a 28-day cycle) in combination with FOLFIRI/bevacizumab (days 1 and 15) in patients with KRAS-mutant metastatic colorectal cancer who had prior oxaliplatin exposure. Safety, efficacy, and changes in circulating tumor DNA (ctDNA) were assessed.

RESULTS

In preclinical models, onvansertib displayed superior activity in KRAS-mutant than wild-type isogenic colorectal cancer cells and demonstrated potent antitumor activity in combination with irinotecan in vivo. Eighteen patients enrolled in the phase Ib study. Onvansertib recommended phase II dose was established at 15 mg/m2. Grade 3 and 4 adverse events (AE) represented 15% of all treatment-related AEs, with neutropenia being the most common. Partial responses were observed in 44% of patients, with a median duration of response of 9.5 months. Early ctDNA dynamics were predictive of treatment efficacy.

CONCLUSIONS

Onvansertib combined with FOLIFRI/bevacizumab exhibited manageable safety and promising efficacy in second-line treatment of patients with KRAS-mutant metastatic colorectal cancer. Further exploration of this combination therapy is ongoing. See related commentary by Stebbing and Bullock, p. 2005.

Polo-like Kinase 1 Inhibition in KRAS-Mutated Metastatic Colorectal Cancer

Inhibition of Polo-like kinase 1 (Plk1) is a promising new target and therapeutic strategy in metastatic colorectal cancer, especially those with KRAS mutations. New data support further development of onvansertib, and highlights the role of circulating tumor DNA in phase I clinical trials. See related article by Ahn et al., p. 2039.

mTORC1/S6K1 signaling promotes sustained oncogenic translation through modulating CRL3IBTK-mediated ubiquitination of eIF4A1 in cancer cells

Enhanced protein synthesis is a crucial molecular mechanism that allows cancer cells to survive, proliferate, metastasize, and develop resistance to anti-cancer treatments, and often arises as a consequence of increased signaling flux channeled to mRNA-bearing eukaryotic initiation factor 4F (eIF4F). However, the post-translational regulation of eIF4A1, an ATP-dependent RNA helicase and subunit of the eIF4F complex, is still poorly understood. Here, we demonstrate that IBTK, a substrate-binding adaptor of the Cullin 3-RING ubiquitin ligase (CRL3) complex, interacts with eIF4A1. The non-degradative ubiquitination of eIF4A1 catalyzed by the CRL3IBTK complex promotes cap-dependent translational initiation, nascent protein synthesis, oncogene expression, and cervical tumor cell growth both in vivo and in vitro. Moreover, we show that mTORC1 and S6K1, two key regulators of protein synthesis, directly phosphorylate IBTK to augment eIF4A1 ubiquitination and sustained oncogenic translation. This link between the CRL3IBTK complex and the mTORC1/S6K1 signaling pathway, which is frequently dysregulated in cancer, represents a promising target for anti-cancer therapies.

Targeting RAF dimers in RAS mutant tumors: From biology to clinic

RAS mutations occur in approximately 30% of tumors worldwide and have a poor prognosis due to limited therapies. Covalent targeting of KRAS G12C has achieved significant success in recent years, but there is still a lack of efficient therapeutic approaches for tumors with non-G12C KRAS mutations. A highly promising approach is to target the MAPK pathway downstream of RAS, with a particular focus on RAF kinases. First-generation RAF inhibitors have been authorized to treat BRAF mutant tumors for over a decade. However, their use in RAS-mutated tumors is not recommended due to the paradoxical ERK activation mainly caused by RAF dimerization. To address the issue of RAF dimerization, type II RAF inhibitors have emerged as leading candidates. Recent clinical studies have shown the initial effectiveness of these agents against RAS mutant tumors. Promisingly, type II RAF inhibitors in combination with MEK or ERK inhibitors have demonstrated impressive efficacy in RAS mutant tumors. This review aims to clarify the importance of RAF dimerization in cellular signaling and resistance to treatment in tumors with RAS mutations, as well as recent progress in therapeutic approaches to address the problem of RAF dimerization in RAS mutant tumors.

Identification of common genes and pathways between type 2 diabetes and COVID-19

Background

Numerous studies have reported a high incidence and risk of severe illness due to coronavirus disease 2019 (COVID-19) in patients with type 2 diabetes (T2DM). COVID-19 patients may experience elevated or decreased blood sugar levels and may even develop diabetes. However, the molecular mechanisms linking these two diseases remain unclear. This study aimed to identify the common genes and pathways between T2DM and COVID-19.

Methods

Two public datasets from the Gene Expression Omnibus (GEO) database (GSE95849 and GSE164805) were analyzed to identify differentially expressed genes (DEGs) in blood between people with and without T2DM and COVID-19. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed on the common DEGs. A protein-protein interaction (PPI) network was constructed to identify common genes, and their diagnostic performance was evaluated by receiver operating characteristic (ROC) curve analysis. Validation was performed on the GSE213313 and GSE15932 datasets. A gene co-expression network was constructed using the GeneMANIA database to explore interactions among core DEGs and their co-expressed genes. Finally, a microRNA (miRNA)-transcription factor (TF)-messenger RNA (mRNA) regulatory network was constructed based on the common feature genes.

Results

In the GSE95849 and GSE164805 datasets, 81 upregulated genes and 140 downregulated genes were identified. GO and KEGG enrichment analyses revealed that these DEGs were closely related to the negative regulation of phosphate metabolic processes, the positive regulation of mitotic nuclear division, T-cell co-stimulation, and lymphocyte co-stimulation. Four upregulated common genes (DHX15, USP14, COPS3, TYK2) and one downregulated common feature gene (RIOK2) were identified and showed good diagnostic accuracy for T2DM and COVID-19. The AUC values of DHX15, USP14, COPS3, TYK2, and RIOK2 in T2DM diagnosis were 0.931, 0.917, 0.986, 0.903, and 0.917, respectively. In COVID-19 diagnosis, the AUC values were 0.960, 0.860, 1.0, 0.9, and 0.90, respectively. Validation in the GSE213313 and GSE15932 datasets confirmed these results. The miRNA-TF-mRNA regulatory network showed that TYH2 was targeted by PITX1, PITX2, CRX, NFYA, SREBF1, RELB, NR1L2, and CEBP, whereas miR-124-3p regulates THK2, RIOK2, and USP14.

Conclusion

We identified five common feature genes (DHX15, USP14, COPS3, TYK2, and RIOK2) and their co-regulatory pathways between T2DM and COVID-19, which may provide new insights for further molecular mechanism studies.

Concurrent targeting of GSK3 and MEK as a therapeutic strategy to treat pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies worldwide. However, drug discovery for PDAC treatment has proven complicated, leading to stagnant therapeutic outcomes. Here, we identify Glycogen synthase kinase 3 (GSK3) as a therapeutic target through a whole-body genetic screening utilizing a '4-hit' Drosophila model mimicking the PDAC genotype. Reducing the gene dosage of GSK3 in a whole-body manner or knocking down GSK3 specifically in transformed cells suppressed 4-hit fly lethality, similar to Mitogen-activated protein kinase kinase (MEK), the therapeutic target in PDAC we have recently reported. Consistently, a combination of the GSK3 inhibitor CHIR99021 and the MEK inhibitor trametinib suppressed the phosphorylation of Polo-like kinase 1 (PLK1) as well as the growth of orthotopic human PDAC xenografts in mice. Additionally, reducing PLK1 genetically in 4-hit flies rescued their lethality. Our results reveal a therapeutic vulnerability in PDAC that offers a treatment opportunity for patients by inhibiting multiple targets.

Molecular panorama of therapy resistance in prostate cancer: a pre-clinical and bioinformatics analysis for clinical translation

Prostate cancer (PCa) is a malignant disorder of prostate gland being asymptomatic in early stages and high metastatic potential in advanced stages. The chemotherapy and surgical resection have provided favourable prognosis of PCa patients, but advanced and aggressive forms of PCa including CRPC and AVPC lack response to therapy properly, and therefore, prognosis of patients is deteriorated. At the advanced stages, PCa cells do not respond to chemotherapy and radiotherapy in a satisfactory level, and therefore, therapy resistance is emerged. Molecular profile analysis of PCa cells reveals the apoptosis suppression, pro-survival autophagy induction, and EMT induction as factors in escalating malignant of cancer cells and development of therapy resistance. The dysregulation in molecular profile of PCa including upregulation of STAT3 and PI3K/Akt, downregulation of STAT3, and aberrant expression of non-coding RNAs are determining factor for response of cancer cells to chemotherapy. Because of prevalence of drug resistance in PCa, combination therapy including co-utilization of anti-cancer drugs and nanotherapeutic approaches has been suggested in PCa therapy. As a result of increase in DNA damage repair, PCa cells induce radioresistance and RelB overexpression prevents irradiation-mediated cell death. Similar to chemotherapy, nanomaterials are promising for promoting radiosensitivity through delivery of cargo, improving accumulation in PCa cells, and targeting survival-related pathways. In respect to emergence of immunotherapy as a new tool in PCa suppression, tumour cells are able to increase PD-L1 expression and inactivate NK cells in mediating immune evasion. The bioinformatics analysis for evaluation of drug resistance-related genes has been performed.

The function of BCL11B in base excision repair contributes to its dual role as an oncogene and a haplo-insufficient tumor suppressor gene

Genetic studies in mice and human cancers established BCL11B as a haploinsufficient tumor suppressor gene. Paradoxically, BCL11B is overexpressed in some human cancers where its knockdown is synthetic lethal. We identified the BCL11B protein in a proximity-dependent biotinylation screen performed with the DNA glycosylase NTHL1. In vitro DNA repair assays demonstrated that both BCL11B and a small recombinant BCL11B213-560 protein lacking transcription regulation potential can stimulate the enzymatic activities of two base excision repair (BER) enzymes: NTHL1 and Pol β. In cells, BCL11B is rapidly recruited to sites of DNA damage caused by laser microirradiation. BCL11B knockdown delays, whereas ectopic expression of BCL11B213-560 accelerates, the repair of oxidative DNA damage. Inactivation of one BCL11B allele in TK6 lymphoblastoid cells causes an increase in spontaneous and radiation-induced mutation rates. In turn, ectopic expression of BCL11B213-560 cooperates with the RAS oncogene in cell transformation by reducing DNA damage and cellular senescence. These findings indicate that BCL11B functions as a BER accessory factor, safeguarding normal cells from acquiring mutations. Paradoxically, it also enables the survival of cancer cells that would otherwise undergo senescence or apoptosis due to oxidative DNA damage resulting from the elevated production of reactive oxygen species.

Pathway-driven analysis of synthetic lethal interactions in cancer using perturbation screens

Synthetic lethality offers a promising approach for developing effective therapeutic interventions in cancer when direct targeting of driver genes is impractical. In this study, we comprehensively analyzed large-scale CRISPR, shRNA, and PRISM screens to identify potential synthetic lethal (SL) interactions in pan-cancer and 12 individual cancer types, using a new computational framework that leverages the biological function and signaling pathway information of key driver genes to mitigate the confounding effects of background genetic alterations in different cancer cell lines. This approach has successfully identified several putative SL interactions, including KRAS-MAP3K2 and APC-TCF7L2 in pan cancer, and CCND1-METTL1, TP53-FRS3, SMO-MDM2, and CCNE1-MTOR in liver, blood, skin, and gastric cancers, respectively. In addition, we proposed several FDA-approved cancer-targeted drugs for various cancer types through PRISM drug screens, such as cabazitaxel for VHL-mutated kidney cancer and alectinib for lung cancer with NRAS or KRAS mutations. Leveraging pathway information can enhance the concordance of shRNA and CRISPR screens and provide clinically relevant findings such as the potential efficacy of dasatinib, an inhibitor of SRC, for colorectal cancer patients with mutations in the WNT signaling pathway. These analyses revealed that taking signaling pathway information into account results in the identification of more promising SL interactions.

Oncogenic KRAS effector USP13 promotes metastasis in non-small cell lung cancer through deubiquitinating β-catenin

KRAS mutations are frequently detected in non-small cell lung cancers (NSCLCs). Although covalent KRASG12C inhibitors have been developed to treat KRASG12C-mutant cancers, effective treatments are still lacking for other KRAS-mutant NSCLCs. Thus, identifying a KRAS effector that confers poor prognosis would provide an alternative strategy for the treatment of KRAS-driven cancers. Here, we show that KRAS drives expression of deubiquitinase USP13 through Ras-responsive element-binding protein 1 (RREB1). Elevated USP13 promotes KRAS-mutant NSCLC metastasis, which is associated with poor prognosis in NSCLC patients. Mechanistically, USP13 interacts with and removes the K63-linked polyubiquitination of β-catenin at lysine 508, which enhances the binding between β-catenin and transcription factor TCF4. Importantly, we identify 2-methoxyestradiol as an effective inhibitor for USP13 from a natural compound library, and it could potently suppress the metastasis of KRAS-mutant NSCLC cells in vitro and in vivo. These findings identify USP13 as a therapeutic target for metastatic NSCLC with KRAS mutations.

Targeting ST8SIA6-AS1 counteracts KRASG12C inhibitor resistance through abolishing the reciprocal activation of PLK1/c-Myc signaling

BACKGROUND

KRASG12C inhibitors (KRASG12Ci) AMG510 and MRTX849 have shown promising efficacy in clinical trials and been approved for the treatment of KRASG12C-mutant cancers. However, the emergence of therapy-related drug resistance limits their long-term potential. This study aimed to identify the critical mediators and develop overcoming strategies.

METHODS

By using RNA sequencing, RT-qPCR and immunoblotting, we identified and validated the upregulation of c-Myc activity and the amplification of the long noncoding RNA ST8SIA6-AS1 in KRASG12Ci-resistant cells. The regulatory axis ST8SIA6-AS1/Polo-like kinase 1 (PLK1)/c-Myc was investigated by bioinformatics, RNA fluorescence in situ hybridization, RNA immunoprecipitation, RNA pull-down and chromatin immunoprecipitation. Gain/loss-of-function assays, cell viability assay, xenograft models, and IHC staining were conducted to evaluate the anti-cancer effects of co-inhibition of ST8SIA6-AS1/PLK1 pathway and KRAS both in vitro and in vivo.

RESULTS

KRASG12Ci sustainably decreased c-Myc levels in responsive cell lines but not in cell lines with intrinsic or acquired resistance to KRASG12Ci. PLK1 activation contributed to this ERK-independent c-Myc stability, which in turn directly induced PLK1 transcription, forming a positive feedback loop and conferring resistance to KRASG12Ci. ST8SIA6-AS1 was found significantly upregulated in resistant cells and facilitated the proliferation of KRASG12C-mutant cancers. ST8SIA6-AS1 bound to Aurora kinase A (Aurora A)/PLK1 and promoted Aurora A-mediated PLK1 phosphorylation. Concurrent targeting of KRAS and ST8SIA6-AS1/PLK1 signaling suppressed both ERK-dependent and -independent c-Myc expression, synergistically led to cell death and tumor regression and overcame KRASG12Ci resistance.

CONCLUSIONS

Our study deciphers that the axis of ST8SIA6-AS1/PLK1/c-Myc confers both intrinsic and acquired resistance to KRASG12Ci and represents a promising therapeutic target for combination strategies with KRASG12Ci in the treatment of KRASG12C-mutant cancers.

The RioK1 network determines p53 activity at multiple levels

By responding to a host of adverse conditions, ranging from DNA damage to viral infection, transcription factor p53 supports genomic stability, cellular health, and survival. Not surprisingly, tumours across the cancer spectrum carry mutations in p53, misexpress the protein, or dysregulate its activity. Several signalling pathways, many of which comprise oncogenic proteins, converge upon p53 to control its stability and activity. We here present the conserved kinase/ATPase RioK1 as an upstream factor that determines p53 activity at the DNA, RNA, and protein levels. It achieves this task by integrating the regulatory events that act on p53 into a coherent response circuit. We will also discuss how RIOK1 overexpression represents an alternative mechanism for cancers to inactivate p53, and how targeting RioK1 could eradicate malignancies that are driven by a dysregulated RioK1-p53 network.

Proteomic Analysis Reveals a PLK1-Dependent G2/M Degradation Program and Links PKA-AKAP2 to Cell Cycle Control

Targeted protein degradation by the ubiquitin-proteasome system is an essential mechanism regulating cellular division. The kinase PLK1 coordinates protein degradation at the G2/M phase of the cell cycle by promoting the binding of substrates to the E3 ubiquitin ligase SCFβTrCP. However, the magnitude to which PLK1 shapes the mitotic proteome has not been characterized. Combining deep, quantitative proteomics with pharmacologic PLK1 inhibition (PLK1i), we identified more than 200 proteins whose abundances were increased by PLK1i at G2/M. We validate many new PLK1-regulated proteins, including several substrates of the cell cycle E3 SCFCyclin F, demonstrating that PLK1 promotes proteolysis through at least two distinct SCF-family E3 ligases. Further, we found that the protein kinase A anchoring protein AKAP2 is cell cycle regulated and that its mitotic degradation is dependent on the PLK1/βTrCP-signaling axis. Interactome analysis revealed that the strongest interactors of AKAP2 function in signaling networks regulating proliferation, including MAPK, AKT, and Hippo. Altogether, our data demonstrate that PLK1 coordinates a widespread program of protein breakdown at G2/M. We propose that dynamic proteolytic changes mediated by PLK1 integrate proliferative signals with the core cell cycle machinery during cell division. This has potential implications in malignancies where PLK1 is aberrantly regulated.

Precision Oncology Comes of Age: Designing Best-in-Class Small Molecules by Integrating Two Decades of Advances in Chemistry, Target Biology, and Data Science

Small-molecule drugs have enabled the practice of precision oncology for genetically defined patient populations since the first approval of imatinib in 2001. Scientific and technology advances over this 20-year period have driven the evolution of cancer biology, medicinal chemistry, and data science. Collectively, these advances provide tools to more consistently design best-in-class small-molecule drugs against known, previously undruggable, and novel cancer targets. The integration of these tools and their customization in the hands of skilled drug hunters will be necessary to enable the discovery of transformational therapies for patients across a wider spectrum of cancers.

SIGNIFICANCE

Target-centric small-molecule drug discovery necessitates the consideration of multiple approaches to identify chemical matter that can be optimized into drug candidates. To do this successfully and consistently, drug hunters require a comprehensive toolbox to avoid following the "law of instrument" or Maslow's hammer concept where only one tool is applied regardless of the requirements of the task. Combining our ever-increasing understanding of cancer and cancer targets with the technological advances in drug discovery described below will accelerate the next generation of small-molecule drugs in oncology.

A new wave of innovations within the DNA damage response

Genome instability has been identified as one of the enabling hallmarks in cancer. DNA damage response (DDR) network is responsible for maintenance of genome integrity in cells. As cancer cells frequently carry DDR gene deficiencies or suffer from replicative stress, targeting DDR processes could induce excessive DNA damages (or unrepaired DNA) that eventually lead to cell death. Poly (ADP-ribose) polymerase (PARP) inhibitors have brought impressive benefit to patients with breast cancer gene (BRCA) mutation or homologous recombination deficiency (HRD), which proves the concept of synthetic lethality in cancer treatment. Moreover, the other two scenarios of DDR inhibitor application, replication stress and combination with chemo- or radio- therapy, are under active clinical exploration. In this review, we revisited the progress of DDR targeting therapy beyond the launched first-generation PARP inhibitors. Next generation PARP1 selective inhibitors, which could maintain the efficacy while mitigating side effects, may diversify the application scenarios of PARP inhibitor in clinic. Albeit with unavoidable on-mechanism toxicities, several small molecules targeting DNA damage checkpoints (gatekeepers) have shown great promise in preliminary clinical results, which may warrant further evaluations. In addition, inhibitors for other DNA repair pathways (caretakers) are also under active preclinical or clinical development. With these progresses and efforts, we envision that a new wave of innovations within DDR has come of age.

A super-enhancer-regulated RNA-binding protein cascade drives pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy in need of new therapeutic options. Using unbiased analyses of super-enhancers (SEs) as sentinels of core genes involved in cell-specific function, here we uncover a druggable SE-mediated RNA-binding protein (RBP) cascade that supports PDAC growth through enhanced mRNA translation. This cascade is driven by a SE associated with the RBP heterogeneous nuclear ribonucleoprotein F, which stabilizes protein arginine methyltransferase 1 (PRMT1) to, in turn, control the translational mediator ubiquitin-associated protein 2-like. All three of these genes and the regulatory SE are essential for PDAC growth and coordinately regulated by the Myc oncogene. In line with this, modulation of the RBP network by PRMT1 inhibition reveals a unique vulnerability in Myc-high PDAC patient organoids and markedly reduces tumor growth in male mice. Our study highlights a functional link between epigenetic regulation and mRNA translation and identifies components that comprise unexpected therapeutic targets for PDAC.

MAGCN: A Multiple Attention Graph Convolution Networks for Predicting Synthetic Lethality

Synthetic lethality (SL) is a potential cancer therapeutic strategy and drug discovery. Computational approaches to identify synthetic lethality genes have become an effective complement to wet experiments which are time consuming and costly. Graph convolutional networks (GCN) has been utilized to such prediction task as be good at capturing the neighborhood dependency in a graph. However, it is still a lack of the mechanism of aggregating the complementary neighboring information from various heterogeneous graphs. Here, we propose the Multiple Attention Graph Convolution Networks for predicting synthetic lethality (MAGCN). First, we obtain the functional similarity features and topological structure features of genes from different data sources respectively, such as Gene Ontology data and Protein-Protein Interaction. Then, graph convolutional network is utilized to accumulate the knowledge from neighbor nodes according to synthetic lethal associations. Meanwhile, we propose a multiple graphs attention model and construct a multiple graphs attention network to learn the contribution factors of different graphs to generate embedded representation by aggregating these graphs. Finally, the generated feature matrix is decoded to predict potential synthetic lethal interaction. Experimental results show that MAGCN is superior to other baseline methods. Case study demonstrates the ability of MAGCN to predict human SL gene pairs.

Specific inhibition of an anticancer target, polo-like kinase 1, by allosterically dismantling its mechanism of substrate recognition

Polo-like kinase 1 (Plk1) is considered an attractive target for anticancer therapy. Over the years, studies on the noncatalytic polo-box domain (PBD) of Plk1 have raised the expectation of generating highly specific protein-protein interaction inhibitors. However, the molecular nature of the canonical PBD-dependent interaction, which requires extensive water network-mediated interactions with its phospholigands, has hampered efforts to identify small molecules suitable for Plk1 PBD drug discovery. Here, we report the identification of the first allosteric inhibitor of Plk1 PBD, called Allopole, a prodrug that can disrupt intracellular interactions between PBD and its cognate phospholigands, delocalize Plk1 from centrosomes and kinetochores, and induce mitotic block and cancer cell killing. At the structural level, its unmasked active form, Allopole-A, bound to a deep Trp-Phe-lined pocket occluded by a latch-like loop, whose adjoining region was required for securely retaining a ligand anchored to the phospho-binding cleft. Allopole-A binding completely dislodged the L2 loop, an event that appeared sufficient to trigger the dissociation of a phospholigand and inhibit PBD-dependent Plk1 function during mitosis. Given Allopole's high specificity and antiproliferative potency, this study is expected to open an unexplored avenue for developing Plk1 PBD-specific anticancer therapeutic agents.

Trinity of inflammation, innate immune cells and cross-talk of signalling pathways in tumour microenvironment

Unresolved inflammation is a pathological consequence of persistent inflammatory stimulus and perturbation in regulatory mechanisms. It increases the risk of tumour development and orchestrates all stages of tumorigenesis in selected organs. In certain cancers, inflammatory processes create the appropriate conditions for neoplastic transformation. While in other types, oncogenic changes pave the way for an inflammatory microenvironment that leads to tumour development. Of interest, hallmarks of tumour-promoting and cancer-associated inflammation are striking similar, sharing a complex network of stromal (fibroblasts and vascular cells) and inflammatory immune cells that collectively form the tumour microenvironment (TME). The cross-talks of signalling pathways initially developed to support homeostasis, change their role, and promote atypical proliferation, survival, angiogenesis, and subversion of adaptive immunity in TME. These transcriptional and regulatory pathways invariably contribute to cancer-promoting inflammation in chronic inflammatory disorders and foster "smouldering" inflammation in the microenvironment of various tumour types. Besides identifying common target sites of numerous cancer types, signalling programs and their cross-talks governing immune cells' plasticity and functional diversity can be used to develop new fate-mapping and lineage-tracing mechanisms. Here, we review the vital molecular mechanisms and pathways that establish the connection between inflammation and tumour development, progression, and metastasis. We also discussed the cross-talks between signalling pathways and devised strategies focusing on these interaction mechanisms to harness synthetic lethal drug combinations for targeted cancer therapy.

Genetic enhancers of partial PLK1 inhibition reveal hypersensitivity to kinetochore perturbations

Polo-like kinase 1 (PLK1) is a serine/threonine kinase required for mitosis and cytokinesis. As cancer cells are often hypersensitive to partial PLK1 inactivation, chemical inhibitors of PLK1 have been developed and tested in clinical trials. However, these small molecule inhibitors alone are not completely effective. PLK1 promotes numerous molecular and cellular events in the cell division cycle and it is unclear which of these events most crucially depend on PLK1 activity. We used a CRISPR-based genome-wide screening strategy to identify genes whose inactivation enhances cell proliferation defects upon partial chemical inhibition of PLK1. Genes identified encode proteins that are functionally linked to PLK1 in multiple ways, most notably factors that promote centromere and kinetochore function. Loss of the kinesin KIF18A or the outer kinetochore protein SKA1 in PLK1-compromised cells resulted in mitotic defects, activation of the spindle assembly checkpoint and nuclear reassembly defects. We also show that PLK1-dependent CENP-A loading at centromeres is extremely sensitive to partial PLK1 inhibition. Our results suggest that partial inhibition of PLK1 compromises the integrity and function of the centromere/kinetochore complex, rendering cells hypersensitive to different kinetochore perturbations. We propose that KIF18A is a promising target for combinatorial therapies with PLK1 inhibitors.

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

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

Identification of acquired Notch3 dependency in metastatic Head and Neck Cancer

During cancer development, tumor cells acquire changes that enable them to invade surrounding tissues and seed metastasis at distant sites. These changes contribute to the aggressiveness of metastatic cancer and interfere with success of therapy. Our comprehensive analysis of "matched" pairs of HNSCC lines derived from primary tumors and corresponding metastatic sites identified several components of Notch3 signaling that are differentially expressed and/or altered in metastatic lines and confer a dependency on this pathway. These components were also shown to be differentially expressed between early and late stages of tumors in a TMA constructed from over 200 HNSCC patients. Finally, we show that suppression of Notch3 improves survival in mice in both subcutaneous and orthotopic models of metastatic HNSCC. Novel treatments targeting components of this pathway may prove effective in targeting metastatic HNSCC cells alone or in combination with conventional therapies.

The role of noncoding RNAs in metabolic reprogramming of cancer cells

Metabolic reprogramming is a well-known feature of cancer that allows malignant cells to alter metabolic reactions and nutrient uptake, thereby promoting tumor growth and spread. It has been discovered that noncoding RNAs (ncRNAs), including microRNA (miRNA), long noncoding RNA (lncRNA), and circular RNA (circRNA), have a role in a variety of biological functions, control physiologic and developmental processes, and even influence disease. They have been recognized in numerous cancer types as tumor suppressors and oncogenic agents. The role of ncRNAs in the metabolic reprogramming of cancer cells has recently been noticed. We examine this subject, with an emphasis on the metabolism of glucose, lipids, and amino acids, and highlight the therapeutic use of targeting ncRNAs in cancer treatment.

Targeting Myc-driven stress addiction in colorectal cancer

MYC is a proto-oncogene that encodes a powerful regulator of transcription and cellular programs essential for normal development, as well as the growth and survival of various types of cancer cells. MYC rearrangement and amplification is a common cause of hematologic malignancies. In epithelial cancers such as colorectal cancer, genetic alterations in MYC are rare. Activation of Wnt, ERK/MAPK, and PI3K/mTOR pathways dramatically increases Myc levels through enhanced transcription, translation, and protein stability. Elevated Myc promotes stress adaptation, metabolic reprogramming, and immune evasion to drive cancer development and therapeutic resistance through broad changes in transcriptional and translational landscapes. Despite intense interest and effort, Myc remains a difficult drug target. Deregulation of Myc and its targets has profound effects that vary depending on the type of cancer and the context. Here, we summarize recent advances in the mechanistic understanding of Myc-driven oncogenesis centered around mRNA translation and proteostress. Promising strategies and agents under development to target Myc are also discussed with a focus on colorectal cancer.

HIGD2A silencing impairs hepatocellular carcinoma growth via inhibiting mitochondrial function and the MAPK/ERK pathway

BACKGROUND

The Hypoxia inducible gene domain family member 2A (HIGD2A) protein is indispensable for the assembly of the mitochondrial respiratory supercomplex, which has been implicated in cell proliferation and cell survival under hypoxic conditions. Because the liver has a naturally low oxygen microenvironment, the role of HIGD2A in the development of hepatocellular carcinoma (HCC) remains largely unknown.

METHODS

Gene expression data and clinical information were obtained from multiple public databases. A lentivirus-mediated gene knockdown approach was conducted to explore the function and mechanism of HIGD2A activity in HCC cells. In vivo and in vitro assays were performed to investigate the biological roles of HIGD2A.

RESULTS

HIGD2A was overexpressed in HCC tissues and cell lines and was associated with a worse prognosis. Silencing HIGD2A expression significantly attenuated cell proliferation and migration, caused S-phase cell cycle arrest, and decreased tumor formation in nude mice. Mechanistically, HIGD2A depletion greatly decreased cellular ATP levels by disrupting mitochondrial ATP production. Moreover, HIGD2A knockdown cells displayed impaired mitochondrial function, such as mitochondrial fusion, increased expression of the mitochondrial stress response protein, and decreased oxygen consumption. Furthermore, knockdown of HIGD2A markedly attenuated the activation of the MAPK/ERK pathway.

CONCLUSIONS

HIGD2A promoted liver cancer cell growth by fueling mitochondrial ATP synthesis and activating the MAPK/ERK pathway, suggested that targeting HIGD2A may represent a new strategy for HCC therapy.

Critical Non-Covalent Binding Intermediate for an Allosteric Covalent Inhibitor of SUMO E1

Post-translational modifications by small ubiquitin-like modifiers (SUMOs) are dysregulated in many types of cancers. The SUMO E1 enzyme has recently been suggested as a new immuno-oncology target. COH000 was recently identified as a highly specific allosteric covalent inhibitor of SUMO E1. However, a marked discrepancy was found between the X-ray structure of the covalent COH000-bound SUMO E1 complex and the available structure-activity relationship (SAR) data of inhibitor analogues due to unresolved noncovalent protein-ligand interactions. Here, we have investigated noncovalent interactions between COH000 and SUMO E1 during inhibitor dissociation through novel Ligand Gaussian accelerated molecular dynamics (LiGaMD) simulations. Our simulations have identified a critical low-energy non-covalent binding intermediate conformation of COH000 that agreed excellently with published and new SAR data of the COH000 analogues, which were otherwise inconsistent with the X-ray structure. Altogether, our biochemical experiments and LiGaMD simulations have uncovered a critical non-covalent binding intermediate during allosteric inhibition of the SUMO E1 complex.

Depleting the 19S proteasome regulatory PSMD1 subunit as a cancer therapy strategy

BACKGROUND

Proteasome inhibitors are in use in treating certain types of cancers. These drugs inhibit the catalytic activity of the 20S proteasome, shared by all the different proteasome complexes. Inhibitors of the 26S-associated deubiquitinating activity explicitly inhibit the 26S proteasomal degradation of ubiquitinylated substrates. We have previously reported an alternative strategy that is based on reducing the 26S/20S ratio by depleting PSMD1, 6, and 11, the subunits of the 19S proteasome regulatory complex. Given the addiction of the many cancer types to a high 26S/20S ratio, the depletion strategy is highly effective in killing many aggressive cancer cell lines but not mouse and human immortalized and normal cells.

METHODS

We used two aggressive cell lines, MDA-MB-231, a triple-negative breast tumor cell line, and OVCAR8, a high-grade ovary adenocarcinoma. Cell culture, mouse MDA-MB-231, OVCAR8 xenografts, and patient-derived ovarian cancer xenograft (PDX) models were transduced with lentivectors expressing PSMD1 shRNA. Tumor size was measured to follow treatment efficacy.

RESULTS

Using different experimental strategies of expressing shRNA, we found that PSMD1 depletion, either by expressing PSMD1 shRNA in an inducible manner or in a constitutive manner, robustly inhibited MDA-MB-231, and OVCAR8 xenograft tumor growth. Furthermore, the PSMD1 depletion strategy compromised the growth of the PDX of primary ovarian cancer.

CONCLUSION

Our results suggest that reducing the 26S/20S ratio might be a valuable strategy for treating drug-resistant aggressive types of cancers.

Systematic assessment of prognostic molecular features across cancers

Precision oncology promises accurate prediction of disease trajectories by utilizing molecular features of tumors. We present a systematic analysis of the prognostic potential of diverse molecular features across large cancer cohorts. We find that the mRNA expression of biologically coherent sets of genes (modules) is substantially more predictive of patient survival than single-locus genomic and transcriptomic aberrations. Extending our analysis beyond existing curated gene modules, we find a large novel class of highly prognostic DNA/RNA cis-regulatory modules associated with dynamic gene expression within cancers. Remarkably, in more than 82% of cancers, modules substantially improve survival stratification compared with conventional clinical factors and prominent genomic aberrations. The prognostic potential of cancer modules generalizes to external cohorts better than conventionally used single-gene features. Finally, a machine-learning framework demonstrates the combined predictive power of multiple modules, yielding prognostic models that perform substantially better than existing histopathological and clinical factors in common use.

Combining Raman spectroscopy and machine learning to assist early diagnosis of gastric cancer

Gastric cancers, with gastric adenocarcinoma (GAC) as the most common histological type, cause quite a few of deaths. In order to improve the survival rate after GAC treatment, it is important to develop a method for early detection and therapy support of GAC. Raman spectroscopy is a potential tool for probing cancer cell due to its real-time and non-destructive measurements without any additional reagents. In this study, we use Raman spectroscopy to examine GAC samples, and distinguish cancerous gastric mucosa from normal gastric mucosa. Average Raman spectra of two groups show differences at 750 cm^-1, 1004 cm^-1, 1449 cm^-1, 1089-1128 cm^-1, 1311-1367 cm^-1 and 1585-1665 cm^-1, These peaks were assigned to cytochrome c, phenylalanine, phospholipid, collagen, lipid, and unsaturated fatty acid respectively. Furthermore, we build a SENet-LSTM model to realize the automatic classification of cancerous gastric mucosa and normal gastric mucosa, with all preprocessed Raman spectra in the range of 400-1800 cm^-1 as input. An accuracy 96.20% was achieved. Besides, by using masking method, we found the Raman spectral features which determine the classification and explore the explainability of the classification model. The results are consistent with the conclusions obtained from the average spectrum. All results indicate it is potential for pre-cancerous screening to combine Raman spectroscopy and machine learning.

SLGNN: synthetic lethality prediction in human cancers based on factor-aware knowledge graph neural network

MOTIVATION

Synthetic lethality (SL) is a form of genetic interaction that can selectively kill cancer cells without damaging normal cells. Exploiting this mechanism is gaining popularity in the field of targeted cancer therapy and anticancer drug development. Due to the limitations of identifying SL interactions from laboratory experiments, an increasing number of research groups are devising computational prediction methods to guide the discovery of potential SL pairs. Although existing methods have attempted to capture the underlying mechanisms of SL interactions, methods that have a deeper understanding of and attempt to explain SL mechanisms still need to be developed.

RESULTS

In this work, we propose a novel SL prediction method, SLGNN. This method is based on the following assumption: SL interactions are caused by different molecular events or biological processes, which we define as SL-related factors that lead to SL interactions. SLGNN, apart from identifying SL interaction pairs, also models the preferences of genes for different SL-related factors, making the results more interpretable for biologists and clinicians. SLGNN consists of three steps: first, we model the combinations of relationships in the gene-related knowledge graph as the SL-related factors. Next, we derive initial embeddings of genes through an explicit message aggregation process of the knowledge graph. Finally, we derive the final gene embeddings through an SL graph, constructed using known SL gene pairs, utilizing factor-based message aggregation. At this stage, a supervised end-to-end training model is used for SL interaction prediction. Based on experimental results, the proposed SLGNN model outperforms all current state-of-the-art SL prediction methods and provides better interpretability.

AVAILABILITY AND IMPLEMENTATION

SLGNN is freely available at https://github.com/zy972014452/SLGNN.

Novel mutant KRAS addiction signature predicts response to the combination of ERBB and MEK inhibitors in lung and pancreatic cancers

KRAS mutations are prevalent in pancreatic and lung cancers, but not all mutant (mt) KRAS tumors are addicted to mt KRAS. Here, we discovered a 30-gene transcriptome signature "KDS30" that encodes a novel EGFR/ERBB2-driven signaling network and predicts mt KRAS, but not NRAS or HRAS, oncogene addiction. High KDS30 tumors from mt KRAS lung and pancreatic cancer patients are enriched in genes upregulated by EGFR, ERBB2, mt KRAS or MEK. EGFR/ERBB2 (neratinib) and MEK (cobimetinib) inhibitor combination inhibits tumor growth and prolongs mouse survival in high, but not low, KDS30 mt KRAS lung and pancreatic xenografts, and is synergistic only in high KDS30 mt KRAS patient-derived organoids. Furthermore, mt KRAS high KDS30 lung and pancreatic cancer patients live significantly shorter lives than those with low KDS30. Thus, KDS30 can identify lung and pancreatic cancer patients whose tumors are addicted to mt KRAS, and predicts EGFR/ERBB2 and MEK inhibitor combination response.

Evolutionary and cellular analysis of the 'dark' pseudokinase PSKH2

Pseudokinases, so named because they lack one or more conserved canonical amino acids that define their catalytically active relatives, have evolved a variety of biological functions in both prokaryotic and eukaryotic organisms. Human PSKH2 is closely related to the canonical kinase PSKH1, which maps to the CAMK family of protein kinases. Primates encode PSKH2 in the form of a pseudokinase, which is predicted to be catalytically inactive due to loss of the invariant catalytic Asp residue. Although the biological role(s) of vertebrate PSKH2 proteins remains unclear, we previously identified species-level adaptions in PSKH2 that have led to the appearance of kinase or pseudokinase variants in vertebrate genomes alongside a canonical PSKH1 paralog. In this paper we confirm that, as predicted, PSKH2 lacks detectable protein phosphotransferase activity, and exploit structural informatics, biochemistry and cellular proteomics to begin to characterise vertebrate PSKH2 orthologues. AlphaFold 2-based structural analysis predicts functional roles for both the PSKH2 N- and C-regions that flank the pseudokinase domain core, and cellular truncation analysis confirms that the N-terminal domain, which contains a conserved myristoylation site, is required for both stable human PSKH2 expression and localisation to a membrane-rich subcellular fraction containing mitochondrial proteins. Using mass spectrometry-based proteomics, we confirm that human PSKH2 is part of a cellular mitochondrial protein network, and that its expression is regulated through client-status within the HSP90/Cdc37 molecular chaperone system. HSP90 interactions are mediated through binding to the PSKH2 C-terminal tail, leading us to predict that this region might act as both a cis and trans regulatory element, driving outputs linked to the PSKH2 pseudokinase domain that are important for functional signalling.

ahctf1 and kras mutations combine to amplify oncogenic stress and restrict liver overgrowth in a zebrafish model of hepatocellular carcinoma

The nucleoporin (NUP) ELYS, encoded by AHCTF1, is a large multifunctional protein with essential roles in nuclear pore assembly and mitosis. Using both larval and adult zebrafish models of hepatocellular carcinoma (HCC), in which the expression of an inducible mutant kras transgene (kras^G12V) drives hepatocyte-specific hyperplasia and liver enlargement, we show that reducing ahctf1 gene dosage by 50% markedly decreases liver volume, while non-hyperplastic tissues are unaffected. We demonstrate that in the context of cancer, ahctf1 heterozygosity impairs nuclear pore formation, mitotic spindle assembly, and chromosome segregation, leading to DNA damage and activation of a Tp53-dependent transcriptional programme that induces cell death and cell cycle arrest. Heterozygous expression of both ahctf1 and ranbp2 (encoding a second nucleoporin), or treatment of heterozygous ahctf1 larvae with the nucleocytoplasmic transport inhibitor, Selinexor, completely blocks kras^G12V-driven hepatocyte hyperplasia. Gene expression analysis of patient samples in the liver hepatocellular carcinoma (LIHC) dataset in The Cancer Genome Atlas shows that high expression of one or more of the transcripts encoding the 10 components of the NUP107-160 subcomplex, which includes AHCTF1, is positively correlated with worse overall survival. These results provide a strong and feasible rationale for the development of novel cancer therapeutics that target ELYS function and suggest potential avenues for effective combinatorial treatments.

Multi-view graph convolutional network for cancer cell-specific synthetic lethality prediction

Synthetic lethal (SL) genetic interactions have been regarded as a promising focus for investigating potential targeted therapeutics to tackle cancer. However, the costly investment of time and labor associated with wet-lab experimental screenings to discover potential SL relationships motivates the development of computational methods. Although graph neural network (GNN) models have performed well in the prediction of SL gene pairs, existing GNN-based models are not designed for predicting cancer cell-specific SL interactions that are more relevant to experimental validation in vitro. Besides, neither have existing methods fully utilized diverse graph representations of biological features to improve prediction performance. In this work, we propose MVGCN-iSL, a novel multi-view graph convolutional network (GCN) model to predict cancer cell-specific SL gene pairs, by incorporating five biological graph features and multi-omics data. Max pooling operation is applied to integrate five graph-specific representations obtained from GCN models. Afterwards, a deep neural network (DNN) model serves as the prediction module to predict the SL interactions in individual cancer cells (iSL). Extensive experiments have validated the model's successful integration of the multiple graph features and state-of-the-art performance in the prediction of potential SL gene pairs as well as generalization ability to novel genes.

Identification of kinases activated by multiple pro-angiogenic growth factors

Antiangiogenic therapy began as an effort to inhibit VEGF signaling, which was thought to be the sole factor driving tumor angiogenesis. It has become clear that there are more pro-angiogenic growth factors that can substitute for VEGF during tumor vascularization. This has led to the development of multi-kinase inhibitors which simultaneously target multiple growth factor receptors. These inhibitors perform better than monotherapies yet to date no multi-kinase inhibitor targets all receptors known to be involved in pro-angiogenic signaling and resistance inevitably occurs. Given the large number of pro-angiogenic growth factors identified, it may be impossible to simultaneously target all pro-angiogenic growth factor receptors. Here we search for kinase targets, some which may be intracellularly localized, that are critical in endothelial cell proliferation irrespective of the growth factor used. We develop a quantitative endothelial cell proliferation assay and combine it with "kinome regression" or KIR, a recently developed method capable of identifying kinases that influence a quantitative phenotype. We report the kinases implicated by KIR and provide orthogonal evidence of their importance in endothelial cell proliferation. Our approach may point to a new strategy to develop a more complete anti-angiogenic blockade.

Inhibitors of the PLK1 polo-box domain: drug design strategies and therapeutic opportunities in cancer

INTRODUCTION

Polo Like Kinase 1 (PLK1) is a key regulator of mitosis and its overexpression is frequently observed in a wide variety of human cancers, while often being associated with poor survival rates. Therefore, it is considered a potential and attractive target for cancer therapeutic development. The Polo like kinase family is characterized by the presence of a unique C terminal polobox domain (PBD) involved in regulating kinase activity and subcellular localization. Among the two functionally essential, druggable sites with distinct properties that PLK1 offers, targeting the PBD presents an alternative approach for therapeutic development.

AREAS COVERED

Significant progress has been made in progressing from the peptidic PBD inhibitors first identified, to peptidomimetic and recently drug-like small molecules. In this review, the rationale for targeting the PBD over the ATP binding site is discussed, along with recent progress, challenges, and outlook.

EXPERT OPINION

The PBD has emerged as a viable alternative target for the inhibition of PLK1, and progress has been made in using compounds to elucidate mechanistic aspects of activity regulation and in determining roles of the PBD. Studies have resulted in proof of concept of in vivo efficacy suggesting promise for PBD binders in clinical development.

RAS: Circuitry and therapeutic targeting

Cancer has affected the lives of millions worldwide and is truly regarded as a devastating disease process. Despite advanced understanding of the genomic underpinning of cancer development and progression, therapeutic challenges are still persistent. Among all the human cancers, around 33% are attributed to mutations in RAS oncogene, a crucial component of the signaling pathways. With time, our understanding of RAS circuitry has improved and now the fact that it activates several downstream effectors, depending on the type and grades of cancer has been established. The circuitry is controlled via post-transcriptional mechanisms and frequent distortions in these mechanisms lead to important metabolic as well as immunological states that favor cancer cells' growth, survival, plasticity and metastasis. Therefore, understanding RAS circuitry can help researchers/clinicians to develop novel and potent therapeutics that, in turn, can save the lives of patients suffering from RAS-mutant cancers. There are many challenges presented by resistance and the potential strategies with a particular focus on novel combinations for overcoming these, that could move beyond transitory responses in the direction of treatment. Here in this review, we will look at how understanding the circuitry of RAS can be put to use in making strategies for developing therapeutics against RAS- driven malignancies.

Synthetic lethal gene pairs: Experimental approaches and predictive models

Synthetic lethality (SL) refers to a genetic interaction in which the simultaneous perturbation of two genes leads to cell or organism death, whereas viability is maintained when only one of the pair is altered. The experimental exploration of these pairs and predictive modeling in computational biology contribute to our understanding of cancer biology and the development of cancer therapies. We extensively reviewed experimental technologies, public data sources, and predictive models in the study of synthetic lethal gene pairs and herein detail biological assumptions, experimental data, statistical models, and computational schemes of various predictive models, speculate regarding their influence on individual sample- and population-based synthetic lethal interactions, discuss the pros and cons of existing SL data and models, and highlight potential research directions in SL discovery.

Electrostatic anti-CD33-antibody-protamine nanocarriers as platform for a targeted treatment of acute myeloid leukemia

BACKGROUND

Acute myeloid leukemia (AML) is a fatal clonal hematopoietic malignancy, which results from the accumulation of several genetic aberrations in myeloid progenitor cells, with a worldwide 5-year survival prognosis of about 30%. Therefore, the development of more effective therapeutics with novel mode of action is urgently demanded. One common mutated gene in the AML is the DNA-methyltransferase DNMT3A whose function in the development and maintenance of AML is still unclear. To specifically target "undruggable" oncogenes, we initially invented an RNAi-based targeted therapy option that uses the internalization capacity of a colorectal cancer specific anti-EGFR-antibody bound to cationic protamine and the anionic siRNA. Here, we present a new experimental platform technology of molecular oncogene targeting in AML.

METHODS

Our AML-targeting system consists of an internalizing anti-CD33-antibody-protamine conjugate, which together with anionic molecules such as siRNA or ibrutinib-Cy3.5 and cationic free protamine spontaneously assembles into vesicular nanocarriers in aqueous solution. These nanocarriers were analyzed concerning their physical properties and relevant characteristics in vitro in cell lines and in vivo in xenograft tumor models and patient-derived xenograft leukemia models with the aim to prepare them for translation into clinical application.

RESULTS

The nanocarriers formed depend on a balanced electrostatic combination of the positively charged cationic protamine-conjugated anti-CD33 antibody, unbound cationic protamine and the anionic cargo. This nanocarrier transports its cargo safely into the AML target cells and has therapeutic activity against AML in vitro and in vivo. siRNAs directed specifically against two common mutated genes in the AML, the DNA-methyltransferase DNMT3A and FLT3-ITD lead to a reduction of clonal growth in vitro in AML cell lines and inhibit tumor growth in vivo in xenotransplanted cell lines. Moreover, oncogene knockdown of DNMT3A leads to increased survival of mice carrying leukemia patient-derived xenografts. Furthermore, an anionic derivative of the approved Bruton's kinase (BTK) inhibitor ibrutinib, ibrutinib-Cy3.5, is also transported by this nanocarrier into AML cells and decreases colony formation.

CONCLUSIONS

We report important results toward innovative personalized, targeted treatment options via electrostatic nanocarrier therapy in AML.

Non-genetic adaptive resistance to KRASG12C inhibition: EMT is not the only culprit

Adaptions to therapeutic pressures exerted on cancer cells enable malignant progression of the tumor, culminating in escape from programmed cell death and development of resistant diseases. A common form of cancer adaptation is non-genetic alterations that exploit mechanisms already present in cancer cells and do not require genetic modifications that can also lead to resistance mechanisms. Epithelial-to-mesenchymal transition (EMT) is one of the most prevalent mechanisms of adaptive drug resistance and resulting cancer treatment failure, driven by epigenetic reprogramming and EMT-specific transcription factors. A recent breakthrough in cancer treatment is the development of KRASG12C inhibitors, which herald a new era of therapy by knocking out a unique substitution of an oncogenic driver. However, these highly selective agents targeting KRASG12C, such as FDA-approved sotorasib (AMG510) and adagrasib (MRTX849), inevitably encounter multiple mechanisms of drug resistance. In addition to EMT, cancer cells can hijack or rewire the sophisticated signaling networks that physiologically control cell proliferation, growth, and differentiation to promote malignant cancer cell phenotypes, suggesting that inhibition of multiple interconnected signaling pathways may be required to block tumor progression on KRASG12C inhibitor therapy. Furthermore, the tumor microenvironment (TME) of cancer cells, such as tumor-infiltrating lymphocytes (TILs), contribute significantly to immune escape and tumor progression, suggesting a therapeutic approach that targets not only cancer cells but also the TME. Deciphering and targeting cancer adaptions promises mechanistic insights into tumor pathobiology and improved clinical management of KRASG12C-mutant cancer. This review presents recent advances in non-genetic adaptations leading to resistance to KRASG12C inhibitors, with a focus on oncogenic pathway rewiring, TME, and EMT.

New anti-cancer explorations based on metal ions

Due to the urgent demand for more anti-cancer methods, the new applications of metal ions in cancer have attracted increasing attention. Especially the three kinds of the new mode of cell death, including ferroptosis, calcicoptosis, and cuproptosis, are of great concern. Meanwhile, many metal ions have been found to induce cell death through different approaches, such as interfering with osmotic pressure, triggering biocatalysis, activating immune pathways, and generating the prooxidant effect. Therefore, varieties of new strategies based on the above approaches have been studied and applied for anti-cancer applications. Moreover, many contrast agents based on metal ions have gradually become the core components of the bioimaging technologies, such as MRI, CT, and fluorescence imaging, which exhibit guiding significance for cancer diagnosis. Besides, the new nano-theranostic platforms based on metal ions have experimentally shown efficient response to endogenous and exogenous stimuli, which realizes simultaneous cancer therapy and diagnosis through a more controlled nano-system. However, most metal-based agents have still been in the early stages, and controlled clinical trials are necessary to confirm or not the current expectations. This article will focus on these new explorations based on metal ions, hoping to provide some theoretical support for more anti-cancer ideas.

An investigation of Plk1 PBD inhibitor KBJK557 as a tumor growth suppressor in non-small cell lung cancer

Lung cancer is the second most commonly reported type of cancer worldwide. Approximately 80–85% of lung cancer occurrences are accounted by non-small cell lung cancer (NSCLC). Polo-like kinase-1 (Plk1) plays multiple roles in cell cycle progression and its overexpression is observed in majority of malignancies, including NSCLC. A combination of frontline drugs and inhibitors targeting the Plk kinase domain (KD) has been used to overcome drug resistance in NSCLC. Plk1 KD inhibitors are highly prone to cross-reactivity with similar kinases, eventually leading to undesirable side effects. Moreover, there have been no reports of Plk1 PBD inhibitors showing antitumorigenic effects on NSCLC cells or animal models so far. To address this issue herein, for the first time, our recently reported Plk1 PBD inhibitor KBJK557 was evaluated for the anticancer potential against NSCLC cells. KBJK557 displayed notable cytotoxic effects in A549, PC9, and H1975 cells. Mechanistic investigations revealed that KBJK557-treated cells underwent G2/M cell cycle arrest, triggering subsequent apoptosis. In vivo antitumorigenic activity in xenograft mice model demonstrates that KBJK557-treated mice showed a considerable decrease in tumor size, proving the significances of Plk1 in lung cancer. Collectively, this study demonstrates that KBJK557 can serve as a promising drug candidate for treating the lung cancer through Plk1 PBD inhibition.

The DNA repair function of BCL11A suppresses senescence and promotes continued proliferation of triple-negative breast cancer cells

We identified the BCL11A protein in a proximity-dependent biotinylation screen performed with the DNA glycosylase NTHL1. In vitro, DNA repair assays demonstrate that both BCL11A and a small recombinant BCL11A^160-520 protein that is devoid of DNA binding and transcription regulatory domains can stimulate the enzymatic activities of two base excision repair enzymes: NTHL1 and DNA Pol β. Increased DNA repair efficiency, in particular of the base excision repair pathway, is essential for many cancer cells to proliferate in the presence of elevated reactive oxygen species (ROS) produced by cancer-associated metabolic changes. BCL11A is highly expressed in triple-negative breast cancers (TNBC) where its knockdown was reported to reduce clonogenicity and cause tumour regression. We show that BCL11A knockdown in TNBC cells delays repair of oxidative DNA damage, increases the number of oxidized bases and abasic sites in genomic DNA, slows down proliferation and induces cellular senescence. These phenotypes are rescued by ectopic expression of the short BCL11A^160-520 protein. We further show that the BCL11A^160-520 protein accelerates the repair of oxidative DNA damage and cooperates with RAS in cell transformation assays, thereby enabling cells to avoid senescence and continue to proliferate in the presence of high ROS levels.

SLOAD: a comprehensive database of cancer-specific synthetic lethal interactions for precision cancer therapy via multi-omics analysis

Synthetic lethality has been widely concerned because of its potential role in cancer treatment, which can be harnessed to selectively kill cancer cells via identifying inactive genes in a specific cancer type and further targeting the corresponding synthetic lethal partners. Herein, to obtain cancer-specific synthetic lethal interactions, we aimed to predict genetic interactions via a pan-cancer analysis from multiple molecular levels using random forest and then develop a user-friendly database. First, based on collected public gene pairs with synthetic lethal interactions, candidate gene pairs were analyzed via integrating multi-omics data, mainly including DNA mutation, copy number variation, methylation and mRNA expression data. Then, integrated features were used to predict cancer-specific synthetic lethal interactions using random forest. Finally, SLOAD (http://www.tmliang.cn/SLOAD) was constructed via integrating these findings, which was a user-friendly database for data searching, browsing, downloading and analyzing. These results can provide candidate cancer-specific synthetic lethal interactions, which will contribute to drug designing in cancer treatment that can promote therapy strategies based on the principle of synthetic lethality.

Database URL http://www.tmliang.cn/SLOAD/

Targeting RAS in neuroblastoma: Is it possible?

Neuroblastoma is a common solid tumor in children and a leading cause of cancer death in children. Neuroblastoma exhibits genetic, morphological, and clinical heterogeneity that limits the efficacy of current monotherapies. With further research on neuroblastoma, the pathogenesis of neuroblastoma is found to be complex, and more and more treatment therapies are needed. The importance of personalized therapy is growing. Currently, various molecular features, including RAS mutations, are being used as targets for the development of new therapies for patients with neuroblastoma. A recent study found that RAS mutations are frequently present in recurrent neuroblastoma. RAS mutations have been shown to activate the MAPK pathway and play an important role in neuroblastoma. Treating RAS mutated neuroblastoma is a difficult challenge, but many preclinical studies have yielded effective results. At the same time, many of the therapies used to treat RAS mutated tumors also have good reference values for treating RAS mutated neuroblastoma. The success of KRAS-G12C inhibitors has greatly stimulated confidence in the direct suppression of RAS. This review describes the biological role of RAS and the frequency of RAS mutations in neuroblastoma. This paper focuses on the strategies, preclinical, and clinical progress of targeting carcinogenic RAS in neuroblastoma, and proposes possible prospects and challenges in the future.

A proteomic approach identifies isoform-specific and nucleotide-dependent RAS interactions

Active mutations in the RAS genes are found in ∼30% of human cancers. Although thought to have overlapping functions, RAS isoforms show preferential activation in human tumors, which prompted us to employ a comparative and quantitative proteomics approach to generate isoform-specific and nucleotide-dependent interactomes of the four RAS isoforms, KRAS4A, KRAS4B, HRAS, and NRAS. Many isoform-specific interacting proteins were identified, including HRAS-specific CARM1 and CHK1 and KRAS-specific PIP4K2C and IPO7. Comparing the interactomes of WT and constitutively active G12D mutant of RAS isoforms, we identified several potential previously unknown effector proteins of RAS, one of which was recently reported while this article was in preparation, RADIL. These interacting proteins play important roles as knockdown or pharmacological inhibition leads to potent inhibition of cancer cells. The HRAS-specific interacting protein CARM1 plays a role in HRAS-induced senescence, with CARM1 knockdown or inhibition selectively increasing senescence in HRAS-transformed cells but not in KRAS4B-transformed cells. By revealing new isoform-specific and nucleotide-dependent RAS interactors, the study here provides insights to help understand the overlapping functions of the RAS isoforms.

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RAS interactome uncovers isoform-specific and nucleotide-dependent interactors.

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Potential novel RAS effector proteins are introduced.

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RAS interactors are possible new targets for RAS-driven cancer cells.