Targeting cancer-specific vulnerabilities through synthetic lethality (SL) is an emerging paradigm in precision oncology. A SL strategy based on PARP inhibitors has demonstrated clinical efficacy. Advances in DNA damage response (DDR) uncover novel SL gene pairs. Beyond BRCA-PARP, emerging SL targets like ATR, ATM, DNA-PK, CHK1, WEE1, CDK12, RAD51, and RAD52 show clinical promise. Selective and bioavailable small molecule inhibitors have been developed to induce SL, but optimization for potency, specificity, and drug-like properties remains challenging. This article illuminated recent progress in the field of medicinal chemistry centered on the rational design of agents capable of eliciting SL specifically in neoplastic cells. It is envisioned that innovative strategies harnessing SL for small molecule design may unlock novel prospects for targeted cancer therapeutics going forward.

Statins, widely used cardiovascular drugs that lower cholesterol by inhibiting HMG-CoA reductase, have been increasingly recognized for their potential anticancer properties. This study elucidates the underlying mechanism, revealing that statins exploit Synthetic Lethality, a principle where the co-occurrence of two non-lethal events leads to cell death. Our computational analysis of approximately 37,000 SL pairs identified statins as potential drugs targeting genes involved in SL pairs with metastatic genes. In vitro validation on various cancer cell lines confirmed the anticancer efficacy of statins. This data-driven drug repurposing strategy provides a molecular basis for the anticancer effects of statins, offering translational opportunities in oncology.

Synthetic lethality (SL) has shown great promise for the discovery of novel targets in cancer. CRISPR double-knockout (CDKO) technologies can only screen several hundred genes and their combinations, but not genome-wide. Therefore, good SL prediction models are highly needed for genes and gene pairs selection in CDKO experiments. However, lack of scalable SL properties prevents generalizability of SL interactions to out-of-sample data, thereby hindering modeling efforts. In this paper, we recognize that SL connectivity is a scalable and generalizable SL property. We develop a novel two-step multilayer encoder for individual sample-specific SL prediction model (MLEC-iSL), which predicts SL connectivity first and SL interactions subsequently. MLEC-iSL has three encoders, namely, gene, graph, and transformer encoders. MLEC-iSL achieves high SL prediction performance in K562 (AUPR, 0.73; AUC, 0.72) and Jurkat (AUPR, 0.73; AUC, 0.71) cells, while no existing methods exceed 0.62 AUPR and AUC. The prediction performance of MLEC-iSL is validated in a CDKO experiment in 22Rv1 cells, yielding a 46.8% SL rate among 987 selected gene pairs. The screen also reveals SL dependency between apoptosis and mitosis cell death pathways.

BACKGROUND: Synthetic lethality (SL) emerges as a novel concept being explored to combat cancer progression and resistance to conventional therapy. Despite the efficacy of chemotherapy in select cases of colorectal cancer (CRC), a substantial proportion of patients encounter challenges, leading to an adverse prognosis of CRC patients. CRC-related SL genes offer a potential avenue for identifying therapeutic targets.
METHODS: CRC-related SL genes were obtained from the SynLethDB database. The bulk RNA sequencing data, mutation data, and clinical information for treated and untreated CRC patients were enrolled from the UCSC and GEO databases. The Tumor Immunology Single Cell Center database served as the repository for collecting and analyzing single-cell RNA sequencing data. The synergistic killing effect of SL genes and chemotherapeutic drugs on resistant cells was experimentally verified.
RESULTS: In the present study, pivotal SL genes associated with chemoresistance identified by using WGCNA and CRC patients categorized into two groups based on these genes. Variations between the groups were most pronounced in pathways associated with extracellular matrix remodeling. Further by integrating mutation data, five potential SL genes were discerned, which were highly expressed in the presence of TP53 or KRAS mutations, leading to a severely poor prognosis. Subsequent time series analysis revealed that the expression of GTF2H5 was gradually elevated at different stages of the transition from sensitive to resistant in CRC cells. Finally, it was preliminarily verified by experiments that GTF2H5 may play a key role in driving the drug-resistant transition within CRC cells.
CONCLUSIONS: The identification of SL genes that collaboratively interact with chemotherapeutic agents could provide new insights into solving the issue of chemotherapy resistance in CRC patients. And GTF2H5 wields a fundamental influence in inducing chemoresistance in CRC, which provided a potential therapeutic target for CRC.

Here we report that simultaneous inhibition of the three primary DNA damage recognition PI3 kinase-like kinases (PIKKs) -ATM, ATR, and DNA-PK- induces severe combinatorial synthetic lethality in mammalian cells. Utilizing Chinese hamster cell lines CHO and V79 and their respective PIKK mutants, we evaluated effects of inhibiting these three kinases on cell viability, DNA damage response, and chromosomal integrity. Our results demonstrate that while single or dual kinase inhibition increased cytotoxicity, inhibition of all three PIKKs results in significantly higher synergistic lethality, chromosomal aberrations, and DNA double-strand break (DSB) induction as calculated by their synergy scores. These findings suggest that the overlapping redundancy of ATM, ATR, and DNA-PK functions is critical for cell survival, and their combined inhibition greatly disrupts DNA damage signaling and repair processes, leading to cell death. This study provides insights into the potential of multi-targeted DDR kinase inhibition as an effective anticancer strategy, necessitating further research to elucidate underlying mechanisms and therapeutic applications.

Advanced epithelial ovarian cancer is the commonest cause of gynaecological cancer deaths. First-line treatment for advanced disease includes a combination of platinum-taxane chemotherapy (post-operatively or peri-operatively) and maximal debulking surgery whenever feasible. Initial response rate to chemotherapy is high (up to 80%) but most patients will develop recurrence (approximately 70-90%) and succumb to the disease. Recently, poly-ADP-ribose polymerase (PARP) inhibition (by drugs such as Olaparib, Niraparib or Rucaparib) directed synthetic lethality approach in BRCA germline mutant or platinum sensitive disease has generated real hope for patients. PARP inhibitor (PARPi) maintenance therapy can prolong survival but therapeutic response is not sustained due to intrinsic or acquired secondary resistance to PARPi therapy. Reversion of BRCA1/2 mutation can lead to clinical PARPi resistance in BRCA-germline mutated ovarian cancer. However, in the more common platinum sensitive sporadic HGSOC, the clinical mechanisms of development of PARPi resistance remains to be defined. Here we provide a comprehensive review of the current status of PARPi and the mechanisms of resistance to therapy.

Neurofibromatosis type 1 (NF1) is a genetic disorder caused by mutation of the NF1 gene that is associated with various symptoms, including the formation of benign tumors, called neurofibromas, within nerves. Drug treatments are currently limited. The mitogen-activated protein kinase kinase (MEK) inhibitor selumetinib is used for a subset of plexiform neurofibromas (PNs) but is not always effective and can cause side effects. Therefore, there is a clear need to discover new drugs to target NF1-deficient tumor cells. Using a Drosophila cell model of NF1, we performed synthetic lethal screens to identify novel drug targets. We identified 54 gene candidates, which were validated with variable dose analysis as a secondary screen. Pathways associated with five candidates could be targeted using existing drugs. Among these, chloroquine (CQ) and bafilomycin A1, known to target the autophagy pathway, showed the greatest potential for selectively killing NF1-deficient Drosophila cells. When further investigating autophagy-related genes, we found that 14 out of 30 genes tested had a synthetic lethal interaction with NF1. These 14 genes are involved in multiple aspects of the autophagy pathway and can be targeted with additional drugs that mediate the autophagy pathway, although CQ was the most effective. The lethal effect of autophagy inhibitors was conserved in a panel of human NF1-deficient Schwann cell lines, highlighting their translational potential. The effect of CQ was also conserved in a Drosophila NF1 in vivo model and in a xenografted NF1-deficient tumor cell line grown in mice, with CQ treatment resulting in a more significant reduction in tumor growth than selumetinib treatment. Furthermore, combined treatment with CQ and selumetinib resulted in a further reduction in NF1-deficient cell viability. In conclusion, NF1-deficient cells are vulnerable to disruption of the autophagy pathway. This pathway represents a promising target for the treatment of NF1-associated tumors, and we identified CQ as a candidate drug for the treatment of NF1 tumors.

BACKGROUND: Cancer is a major public health challenge globally. However, little is known about the evolution patterns of cancer research communities and the influencing factors of their research capacity and impact, which is affected not only by the social networks established through research collaboration but also by the knowledge networks in which the research projects are embedded.
METHODS: The focus of this study was narrowed to a specific topic - \'synthetic lethality\' - in cancer research. This field has seen vibrant growth and multidisciplinary collaboration in the past decade. Multi-level collaboration and knowledge networks were established and analysed on the basis of bibliometric data from \'synthetic lethality\'-related cancer research papers. Negative binomial regression analysis was further applied to explore how node attributes within these networks, along with other potential factors, affected paper citations, which are widely accepted as proxies for assessing research capacity and impact.
RESULTS: Our study revealed that the synthetic lethality-based cancer research field is characterized by a knowledge network with high integration, alongside a collaboration network exhibiting some clustering. We found significant correlations between certain factors and citation counts. Specifically, a leading status within the nation-level international collaboration network and industry involvement were both found to be significantly related to higher citations. In the individual-level collaboration networks, lead authors\' degree centrality has an inverted U-shaped relationship with citations, while their structural holes exhibit a positive and significant effect. Within the knowledge network, however, only measures of structural holes have a positive and significant effect on the number of citations.
CONCLUSIONS: To enhance cancer research capacity and impact, non-leading countries should take measures to enhance their international collaboration status. For early career researchers, increasing the number of collaborators seems to be more effective. University-industry cooperation should also be encouraged, enhancing the integration of human resources, technology, funding, research platforms and medical resources. Insights gained through this study also provide recommendations to researchers or administrators in designing future research directions from a knowledge network perspective. Focusing on unique issues especially interdisciplinary fields will improve output and influence their research work.

UNASSIGNED: Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest malignancies. An epigenetic-based synthetic lethal strategy provides a novel opportunity for PDAC treatment. Finding more DNA damage repair (DDR)-related or cell fate-related molecules with aberrant epigenetic changes is becoming very important. Family with sequence similarity 110C (FAM110C) is a cell fate-related gene and its function in cancer remains unclear.
UNASSIGNED: Seven cell lines, 34 cases of intraductal papillary mucinous neoplasm (IPMN), 15 cases of mucinous cystic neoplasm (MCN) and 284 cases of PDAC samples were employed. Methylation-specific PCR, western blot, CRISPR knockout, immunoprecipitation and a xenograft mouse model were used in this study.
UNASSIGNED: FAM110C is methylated in 41.18% (14/34) of IPMN, 46.67% (7/15) of MCN and 72.89% (207/284) of PDAC, with a progression trend from IPMN/MCN to pancreatic cancer (P = 0.0001, P = 0.0389). FAM110C methylation is significantly associated with poor overall survival (OS) (P = 0.0065) and is an independent prognostic marker for poor OS (P = 0.0159). FAM110C inhibits PDAC cells growth both in vitro and in vivo, serving as a novel tumor suppressor. FAM110C activates ATM and NHEJ signaling pathways by interacting with HMGB1. Loss of FAM110C expression sensitizes PDAC cells to VE-822 (an ATR inhibitor) and MK-8776 (a CHK1 inhibitor).
UNASSIGNED: FAM110C methylation is a potential diagnostic and prognostic marker in PDAC, and its epigenetic silencing sensitizes PDAC cells to ATR/CHK1 inhibitors.

Enzymes of the apolipoprotein B mRNA editing catalytic polypeptide like (APOBEC) family are cytosine deaminases that convert cytosine to uracil in DNA and RNA. Among these proteins, APOBEC3 sub-family members, APOBEC3A (A3A) and APOBEC3B (A3B), are prominent sources of mutagenesis in cancer cells. The aberrant expression of A3A and A3B in cancer cells leads to accumulation of mutations with specific single-base substitution (SBS) signatures, characterized by C→T and C→G changes, in a number of tumor types. In addition to fueling mutagenesis, A3A and A3B, particularly A3A, induce DNA replication stress, DNA damage, and chromosomal instability through their catalytic activities, triggering a range of cellular responses. Thus, A3A/B have emerged as key drivers of genome evolution during cancer development, contributing to tumorigenesis, tumor heterogeneity, and therapeutic resistance. Yet, the expression of A3A/B in cancer cells presents a cancer vulnerability that can be exploited therapeutically. In this review, we discuss the recent studies that shed light on the mechanisms regulating A3A expression and the impact of A3A in cancer. We also review recent advances in the development of A3A inhibitors and provide perspectives on the future directions of A3A research.