Adeno-to-squamous transition drives resistance to KRAS inhibition in LKB1 mutant lung cancer.

KRASG12C inhibitors (adagrasib and sotorasib) have shown clinical promise in targeting KRASG12C-mutated lung cancers; however, most patients eventually develop resistance. In lung patients with adenocarcinoma with KRASG12C and STK11/LKB1 co-mutations, we find an enrichment of the squamous cell carcinoma gene signature in pre-treatment biopsies correlates with a poor response to adagrasib. Studies of Lkb1-deficient KRASG12C and KrasG12D lung cancer mouse models and organoids treated with KRAS inhibitors reveal tumors invoke a lineage plasticity program, adeno-to-squamous transition (AST), that enables resistance to KRAS inhibition. Transcriptomic and epigenomic analyses reveal ΔNp63 drives AST and modulates response to KRAS inhibition. We identify an intermediate high-plastic cell state marked by expression of an AST plasticity signature and Krt6a. Notably, expression of the AST plasticity signature and KRT6A at baseline correlates with poor adagrasib responses. These data indicate the role of AST in KRAS inhibitor resistance and provide predictive biomarkers for KRAS-targeted therapies in lung cancer.

Aging-disturbed FUS phase transition impairs hematopoietic stem cells by altering chromatin structure.

ABSTRACT: Aged hematopoietic stem cells (HSCs) exhibit compromised reconstitution capacity. The molecular mechanisms behind this phenomenon are not fully understood. Here, we observed that the expression of FUS is increased in aged HSCs, and enforced FUS recapitulates the phenotype of aged HSCs through arginine-glycine-glycine-mediated aberrant FUS phase transition. By using Fus-gfp mice, we observed that FUShigh HSCs exhibit compromised FUS mobility and resemble aged HSCs both functionally and transcriptionally. The percentage of FUShigh HSCs is increased upon physiological aging and replication stress, and FUSlow HSCs of aged mice exhibit youthful function. Mechanistically, FUShigh HSCs exhibit a different global chromatin organization compared with FUSlow HSCs, which is observed in aged HSCs. Many topologically associating domains (TADs) are merged in aged HSCs because of the compromised binding of CCCTC-binding factor with chromatin, which is invoked by aberrant FUS condensates. It is notable that the transcriptional alteration between FUShigh and FUSlow HSCs originates from the merged TADs and is enriched in HSC aging-related genes. Collectively, this study reveals for the first time that aberrant FUS mobility promotes HSC aging by altering chromatin structure.

Chromatin-associated RNA Dictates the ecDNA Interactome in the Nucleus.

Extrachromosomal DNA (ecDNA) promotes cancer by driving copy number heterogeneity and amplifying oncogenes along with functional enhancers. More recent studies suggest two additional mechanisms for further enhancing their oncogenic potential, one via forming ecDNA hubs to augment oncogene expression 1 and the other through acting as portable enhancers to trans-activate target genes 2. However, it has remained entirely elusive about how ecDNA explores the three-dimensional space of the nucleus and whether different ecDNA have distinct interacting mechanisms. Here, by profiling the DNA-DNA and DNA-RNA interactomes in tumor cells harboring different types of ecDNAs in comparison with similarly amplified homogenously staining regions (HSRs) in the chromosome, we show that specific ecDNA interactome is dictated by ecDNA-borne nascent RNA. We demonstrate that the ecDNA co-amplifying PVT1 and MYC utilize nascent noncoding PVT1 transcripts to mediate specific trans-activation of both ecDNA and chromosomal genes. In contrast, the ecDNA amplifying EGFR is weak in this property because of more efficient splicing to remove chromatin-associated nascent RNA. These findings reveal a noncoding RNA-orchestrated program hijacked by cancer cells to enhance the functional impact of amplified oncogenes and associated regulatory elements.

Aging-induced pseudouridine synthase 10 impairs hematopoietic stem cells.

Aged hematopoietic stem cells (HSC) exhibit compromised reconstitution capacity and differentiation-bias towards myeloid lineage, however, the molecular mechanism behind it remains not fully understood. In this study, we observed that the expression of pseudouridine (Ψ) synthase 10 is increased in aged hematopoietic stem and progenitor cells (HSPC) and enforced protein of Ψ synthase 10 (PUS10) recapitulates the phenotype of aged HSC, which is not achieved by its Ψ synthase activity. Consistently, we observed no difference of transcribed RNA pseudouridylation profile between young and aged HSPC. No significant alteration of hematopoietic homeostasis and HSC function is observed in young Pus10-/- mice, while aged Pus10-/- mice exhibit mild alteration of hematopoietic homeostasis and HSC function. Moreover, we observed that PUS10 is ubiquitinated by E3 ubiquitin ligase CRL4DCAF1 complex and the increase of PUS10 in aged HSPC is due to aging-declined CRL4DCAF1- mediated ubiquitination degradation signaling. Taken together, this study for the first time evaluated the role of PUS10 in HSC aging and function, and provided a novel insight into HSC rejuvenation and its clinical application.

Development and Experimental Validation of a Novel Prognostic Signature for Gastric Cancer.

BACKGROUND: Gastric cancer is a malignant tumor with high morbidity and mortality. Therefore, the accurate recognition of prognostic molecular markers is the key to improving treatment efficacy and prognosis. METHODS: In this study, we developed a stable and robust signature through a series of processes using machine-learning approaches. This PRGS was further experimentally validated in clinical samples and a gastric cancer cell line. RESULTS: The PRGS is an independent risk factor for overall survival that performs reliably and has a robust utility. Notably, PRGS proteins promote cancer cell proliferation by regulating the cell cycle. Besides, the high-risk group displayed a lower tumor purity, higher immune cell infiltration, and lower oncogenic mutation than the low-PRGS group. CONCLUSIONS: This PRGS could be a powerful and robust tool to improve clinical outcomes for individual gastric cancer patients.

SOTIP is a versatile method for microenvironment modeling with spatial omics data.

The rapidly developing spatial omics generated datasets with diverse scales and modalities. However, most existing methods focus on modeling dynamics of single cells while ignore microenvironments (MEs). Here we present SOTIP (Spatial Omics mulTIPle-task analysis), a versatile method incorporating MEs and their interrelationships into a unified graph. Based on this graph, spatial heterogeneity quantification, spatial domain identification, differential microenvironment analysis, and other downstream tasks can be performed. We validate each module's accuracy, robustness, scalability and interpretability on various spatial omics datasets. In two independent mouse cerebral cortex spatial transcriptomics datasets, we reveal a gradient spatial heterogeneity pattern strongly correlated with the cortical depth. In human triple-negative breast cancer spatial proteomics datasets, we identify molecular polarizations and MEs associated with different patient survivals. Overall, by modeling biologically explainable MEs, SOTIP outperforms state-of-art methods and provides some perspectives for spatial omics data exploration and interpretation.

DAZL regulates proliferation of human primordial germ cells by direct binding to precursor miRNAs and enhances DICER processing activity.

Understanding the molecular and cellular mechanisms of human primordial germ cells (hPGCs) is essential in studying infertility and germ cell tumorigenesis. Many RNA-binding proteins (RBPs) and non-coding RNAs are specifically expressed and functional during hPGC developments. However, the roles and regulatory mechanisms of these RBPs and non-coding RNAs, such as microRNAs (miRNAs), in hPGCs remain elusive. In this study, we reported a new regulatory function of DAZL, a germ cell-specific RBP, in miRNA biogenesis and cell proliferation. First, DAZL co-localized with miRNA let-7a in human PGCs and up-regulated the levels of >100 mature miRNAs, including eight out of nine let-7 family, miR21, miR22, miR125, miR10 and miR199. Purified DAZL directly bound to the loops of precursor miRNAs with sequence specificity of GUU. The binding of DAZL to the precursor miRNA increased the maturation of miRNA by enhancing the cleavage activity of DICER. Furthermore, cell proliferation assay and cell cycle analysis confirmed that DAZL inhibited the proliferation of in vitro PGCs by promoting the maturation of these miRNAs. Evidently, the mature miRNAs up-regulated by DAZL silenced cell proliferation regulators including TRIM71. Moreover, DAZL inhibited germline tumor cell proliferation and teratoma formation. These results demonstrate that DAZL regulates hPGC proliferation by enhancing miRNA processing.

Prostate Cancer Transcriptomic Regulation by the Interplay of Germline Risk Alleles, Somatic Mutations, and 3D Genomic Architecture.

Prostate cancer is one of the most heritable human cancers. Genome-wide association studies have identified at least 185 prostate cancer germline risk alleles, most noncoding. We used integrative three-dimensional (3D) spatial genomics to identify the chromatin interaction targets of 45 prostate cancer risk alleles, 31 of which were associated with the transcriptional regulation of target genes in 565 localized prostate tumors. To supplement these 31, we verified transcriptional targets for 56 additional risk alleles using linear proximity and linkage disequilibrium analysis in localized prostate tumors. Some individual risk alleles influenced multiple target genes; others specifically influenced only distal genes while leaving proximal ones unaffected. Several risk alleles exhibited widespread germline-somatic interactions in transcriptional regulation, having different effects in tumors with loss of PTEN or RB1 relative to those without. These data clarify functional prostate cancer risk alleles in large linkage blocks and outline a strategy to model multidimensional transcriptional regulation. SIGNIFICANCE: Many prostate cancer germline risk alleles are enriched in the noncoding regions of the genome and are hypothesized to regulate transcription. We present a 3D genomics framework to unravel risk SNP function and describe the widespread germline-somatic interplay in transcription control. This article is highlighted in the In This Issue feature, p. 2711.

HPVMD-C: a disease-based mutation database of human papillomavirus in China.

Human papillomavirus (HPV) can cause condyloma acuminatum and cervical cancer. Some mutations of these viruses are closely related to the persistent infection of cervical cancer and are ideal cancer vaccine targets. Several databases have been developed to collect HPV sequences, but no HPV mutation database has been published. This paper reports a Chinese HPV mutation database (HPVMD-C), which contains 149 HPV genotypes, 468 HPV mutations, 3409 protein sequences, 4727 domains and 236 epitopes. We analyzed the mutation distribution among HPV genotypes, domains and epitopes. We designed a visualization tool to display these mutations, domains and epitopes and provided more detailed information about the disease, region and related literature. We also proposed an HPV genotype prediction tool, which can predict HPV carcinogenic or non-carcinogenic risk genotypes. We expect that HPVMD-C will complement the existing database and provide valuable resources for HPV vaccine research and cervical cancer treatment. HPVMD-C is freely available at Database URL: http://bioinfo.zstu.edu.cn/hpv.

MarkovHC: Markov hierarchical clustering for the topological structure of high-dimensional single-cell omics data with transition pathway and critical point detection.

Clustering cells and depicting the lineage relationship among cell subpopulations are fundamental tasks in single-cell omics studies. However, existing analytical methods face challenges in stratifying cells, tracking cellular trajectories, and identifying critical points of cell transitions. To overcome these, we proposed a novel Markov hierarchical clustering algorithm (MarkovHC), a topological clustering method that leverages the metastability of exponentially perturbed Markov chains for systematically reconstructing the cellular landscape. Briefly, MarkovHC starts with local connectivity and density derived from the input and outputs a hierarchical structure for the data. We firstly benchmarked MarkovHC on five simulated datasets and ten public single-cell datasets with known labels. Then, we used MarkovHC to investigate the multi-level architectures and transition processes during human embryo preimplantation development and gastric cancer procession. MarkovHC found heterogeneous cell states and sub-cell types in lineage-specific progenitor cells and revealed the most possible transition paths and critical points in the cellular processes. These results demonstrated MarkovHC's effectiveness in facilitating the stratification of cells, identification of cell populations, and characterization of cellular trajectories and critical points.

ScaffComb: A Phenotype-Based Framework for Drug Combination Virtual Screening in Large-Scale Chemical Datasets.

Combinational therapy is used for a long time in cancer treatment to overcome drug resistance related to monotherapy. Increased pharmacological data and the rapid development of deep learning methods have enabled the construction of models to predict and screen drug pairs. However, the size of drug libraries is restricted to hundreds to thousands of compounds. The ScaffComb framework, which aims to bridge the gaps in the virtual screening of drug combinations in large-scale databases, is proposed here. Inspired by phenotype-based drug design, ScaffComb integrates phenotypic information into molecular scaffolds, which can be used to screen the drug library and identify potent drug combinations. First, ScaffComb is validated using the US food and drug administration dataset and known drug combinations are successfully reidentified. Then, ScaffComb is applied to screen the ZINC and ChEMBL databases, which yield novel drug combinations and reveal an ability to discover new synergistic mechanisms. To our knowledge, ScaffComb is the first method to use phenotype-based virtual screening of drug combinations in large-scale chemical datasets.

3D genome alterations associated with dysregulated HOXA13 expression in high-risk T-lineage acute lymphoblastic leukemia.

3D genome alternations can dysregulate gene expression by rewiring enhancer-promoter interactions and lead to diseases. We report integrated analyses of 3D genome alterations and differential gene expressions in 18 newly diagnosed T-lineage acute lymphoblastic leukemia (T-ALL) patients and 4 healthy controls. 3D genome organizations at the levels of compartment, topologically associated domains and loop could hierarchically classify different subtypes of T-ALL according to T cell differentiation trajectory, similar to gene expressions-based classification. Thirty-four previously unrecognized translocations and 44 translocation-mediated neo-loops are mapped by Hi-C analysis. We find that neo-loops formed in the non-coding region of the genome could potentially regulate ectopic expressions of TLX3, TAL2 and HOXA transcription factors via enhancer hijacking. Importantly, both translocation-mediated neo-loops and NUP98-related fusions are associated with HOXA13 ectopic expressions. Patients with HOXA11-A13 expressions, but not other genes in the HOXA cluster, have immature immunophenotype and poor outcomes. Here, we highlight the potentially important roles of 3D genome alterations in the etiology and prognosis of T-ALL.

DAGM: A novel modelling framework to assess the risk of HER2-negative breast cancer based on germline rare coding mutations.

BACKGROUND: Breast cancers can be divided into HER2-negative and HER2-positive subtypes according to different status of HER2 gene. Despite extensive studies connecting germline mutations with possible risk of HER2-negative breast cancer, the main category of breast cancer, it remains challenging to obtain accurate risk assessment and to understand the potential underlying mechanisms. METHODS: We developed a novel framework named Damage Assessment of Genomic Mutations (DAGM), which projects rare coding mutations and gene expressions into Activity Profiles of Signalling Pathways (APSPs). FINDINGS: We characterized and validated DAGM framework at multiple levels. Based on an input of germline rare coding mutations, we obtained the corresponding APSP spectrum to calculate the APSP risk score, which was capable of distinguish HER2-negative from HER2-positive cases. These findings were validated using breast cancer data from TCGA (AUC = 0.7). DAGM revealed that HER2 signalling pathway was up-regulated in germline of HER2-negative patients, and those with high APSP risk scores had exhibited immune suppression. These findings were validated using RNA sequencing, phosphoproteome analysis, and CyTOF. Moreover, using germline mutations, DAGM could evaluate the risk for HER2-negative breast cancer, not only in women carrying BRCA1/2 mutations, but also in those without known disease-associated mutations. INTERPRETATION: The DAGM can facilitate the screening of subjects at high risk of HER2-negative breast cancer for primary prevention. This study also provides new insights into the potential mechanisms of developing HER2-negative breast cancer. The DAGM has the potential to be applied in the prevention, diagnosis, and treatment of HER2-negative breast cancer. FUNDING: This work was supported by the National Key Research and Development Program of China (grant no. 2018YFC0910406 and 2018AAA0103302 to CZ); the National Natural Science Foundation of China (grant no. 81202076 and 82072939 to MY, 81871513 to KW); the Guangzhou Science and Technology Program key projects (grant no. 2014J2200007 to MY, 202002030236 to KW); the National Key R&D Program of China (grant no. 2017YFC1309100 to CL); Shenzhen Science and Technology Planning Project (grant no. JCYJ20170817095211560 574 to YN); and the Natural Science Foundation of Guangdong Province (grant no. 2017A030313882 to KW and S2013010012048 to MY); Hefei National Laboratory for Physical Sciences at the Microscale (grant no. KF2020009 to GN); and RGC General Research Fund (grant no. 17114519 to YQS).

Integrative Genomic Analysis of Gemcitabine Resistance in Pancreatic Cancer by Patient-derived Xenograft Models.

PURPOSE: Gemcitabine is most commonly used for pancreatic cancer. However, the molecular features and mechanisms of the frequently occurring resistance remain unclear. This work aims at exploring the molecular features of gemcitabine resistance and identifying candidate biomarkers and combinatorial targets for the treatment. EXPERIMENTAL DESIGN: In this study, we established 66 patient-derived xenografts (PDXs) on the basis of clinical pancreatic cancer specimens and treated them with gemcitabine. We generated multiomics data (including whole-exome sequencing, RNA sequencing, miRNA sequencing, and DNA methylation array) of 15 drug-sensitive and 13 -resistant PDXs before and after the gemcitabine treatment. We performed integrative computational analysis to identify the molecular networks related to gemcitabine intrinsic and acquired resistance. Then, short hairpin RNA-based high-content screening was implemented to validate the function of the deregulated genes. RESULTS: The comprehensive multiomics analysis and functional experiment revealed that MRPS5 and GSPT1 had strong effects on cell proliferation, and CD55 and DHTKD1 contributed to gemcitabine resistance in pancreatic cancer cells. Moreover, we found miR-135a-5p was significantly associated with the prognosis of patients with pancreatic cancer and could be a candidate biomarker to predict gemcitabine response. Comparing the molecular features before and after the treatment, we found that PI3K-Akt, p53, and hypoxia-inducible factor-1 pathways were significantly altered in multiple patients, providing candidate target pathways for reducing the acquired resistance. CONCLUSIONS: This integrative genomic study systematically investigated the predictive markers and molecular mechanisms of chemoresistance in pancreatic cancer and provides potential therapy targets for overcoming gemcitabine resistance.

Single­cell RNA sequencing of t(8;21) acute myeloid leukemia for risk prediction.

Single­cell RNA sequencing (scRNA­seq) of bone marrow or peripheral blood samples from patients with acute myeloid leukemia (AML) enables the characterization of heterogeneous malignant cells. A total of 87 cells from two patients with t(8;21) AML were analyzed using scRNA­seq. Clustering methods were used to separate leukemia cells into different sub­populations, and the expression patterns of specific marker genes were used to annotate these populations. Among the 31 differentially expressed genes in the cells of a patient who relapsed after hematopoietic stem cell transplantation, 13 genes were identified to be associated with leukemia. Furthermore, three genes, namely AT­rich interaction domain 2, lysine methyltransferase 2A and synaptotagmin binding cytoplasmic RNA interacting protein were validated as possible prognostic biomarkers using two bulk expression datasets. Taking advantage of scRNA­seq, the results of the present study may provide clinicians with several possible biomarkers to predict the prognostic outcomes of t(8;21) AML.

The landscape of RNA polymerase II-associated chromatin interactions in prostate cancer.

Transcriptional dysregulation is a hallmark of prostate cancer (PCa). We mapped the RNA polymerase II-associated (RNA Pol II-associated) chromatin interactions in normal prostate cells and PCa cells. We discovered thousands of enhancer-promoter, enhancer-enhancer, as well as promoter-promoter chromatin interactions. These transcriptional hubs operate within the framework set by structural proteins - CTCF and cohesins - and are regulated by the cooperative action of master transcription factors, such as the androgen receptor (AR) and FOXA1. By combining analyses from metastatic castration-resistant PCa (mCRPC) specimens, we show that AR locus amplification contributes to the transcriptional upregulation of the AR gene by increasing the total number of chromatin interaction modules comprising the AR gene and its distal enhancer. We deconvoluted the transcription control modules of several PCa genes, notably the biomarker KLK3, lineage-restricted genes (KRT8, KRT18, HOXB13, FOXA1, ZBTB16), the drug target EZH2, and the oncogene MYC. By integrating clinical PCa data, we defined a germline-somatic interplay between the PCa risk allele rs684232 and the somatically acquired TMPRSS2-ERG gene fusion in the transcriptional regulation of multiple target genes - VPS53, FAM57A, and GEMIN4. Our studies implicate changes in genome organization as a critical determinant of aberrant transcriptional regulation in PCa.

A novel cytogenetic method to image chromatin interactions at subkilobase resolution: Tn5 transposase-based fluorescence in situ hybridization.

There is an increasing interest in understanding how three-dimensional organization of the genome is regulated. Different strategies have been used to identify genome-wide chromatin interactions. However, owing to current limitations in resolving genomic contacts, visualization and validation of these genomic loci at subkilobase resolution remain unsolved to date. Here, we describe Tn5 transposase-based fluorescence in situ hybridization (Tn5-FISH), a polymerase chain reaction-based, cost-effective imaging method, which can colocalize the genomic loci at subkilobase resolution, dissect genome architecture, and verify chromatin interactions detected by chromatin configuration capture-derived methods. To validate this method, short-range interactions in the keratin-encoding gene (KRT) locus in the topologically associated domain were imaged by triple-color Tn5-FISH, indicating that Tn5-FISH is very useful to verify short-range chromatin interactions inside the contact domain and TAD. Therefore, Tn5-FISH can be a powerful molecular tool for clinical detection of cytogenetic changes in numerous genetic diseases such as cancers.

Integrative molecular analysis of metastatic hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is the major type of primary liver cancer. Intrahepatic metastasis, such as portal vein tumor thrombosis (PVTT), strongly indicates poor prognosis of HCC. But now, there are limited understandings of the molecular features and mechanisms of those metastatic HCCs. METHODS: To characterize the molecular alterations of the metastatic HCCs, we implemented an integrative analysis of the copy number variations (CNVs), DNA methylations and transcriptomes of matched adjacent normal, primary tumor and PVTT samples from 19 HCC patients. RESULTS: CNV analysis identified a frequently amplified focal region chr11q13.3 and a novel deletion peak chr19q13.41 containing three miRNAs. The integrative analysis with RNA-seq data suggests that CNVs and differential promoter methylations regulate distinct oncogenic processes. Then, we used individualized differential analysis to identify the differentially expressed genes between matched primary tumor and PVTT of each patient. Results show that 5 out of 19 studied patients acquire evidential progressive alterations of gene expressions (more than 1000 differentially expressed genes were identified in each patient). While, another subset of eight patients have nearly identical gene expressions between the corresponding matched primary tumor and PVTT. Twenty genes were found to be recurrently and progressively differentially expressed in multiple patients. These genes are mainly associated with focal adhesion, xenobiotics metabolism by cytochrome P450 and amino acid metabolism. For several differentially expressed genes in metabolic pathways, their expressions are significantly associated with overall survivals and vascular invasions of HCC patients. The following transwell assay experiments validate that they can regulate invasive phenotypes of HCC cells. CONCLUSIONS: The metastatic HCCs with PVTTs have significant molecular alterations comparing with adjacent normal tissues. The recurrent alteration patterns are similar to several previously published general HCC cohorts, but usually with higher severity. By an individualized differential analysis strategy, the progressively differentially expressed genes between the primary tumor and PVTT were identified for each patient. A few patients aquire evidential progressive alterations of gene expressions. And, experiments show that several recurrently differentially expressed genes can strongly regulate HCC cell invasions.

Pervasive Chromatin-RNA Binding Protein Interactions Enable RNA-Based Regulation of Transcription.

Increasing evidence suggests that transcriptional control and chromatin activities at large involve regulatory RNAs, which likely enlist specific RNA-binding proteins (RBPs). Although multiple RBPs have been implicated in transcription control, it has remained unclear how extensively RBPs directly act on chromatin. We embarked on a large-scale RBP ChIP-seq analysis, revealing widespread RBP presence in active chromatin regions in the human genome. Like transcription factors (TFs), RBPs also show strong preference for hotspots in the genome, particularly gene promoters, where their association is frequently linked to transcriptional output. Unsupervised clustering reveals extensive co-association between TFs and RBPs, as exemplified by YY1, a known RNA-dependent TF, and RBM25, an RBP involved in splicing regulation. Remarkably, RBM25 depletion attenuates all YY1-dependent activities, including chromatin binding, DNA looping, and transcription. We propose that various RBPs may enhance network interaction through harnessing regulatory RNAs to control transcription.

A large-scale CRISPR screen and identification of essential genes in cellular senescence bypass.

Cellular senescence is an important mechanism of autonomous tumor suppression, while its consequence such as the senescence-associated secretory phenotype (SASP) may drive tumorigenesis and age-related diseases. Therefore, controlling the cell fate optimally when encountering senescence stress is helpful for anti-cancer or anti-aging treatments. To identify genes essential for senescence establishment or maintenance, we carried out a CRISPR-based screen with a deliberately designed single-guide RNA (sgRNA) library. The library comprised of about 12,000 kinds of sgRNAs targeting 1378 senescence-associated genes selected by integrating the information of literature mining, protein-protein interaction network, and differential gene expression. We successfully detected a dozen gene deficiencies potentially causing senescence bypass, and their phenotypes were further validated with a high true positive rate. RNA-seq analysis showed distinct transcriptome patterns of these bypass cells. Interestingly, in the bypass cells, the expression of SASP genes was maintained or elevated with CHEK2, HAS1, or MDK deficiency; but neutralized with MTOR, CRISPLD2, or MORF4L1 deficiency. Pathways of some age-related neurodegenerative disorders were also downregulated with MTOR, CRISPLD2, or MORF4L1 deficiency. The results demonstrated that disturbing these genes could lead to distinct cell fates as a consequence of senescence bypass, suggesting that they may play essential roles in cellular senescence.