Direct Tumor Killing and Immunotherapy through Anti-SerpinB9 Therapy.

Cancer therapies kill tumors either directly or indirectly by evoking immune responses and have been combined with varying levels of success. Here, we describe a paradigm to control cancer growth that is based on both direct tumor killing and the triggering of protective immunity. Genetic ablation of serine protease inhibitor SerpinB9 (Sb9) results in the death of tumor cells in a granzyme B (GrB)-dependent manner. Sb9-deficient mice exhibited protective T cell-based host immunity to tumors in association with a decline in GrB-expressing immunosuppressive cells within the tumor microenvironment (TME). Maximal protection against tumor development was observed when the tumor and host were deficient in Sb9. The therapeutic utility of Sb9 inhibition was demonstrated by the control of tumor growth, resulting in increased survival times in mice. Our studies describe a molecular target that permits a combination of tumor ablation, interference within the TME, and immunotherapy in one potential modality.

IL-1ß-associated NNT acetylation orchestrates iron-sulfur cluster maintenance and cancer immunotherapy resistance.

Interleukin-1ß (IL-1ß) is a key protein in inflammation and contributes to tumor progression. However, the role of IL-1ß in cancer is ambiguous or even contradictory. Here, we found that upon IL-1ß stimulation, nicotinamide nucleotide transhydrogenase (NNT) in cancer cells is acetylated at lysine (K) 1042 (NNT K1042ac) and thereby induces the mitochondrial translocation of p300/CBP-associated factor (PCAF). This acetylation enhances NNT activity by increasing the binding affinity of NNT for NADP+ and therefore boosts NADPH production, which subsequently sustains sufficient iron-sulfur cluster maintenance and protects tumor cells from ferroptosis. Abrogating NNT K1042ac dramatically attenuates IL-1ß-promoted tumor immune evasion and synergizes with PD-1 blockade. In addition, NNT K1042ac is associated with IL-1ß expression and the prognosis of human gastric cancer. Our findings demonstrate a mechanism of IL-1ß-promoted tumor immune evasion, implicating the therapeutic potential of disrupting the link between IL-1ß and tumor cells by inhibiting NNT acetylation.

LncRNA CamK-A Regulates Ca2+-Signaling-Mediated Tumor Microenvironment Remodeling.

Cancer cells entail metabolic adaptation and microenvironmental remodeling to survive and progress. Both calcium (Ca2+) flux and Ca2+-dependent signaling play a crucial role in this process, although the underlying mechanism has yet to be elucidated. Through RNA screening, we identified one long noncoding RNA (lncRNA) named CamK-A (lncRNA for calcium-dependent kinase activation) in tumorigenesis. CamK-A is highly expressed in multiple human cancers and involved in cancer microenvironment remodeling via activation of Ca2+-triggered signaling. Mechanistically, CamK-A activates Ca2+/calmodulin-dependent kinase PNCK, which in turn phosphorylates IκBα and triggers calcium-dependent nuclear factor κB (NF-κB) activation. This regulation results in the tumor microenvironment remodeling, including macrophage recruitment, angiogenesis, and tumor progression. Notably, our human-patient-derived xenograft (PDX) model studies demonstrate that targeting CamK-A robustly impaired cancer development. Clinically, CamK-A expression coordinates with the activation of CaMK-NF-κB axis, and its high expression indicates poor patient survival rate, suggesting its role as a potential biomarker and therapeutic target.

Antibody Profiling of Pan-Cancer Viral Proteome Reveals Biomarkers for Nasopharyngeal Carcinoma Diagnosis and Prognosis.

Diagnosing, predicting disease outcome, and identifying effective treatment targets for virus-related cancers are lacking. Protein biomarkers have the potential to bridge the gap between prevention and treatment for these types of cancers. While it has been shown that certain antibodies against EBV proteins could be used to detect nasopharyngeal carcinoma (NPC), antibodies targeting are solely a tiny part of the about 80 proteins expressed by the EBV genome. Furthermore, it remains unclear what role other viruses play in NPC since many diseases are the result of multiple viral infections. For the first time, this study measured both IgA and IgG antibody responses against 646 viral proteins from 23 viruses in patients with NPC and control subjects using nucleic acid programmable protein arrays. Candidate seromarkers were then validated by ELISA using 1665 serum samples from three clinical cohorts. We demonstrated that the levels of five candidate seromarkers (EBV-BLLF3-IgA, EBV-BLRF2-IgA, EBV-BLRF2-IgG, EBV-BDLF1-IgA, EBV-BDLF1-IgG) in NPC patients were significantly elevated than controls. Additional examination revealed that NPC could be successfully diagnosed by combining the clinical biomarker EBNA1-IgA with the five anti-EBV antibodies. The sensitivity of the six-antibody signature at 95% specificity to diagnose NPC was comparable to the current clinically-approved biomarker combination, VCA-IgA, and EBNA1-IgA. However, the recombinant antigens of the five antibodies are easier to produce and standardize compared to the native viral VCA proteins. This suggests the potential replacement of the traditional VCA-IgA assay with the 5-antibodies combination to screen and diagnose NPC. Additionally, we investigated the prognostic significance of these seromarkers titers in NPC. We showed that NPC patients with elevated BLLF3-IgA and BDLF1-IgA titers in their serum exhibited significantly poorer disease-free survival, suggesting the potential of these two seromarkers as prognostic indicators of NPC. These findings will help develop serological tests to detect and treat NPC in the future.

dSCOPE: a software to detect sequences critical for liquid-liquid phase separation.

Membrane-based cells are the fundamental structural and functional units of organisms, while evidences demonstrate that liquid-liquid phase separation (LLPS) is associated with the formation of membraneless organelles, such as P-bodies, nucleoli and stress granules. Many studies have been undertaken to explore the functions of protein phase separation (PS), but these studies lacked an effective tool to identify the sequence segments that critical for LLPS. In this study, we presented a novel software called dSCOPE (http://dscope.omicsbio.info) to predict the PS-driving regions. To develop the predictor, we curated experimentally identified sequence segments that can drive LLPS from published literature. Then sliding sequence window based physiological, biochemical, structural and coding features were integrated by random forest algorithm to perform prediction. Through rigorous evaluation, dSCOPE was demonstrated to achieve satisfactory performance. Furthermore, large-scale analysis of human proteome based on dSCOPE showed that the predicted PS-driving regions enriched various protein post-translational modifications and cancer mutations, and the proteins which contain predicted PS-driving regions enriched critical cellular signaling pathways. Taken together, dSCOPE precisely predicted the protein sequence segments critical for LLPS, with various helpful information visualized in the webserver to facilitate LLPS-related research.

qPTM: an updated database for PTM dynamics in human, mouse, rat and yeast.

Post-translational modifications (PTMs) are critical molecular mechanisms that regulate protein functions temporally and spatially in various organisms. Since most PTMs are dynamically regulated, quantifying PTM events under different states is crucial for understanding biological processes and diseases. With the rapid development of high-throughput proteomics technologies, massive quantitative PTM proteome datasets have been generated. Thus, a comprehensive one-stop data resource for surfing big data will benefit the community. Here, we updated our previous phosphorylation dynamics database qPhos to the qPTM (http://qptm.omicsbio.info). In qPTM, 11 482 553 quantification events among six types of PTMs, including phosphorylation, acetylation, glycosylation, methylation, SUMOylation and ubiquitylation in four different organisms were collected and integrated, and the matched proteome datasets were included if available. The raw mass spectrometry based false discovery rate control and the recurrences of identifications among datasets were integrated into a scoring system to assess the reliability of the PTM sites. Browse and search functions were improved to facilitate users in swiftly and accurately acquiring specific information. The results page was revised with more abundant annotations, and time-course dynamics data were visualized in trend lines. We expected the qPTM database to be a much more powerful and comprehensive data repository for the PTM research community.

Multi-modal optimization to identify personalized biomarkers for disease prediction of individual patients with cancer.

Finding personalized biomarkers for disease prediction of patients with cancer remains a massive challenge in precision medicine. Most methods focus on one subnetwork or module as a network biomarker; however, this ignores the early warning capabilities of other modules with different configurations of biomarkers (i.e. multi-modal personalized biomarkers). Identifying such modules would not only predict disease but also provide effective therapeutic drug target information for individual patients. To solve this problem, we developed a novel model (denoted multi-modal personalized dynamic network biomarkers (MMPDNB)) based on a multi-modal optimization mechanism and personalized dynamic network biomarker (PDNB) theory, which can provide multiple modules of personalized biomarkers and unveil their multi-modal properties. Using the genomics data of patients with breast or lung cancer from The Cancer Genome Atlas database, we validated the effectiveness of the MMPDNB model. The experimental results showed that compared with other advanced methods, MMPDNB can more effectively predict the critical state with the highest early warning signal score during cancer development. Furthermore, MMPDNB more significantly identified PDNBs containing driver and biomarker genes specific to cancer tissues. More importantly, we validated the biological significance of multi-modal PDNBs, which could provide effective drug targets of individual patients as well as markers for predicting early warning signals of the critical disease state. In conclusion, multi-modal optimization is an effective method to identify PDNBs and offers a new perspective for understanding tumor heterogeneity in cancer precision medicine.

qPTMplants: an integrative database of quantitative post-translational modifications in plants.

As a crucial molecular mechanism, post-translational modifications (PTMs) play critical roles in a wide range of biological processes in plants. Recent advances in mass spectrometry-based proteomic technologies have greatly accelerated the profiling and quantification of plant PTM events. Although several databases have been constructed to store plant PTM data, a resource including more plant species and more PTM types with quantitative dynamics still remains to be developed. In this paper, we present an integrative database of quantitative PTMs in plants named qPTMplants (http://qptmplants.omicsbio.info), which hosts 1 242 365 experimentally identified PTM events for 429 821 nonredundant sites on 123 551 proteins under 583 conditions for 23 PTM types in 43 plant species from 293 published studies, with 620 509 quantification events for 136 700 PTM sites on 55 361 proteins under 354 conditions. Moreover, the experimental details, such as conditions, samples, instruments and methods, were manually curated, while a variety of annotations, including the sequence and structural characteristics, were integrated into qPTMplants. Then, various search and browse functions were implemented to access the qPTMplants data in a user-friendly manner. Overall, we anticipate that the qPTMplants database will be a valuable resource for further research on PTMs in plants.

C9orf72 poly(PR) aggregation in nucleus induces ALS/FTD-related neurodegeneration in cynomolgus monkeys.

Poly(PR) is a dipeptide repeat protein comprising proline and arginine residues. It is one of the translational product of expanded G4C2 repeats in the C9orf72 gene, and its accumulation is contributing to the neuropathogenesis of C9orf72-associated amyotrophic lateral sclerosis and/or frontotemporal dementia (C9-ALS/FTD). In this study, we demonstrate that poly(PR) protein alone is sufficient to induce neurodegeneration related to ALS/FTD in cynomolgus monkeys. By delivering poly(PR) via AAV, we observed that the PR proteins were located within the nucleus of infected cells. The expression of (PR)50 protein, consisting of 50 PR repeats, led to increased loss of cortical neurons, cytoplasmic lipofuscin, and gliosis in the brain, as well as demyelination and loss of ChAT positive neurons in the spinal cord of monkeys. While, these pathologies were not observed in monkeys expressing (PR)5, a protein comprising only 5 PR repeats. Furthermore, the (PR)50-expressing monkeys exhibited progressive motor deficits, cognitive impairment, muscle atrophy, and abnormal electromyography (EMG) potentials, which closely resemble clinical symptoms seen in C9-ALS/FTD patients. By longitudinally tracking these monkeys, we found that changes in cystatin C and chitinase-1 (CHIT1) levels in the cerebrospinal fluid (CSF) corresponded to the phenotypic progression of (PR)50-induced disease. Proteomic analysis revealed that the major clusters of dysregulated proteins were nuclear-localized, and downregulation of the MECP2 protein was implicated in the toxic process of poly(PR). This research indicates that poly(PR) expression alone induces neurodegeneration and core phenotypes associated with C9-ALS/FTD in monkeys, which may provide insights into the mechanisms of disease pathogenesis.

A novel scoring model based on RNA modification "writers" can predict the prognosis and guide immunotherapy in gastric cancer.

Although extensive research has been carried out on the epigenetic regulation of single RNA modifications in gastric cancer, little is known regarding the crosstalk of four major RNA adenosine modifications, namely, m6A, m1A, alternative polyadenylation and adenosine-to-inosine RNA editing. By analyzing 26 RNA modification "writers" in 1750 gastric cancer samples, we creatively constructed a scoring model called the "Writers" of the RNA Modification Score (WRM_Score), which was able to quantify the RNA modification subtypes of individual patients. In addition, we explored the relationship between WRM_Score and transcriptional and posttranscriptional regulation, tumor microenvironment, clinical features and molecular subtypes. We constructed an RNA modification scoring model including two different subgroups: WRM_Score_low and WRM_Score_high. The former was associated with survival benefit and good efficacy of immune checkpoint inhibitors (ICIs) due to gene repair and immune activation, while the latter was related to poor prognosis and bad efficacy of ICIs because of stromal activation and immunosuppression. The WRM score based on immune and molecular characteristics of the RNA modification pattern is a reliable predictor of the prognosis of gastric cancer and the therapeutic efficacy of immune checkpoint inhibitors in gastric cancer.

iCysMod: an integrative database for protein cysteine modifications in eukaryotes.

As important post-translational modifications, protein cysteine modifications (PCMs) occurring at cysteine thiol group play critical roles in the regulation of various biological processes in eukaryotes. Due to the rapid advancement of high-throughput proteomics technologies, a large number of PCM events have been identified but remain to be curated. Thus, an integrated resource of eukaryotic PCMs will be useful for the research community. In this work, we developed an integrative database for protein cysteine modifications in eukaryotes (iCysMod), which curated and hosted 108 030 PCM events for 85 747 experimentally identified sites on 31 483 proteins from 48 eukaryotes for 8 types of PCMs, including oxidation, S-nitrosylation (-SNO), S-glutathionylation (-SSG), disulfide formation (-SSR), S-sulfhydration (-SSH), S-sulfenylation (-SOH), S-sulfinylation (-SO2H) and S-palmitoylation (-S-palm). Then, browse and search options were provided for accessing the dataset, while various detailed information about the PCM events was well organized for visualization. With human dataset in iCysMod, the sequence features around the cysteine modification sites for each PCM type were analyzed, and the results indicated that various types of PCMs presented distinct sequence recognition preferences. Moreover, different PCMs can crosstalk with each other to synergistically orchestrate specific biological processes, and 37 841 PCM events involved in 119 types of PCM co-occurrences at the same cysteine residues were finally obtained. Taken together, we anticipate that the database of iCysMod would provide a useful resource for eukaryotic PCMs to facilitate related researches, while the online service is freely available at http://icysmod.omicsbio.info.

gutMEGA: a database of the human gut MEtaGenome Atlas.

The gut microbiota plays important roles in human health through regulating both physiological homeostasis and disease emergence. The accumulation of metagenomic sequencing studies enables us to better understand the temporal and spatial variations of the gut microbiota under different physiological and pathological conditions. However, it is inconvenient for scientists to query and retrieve published data; thus, a comprehensive resource for the quantitative gut metagenome is urgently needed. In this study, we developed gut MEtaGenome Atlas (gutMEGA), a well-annotated comprehensive database, to curate and host published quantitative gut microbiota datasets from Homo sapiens. By carefully curating the gut microbiota composition, phenotypes and experimental information, gutMEGA finally integrated 59 132 quantification events for 6457 taxa at seven different levels (kingdom, phylum, class, order, family, genus and species) under 776 conditions. Moreover, with various browsing and search functions, gutMEGA provides a fast and simple way for users to obtain the relative abundances of intestinal microbes among phenotypes. Overall, gutMEGA is a convenient and comprehensive resource for gut metagenome research, which can be freely accessed at http://gutmega.omicsbio.info.

DrugCVar: a platform for evidence-based drug annotation for genetic variants in cancer.

MOTIVATION: Targeted therapy for cancer-related genetic variants is critical for precision medicine. Although several databases including The Clinical Interpretation of Variants in Cancer (CIViC), The Oncology Knowledge Base (OncoKB), The Cancer Genome Interpreter (CGI) and My Cancer Genome (MCG) provide clinical interpretations of variants in cancer, the clinical evidence was limited and miscellaneous. In this study, we developed the DrugCVar database, which integrated our manually curated cancer variant-drug targeting evidence from literature and the interpretations from the public resources. RESULTS: In total, 7830 clinical evidences for cancer variant-drug targeting were integrated and classified into 10 evidence tiers. Searching and browsing functions were provided for quick queries of cancer variant-drug targeting evidence. Also, batch annotation module was developed for user-provided massive genetic variants in various formats. Details, such as the mutation function, location of the variants in gene and protein structures and mutation statistics of queried genes in various tumor types, were also provided for further investigations. Thus, DrugCVar could serve as a comprehensive annotation tool to interpret potential drugs for cancer variants especially the massive ones from clinical cancer genomics studies. AVAILABILITY AND IMPLEMENTATION: The database is available at http://drugcvar.omicsbio.info. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Position of lumbar plexus nerves in the psoas major: Application to transpsoas approaches to the lumbar spine.

Far lateral interbody fusion is a minimally invasive operating technique. However, the incidence of postoperative neurological complications is high, and some scholars question its safety. This study describes the neuroanatomical features and spatial orientation within the psoas major. Ten embalmed male cadavers were selected and the left psoas major was dissected. Subsequently, the area between the anterior and the posterior edges of the vertebral body was divided into three equal zones. The nerves' distribution, number, and spatial orientation of the L1/2 to L4/5 intervertebral discs were examined. A caliper was used to measure the diameter of the nerve. The safety zone of the L1/2 intervertebral disc level is located in zone I and II, the relative safe zones of the L2/3 and L4/5 intervertebral discs are located in zone II, and the safety zone of the L3/4 intervertebral disc level is located in the caudal side of zone II. The genitofemoral nerve exits the psoas major in a co-trunk or two-branch pattern, and its exit point was distributed between the L3 and L4 vertebral bodies, mainly at the L3/4 intervertebral disc level. The sympathetic ganglia in the psoas major appeared only in zone I at the L2/3 intervertebral disc level. This is a systematic anatomical study that describes the nerves of the psoas major. Spine surgeons can use this study-which consists of important clinical implications-for preoperative planning, and thus, reduce the risk of nerve injury during surgery.

CrossICC: iterative consensus clustering of cross-platform gene expression data without adjusting batch effect.

Unsupervised clustering of high-throughput gene expression data is widely adopted for cancer subtyping. However, cancer subtypes derived from a single dataset are usually not applicable across multiple datasets from different platforms. Merging different datasets is necessary to determine accurate and applicable cancer subtypes but is still embarrassing due to the batch effect. CrossICC is an R package designed for the unsupervised clustering of gene expression data from multiple datasets/platforms without the requirement of batch effect adjustment. CrossICC utilizes an iterative strategy to derive the optimal gene signature and cluster numbers from a consensus similarity matrix generated by consensus clustering. This package also provides abundant functions to visualize the identified subtypes and evaluate subtyping performance. We expected that CrossICC could be used to discover the robust cancer subtypes with significant translational implications in personalized care for cancer patients. AVAILABILITY AND IMPLEMENTATION: The package is implemented in R and available at GitHub (https://github.com/bioinformatist/CrossICC) and Bioconductor (http://bioconductor.org/packages/release/bioc/html/CrossICC.html) under the GPL v3 License.

Deep learning based prediction of reversible HAT/HDAC-specific lysine acetylation.

Protein lysine acetylation regulation is an important molecular mechanism for regulating cellular processes and plays critical physiological and pathological roles in cancers and diseases. Although massive acetylation sites have been identified through experimental identification and high-throughput proteomics techniques, their enzyme-specific regulation remains largely unknown. Here, we developed the deep learning-based protein lysine acetylation modification prediction (Deep-PLA) software for histone acetyltransferase (HAT)/histone deacetylase (HDAC)-specific acetylation prediction based on deep learning. Experimentally identified substrates and sites of several HATs and HDACs were curated from the literature to generate enzyme-specific data sets. We integrated various protein sequence features with deep neural network and optimized the hyperparameters with particle swarm optimization, which achieved satisfactory performance. Through comparisons based on cross-validations and testing data sets, the model outperformed previous studies. Meanwhile, we found that protein-protein interactions could enrich enzyme-specific acetylation regulatory relations and visualized this information in the Deep-PLA web server. Furthermore, a cross-cancer analysis of acetylation-associated mutations revealed that acetylation regulation was intensively disrupted by mutations in cancers and heavily implicated in the regulation of cancer signaling. These prediction and analysis results might provide helpful information to reveal the regulatory mechanism of protein acetylation in various biological processes to promote the research on prognosis and treatment of cancers. Therefore, the Deep-PLA predictor and protein acetylation interaction networks could provide helpful information for studying the regulation of protein acetylation. The web server of Deep-PLA could be accessed at http://deeppla.cancerbio.info.

An anatomical study of the origins courses and distributions of the transverse branches of lumbar arteries at the L1-L4 levels.

Pseudoaneurysms of the lumbar arteries following transforaminal lumbar interbody fusion (TLIF) are rare postoperative complications that usually occur around the transverse process. However, there are few detailed descriptions of the transverse branch and other branches of the dorsal branches at the L1-L4 disks. STUDY DESIGN: Ten adult embalmed cadavers were anatomically studied. OBJECTIVES: The purposes of the study were to describe the vascular distribution of the dorsal branches, especially the transverse branches, at the L1-L4 levels and provide information useful for TLIF. METHODS: Ten embalmed cadavers studied after their arterial systems were injected with red latex. The quantity, origin, pathway, distribution range and diameter of the branches were recorded and photographed. RESULTS: The transverse branch appeared in all 80 intervertebral foramina. The transverse branch was divided into 2 types: In type 1, the arteries divided into superior branches and inferior branches; the arteries in type 2 divided into 3 branches (superior, intermedius and inferior branches). CONCLUSIONS: The transverse branches of the dorsal arteries are common structures from L1 to L4, and 2 types of transverse branches were found. A thorough understanding of the dorsal branches, especially the transverse branches of the lumbar artery, may be very important for reducing both intraoperative bleeding during the surgery and the occurrence of pseudoaneurysms after transforaminal lumbar interbody fusion.

CDK1/2/5 inhibition overcomes IFNG-mediated adaptive immune resistance in pancreatic cancer.

OBJECTIVE: Adaptive immune resistance mediated by the cytokine interferon gamma (IFNG) still constitutes a major problem in cancer immunotherapy. We develop strategies for overcoming IFNG-mediated adaptive immune resistance in pancreatic ductal adenocarcinoma cancer (PDAC). DESIGN: We screened 429 kinase inhibitors for blocking IFNG-induced immune checkpoint (indoleamine 2,3-dioxygenase 1 (IDO1) and CD274) expression in a human PDAC cell line. We evaluated the ability of the cyclin-dependent kinase (CDK) inhibitor dinaciclib to block IFNG-induced IDO1 and CD274 expression in 24 human and mouse cancer cell lines as well as in primary cancer cells from patients with PDAC or ovarian carcinoma. We tested the effects of dinaciclib on IFNG-induced signal transducer and activator of transcription 1 activation and immunological cell death, and investigated the potential utility of dinaciclib in combination with IFNG for pancreatic cancer therapy in vivo, and compared gene expression levels between human cancer tissues with patient survival times using the Cancer Genome Atlas datasets. RESULTS: Pharmacological (using dinaciclib) or genetic (using shRNA or siRNA) inactivation of CDK1/2/5 not only blocks JUN-dependent immune checkpoint expression, but also triggers histone-dependent immunogenic cell death in immortalised or primary cancer cells in response to IFNG. This dual mechanism turns an immunologically 'cold' tumour microenvironment into a 'hot' one, dramatically improving overall survival rates in mouse pancreatic tumour models (subcutaneous, orthotopic and transgenic models). The abnormal expression of CDK1/2/5 and IDO1 was associated with poor patient survival in several cancer types, including PDAC. CONCLUSION: CDK1/2/5 kinase activity is essential for IFNG-mediated cancer immunoevasion. CDK1/2/5 inhibition by dinaciclib provides a novel strategy to overcome IFNG-triggered acquired resistance in pancreatic tumour immunity.

qPhos: a database of protein phosphorylation dynamics in humans.

Temporal and spatial protein phosphorylation dynamically orchestrates a broad spectrum of biological processes and plays various physiological and pathological roles in diseases and cancers. Recent advancements in high-throughput proteomics techniques greatly promoted the profiling and quantification of phosphoproteome. However, although several comprehensive databases have reserved the phosphorylated proteins and sites, a resource for phosphorylation quantification still remains to be constructed. In this study, we developed the qPhos (http://qphos.cancerbio.info) database to integrate and host the data on phosphorylation dynamics. A total of 3 537 533 quantification events for 199 071 non-redundant phosphorylation sites on 18 402 proteins under 484 conditions were collected through exhaustive curation of published literature. The experimental details, including sample materials, conditions and methods, were recorded. Various annotations, such as protein sequence and structure properties, potential upstream kinases and their inhibitors, were systematically integrated and carefully organized to present details about the quantified phosphorylation sites. Various browse and search functions were implemented for the user-defined filtering of samples, conditions and proteins. Furthermore, the qKinAct service was developed to dissect the kinase activity profile from user-submitted quantitative phosphoproteome data through annotating the kinase activity-related phosphorylation sites. Taken together, the qPhos database provides a comprehensive resource for protein phosphorylation dynamics to facilitate related investigations.