Poly(ADP-ribose) polymerase inhibitors (PARPi) have greatly improved survival of cancer patients harboring BRCA1 mutations. However, therapy resistance develops via either restoration of homologous recombination or replication fork stabilization. Therapeutic targets to overcome PARPi resistance are critically needed. We identified the deubiquitinase USP37 as a key determinant of PARPi toxicity in BRCA1-deficient cells via whole-genome CRISPR screens. USP37 ablation enhanced PARPi sensitivity in BRCA1-deficient cells and also overcame PARPi resistance due to 53BP1 loss. USP37 interacts with and deubiquitinates replication protein A (RPA) at stalled replication forks to limit excessive RPA accumulation, progressive RPA exhaustion, and the conversion of RPA-coated single-stranded DNAs to DNA double-strand breaks. Moreover, USP37 limits helicase-like transcription factor (HLTF) accumulation at replication forks and thus prevents MRE11-dependent fork degradation upon replication stress. Depletion of HLTF reversed the replication-associated damage observed in USP37 knockout cells. Our data suggest that USP37 protects replication fork stability by counteracting HLTF function and promotes survival of BRCA1-deficient cells, making it a promising drug target to overcome PARPi resistance in BRCA1-deficient tumors.

Cell cycle checkpoints are the regulatory mechanisms that secure the strict order of cellular events for cell division that ensure genome integrity. It has been proposed that mitosis initiation depends on the completion of DNA replication, which must be tightly controlled to guarantee genome duplication. Contrary to these conventional hypotheses, we showed here that cells were able to enter mitosis without completion of DNA replication. Although DNA replication was not completed in cells upon depletion of MCM2, CDC45 or GINS4, these under-replicated cells progressed into mitosis, which led to cell death. These unexpected results challenge current model and suggest the absence of a cell cycle checkpoint that monitors the completion of DNA replication.

BRCA1, a breast cancer susceptibility gene, has emerged as a central mediator that brings together multiple signaling complexes in response to DNA damage. The A, B, and C complexes of BRCA1, which are formed based on their phosphorylation-dependent interactions with the BRCA1-C-terminal domains, contribute to the roles of BRCA1 in DNA repair and cell cycle checkpoint control. However, their functions in DNA damage response remain to be fully appreciated. Specifically, there has been no systematic investigation of the roles of BRCA1-A, -B, and -C complexes in the regulation of BRCA1 localization and functions, in part because of cellular lethality associated with loss of CtIP protein, which is an essential component in BRCA1-C complex. To systematically investigate the functions of these complexes in DNA damage response, we depleted a key component in each of these complexes. We used the degradation tag system to inducibly deplete endogenous CtIP and obtained a series of RAP80/FANCJ/CtIP single-, double-, and triple-knockout cells. We showed that loss of BRCA1-B/FANCJ and BRCA1-C/CtIP, but not BRCA1-A/RAP80, resulted in reduced cell proliferation and increased sensitivity to DNA damage. BRCA1-C/CtIP and BRCA1-A/RAP80 were involved in BRCA1 recruitment to sites of DNA damage. However, BRCA1-A/RAP80 was not essential for damage-induced BRCA1 localization. Instead, RAP80/H2AX and CtIP have redundant roles in BRCA1 recruitment. Altogether, our systematic analysis uncovers functional differences between BRCA1-A, -B, and -C complexes and provides new insights into the roles of these BRCA1-associated protein complexes in DNA damage response and DNA repair.

Poly(ADP-ribose)ylation or PARylation by PAR polymerase 1 (PARP1) and dePARylation by poly(ADP-ribose) glycohydrolase (PARG) are equally important for the dynamic regulation of DNA damage response. PARG, the most active dePARylation enzyme, is recruited to sites of DNA damage via pADPr-dependent and PCNA-dependent mechanisms. Targeting dePARylation is considered an alternative strategy to overcome PARP inhibitor resistance. However, precisely how dePARylation functions in normal unperturbed cells remains elusive. To address this challenge, we conducted multiple CRISPR screens and revealed that dePARylation of S phase pADPr by PARG is essential for cell viability. Loss of dePARylation activity initially induced S phase-specific pADPr signaling, which resulted from unligated Okazaki fragments and eventually led to uncontrolled pADPr accumulation and PARP1/2-dependent cytotoxicity. Moreover, we demonstrated that proteins involved in Okazaki fragment ligation and/or base excision repair regulate pADPr signaling and cell death induced by PARG inhibition. In addition, we determined that PARG expression is critical for cellular sensitivity to PARG inhibition. Additionally, we revealed that PARG is essential for cell survival by suppressing pADPr. Collectively, our data not only identify an essential role for PARG in normal proliferating cells but also provide a potential biomarker for the further development of PARG inhibitors in cancer therapy.

Radiation therapy (RT) is one of the most commonly used anticancer therapies. However, the landscape of cellular response to irradiation, especially to a single high-dose irradiation, remains largely unknown. In this study, we performed a whole-genome CRISPR loss-of-function screen and revealed temporal inherent and acquired responses to RT. Specifically, we found that loss of the IL1R1 pathway led to cellular resistance to RT. This is in part because of the involvement of radiation-induced IL1R1-dependent transcriptional regulation, which relies on the NF-κB pathway. Moreover, the mitochondrial anti-apoptotic pathway, particularly the BCL2L1 gene, is crucially important for cell survival after radiation. BCL2L1 inhibition combined with RT dramatically impeded tumor growth in several breast cancer cell lines and syngeneic models. Taken together, our results suggest that the combination of an apoptosis inhibitor such as a BCL2L1 inhibitor with RT may represent a promising anticancer strategy for solid cancers including breast cancer.

CRISPR-Cas9 system has emerged as an effective tool for sequence-specific gene knockout through non-homologous end joining (NHEJ). However, the inefficient precise editing of genome sequences remains a challenge for clinical treatment. Herein, an erythrocyte membrane (EM)-camouflaged and tumor microenvironment (TME)-responsive nanosystem was constructed to achieve synergistic combination of enhanced Cas9 ribonucleoprotein (RNP) gene editing efficiency and telomere dysfunction, and thus precise induced tumor inhibition. The EM-camouflaged nanosystem escaped from the reticuloendothelial system (RES) and was endocytosed by tumor cells. Azidothymidine (AZT) was gradually released as the erythrocyte shell ablation, which competitively prevented the binding of single nucleotides to the telomere replication template TR, terminate the extension of the telomerase DNA chain. Additionally, Cas9 RNP was released through disulfide bond cleavage and entered into the nucleus to realize genome editing of telomerase reverse transcriptase (TERT) gene. Simultaneous, AZT enhanced NHEJ pathway to improve the gene editing efficiency of Cas9 RNP, which further promoted the progressive telomere erosion and thus induced tumor inhibition. Overall, this biomembrane-camouflaged nanosystem realizes enhanced Cas9 RNP gene editing efficiency with high-level biosafety and promotes tumor senescence by triggering telomere disorder, which provides strategy for improving the gene editing efficiency to induce senescence of tumor cells.

Immune evasion is not only critical for tumor initiation and progression, but also determines the efficacy of immunotherapies. Through iterative in vivo CRISPR screens with seven syngeneic tumor models, we identified core and context-dependent immune evasion pathways across cancer types. This valuable high-confidence dataset is available for the further understanding of tumor intrinsic immunomodulators, which may lead to the discovery of effective anticancer therapeutic targets. With a focus on triple-negative breast cancer (TNBC), we found thatMgaknock-out significantly enhances antitumor immunity and inhibits tumor growth. Transcriptomics and single-cell RNA sequencing analyses revealed that Mga influences various immune-related pathways in the tumor microenvironment. Our findings suggest that Mga may play a role in modulating the tumor immune landscape, though the precise mechanisms require further investigation. Interestingly, we observed that low MGA expression in breast cancer patients correlates with a favorable prognosis, particularly in those with active interferon-γ signaling. These observations provide insights into tumor immune escape mechanisms and suggest that further exploration of MGA’s function could potentially lead to effective therapeutic strategies in TNBC.

An individual’s health trajectory is most influenced by personal lifestyle choices made regularly and frequently. It is now possible to measure, store, and analyze both multimodal lifestyle signals as well as multimodal physiological and behavioral health signals perpetually. Moreover, it is possible to model the effects of lifestyle precisely on health signals by collecting a variety of longitudinal data. These actions provide the inputs that affect changes in the health state of an individual based on their lifestyle decisions. With the advent of modern relatively inexpensive and common multi-modal data streams and sensing technologies, individuals now have large amounts of data and information about themselves that have the potential to transform decision-making in day-to-day life for health improvement. Multimodal analytics and contextual prediction and retrieval allow this data to make the best decisions to keep the health state optimal while making good lifestyle choices. This critical problem requires making a large variety of data constantly useful, contextually relevant, and most importantly useful in personalized decision-making. In order to address this challenge, we implement a generalized Personal Health Navigation (PHN) framework. PHN takes individuals toward their personal health goals through a system that perpetually digests multi-modal data streams from diverse sources, estimates current health status, computes the best route through intermediate states utilizing personal models, and guides the best inputs that carry a user towards their goal. We show the effectiveness of this approach using two examples in cardiac health. First, we prospectively test a knowledge-infused cardiovascular PHN system with a pilot prospective experiment of 41 users. Second, we create a data-driven personalized model on cardiovascular exercise response variability on a smartwatch data set of 33,269 real-world users. We conclude with critical challenges in multi-modal computing for PHN systems that require deep future investigation.

Etoposide (ETO) is an anticancer drug that targets topoisomerase II (TOP2). It stabilizes a normally transient TOP2–DNA covalent complex (TOP2cc), thus leading to DNA double-strand breaks (DSBs). Tyrosyl-DNA phosphodiesterases two (TDP2) is directly involved in the repair of TOP2cc by removing phosphotyrosyl peptides from 5′-termini of DSBs. Recent studies suggest that additional factors are required for TOP2cc repair, which include the proteasome and the zinc finger protein associated with TDP2 and TOP2, named ZATT. ZATT may alter the conformation of TOP2cc in a way that renders the accessibility of TDP2 for TOP2cc removal. In this study, our genome-wide clustered regularly interspaced short palindromic repeats (CRISPR) screens revealed that ZATT also has a TDP2-independent role in promoting cell survival following ETO treatment. ZATT KO cells showed relatively higher ETO sensitivity than TDP2-KO cells, and ZATT/TDP2 DKO cells displayed additive hypersensitivity to ETO treatment. The study using a series of deletion mutants of ZATT determined that the N-terminal 1–168 residues of ZATT are required for interaction with TOP2 and this interaction is critical to ETO sensitivity. Moreover, depletion of ZATT resulted in accelerated TOP2 degradation after ETO or cycloheximide (CHX) treatment, suggesting that ZATT may increase TOP2 stability and likely participate in TOP2 turnover. Taken together, this study suggests that ZATT is a critical determinant that dictates responses to ETO treatment and targeting. ZATT is a promising strategy to increase ETO efficacy for cancer therapy.

Type II topoisomerases (TOP2) form transient TOP2 cleavage complexes (TOP2ccs) during their catalytic cycle to relieve topological stress. TOP2ccs are covalently linked TOP2-DNA intermediates that are reversible but can be trapped by TOP2 poisons. Trapped TOP2ccs block transactions on DNA and generate genotoxic stress, which are the mechanisms of action of TOP2 poisons. How cells avoid TOP2cc accumulation remains largely unknown. In this study, we uncovered RAD54 like 2 (RAD54L2) as a key factor that mediates a TOP2-specific DNA damage avoidance pathway. RAD54L2 deficiency conferred unique sensitivity to treatment with TOP2 poisons. RAD54L2 interacted with TOP2A/TOP2B and ZATT/ZNF451 and promoted the turnover of TOP2 from DNA with or without TOP2 poisons. Additionally, inhibition of proteasome activity enhanced the chromatin binding of RAD54L2, which in turn led to the removal of TOP2 from chromatin. In conclusion, we propose that RAD54L2-mediated TOP2 turnover is critically important for the avoidance of potential TOP2-linked DNA damage under physiological conditions and in response to TOP2 poisons.

DNA damage-activated signaling pathways are critical for coordinating multiple cellular processes, which must be tightly regulated to maintain genome stability. To provide a comprehensive and unbiased perspective of DNA damage response (DDR) signaling pathways, we performed 30 fluorescence-activated cell sorting (FACS)-based genome-wide CRISPR screens in human cell lines with antibodies recognizing distinct endogenous DNA damage signaling proteins to identify critical regulators involved in DDR. We discovered that proteasome-mediated processing is an early and prerequisite event for cells to trigger camptothecin- and etoposide-induced DDR signaling. Furthermore, we identified PRMT1 and PRMT5 as modulators that regulate ATM protein level. Moreover, we discovered that GNB1L is a key regulator of DDR signaling via its role as a co-chaperone specifically regulating PIKK proteins. Collectively, these screens offer a rich resource for further investigation of DDR, which may provide insight into strategies of targeting these DDR pathways to improve therapeutic outcomes.

The Clustered Regularly Interspaced Short Palindromic Repeats/CRISPR-associated protein 9 (CRISPR/Cas9) system, an RNA-based adaptive immune system found in bacteria and archaea, has catalyzed the development and application of a new generation of gene editing tools. Numerous studies have shown that this system can precisely target a wide range of human genes, including those associated with diseases such as cancer. In cancer research, the intricate genetic mutations in tumors have promoted extensive utilization of the CRISPR/Cas9 system due to its efficient and accurate gene editing capabilities. This includes improvements in Chimeric Antigen Receptor (CAR)-T-cell therapy, the establishment of tumor models, and gene and drug target screening. Such progress has propelled the investigation of cancer molecular mechanisms and the advancement of precision medicine. However, the therapeutic potential of genome editing remains underexplored, and lingering challenges could elevate the risk of additional genetic mutations. Here, we elucidate the fundamental principles of CRISPR/Cas9 gene editing and its practical applications in tumor research. We also briefly discuss the primary challenges faced by CRISPR technology and existing solutions, intending to enhance the efficacy of this gene editing therapy and shed light on the underlying mechanisms of tumors.

Image stitching is the process of stitching several images that overlap each other into a single, larger image. The traditional image stitching algorithm searches the feature points of the image, performs alignments, and constructs the projection transformation relationship. The traditional algorithm has a strong dependence on feature points; as such, if feature points are sparse or unevenly distributed in the scene, the stitching will be misaligned or even fail completely. In scenes with obvious parallaxes, the global homography projection transformation relationship cannot be used for image alignment. To address these problems, this paper proposes a method of image stitching based on fixed camera positions and a hierarchical projection method based on depth information. The method does not depend on the number and distribution of feature points, so it avoids the complexity of feature point detection. Additionally, the effect of parallax on stitching is eliminated to a certain extent. Our experiments showed that the proposed method based on the camera calibration model can achieve more robust stitching results when a scene has few feature points, uneven feature point distribution, or significant parallax.

Cell surface proteins play essential roles in various biological processes and are highly related to cancer development. They also serve as important markers for cell identity and targets for pharmacological intervention. Despite their great potentials in biomedical research, comprehensive functional analysis of cell surface proteins remains scarce. Here, with a de novo designed library targeting cell surface proteins, we performed in vivo CRISPR screens to evaluate the effects of cell surface proteins on tumor survival and proliferation. We found that Kirrel1 loss markedly promoted tumor growth in vivo. Moreover, KIRREL was significantly enriched in a separate CRISPR screen based on a specific Hippo pathway reporter. Further studies revealed that KIRREL binds directly to SAV1 to activate the Hippo tumor suppressor pathway. Together, our integrated screens reveal a cell surface tumor suppressor involved in the Hippo pathway and highlight the potential of these approaches in biomedical research.

Replication timing regulatory factor 1 (RIF1) acts downstream of p53-binding protein 53BP1 to inhibit the resection of DNA broken ends, which plays critical roles in determining the DNA double-strand break repair pathway choice between nonhomologous end joining and homologous recombination (HR). However, the mechanism by which this choice is made is not yet clear. In this study, we identified that histone chaperone protein ASF1 associates with RIF1 and regulates RIF1-dependent functions in the DNA damage response. Similar to loss of RIF1, we found that loss of ASF1 resulted in resistance to poly (ADP-ribose) polymerase (PARP) inhibition in BRCA1-deficient cells with restored HR and decreased telomere fusion in telomeric repeat-binding protein 2 (TRF2)-depleted cells. Moreover, we showed that these functions of ASF1 are dependent on its interaction with RIF1 but not on its histone chaperone activity. Thus, our study supports a new role for ASF1 in dictating double-strand break repair choice. Considering that the status of 53BP1-RIF1 axis is important in determining the outcome of PARP inhibitor-based therapy in BRCA1- or HR-deficient cancers, the identification of ASF1 function in this critical pathway uncovers an interesting connection between these S-phase events, which may reveal new strategies to overcome PARP inhibitor resistance.

The rapid deployment of facial biometric system has raised attention about their vulnerability to presentation attacks (PAs). Currently, due to the feature extraction capability of convolution neural network (CNN), it has achieved excellent results in most multi-modal face anti-spoofing (FAS) algorithms Similarly, we proposed multi-modal FAS using Channel Cross Fusion Network (CCFN) and Depth-wise Convolution (GDConv), FaceBagNets for short. The CCFN is utilized to cross-fuse multi-modal feature by using the pairwise cross approach before fusing multi-modal feature in the channel direction, and the GDConv replaces the global average pooling (GAP) to raise the performance. We also utilized the patch-based strategy to obtain richer feature, the random model feature erasing (RMFE) strategy to prevent the over-fitting and the squeeze-and-excitation network (SE-NET) to focus on key feature. Finally, we conducted extensive experiments on two multi-modal datasets, then verified the effectiveness of the CCFN and the GDConv. Much advanced results were acquired and outperformed most state-of-the-art methods.

Anticancer drugs, such as camptothecin (CPT), trap topoisomerase I (TOP1) on DNA and form TOP1 cleavage complexes (TOP1cc). Alternative repair pathways have been suggested in the repair of TOP1cc. However, how these pathways work with TDP1, a key repair enzyme that specifically hydrolyze the covalent bond between TOP1 catalytic tyrosine and the 3'-end of DNA and contribute to the repair of TOP1cc is poorly understood. Here, using unbiased whole-genome CRISPR screens and generation of co-deficient cells with TDP1 and other genes, we demonstrate that MUS81 is an important factor that mediates the generation of excess double-strand breaks (DSBs) in TDP1 KO cells. APEX1/2 are synthetic lethal with TDP1. However, deficiency of APEX1/2 does not reduce DSB formation in TDP1 KO cells. Together, our data suggest that TOP1cc can be either resolved directly by TDP1 or be converted into DSBs and repaired further by the Homologous Recombination (HR) pathway.

Exploiting cancer vulnerabilities is critical for the discovery of anticancer drugs. However, tumor suppressors cannot be directly targeted because of their loss of function. To uncover specific vulnerabilities for cells with deficiency in any given tumor suppressor(s), we performed genome-scale CRISPR loss-of-function screens using a panel of isogenic knockout cells we generated for 12 common tumor suppressors. Here, we provide a comprehensive and comparative dataset for genetic interactions between the whole-genome protein-coding genes and a panel of tumor suppressor genes, which allows us to uncover known and new high-confidence synthetic lethal interactions. Mining this dataset, we uncover essential paralog gene pairs, which could be a common mechanism for interpreting synthetic lethality. Moreover, we propose that some tumor suppressors could be targeted to suppress proliferation of cells with deficiency in other tumor suppressors. This dataset provides valuable information that can be further exploited for targeted cancer therapy.

The Notch signaling pathway controls cell growth, differentiation, and fate decisions, and its dysregulation has been linked to various human genetic disorders and cancers. To comprehensively understand the global organization of the Notch pathway and identify potential drug targets for Notch-related diseases, we established a protein interaction landscape for the human Notch pathway. By combining and analyzing genetic and phenotypic data with bioinformatics analysis, we greatly expanded this pathway and identified many key regulators, including low-density-lipoprotein-receptor-related protein 1 (LRP1). We demonstrated that LRP1 mediates the ubiquitination chain linkage switching of Delta ligands, which further affects ligand recycling, membrane localization, and stability. LRP1 inhibition led to Notch signaling inhibition and decreased tumorigenesis in leukemia models. Our study provides a glimpse into the Notch pathway interaction network and uncovers LRP1 as one critical regulator of the Notch pathway, as well as a possible therapeutic target for Notch-related cancers.

Host–virus protein–protein interactions play key roles in the life cycle of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2). We conducted a comprehensive interactome study between the virus and host cells using tandem affinity purification and proximity‐labeling strategies and identified 437 human proteins as the high‐confidence interacting proteins. Further characterization of these interactions and comparison to other large‐scale study of cellular responses to SARS‐CoV‐2 infection elucidated how distinct SARS‐CoV‐2 viral proteins participate in its life cycle. With these data mining, we discovered potential drug targets for the treatment of COVID‐19. The interactomes of two key SARS‐CoV‐2‐encoded viral proteins, NSP1 and N, were compared with the interactomes of their counterparts in other human coronaviruses. These comparisons not only revealed common host pathways these viruses manipulate for their survival, but also showed divergent protein–protein interactions that may explain differences in disease pathology. This comprehensive interactome of SARS‐CoV‐2 provides valuable resources for the understanding and treating of this disease.