Quantitative Proteomics of the Cancer Cell Line Encyclopedia

TOP2A modulates signaling via the AKT/mTOR pathway to promote ovarian cancer cell proliferation

Ovarian cancer (OC) is a form of gynecological malignancy that is associated with worse patient outcomes than any other cancer of the female reproductive tract. Topoisomerase II α (TOP2A) is commonly regarded as an oncogene that is associated with malignant disease progression in a variety of cancers, its mechanistic functions in OC have yet to be firmly established. We explored the role of TOP2A in OC through online databases, clinical samples, in vitro and in vivo experiments. And initial analyses of public databases revealed high OC-related TOP2A expression in patient samples that was related to poorer prognosis. This was confirmed by clinical samples in which TOP2A expression was elevated in OC relative to healthy tissue. Kaplan-Meier analyses further suggested that higher TOP2A expression levels were correlated with worse prognosis in OC patients. In vitro, TOP2A knockdown resulted in the inhibition of OC cell proliferation, with cells entering G1 phase arrest and undergoing consequent apoptotic death. In rescue assays, TOP2A was confirmed to regulate cell proliferation and cell cycle through AKT/mTOR pathway activity. Mouse model experiments further affirmed the key role that TOP2A plays as a driver of OC cell proliferation. These data provide strong evidence supporting TOP2A as an oncogenic mediator and prognostic biomarker related to OC progression and poor outcomes. At the mechanistic level, TOP2A can control tumor cell growth via AKT/mTOR pathway modulation. These preliminary results provide a foundation for future research seeking to explore the utility of TOP2A inhibitor-based combination treatment regimens in platinum-resistant recurrent OC patients.

A CRISPR activation screen identifies FBXO22 supporting targeted protein degradation

Targeted protein degradation (TPD) represents a potent chemical biology paradigm that leverages the cellular degradation machinery to pharmacologically eliminate specific proteins of interest. Although multiple E3 ligases have been discovered to facilitate TPD, there exists a compelling requirement to diversify the pool of E3 ligases available for such applications. Here we describe a clustered regularly interspaced short palindromic repeats (CRISPR)-based transcriptional activation screen focused on human E3 ligases, with the goal of identifying E3 ligases that can facilitate heterobifunctional compound-mediated target degradation. Through this approach, we identified a candidate proteolysis-targeting chimera (PROTAC), 22-SLF, that induces the degradation of FK506-binding protein 12 when the transcription of FBXO22 gene is activated. Subsequent mechanistic investigations revealed that 22-SLF interacts with C227 and/or C228 in F-box protein 22 (FBXO22) to achieve target degradation. Lastly, we demonstrated the versatility of FBXO22-based PROTACs by effectively degrading additional endogenous proteins, including bromodomain-containing protein 4 and the echinoderm microtubule-associated protein-like 4-anaplastic lymphoma kinase fusion protein.

The causal relationship between immune cells mediating FIT3L, CCL4, OSM, and skin-derived deteriorated tumors

OBJECTIVE

Observational studies have identified a dual effect of circulating inflammatory proteins and immune cells on cancer progression. However, the specific mechanisms of action have not been clarified in the exacerbation of cutaneous-origin tumors. Therefore, this study aims to investigate whether the causal relationship between circulating inflammatory factors and basal cell carcinoma (BCC), cutaneous malignant melanoma (SKCM), and cutaneous squamous cell carcinoma (cSCC) is regulated by immune cells.

METHODS

This study employed the Two-Sample Mendelian Randomization (TSMR) approach to investigate the causal relationships between 91 circulating inflammatory factors and three prevalent types of skin cancer from a genetic perspective. Bayesian Weighted Mendelian Randomization (BWMR) was also used to validate correlation and reverse MR to assess inverse relationships. Subsequent sensitivity analyses were conducted to limit the impact of heterogeneity and pleiotropy. Finally, the two-step Mendelian Randomization (two-step MR) method was utilized to ascertain the mediating effects of specific immune cell traits in the causal pathways linking circulating inflammatory factors with BCC, SKCM, and cSCC.

RESULTS

The Inverse Variance Weighted (IVW) method and the Bayesian Weighted Algorithm collectively identified nine inflammatory factors causally associated with BCC, SKCM, and cSCC. The results from Cochran's Q test, mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO), and MR-Egger intercept were not statistically significant (p < 0.05). Additionally, the proportions mediated by CD4+ CD8dim T cell %leukocyte, CD4-CD8-Natural Killer T %T cell, and CD20 on IgD-CD38-B cell for FIt3L, CCL4, and OSM were 9.26%, 8.96%, and 10.16%, respectively.

CONCLUSION

Immune cell levels potentially play a role in the modulation process between circulating inflammatory proteins and cutaneous-origin exacerbated tumors. This finding offers a new perspective for the in-depth exploration of cutaneous malignancies.

Identification of protein aggregates in the aging vertebrate brain with prion-like and phase-separation properties

Protein aggregation, which can sometimes spread in a prion-like manner, is a hallmark of neurodegenerative diseases. However, whether prion-like aggregates form during normal brain aging remains unknown. Here, we use quantitative proteomics in the African turquoise killifish to identify protein aggregates that accumulate in old vertebrate brains. These aggregates are enriched for prion-like RNA-binding proteins, notably the ATP-dependent RNA helicase DDX5. We validate that DDX5 forms aggregate-like puncta in the brains of old killifish and mice. Interestingly, DDX5's prion-like domain allows these aggregates to propagate across many generations in yeast. In vitro, DDX5 phase separates into condensates. Mutations that abolish DDX5 prion propagation also impair the protein's ability to phase separate. DDX5 condensates exhibit enhanced enzymatic activity, but they can mature into inactive, solid aggregates. Our findings suggest that protein aggregates with prion-like properties form during normal brain aging, which could have implications for the age-dependency of cognitive decline.

Pan-cancer exploration of oncogenic and clinical impacts revealed that HOXA9 is a diagnostic indicator of tumorigenesis

Homeodomain transcription factor A9 (HOXA9) is a member of the HOX cluster family of transcription factors that are crucially involved in embryo implantation, morphogenesis, body axis development, and endothelial cell differentiation. Despite numerous reports on its aberrant expression in a few malignancies, the molecular and functional complexity of HOXA9 across cancers remains obscure. We aimed to analyze the dynamic role of HOXA9 across cancers by identifying, analyzing, and understanding its multiple modes of regulation and functional implications and identifying possible therapeutic avenues. We conducted a comprehensive analysis to determine the role of HOXA9 across cancers. This approach involved the integration of large-scale datasets from public repositories such as the Genomic Data Commons, specifically the Cancer Genome Atlas (GDC-TCGA), across 33 different cancer types. The multiple modes of HOXA9 regulation by genetic and epigenetic factors were determined using online tools, which comprised experimentally validated observations. Furthermore, downstream pathways were identified by predicting the targets of HOXA9 and by performing functional enrichment analysis. We also assessed the clinical significance of HOXA9 in terms of prognosis and stage stratification. This study evaluated the correlation between HOXA9 and tumor-infiltrating molecules and discussed its association with therapeutically approved antineoplastic drugs. HOXA9 was significantly upregulated in 9 tumors and downregulated in 2 cancers. The deregulation of HOXA9 is primarily attributed to epigenetic factors, including promoter DNA methylation and noncoding RNAs (ncRNAs). The HOXA9 transcription factor interacts with PBX/MEIS cofactors and regulates multiple genes involved in cancer-associated EMT, autophagy, the cell cycle, metabolic pathways, Wnt signaling, TGF-β signaling, the AMPK pathway, PI3K/AKT signaling, and NF-κB signaling, thereby establishing control over downstream mechanisms. Differential expression in various clinical stages across cancers was shown to have prognostic significance and to be correlated with tumor-infiltrating immune molecules. The assessment of the correlation of HOXA9 expression with approved antineoplastic drugs revealed that targeting HOXA9 could be the most reliable strategy for preventing cancer progression. HOXA9 is upregulated in the majority of malignancies and drives cancer progression by regulating multiple signaling mechanisms. Hence, HOXA9 could be a reliable diagnostic indicator and a potential therapeutic candidate for solid cancer types.

Multi-omics revealed anti-fatigue property of polyphenol from areca nut

BACKGROUND

Areca nut polyphenols (AP) that extracted from areca nut, have been demonstrated for their potential of anti-fatigue effects. However, the underlying mechanisms for the anti-fatigue properties of AP has not been fully elucidated to date. Previous studies have predominantly concentrated on single aspects, such as antioxidation and anti-inflammation, yet have lacked comprehensive multi-dimensional analyses.

PURPOSE

To explore the underlying mechanism of AP in exerting anti-fatigue effects.

METHODS

In this study, we developed a chronic sleep deprivation-induced fatigue model and used physiological, hematological, and biochemical indicators to evaluate the anti- fatigue efficacy of AP. Additionally, a multi-omics approach was employed to reveal the anti-fatigue mechanisms of AP from the perspective of microbiome, metabolome, and proteome.

RESULTS

The detection of physiology, hematology and biochemistry index indicated that AP markedly alleviate mice fatigue state induced by sleep deprivation. The 16S rRNA sequencing showed the AP promoted the abundance of probiotics (Odoribacter, Dubosiella, Marvinbryantia, and Eubacterium) and suppressed harmful bacteria (Ruminococcus). On the other hand, AP was found to regulate the expression of colonic proteins, such as increases of adenosine triphosphate (ATP) synthesis and mitochondrial function related proteins, including ATP5A1, ATP5O, ATP5L, ATP5H, NDUFA, NDUFB, NDUFS, and NDUFV. Serum metabolomic analysis revealed AP upregulated the levels of anti-fatigue amino acids, such as taurine, leucine, arginine, glutamine, lysine, and l-proline. Hepatic proteins express levels, especially tricarboxylic acid (TCA) cycle (CS, SDHB, MDH2, and DLST) and redox-related proteins (SOD1, SOD2, GPX4, and PRDX3), were significantly recovered by AP administration. Spearman correlation analysis uncovered the strong correlation between microbiome, metabolome and proteome, suggesting the anti-fatigue effects of AP is attribute to the energy homeostasis and redox balance through gut-liver axis.

CONCLUSION

AP increased colonic ATP production and improve mitochondrial function by regulating gut microbiota, and further upregulated anti-fatigue amino acid levels in the blood. Based on the gut-liver axis, AP upregulated the hepatic tricarboxylic acid cycle and oxidoreductase-related protein expression, regulating energy homeostasis and redox balance, and ultimately exerting anti-fatigue effects. This study provides insights into the anti-fatigue mechanisms of AP, highlighting its potential as a therapeutic agent.

AMBRA1 levels predict resistance to MAPK inhibitors in melanoma

Intrinsic and acquired resistance to mitogen-activated protein kinase inhibitors (MAPKi) in melanoma remains a major therapeutic challenge. Here, we show that the clinical development of resistance to MAPKi is associated with reduced tumor expression of the melanoma suppressor Autophagy and Beclin 1 Regulator 1 (AMBRA1) and that lower expression levels of AMBRA1 predict a poor response to MAPKi treatment. Functional analyses show that loss of AMBRA1 induces phenotype switching and orchestrates an extracellular signal-regulated kinase (ERK)-independent resistance mechanism by activating focal adhesion kinase 1 (FAK1). In both in vitro and in vivo settings, melanomas with low AMBRA1 expression exhibit intrinsic resistance to MAPKi therapy but higher sensitivity to FAK1 inhibition. Finally, we show that the rapid development of resistance in initially MAPKi-sensitive melanomas can be attributed to preexisting subclones characterized by low AMBRA1 expression and that cotreatment with MAPKi and FAK1 inhibitors (FAKi) effectively prevents the development of resistance in these tumors. In summary, our findings underscore the value of AMBRA1 expression for predicting melanoma response to MAPKi and supporting the therapeutic efficacy of FAKi to overcome MAPKi-induced resistance.

Pan-cancer proteogenomics expands the landscape of therapeutic targets

Fewer than 200 proteins are targeted by cancer drugs approved by the Food and Drug Administration (FDA). We integrate Clinical Proteomic Tumor Analysis Consortium (CPTAC) proteogenomics data from 1,043 patients across 10 cancer types with additional public datasets to identify potential therapeutic targets. Pan-cancer analysis of 2,863 druggable proteins reveals a wide abundance range and identifies biological factors that affect mRNA-protein correlation. Integration of proteomic data from tumors and genetic screen data from cell lines identifies protein overexpression- or hyperactivation-driven druggable dependencies, enabling accurate predictions of effective drug targets. Proteogenomic identification of synthetic lethality provides a strategy to target tumor suppressor gene loss. Combining proteogenomic analysis and MHC binding prediction prioritizes mutant KRAS peptides as promising public neoantigens. Computational identification of shared tumor-associated antigens followed by experimental confirmation nominates peptides as immunotherapy targets. These analyses, summarized at https://targets.linkedomics.org, form a comprehensive landscape of protein and peptide targets for companion diagnostics, drug repurposing, and therapy development.

A Novel AMPK Inhibitor Sensitizes Pancreatic Cancer Cells to Ferroptosis Induction

Cancer cells must develop strategies to adapt to the dynamically changing stresses caused by intrinsic or extrinsic processes, or therapeutic agents. Metabolic adaptability is crucial to mitigate such challenges. Considering metabolism as a central node of adaptability, it is focused on an energy sensor, the AMP-activated protein kinase (AMPK). In a subtype of pancreatic ductal adenocarcinoma (PDAC) elevated AMPK expression and phosphorylation is identified. Using drug repurposing that combined screening experiments and chemoproteomic affinity profiling, it is identified and characterized PF-3758309, initially developed as an inhibitor of PAK4, as an AMPK inhibitor. PF-3758309 shows activity in pre-clinical PDAC models, including primary patient-derived organoids. Genetic loss-of-function experiments showed that AMPK limits the induction of ferroptosis, and consequently, PF-3758309 treatment restores the sensitivity toward ferroptosis inducers. The work established a chemical scaffold for the development of specific AMPK-targeting compounds and deciphered the framework for the development of AMPK inhibitor-based combination therapies tailored for PDAC.

Bioinformatic Analysis Reveals the Association of Human N-Terminal Acetyltransferase Complexes with Distinct Transcriptional and Post-Transcriptional Processes

N-terminal acetyltransferases (NAT) are the protein complexes that deposit the abundant N-terminal acetylation (Nt-Ac) on eukaryotic proteins, with seven human complexes currently identified. Despite the increasing recognition of their biological and clinical importance, NAT regulation remains elusive. In this study, we performed a bioinformatic investigation to identify transcriptional and post-transcriptional processes that could be involved in the regulation of human NAT complexes. First, co-expression analysis of independent transcriptomic datasets revealed divergent pathway associations for human NAT, which are potentially connected to their distinct cellular functions. One interesting connection uncovered was the coordinated regulation of the NatA and proteasomal genes in cancer and immune cells, confirmed by analysis of multiple datasets and in isolated primary T cells. Another distinctive association was of NAA40 (NatD) with DNA replication, in cancer and non-cancer settings. The link between NAA40 transcription and DNA replication is potentially mediated through E2F1, which we have experimentally shown to bind the promoter of this NAT. Second, the coupled examination of transcriptomic and proteomic datasets revealed a much greater intra-complex concordance of NAT subunits at the protein compared to the transcript level, indicating the predominance of post-transcriptional processes for achieving their coordination. In agreement with this concept, we also found that the effects of somatic copy number alterations affecting NAT genes are attenuated post-transcriptionally. In conclusion, this study provides novel insights into the regulation of human NAT complexes.

Aberrant spliceosome activity via elevated intron retention and upregulation and phosphorylation of SF3B1 in chronic lymphocytic leukemia

Splicing factor 3b subunit 1 (SF3B1) is the largest subunit and core component of the spliceosome. Inhibition of SF3B1 was associated with an increase in broad intron retention (IR) on most transcripts, suggesting that IR can be used as a marker of spliceosome inhibition in chronic lymphocytic leukemia (CLL) cells. Furthermore, we separately analyzed exonic and intronic mapped reads on annotated RNA-sequencing transcripts obtained from B cells (n = 98 CLL patients) and healthy volunteers (n = 9). We measured intron/exon ratio to use that as a surrogate for alternative RNA splicing (ARS) and found that 66% of CLL-B cell transcripts had significant IR elevation compared with normal B cells (NBCs) and that correlated with mRNA downregulation and low expression levels. Transcripts with the highest IR levels belonged to biological pathways associated with gene expression and RNA splicing. A >2-fold increase of active pSF3B1 was observed in CLL-B cells compared with NBCs. Additionally, when the CLL-B cells were treated with macrolides (pladienolide-B), a significant decrease in pSF3B1, but not total SF3B1 protein, was observed. These findings suggest that IR/ARS is increased in CLL, which is associated with SF3B1 phosphorylation and susceptibility to SF3B1 inhibitors. These data provide additional support to the relevance of ARS in carcinogenesis and evidence of pSF3B1 participation in this process.

Exploring the prognostic significance of arm-level copy number alterations in triple-negative breast cancer

Somatic copy number alterations (SCNAs) are prevalent in cancer and play a significant role in both tumorigenesis and therapeutic resistance. While focal SCNAs have been extensively studied, the impact of larger arm-level SCNAs remains poorly understood. Here, we investigated the association between arm-level SCNAs and overall survival in triple-negative breast cancer (TNBC), an aggressive subtype of breast cancer lacking targeted therapies. We identified frequent arm-level SCNAs, including 21q gain and 7p gain, which correlated with poor overall survival in TNBC patients. Further, we identified the expression of specific genes within these SCNAs associated with survival. Notably, we found that the expression of RIPK4, a gene located on 21q, exhibited a strong correlation with poor overall survival. In functional assays, we demonstrated that targeting Ripk4 in a murine lung metastatic TNBC model significantly reduced tumor burden, improved survival, and increased CD4+ and CD8+ T cell infiltration. RIPK4 enhanced the survival of triple-negative breast cancer cells at secondary sites, thereby facilitating the formation of metastatic lesions. Our findings highlight the significance of arm-level SCNAs in breast cancer progression and identify RIPK4 as a putative driver of TNBC metastasis and immunosuppression.

Proteomics analysis of histone deacetylase inhibitor-resistant solid tumors reveals resistant signatures and potential drug combinations

Histone deacetylase inhibitors (HDACis) are important drugs for cancer therapy, but the indistinct resistant mechanisms of solid tumor therapy greatly limit their clinical application. In this study we conducted HDACi-perturbated proteomics and phosphoproteomics analyses in HDACi-sensitive and -resistant cell lines using a tandem mass tag (TMT)-based quantitative proteomic strategy. We found that the ribosome biogenesis proteins MRTO4, PES1, WDR74 and NOP16 vital to tumorigenesis might regulate the tumor sensitivity to HDACi. By integrating HDACi-perturbated protein signature with previously reported proteomics and drug sensitivity data, we predicted and validated a series of drug combination pairs potentially to enhance the sensitivity of HDACi in diverse solid tumor. Functional phosphoproteomic analysis further identified the kinase PDK1 and ROCK as potential HDACi-resistant signatures. Overall, this study reveals the potential HDACi-resistant signatures and may provide promising drug combination strategies to attenuate the resistance of solid tumor to HDACi.

WDR4 promotes HCC pathogenesis through N7-methylguanosine by regulating and interacting with METTL1

BACKGROUND

The N7-methylguanosine (m7G), a modification at defined internal positions within tRNAs and rRNAs, is correlated with tumor progression. Methyltransferase like 1 (METTL1)/ WD repeat domain 4 (WDR4) mediated tRNA m7G modification, which could alter many oncogenic mRNAs translation to promote progress of multiple cancer types. However, whether and how the internal mRNA m7G modification is involved in tumorigenesis remains unclear.

METHODS

The immunohistochemistry assay was conducted to detect the expression of WDR4 and METTL1 in hepatocellular carcinoma (HCC) and the expression of both genes whether contributes to the prognosis of the survival rate of HCC patients. Then, CCK8, colony formation assays and tumor xenograft models were conducted to determine the effects of WDR4 on HCC cells in vitro and vivo. Besides, dot blot assay, m7G-MeRIP-seq and RNA-seq analysis were conducted to determine whether WDR4 contributes to m7G modification and underlying mechanism in HCC cells. Finally, rescue and CO-IP assay were conducted to explore whether WDR4 and METTL1 proteins form a complex in Huh7 cells.

RESULTS

WDR4 modulates m7G modification at the internal sites of tumor-promoting mRNAs by forming the WDR4-METTL1 complex. WDR4 knockdown downregulated the expression of mRNA and protein levels of METTL1 gene and thus further modulate the formation of WDR4-METTL1 complex indirectly. METTL1 expression was markedly correlated with WDR4 expression in HCC tissues. HCC patients with high expression of both genes had a poor prognosis.

CONCLUSIONS

WDR4 may contribute to HCC pathogenesis by interacting with and regulating the expression of METTL1 to synergistically modulate the m7G modification of target mRNAs in tumor cells.

RAS-RAF-miR-296-3p signaling axis increases Rad18 expression to augment radioresistance in pancreatic and thyroid cancers

Oncogenic RAS and RAF signaling has been implicated in contributing to radioresistance in pancreatic and thyroid cancers. In this study, we sought to better clarify molecular mechanisms contributing to this effect. We discovered that miRNA 296-3p (miR-296-3p) is significantly correlated with radiosensitivity in a panel of pancreatic cancer cells, and miR-296-3p is highly expressed in normal cells, but low in cancer cell lines. Elevated expression of miR-296-3p increases radiosensitization while decreasing the expression of the DNA repair enzyme RAD18 in both pancreatic and thyroid cancer cells. RAD18 is overexpressed in both pancreatic and thyroid tumors compared to matched normal controls, and high expression of RAD18 in tumors is associated with poor prognostic features. Modulating the expression of mutant KRAS in pancreatic cancer cells or mutant BRAF in thyroid cancer cells demonstrates a tight regulation of RAD18 expression in both cancer types. Depletion of RAD18 results in DNA damage and radiation-induced cell death. Importantly, RAD18 depletion in combination with radiotherapy results in marked and sustained tumor regression in KRAS mutant pancreatic cancer orthotopic tumors and BRAF mutant thyroid heterotopic tumors. Overall, our findings identify a novel coordinated RAS/RAF-miR-296-3p-RAD18 signaling network in pancreatic and thyroid cancer cells, which leads to enhanced radioresistance.

ADAM-17 Activity and Its Relation to ACE2: Implications for Severe COVID-19

There is a lack of studies aiming to assess cellular a disintegrin and metalloproteinase-17 (ADAM-17) activity in COVID-19 patients and the eventual associations with the shedding of membrane-bound angiotensin-converting enzyme 2 (mACE2). In addition, studies that investigate the relationship between ACE2 and ADAM-17 gene expressions in organs infected by SARS-CoV-2 are lacking. We used data from the Massachusetts general hospital COVID-19 study (306 COVID-19 patients and 78 symptomatic controls) to investigate the association between plasma levels of 33 different ADAM-17 substrates and COVID-19 severity and mortality. As a surrogate of cellular ADAM-17 activity, an ADAM-17 substrate score was calculated. The associations between soluble ACE2 (sACE2) and the ADAM-17 substrate score, renin, key inflammatory markers, and lung injury markers were investigated. Furthermore, we used data from the Genotype-Tissue Expression (GTEx) database to evaluate ADAM-17 and ACE2 gene expressions by age and sex in ages between 20-80 years. We found that increased ADAM-17 activity, as estimated by the ADAM-17 substrates score, was associated with COVID-19 severity (p = 0.001). ADAM-17 activity was also associated with increased mortality but did not reach statistical significance (p = 0.06). Soluble ACE2 showed the strongest positive correlation with the ADAM-17 substrate score, follow by renin, interleukin-6, and lung injury biomarkers. The ratio of ADAM-17 to ACE2 gene expression was highest in the lung. This study indicates that increased ADAM-17 activity is associated with severe COVID-19. Our findings also indicate that there may a bidirectional relationship between membrane-bound ACE2 shedding via increased ADAM-17 activity, dysregulated renin-angiotensin system (RAS) and immune signaling. Additionally, differences in ACE2 and ADAM-17 gene expressions between different tissues may be of importance in explaining why the lung is the organ most severely affected by COVID-19, but this requires further evaluation in prospective studies.

Identification and Validation of Nicotinamide Metabolism-Related Gene Signatures as a Novel Prognostic Model for Hepatocellular Carcinoma

Background

Nicotinamide (NAM+) regulates redox and metabolic activities in the mitochondria. The intention of the research was to identify key genes that relate to nicotinamide in hepatocellular carcinoma (HCC).

Methods

Relevant clinical information were collected as well as RNA-seq data using the Cancer Genome Atlas (TCGA) database. Differential analysis was used to discover the genes that were differently expressed. On the key genes associated with NAM, functional enrichment analysis was carried out. Next, receiver operating characteristic (ROC) and prognosis Kaplan-Meier (K-M) curve analyses were used to evaluate the importance of important gene expression, respectively. The immune cell signatures were estimated using the CIBERSORT algorithm. Finally, the anticancer impact of NAM on HCC was experimentally confirmed, and important genes NADSYN1 and NT5C were validated at the protein level in clinical specimens.

Results

Six prognostic key genes (NAXE, NADSYN1, NT5C, NT5C3A, PNP and NT5E) were identified. There is an association between the level of key gene expression and the clinical prognosis. Four key genes (NAXE, NADSYN1, NT5C and NT5C3A) have statistical significance of survival prognosis. Finally, the expression of NAM-related genes and the inhibitory effect of NAM on HCC were verified by experiments.

Conclusion

The study first found some Nicotinamide metabolism-related differentially expressed genes (NMRDEGs) that are related to HCC can contribute to predicting survival and monitoring the treatment.

Lineage-specific proteome remodeling of diverse lung cancer cells by targeted epigenetic inhibitors

Epigenetic inhibitors exhibit powerful antiproliferative and anticancer activities. However, cellular responses to small-molecule epigenetic inhibition are heterogenous and dependent on factors such as the genetic background, metabolic state, and on-/off-target engagement of individual small-molecule drugs. To determine the mechanisms that drive these heterogeneous cellular responses, we quantified chromatin, proteome, and transcriptome remodeling due to histone deacetylase inhibitor (HDACi) -treated cells derived from diverse genetic backgrounds. We utilized high-throughput sample multiplexed proteomics and integrated intelligent data acquisition methods to map proteomes of cancer cell lines in response to HDACi. We determined cell type-specific and ubiquitous cellular responses based on the quantification of 10,621 total proteins. We then established how coordinated remodeling of the proteome, transcriptome and chromatin state of HDACi treated cancer cells revealed convergent (JUN, MAP2K3, CDKN1A) and divergent (CCND3, ASF1B, BRD7) molecular phenotypes. HDACi-regulated proteins differ greatly across cell lines owing to heterogeneous molecular states of these cell lines. Finally, we demonstrated that HDACi treatment drove a highly cell-type specific response that may in part be explained by cell line-specific off-target drug engagement.

Proteomic analysis of the urothelial cancer landscape

Urothelial bladder cancer (UC) has a wide tumor biological spectrum with challenging prognostic stratification and relevant therapy-associated morbidity. Most molecular classifications relate only indirectly to the therapeutically relevant protein level. We improve the pre-analytics of clinical samples for proteome analyses and characterize a cohort of 434 samples with 242 tumors and 192 paired normal mucosae covering the full range of UC. We evaluate sample-wise tumor specificity and rank biomarkers by target relevance. We identify robust proteomic subtypes with prognostic information independent from histopathological groups. In silico drug prediction suggests efficacy of several compounds hitherto not in clinical use. Both in silico and in vitro data indicate predictive value of the proteomic clusters for these drugs. We underline that proteomics is relevant for personalized oncology and provide abundance and tumor specificity data for a large part of the UC proteome ( www.cancerproteins.org ).

Tissue-specific landscape of protein aggregation and quality control in an aging vertebrate

Protein aggregation is a hallmark of age-related neurodegeneration. Yet, aggregation during normal aging and in tissues other than the brain is poorly understood. Here, we leverage the African turquoise killifish to systematically profile protein aggregates in seven tissues of an aging vertebrate. Age-dependent aggregation is strikingly tissue specific and not simply driven by protein expression differences. Experimental interrogation in killifish and yeast, combined with machine learning, indicates that this specificity is linked to protein-autonomous biophysical features and tissue-selective alterations in protein quality control. Co-aggregation of protein quality control machinery during aging may further reduce proteostasis capacity, exacerbating aggregate burden. A segmental progeria model with accelerated aging in specific tissues exhibits selectively increased aggregation in these same tissues. Intriguingly, many age-related protein aggregates arise in wild-type proteins that, when mutated, drive human diseases. Our data chart a comprehensive landscape of protein aggregation during vertebrate aging and identify strong, tissue-specific associations with dysfunction and disease.

GAS-Luc2 Reporter Cell Lines for Immune Checkpoint Drug Screening in Solid Tumors

Recent studies highlight the integral role of the interferon gamma receptor (IFNγR) pathway in T cell-mediated cytotoxicity against solid but not liquid tumors. IFNγ not only directly facilitates tumor cell death by T cells but also indirectly promotes cytotoxicity via myeloid phagocytosis in the tumor microenvironment. Meanwhile, full human ex vivo immune checkpoint drug screening remains challenging. We hypothesized that an engineered gamma interferon activation site response element luciferase reporter (GAS-Luc2) can be utilized for immune checkpoint drug screening in diverse ex vivo T cell-solid tumor cell co-culture systems. We comprehensively profiled cell surface proteins in ATCC's extensive collection of human tumor and immune cell lines, identifying those with endogenously high expression of established and novel immune checkpoint molecules and binding ligands. We then engineered three GAS-Luc2 reporter tumor cell lines expressing immune checkpoints PD-L1, CD155, or B7-H3/CD276. Luciferase expression was suppressed upon relevant immune checkpoint-ligand engagement. In the presence of an immune checkpoint inhibitor, T cells released IFNγ, activating the JAK-STAT pathway in GAS-Luc2 cells, and generating a quantifiable bioluminescent signal for inhibitor evaluation. These reporter lines also detected paracrine IFNγ signaling for immune checkpoint-targeted ADCC drug screening. Further development into an artificial antigen-presenting cell line (aAPC) significantly enhanced T cell signaling for superior performance in these ex vivo immune checkpoint drug screening platforms.

N-MYC impairs innate immune signaling in high-grade serous ovarian carcinoma

High-grade serous ovarian cancer (HGSC) is a challenging disease, especially for patients with immunologically "cold" tumors devoid of tumor-infiltrating lymphocytes (TILs). We found that HGSC exhibits among the highest levels of MYCN expression and transcriptional signature across human cancers, which is strongly linked to diminished features of antitumor immunity. N-MYC repressed basal and induced IFN type I signaling in HGSC cell lines, leading to decreased chemokine expression and T cell chemoattraction. N-MYC inhibited the induction of IFN type I by suppressing tumor cell-intrinsic STING signaling via reduced STING oligomerization, and by blunting RIG-I-like receptor signaling through inhibition of MAVS aggregation and localization in the mitochondria. Single-cell RNA sequencing of human clinical HGSC samples revealed a strong negative association between cancer cell-intrinsic MYCN transcriptional program and type I IFN signaling. Thus, N-MYC inhibits tumor cell-intrinsic innate immune signaling in HGSC, making it a compelling target for immunotherapy of cold tumors.

Landscape of human organoids: Ideal model in clinics and research

In the last decade, organoid research has entered a golden era, signifying a pivotal shift in the biomedical landscape. The year 2023 marked a milestone with the publication of thousands of papers in this arena, reflecting exponential growth. However, amid this burgeoning expansion, a comprehensive and accurate overview of the field has been conspicuously absent. Our review is intended to bridge this gap, providing a panoramic view of the rapidly evolving organoid landscape. We meticulously analyze the organoid field from eight distinctive vantage points, harnessing our rich experience in academic research, industrial application, and clinical practice. We present a deep exploration of the advances in organoid technology, underpinned by our long-standing involvement in this arena. Our narrative traverses the historical genesis of organoids and their transformative impact across various biomedical sectors, including oncology, toxicology, and drug development. We delve into the synergy between organoids and avant-garde technologies such as synthetic biology and single-cell omics and discuss their pivotal role in tailoring personalized medicine, enhancing high-throughput drug screening, and constructing physiologically pertinent disease models. Our comprehensive analysis and reflective discourse provide a deep dive into the existing landscape and emerging trends in organoid technology. We spotlight technological innovations, methodological evolution, and the broadening spectrum of applications, emphasizing the revolutionary influence of organoids in personalized medicine, oncology, drug discovery, and other fields. Looking ahead, we cautiously anticipate future developments in the field of organoid research, especially its potential implications for personalized patient care, new avenues of drug discovery, and clinical research. We trust that our comprehensive review will be an asset for researchers, clinicians, and patients with keen interest in personalized medical strategies. We offer a broad view of the present and prospective capabilities of organoid technology, encompassing a wide range of current and future applications. In summary, in this review we attempt a comprehensive exploration of the organoid field. We offer reflections, summaries, and projections that might be useful for current researchers and clinicians, and we hope to contribute to shaping the evolving trajectory of this dynamic and rapidly advancing field.

Molecular and Pathologic Characterization of YAP1-Expressing Small Cell Lung Cancer Cell Lines Leads to Reclassification as SMARCA4-Deficient Malignancies

PURPOSE

The classification of small cell lung cancer (SCLC) into distinct molecular subtypes defined by ASCL1, NEUROD1, POU2F3, or YAP1 (SCLC-A, -N, -P, or -Y) expression, paves the way for a personalized treatment approach. However, the existence of a distinct YAP1-expressing SCLC subtype remains controversial.

EXPERIMENTAL DESIGN

To better understand YAP1-expressing SCLC, the mutational landscape of human SCLC cell lines was interrogated to identify pathogenic alterations unique to SCLC-Y. Xenograft tumors, generated from cell lines representing the four SCLC molecular subtypes, were evaluated by a panel of pathologists who routinely diagnose thoracic malignancies. Diagnoses were complemented by transcriptomic analysis of primary tumors and human cell line datasets. Protein expression profiles were validated in patient tumor tissue.

RESULTS

Unexpectedly, pathogenic mutations in SMARCA4 were identified in six of eight SCLC-Y cell lines and correlated with reduced SMARCA4 mRNA and protein expression. Pathologist evaluations revealed that SMARCA4-deficient SCLC-Y tumors exhibited features consistent with thoracic SMARCA4-deficient undifferentiated tumors (SMARCA4-UT). Similarly, the transcriptional profile SMARCA4-mutant SCLC-Y lines more closely resembled primary SMARCA4-UT, or SMARCA4-deficient non-small cell carcinoma, than SCLC. Furthermore, SMARCA4-UT patient samples were associated with a YAP1 transcriptional signature and exhibited strong YAP1 protein expression. Together, we found little evidence to support a diagnosis of SCLC for any of the YAP1-expressing cell lines originally used to define the SCLC-Y subtype.

CONCLUSIONS

SMARCA4-mutant SCLC-Y cell lines exhibit characteristics consistent with SMARCA4-deficient malignancies rather than SCLC. Our findings suggest that, unlike ASCL1, NEUROD1, and POU2F3, YAP1 is not a subtype defining transcription factor in SCLC. See related commentary by Rekhtman, p. 1708.

Liebig's law of the minimum in the TGF-β/SMAD pathway

Cells use signaling pathways to sense and respond to their environments. The transforming growth factor-β (TGF-β) pathway produces context-specific responses. Here, we combined modeling and experimental analysis to study the dependence of the output of the TGF-β pathway on the abundance of signaling molecules in the pathway. We showed that the TGF-β pathway processes the variation of TGF-β receptor abundance using Liebig's law of the minimum, meaning that the output-modifying factor is the signaling protein that is most limited, to determine signaling responses across cell types and in single cells. We found that the abundance of either the type I (TGFBR1) or type II (TGFBR2) TGF-β receptor determined the responses of cancer cell lines, such that the receptor with relatively low abundance dictates the response. Furthermore, nuclear SMAD2 signaling correlated with the abundance of TGF-β receptor in single cells depending on the relative expression levels of TGFBR1 and TGFBR2. A similar control principle could govern the heterogeneity of signaling responses in other signaling pathways.

Large-scale Pan-cancer Cell Line Screening Identifies Actionable and Effective Drug Combinations

Oncology drug combinations can improve therapeutic responses and increase treatment options for patients. The number of possible combinations is vast and responses can be context-specific. Systematic screens can identify clinically relevant, actionable combinations in defined patient subtypes. We present data for 109 anticancer drug combinations from AstraZeneca's oncology small molecule portfolio screened in 755 pan-cancer cell lines. Combinations were screened in a 7 × 7 concentration matrix, with more than 4 million measurements of sensitivity, producing an exceptionally data-rich resource. We implement a new approach using combination Emax (viability effect) and highest single agent (HSA) to assess combination benefit. We designed a clinical translatability workflow to identify combinations with clearly defined patient populations, rationale for tolerability based on tumor type and combination-specific "emergent" biomarkers, and exposures relevant to clinical doses. We describe three actionable combinations in defined cancer types, confirmed in vitro and in vivo, with a focus on hematologic cancers and apoptotic targets.

SIGNIFICANCE

We present the largest cancer drug combination screen published to date with 7 × 7 concentration response matrices for 109 combinations in more than 750 cell lines, complemented by multi-omics predictors of response and identification of "emergent" combination biomarkers. We prioritize hits to optimize clinical translatability, and experimentally validate novel combination hypotheses. This article is featured in Selected Articles from This Issue, p. 695.

Droplet-based proteomics reveals CD36 as a marker for progenitors in mammary basal epithelium

Deep proteomic profiling of rare cell populations has been constrained by sample input requirements. Here, we present DROPPS (droplet-based one-pot preparation for proteomic samples), an accessible low-input platform that generates high-fidelity proteomic profiles of 100-2,500 cells. By applying DROPPS within the mammary epithelium, we elucidated the connection between mitochondrial activity and clonogenicity, identifying CD36 as a marker of progenitor capacity in the basal cell compartment. We anticipate that DROPPS will accelerate biology-driven proteomic research for a multitude of rare cell populations.

Machine Learning of Three-Dimensional Protein Structures to Predict the Functional Impacts of Genome Variation

Research in the human genome sciences generates a substantial amount of genetic data for hundreds of thousands of individuals, which concomitantly increases the number of variants of unknown significance (VUS). Bioinformatic analyses can successfully reveal rare variants and variants with clear associations with disease-related phenotypes. These studies have had a significant impact on how clinical genetic screens are interpreted and how patients are stratified for treatment. There are few, if any, computational methods for variants comparable to biological activity predictions. To address this gap, we developed a machine learning method that uses protein three-dimensional structures from AlphaFold to predict how a variant will influence changes to a gene's downstream biological pathways. We trained state-of-the-art machine learning classifiers to predict which protein regions will most likely impact transcriptional activities of two proto-oncogenes, nuclear factor erythroid 2 (NFE2L2)-related factor 2 (NRF2) and c-Myc. We have identified classifiers that attain accuracies higher than 80%, which have allowed us to identify a set of key protein regions that lead to significant perturbations in c-Myc or NRF2 transcriptional pathway activities.

Drug repositioning for immunotherapy in breast cancer using single-cell analysis

Immunomodulatory peptides, while exhibiting potential antimicrobial, antifungal, and/or antiviral properties, can play a role in stimulating or suppressing the immune system, especially in pathological conditions like breast cancer (BC). Thus, deregulation of these peptides may serve as an immunotherapeutic strategy to enhance the immune response. In this meta-analysis, we utilized single-cell RNA sequencing data and known therapeutic peptides to investigate the deregulation of these peptides in malignant versus normal human breast epithelial cells. We corroborated our findings at the chromatin level using ATAC-seq. Additionally, we assessed the protein levels in various BC cell lines. Moreover, our in-house drug repositioning approach was employed to identify potential drugs that could positively impact the relapse-free survival of BC patients. Considering significantly deregulated therapeutic peptides and their role in BC pathology, our approach aims to downregulate B2M and SLPI, while upregulating PIGR, DEFB1, LTF, CLU, S100A7, and SCGB2A1 in BC epithelial cells through our drug repositioning pipeline. Leveraging the LINCS L1000 database, we propose BRD-A06641369 for B2M downregulation and ST-4070043 and BRD-K97926541 for SLPI downregulation without negatively affecting the MHC complex as a significantly correlated pathway with these two genes. Furthermore, we have compiled a comprehensive list of drugs for the upregulation of other selected immunomodulatory peptides. Employing an immunotherapeutic approach by integrating our drug repositioning pipeline with single-cell analysis, we proposed potential drugs and drug targets to fortify the immune system against BC.

Rapid profiling of transcription factor-cofactor interaction networks reveals principles of epigenetic regulation

Transcription factor (TF)-cofactor (COF) interactions define dynamic, cell-specific networks that govern gene expression; however, these networks are understudied due to a lack of methods for high-throughput profiling of DNA-bound TF-COF complexes. Here we describe the Cofactor Recruitment (CoRec) method for rapid profiling of cell-specific TF-COF complexes. We define a lysine acetyltransferase (KAT)-TF network in resting and stimulated T cells. We find promiscuous recruitment of KATs for many TFs and that 35% of KAT-TF interactions are condition specific. KAT-TF interactions identify NF-κB as a primary regulator of acutely induced H3K27ac. Finally, we find that heterotypic clustering of CBP/P300-recruiting TFs is a strong predictor of total promoter H3K27ac. Our data supports clustering of TF sites that broadly recruit KATs as a mechanism for widespread co-occurring histone acetylation marks. CoRec can be readily applied to different cell systems and provides a powerful approach to define TF-COF networks impacting chromatin state and gene regulation.

EP300/CREBBP acetyltransferase inhibition limits steroid receptor and FOXA1 signaling in prostate cancer cells

The androgen receptor (AR) is a primary target for treating prostate cancer (PCa), forming the bedrock of its clinical management. Despite their efficacy, resistance often hampers AR-targeted therapies, necessitating new strategies against therapy-resistant PCa. These resistances involve various mechanisms, including AR splice variant overexpression and altered activities of transcription factors like the glucocorticoid receptor (GR) and FOXA1. These factors rely on common coregulators, such as EP300/CREBBP, suggesting a rationale for coregulator-targeted therapies. Our study explores EP300/CREBBP acetyltransferase inhibition's impact on steroid receptor and FOXA1 signaling in PCa cells using genome-wide techniques. Results reveal that EP300/CREBBP inhibition significantly disrupts the AR-regulated transcriptome and receptor chromatin binding by reducing the AR-gene expression. Similarly, GR's regulated transcriptome and receptor binding were hindered, not linked to reduced GR expression but to diminished FOXA1 chromatin binding, restricting GR signaling. Overall, our findings highlight how EP300/CREBBP inhibition distinctively curtails oncogenic transcription factors' signaling, suggesting the potential of coregulatory-targeted therapies in PCa.

A paradigm shift in cancer research based on integrative multi-omics approaches: glutaminase serves as a pioneering cuproptosis-related gene in pan-cancer

BACKGROUND

Cuproptosis is a newly identified form of unprogrammed cell death. As a pivotal metabolic regulator, glutaminase (GLS) has recently been discovered to be linked to cuproptosis. Despite this discovery, the oncogenic functions and mechanisms of GLS in various cancers are still not fully understood.

METHODS

In this study, a comprehensive omics analysis was performed to investigate the differential expression levels, diagnostic and prognostic potential, correlation with tumor immune infiltration, genetic alterations, and drug sensitivity of GLS across multiple malignancies.

RESULTS

Our findings revealed unique expression patterns of GLS across various cancer types and molecular subtypes of carcinomas, underscoring its pivotal role primarily in energy and nutrition metabolism. Additionally, GLS showed remarkable diagnostic and prognostic performance in specific cancers, suggesting its potential as a promising biomarker for cancer detection and prognosis. Furthermore, we focused on uterine corpus endometrial carcinoma (UCEC) and developed a novel prognostic model associated with GLS, indicating a close correlation between GLS and UCEC. Moreover, our exploration into immune infiltration, genetic heterogeneity, tumor stemness, and drug sensitivity provided novel insights and directions for future research and laid the foundation for high-quality verification.

CONCLUSION

Collectively, our study is the first comprehensive investigation of the biological and clinical significance of GLS in pan-cancer. In our study, GLS was identified as a promising biomarker for UCEC, providing valuable evidence and a potential target for anti-tumor therapy. Overall, our findings shed light on the multifaceted functions of GLS in cancer and offer new avenues for further research.

Targeting PRMT9-mediated arginine methylation suppresses cancer stem cell maintenance and elicits cGAS-mediated anticancer immunity

Current anticancer therapies cannot eliminate all cancer cells, which hijack normal arginine methylation as a means to promote their maintenance via unknown mechanisms. Here we show that targeting protein arginine N-methyltransferase 9 (PRMT9), whose activities are elevated in blasts and leukemia stem cells (LSCs) from patients with acute myeloid leukemia (AML), eliminates disease via cancer-intrinsic mechanisms and cancer-extrinsic type I interferon (IFN)-associated immunity. PRMT9 ablation in AML cells decreased the arginine methylation of regulators of RNA translation and the DNA damage response, suppressing cell survival. Notably, PRMT9 inhibition promoted DNA damage and activated cyclic GMP-AMP synthase, which underlies the type I IFN response. Genetically activating cyclic GMP-AMP synthase in AML cells blocked leukemogenesis. We also report synergy of a PRMT9 inhibitor with anti-programmed cell death protein 1 in eradicating AML. Overall, we conclude that PRMT9 functions in survival and immune evasion of both LSCs and non-LSCs; targeting PRMT9 may represent a potential anticancer strategy.

Modulating autophagy to treat diseases: A revisited review on in silico methods

BACKGROUND

Autophagy refers to the conserved cellular catabolic process relevant to lysosome activity and plays a vital role in maintaining the dynamic equilibrium of intracellular matter by degrading harmful and abnormally accumulated cellular components. Accumulating evidence has recently revealed that dysregulation of autophagy by genetic and exogenous interventions may disrupt cellular homeostasis in human diseases. In silico approaches as powerful aids to experiments have also been extensively reported to play their critical roles in the storage, prediction, and analysis of massive amounts of experimental data. Thus, modulating autophagy to treat diseases by in silico methods would be anticipated.

AIM OF REVIEW

Here, we focus on summarizing the updated in silico approaches including databases, systems biology network approaches, omics-based analyses, mathematical models, and artificial intelligence (AI) methods that sought to modulate autophagy for potential therapeutic purposes, which will provide a new insight into more promising therapeutic strategies.

KEY SCIENTIFIC CONCEPTS OF REVIEW

Autophagy-related databases are the data basis of the in silico method, storing a large amount of information about DNA, RNA, proteins, small molecules and diseases. The systems biology approach is a method to systematically study the interrelationships among biological processes including autophagy from a macroscopic perspective. Omics-based analyses are based on high-throughput data to analyze gene expression at different levels of biological processes involving autophagy. mathematical models are visualization methods to describe the dynamic process of autophagy, and its accuracy is related to the selection of parameters. AI methods use big data related to autophagy to predict autophagy targets, design targeted small molecules, and classify diverse human diseases for potential therapeutic applications.

CKAP5 stabilizes CENP-E at kinetochores by regulating microtubule-chromosome attachments

Stabilization of microtubule plus end-directed kinesin CENP-E at the metaphase kinetochores is important for chromosome alignment, but its mechanism remains unclear. Here, we show that CKAP5, a conserved microtubule plus tip protein, regulates CENP-E at kinetochores in human cells. Depletion of CKAP5 impairs CENP-E localization at kinetochores at the metaphase plate and results in increased kinetochore-microtubule stability and attachment errors. Erroneous attachments are also supported by computational modeling. Analysis of CKAP5 knockout cancer cells of multiple tissue origins shows that CKAP5 is preferentially essential in aneuploid, chromosomally unstable cells, and the sensitivity to CKAP5 depletion is correlated to that of CENP-E depletion. CKAP5 depletion leads to reduction in CENP-E-BubR1 interaction and the interaction is rescued by TOG4-TOG5 domain of CKAP5. The same domain can rescue CKAP5 depletion-induced CENP-E removal from the kinetochores. Interestingly, CKAP5 depletion facilitates recruitment of PP1 to the kinetochores and furthermore, a PP1 target site-specific CENP-E phospho-mimicking mutant gets stabilized at kinetochores in the CKAP5-depleted cells. Together, the results support a model in which CKAP5 controls mitotic chromosome attachment errors by stabilizing CENP-E at kinetochores and by regulating stability of the kinetochore-attached microtubules.

RNA modification-mediated mRNA translation regulation in liver cancer: mechanisms and clinical perspectives

Malignant liver cancer is characterized by rapid tumour progression and a high mortality rate, whereas the molecular mechanisms underlying liver cancer initiation and progression are still poorly understood. The dynamic and reversible RNA modifications have crucial functions in gene expression regulation by modulating RNA processing and mRNA translation. Emerging evidence has revealed that alterations in RNA modifications facilitate the selective translation of oncogenic transcripts and promote the diverse tumorigenic processes of liver cancer. In this Review, we first highlight the current progress on the functions and mechanisms underlying RNA modifications in the regulation of mRNA translation and then summarize the exciting discoveries on aberrant RNA modification-mediated mRNA translation in the regulation of tumour initiation, metastasis, metabolism, tumour microenvironment, and drug and radiotherapy resistance in liver cancer. Finally, we discuss the diagnostic and therapeutic potentials of targeting RNA modifications and mRNA translation for the clinical management of liver cancer.

Predicting drug activity against cancer through genomic profiles and SMILES

Due to the constant increase in cancer rates, the disease has become a leading cause of death worldwide, enhancing the need for its detection and treatment. In the era of personalized medicine, the main goal is to incorporate individual variability in order to choose more precisely which therapy and prevention strategies suit each person. However, predicting the sensitivity of tumors to anticancer treatments remains a challenge. In this work, we propose two deep neural network models to predict the impact of anticancer drugs in tumors through the half-maximal inhibitory concentration (IC50). These models join biological and chemical data to apprehend relevant features of the genetic profile and the drug compounds, respectively. In order to predict the drug response in cancer cell lines, this study employed different DL methods, resorting to Recurrent Neural Networks (RNNs) and Convolutional Neural Networks (CNNs). In the first stage, two autoencoders were pre-trained with high-dimensional gene expression and mutation data of tumors. Afterward, this genetic background is transferred to the prediction models that return the IC50 value that portrays the potency of a substance in inhibiting a cancer cell line. When comparing RSEM Expected counts and TPM as methods for displaying gene expression data, RSEM has been shown to perform better in deep models and CNNs model can obtain better insight in these types of data. Moreover, the obtained results reflect the effectiveness of the extracted deep representations in the prediction of the IC50 value that portrays the potency of a substance in inhibiting a tumor, achieving a performance of a mean squared error of 1.06 and surpassing previous state-of-the-art models.

Investigation of GPR143 as a promising novel marker for the progression of skin cutaneous melanoma through bioinformatic analyses and cell experiments

BACKGROUND

Skin cutaneous melanoma (SKCM) is an aggressive and life-threatening skin cancer. G-protein coupled receptor 143 (GPR143) belongs to the superfamily of G protein-coupled receptors.

METHODS

We used the TCGA, GTEx, CCLE, and the Human Protein Atlas databases to examine the mRNA and protein expression of GPR143. In addition, we performed a survival analysis and evaluated the diagnostic efficacy using the Receiver-Operating Characteristic (ROC) curve. Through CIBERSORT, R programming, TIMER, Gene Expression Profiling Interactive Analysis, Sangerbox, and Kaplan-Meier plotter database analyses, we explored the relationships between GPR143, immune infiltration, and gene marker expression of immune infiltrated cells. Furthermore, we investigated the proteins that potentially interact with GPR143 and their functions using R programming and databases including STRING, GeneMANIA, and GSEA. Meanwhile, the cBioPortal, UALCNA, and the MethSurv databases were used to examine the genomic alteration and methylation of GPR143 in SKCM. The Connectivity Map database was used to discover potentially effective therapeutic molecules against SKCM. Finally, we conducted cell experiments to investigate the potential role of GPR143 in SKCM.

RESULTS

We demonstrated a significantly high expression level of GPR143 in SKCM compared with normal tissues. High GPR143 expression and hypomethylation status of GPR143 were associated with a poorer prognosis. ROC analysis showed that the diagnostic efficacy of the GPR143 was 0.900. Furthermore, GPR143 expression was significantly correlated with immune infiltration in SKCM. We identified 20 neighbor genes and the pathways they enriched were anabolic process of pigmentation, immune regulation, and so on. Genomic alteration analysis revealed significantly different copy number variations related to GPR143 expression in SKCM, and shallow deletion could lead to high expression of GPR143. Ten potential therapeutic drugs against SKCM were identified. GPR143 knockdown inhibited melanoma cell proliferation, migration, and colony formation while promoting apoptosis.

CONCLUSIONS

Our findings suggest that GPR143 serves as a novel diagnostic and prognostic biomarker and is associated with the progression of SKCM.

moPepGen: Rapid and Comprehensive Proteoform Identification

Gene expression is a multi-step transformation of biological information from its storage form (DNA) into functional forms (protein and some RNAs). Regulatory activities at each step of this transformation multiply a single gene into a myriad of proteoforms. Proteogenomics is the study of how genomic and transcriptomic variation creates this proteoform diversity, and is limited by the challenges of modeling the complexities of gene-expression. We therefore created moPepGen, a graph-based algorithm that comprehensively enumerates proteoforms in linear time. moPepGen works with multiple technologies, in multiple species and on all types of genetic and transcriptomic data. In human cancer proteomes, it detects and quantifies previously unobserved noncanonical peptides arising from germline and somatic genomic variants, noncoding open reading frames, RNA fusions and RNA circularization. By enabling efficient identification and quantitation of previously hidden proteins in both existing and new proteomic data, moPepGen facilitates all proteogenomics applications. It is available at: https://github.com/uclahs-cds/package-moPepGen.

Integrative modeling and analysis of signaling crosstalk reveal molecular switches coordinating Yes-associated protein transcriptional activities

The transcriptional co-activator YAP forms complexes with distinct transcription factors, controlling cell fate decisions, such as proliferation and apoptosis. However, the mechanisms underlying its context-dependent function are poorly defined. This study explores the interplay between the TGF-β and Hippo pathways and their influence on YAP's association with specific transcription factors. By integrating iterative mathematical modeling with experimental validation, we uncover molecular switches, predominantly controlled by RASSF1A and ITCH, which dictate the formation of YAP-SMAD (proliferative) and YAP-p73 (apoptotic) complexes. Our results show that RASSF1A enhances the formation of apoptotic complexes, whereas ITCH promotes the formation of proliferative complexes. Notably, higher levels of ITCH transform YAP-SMAD activity from a transient to a sustained state, impacting cellular behaviors. Extending these findings to various breast cancer cell lines highlights the role of cellular context in YAP regulation. Our study provides new insights into the mechanisms of YAP transcriptional activities and their therapeutic implications.

Uncovering PROTAC Sensitivity and Efficacy by Multidimensional Proteome Profiling: A Case for STAT3

Proteolysis-targeting chimera (PROTAC) is a powerful technology that can effectively trigger the degradation of target proteins. The intricate interplay among various factors leads to a heterogeneous drug response, bringing about significant challenges in comprehending drug mechanisms. Our study applied data-independent acquisition-based mass spectrometry to multidimensional proteome profiling of PROTAC (DIA-MPP) to uncover the efficacy and sensitivity of the PROTAC compound. We profiled the signal transducer and activator of transcription 3 (STAT3) PROTAC degrader in six leukemia and lymphoma cell lines under multiple conditions, demonstrating the pharmacodynamic properties and downstream biological responses. Through comparison between sensitive and insensitive cell lines, we revealed that STAT1 can be regarded as a biomarker for STAT3 PROTAC degrader, which was validated in cells, patient-derived organoids, and mouse models. These results set an example for a comprehensive description of the multidimensional PROTAC pharmacodynamic response and PROTAC drug sensitivity biomarker exploration.

CD133 significance in glioblastoma development: in silico and in vitro study

BACKGROUND

Glioblastoma multiform (GBM) is among the commonly diagnosed brain malignancies with poor prognosis. CD133 has been introduced as an oncogene in various cancers, like GBM. This study aimed to investigate the significance of CD133 in GBM development using in silico and in vitro techniques.

METHOD

The TCGA-GBM database was analyzed for the correlational and comparative studies. After selecting the U87MG cell line, CD133-siRNA was transfected into U87MG cells and treated with temozolomide. The cell viability, cell cycle, migration, clonogenicity, and apoptosis of groups were investigated using MTT, flow cytometry, wound-healing, colony formation, and annexin V/PI assays. Using qRT-PCR method, the mRNA expression levels of MMP16, SOX2, RAF1, MAP2K1, MAPK3, PIK3CA, AKT3, mTOR, CDK4, and BCL2 were studied.

RESULTS

CD133 silencing improves apoptosis rate, arrests the cell cycle at the sub-G1 phase, suppresses the clonogenicity of U87MG cells, and inhibits the PI3K/Akt and MAPK pathways via downregulating the RAF1, MAP2K1, MAPK3, PIK3CA, AKT3, and mTOR expression. Besides, combining CD133 silencing with temozolomide treatment considerably inhibits the migration of U87MG cells compared to temozolomide monotherapy.

CONCLUSION

CD133 can regulate the PI3K/Akt and MAPK pathways and modulate the clonogenicity, apoptosis, and cell cycle of GBM. Combining CD133 silencing with temozolomide treatment considerably increases apoptosis, arrests the cell cycle at the sub-G1, and suppresses migration of U87MG cells compared to temozolomide monotherapy.

SIRT1 ISGylation accelerates tumor progression by unleashing SIRT1 from the inactive state to promote its deacetylase activity

ISG15 is an interferon-stimulated ubiquitin-like protein (UBL) with multifaceted roles as a posttranslational modifier in ISG15 conjugation (ISGylation). However, the mechanistic consequences of ISGylation in cancer have not been fully elucidated, largely due to a lack of knowledge on the ISG15 target repertoire. Here, we identified SIRT1, a nicotinamide adenine dinucleotide (NAD+)-dependent protein deacetylase, as a new target for ISGylation. SIRT1 ISGylation impairs the association of SIRT1 with its negative regulator, deleted in breast cancer 1 (DBC1), which unleashes SIRT1 from its inactive state and leads to an increase in its deacetylase activity. Importantly, SIRT1 ISGylation promoted lung cancer progression and limited lung cancer cell sensitivity to DNA damage-based therapeutics in vivo and in vitro models. The levels of ISG15 mRNA and protein were significantly higher in lung cancer tissues than in adjacent normal tissues. Accordingly, elevated expression of SIRT1 and ISG15 was associated with poor prognosis in lung cancer patients, a finding that could be translated for lung cancer patient stratification and disease outcome evaluation. Taken together, our findings provide a mechanistic understanding of the regulatory effect of SIRT1 ISGylation on tumor progression and therapeutic efficacy in lung cancer.

Silencing of the PHLDA1 leads to global proteome changes and differentiation pathways of human neuroblastoma cells

Neuroblastoma (NB) is the most common extracranial pediatric solid tumor originating from the abnormal development of cells of the sympathoadrenal lineage of the neural crest. Targeting GD2 ganglioside (GD2), a glycolipid expressed on neuroblastoma cells, with GD2 ganglioside-recognizing antibodies affects several pivotal signaling routes that drive or influence the malignant phenotype of the cells. Previously performed gene expression profiling helped us to identify the PHLDA1 (pleckstrin homology-like domain family A member 1) gene as the most upregulated gene in the IMR-32 human neuroblastoma cells treated with the mouse 14G2a monoclonal antibody. Mass spectrometry-based proteomic analyses were applied to better characterize a role of PHLDA1 protein in the response of neuroblastoma cells to chimeric ch14.18/CHO antibody. Additionally, global protein expression profile analysis in the IMR-32 cell line with PHLDA1 silencing revealed the increase in biological functions of mitochondria, accompanied by differentiation-like phenotype of the cells. Moreover, mass spectrometry analysis of the proteins co-immunoprecipitated using anti-PHLDA1-specific antibody, selected a group of possible PHLDA1 binding partners. Also, a more detailed analysis suggested that PHLDA1 interacts with the DCAF7/AUTS2 complex, a key component of neuronal differentiation in vitro. Importantly, our results indicate that PHLDA1 silencing enhances the EGF receptor signaling pathway and combinatory treatment of gefitinib and ch14.18/CHO antibodies might be beneficial for neuroblastoma patients. Data are available via ProteomeXchange with the identifier PXD044319.

Multiomic profiling of breast cancer cells uncovers stress MAPK-associated sensitivity to AKT degradation

More than 50% of human tumors display hyperactivation of the serine/threonine kinase AKT. Despite evidence of clinical efficacy, the therapeutic window of the current generation of AKT inhibitors could be improved. Here, we report the development of a second-generation AKT degrader, INY-05-040, which outperformed catalytic AKT inhibition with respect to cellular suppression of AKT-dependent phenotypes in breast cancer cell lines. A growth inhibition screen with 288 cancer cell lines confirmed that INY-05-040 had a substantially higher potency than our first-generation AKT degrader (INY-03-041), with both compounds outperforming catalytic AKT inhibition by GDC-0068. Using multiomic profiling and causal network integration in breast cancer cells, we demonstrated that the enhanced efficacy of INY-05-040 was associated with sustained suppression of AKT signaling, which was followed by induction of the stress mitogen-activated protein kinase (MAPK) c-Jun N-terminal kinase (JNK). Further integration of growth inhibition assays with publicly available transcriptomic, proteomic, and reverse phase protein array (RPPA) measurements established low basal JNK signaling as a biomarker for breast cancer sensitivity to AKT degradation. Together, our study presents a framework for mapping the network-wide signaling effects of therapeutically relevant compounds and identifies INY-05-040 as a potent pharmacological suppressor of AKT signaling.

A phase 1b study of zilovertamab in combination with paclitaxel for locally advanced/unresectable or metastatic Her2-negative breast cancer

BACKGROUND

Zilovertamab is a humanized monoclonal antibody targeting ROR1, an onco-embryonic antigen expressed by malignant cells of a variety of solid tumors, including breast cancer. A prior phase 1 study showed that zilovertamab was well tolerated and effective in inhibiting ROR1-signaling, which leads to activation of ERK1/2, NF-κB, and NRF2 target genes. This phase 1b study evaluated the safety and tolerability of zilovertamab with paclitaxel in patients with advanced breast cancer.

PATIENTS AND METHODS

Eligible patients had locally advanced, unresectable, or metastatic HER2- breast cancer with Eastern Cooperative Group performance status of 0-2 and without prior taxane therapy in the advanced setting. Study treatment included 600 mg of zilovertamab administered intravenously (IV) on Days 1 and 15 of Cycle 1 and then Day 1 of each 28-day cycle along with paclitaxel weekly at 80 mg/m2 IV.

RESULTS

Study patients had received a median of 4 prior therapies (endocrine therapy + chemotherapy) for locally advanced, unresectable, or metastatic disease. No patient discontinued therapy due to toxicity ascribed to zilovertamab. Adverse events were consistent with the known safety profile of paclitaxel. Of 16 patients, 6 (38%) had a partial response, and 6/16 (38%) patients had stable disease as best tumor response.

CONCLUSION

The combination of zilovertamab and paclitaxel was safe and well tolerated in heavily pre-treated advanced breast cancer patients. Further evaluation of ROR1 targeting in breast cancer patients with zilovertamab is warranted.

TRIAL REGISTRATION

NCT02776917. Registered on ClinicalTrials.gov on 05/17/2016.

Current Advances in the Use of Tissue Engineering for Cancer Metastasis Therapeutics

Cancer is a leading cause of death worldwide and results in nearly 10 million deaths each year. The global economic burden of cancer from 2020 to 2050 is estimated to be USD 25.2 trillion. The spread of cancer to distant organs through metastasis is the leading cause of death due to cancer. However, as of today, there is no cure for metastasis. Tissue engineering is a promising field for regenerative medicine that is likely to be able to provide rehabilitation procedures to patients who have undergone surgeries, such as mastectomy and other reconstructive procedures. Another important use of tissue engineering has emerged recently that involves the development of realistic and robust in vitro models of cancer metastasis, to aid in drug discovery and new metastasis therapeutics, as well as evaluate cancer biology at metastasis. This review covers the current studies in developing tissue-engineered metastasis structures. This article reports recent developments in in vitro models for breast, prostate, colon, and pancreatic cancer. The review also identifies challenges and opportunities in the use of tissue engineering toward new, clinically relevant therapies that aim to reduce the cancer burden.

8-Br-cGMP activates HSPB6 and increases the antineoplastic activity of quinidine in prostate cancer

Heat shock protein family B [small] member 6 (HSPB6), widely found in various muscles, has been recently identified as a tumor suppressor gene. However, its role in prostate cancer remains unexplored. Herein, we investigated the expression of HSPB6 in prostate cancer and its association with prognosis. Our findings revealed that HSPB6 downregulation in prostate cancer correlated with a poor prognosis. Moreover, we discovered that HSPB6 can be phosphorylated and activated by 8-Br-cGMP, leading to apoptosis in prostate cancer cells by activating Cofilin. Additionally, we demonstrated that knocking down E2F1 by quinidine administration enhances the transcriptional level of HSPB6. Furthermore, we evaluated the combination of quinidine and 8-Br-cGMP as a potential therapeutic strategy for prostate cancer. Our results revealed that the combined treatment was more effective than either treatment alone in inhibiting the growth of prostate cancer through the HSPB6 pathway, both in vitro and in vivo. Overall, our study provides compelling evidence that HSPB6 suppresses malignant behavior in prostate cancer by inducing apoptosis. The combination of quinidine and 8-Br-cGMP emerges as a promising approach for the treatment of prostate cancer.

The protein phosphatase EYA4 promotes homologous recombination (HR) through dephosphorylation of tyrosine 315 on RAD51

Efficient DNA repair and limitation of genome rearrangements rely on crosstalk between different DNA double-strand break (DSB) repair pathways, and their synchronization with the cell cycle. The selection, timing and efficacy of DSB repair pathways are influenced by post-translational modifications of histones and DNA damage repair (DDR) proteins, such as phosphorylation. While the importance of kinases and serine/threonine phosphatases in DDR have been extensively studied, the role of tyrosine phosphatases in DNA repair remains poorly understood. In this study, we have identified EYA4 as the protein phosphatase that dephosphorylates RAD51 on residue Tyr315. Through its Tyr phosphatase activity, EYA4 regulates RAD51 localization, presynaptic filament formation, foci formation, and activity. Thus, it is essential for homologous recombination (HR) at DSBs. DNA binding stimulates EYA4 phosphatase activity. Depletion of EYA4 decreases single-stranded DNA accumulation following DNA damage and impairs HR, while overexpression of EYA4 in cells promotes dephosphorylation and stabilization of RAD51, and thereby nucleoprotein filament formation. Our data have implications for a pathological version of RAD51 in EYA4-overexpressing cancers.