Breast cancer (BC) cell lines are useful experimental models to understand cancer biology. Yet, their relevance to modelling cancer remains unclear. To better understand the tumour-modelling efficacy of cell lines, we performed RNA-seq analyses on a combined dataset of 2D and 3D cultures of tumourigenic MCF7 and non-tumourigenic MCF10A. To our knowledge, this was the first RNA-seq dataset comprising of 2D and 3D cultures of MCF7 and MCF10A within the same experiment, which facilitates the elucidation of differences between MCF7 and MCF10A across culture types. We compared the genes and gene sets distinguishing MCF7 from MCF10A against separate RNA-seq analyses of clinical luminal A (LumA) and normal samples from the TCGA-BRCA dataset. Among the 1031 cancer-related genes distinguishing LumA from normal samples, only 5.1% and 15.7% of these genes also distinguished MCF7 from MCF10A in 2D and 3D cultures respectively, suggesting that different genes drive cancer-related differences in cell lines compared to clinical BC. Unlike LumA tumours which showed increased nuclear division-related gene expression compared to normal tissue, nuclear division-related gene expression in MCF7 was similar to MCF10A. Moreover, although LumA tumours had similar cell adhesion-related gene expression compared to normal tissues, MCF7 showed reduced cell adhesion-related gene expression compared to MCF10A. These findings suggest that MCF7 and MCF10A cell lines were limited in their ability to model cancer-related processes in clinical LumA tumours. Given the concerning global epidemiology of BC, with a projected doubling in incidence to 4.4 million by 20703, research is needed to better understand and treat BC. However, clinical samples are often challenging to obtain and experimentally manipulate. Cell lines are crucial to facilitating scientific experimentation as a limitless source of biological material4. They are key experimental models used in exploring cancer biology5 and evaluating drugs7.Breast cancer (BC) is the most common cancer diagnosed in females, representing 11.7% of global cancer diagnoses with over 2.2 million new BC diagnoses and 680,000 BC-related deaths in 20209. MCF10A is a non-tumourigenic human breast epithelial cell line derived from benign proliferative breast tissue, characterised by a lack of estrogen receptor (ER) expression10. MCF7 is a widely used in vitro model established from pleural effusion samples from a patient with metastatic BC11. It belongs to the Luminal A (LumA) BC subtype14, an ER-positive subtype with the most optimistic prognoses among the BC subtypes15.MCF10A and MCF7 are the most frequently used cell line models for normal breast tissue and BC tumours respectively17. Within BC, cell lines were found to have expression patterns which correlated with their respective intrinsic subtypes of BC19. However, other studies suggested poor concordance between transcriptomes of cell lines and primary tumours21, and where cell lines correlated more with unrelated cell lines from different cancers than their corresponding primary tumours22. These mixed findings call to question the effectiveness of using MCF7 as a model for BC. For MCF10A, two-dimensional (2D) and three-dimensional (3D) cultures of MCF10A were found to express markers which were uncharacteristic of normal human breast tissue9, suggesting that MCF10A may be an inappropriate breast tissue model.Past studies on the clinical relevance of cell lines suggest mixed conclusions which require resolution. A compilation of high-throughput data across hundreds of cell lines from the Cancer Cell Line Encyclopaedia found that cell lines had transcriptional profiles which correlated better with that of their corresponding primary tumours than other tumours, concluding that cell lines represented primary tumours well23. 3D cultures of MCF7 result in spheroidal microtissues with luminal-like morphology and express more breast-specific biomarkers compared to 2D cultures25. Similarly, 3D cultures of MCF10A cells form spheroids with a hollow lumen26, introducing phenotypes that would not have been present in 2D cultures9. However, few studies compared gene expression of cell lines in 3D cultures to primary tumours. Given the costs of 3D cultures27, there is a need to assess its benefits in modelling BC over the less expensive 2D culture systems so that experimenters can better justify switching from 3D culture systems.We compiled a summary of reported functional differences between cell lines and primary tumours, derived from differential expression analyses between cell line and tumour transcriptomes Table . These s28, against clinical transcriptomic data of LumA BC and normal breast samples in The Cancer Genome Atlas (TCGA).In this study, we validated transcriptomic data of MCF7 and MCF10A cell lines in 2D and 3D cultures, augmented with previously published experimental data from all RNA-seq and ChIP-seq sample and signature search (ARCHS4) repositoryWe aimed to identify the key cancer-related processes that differ between the cell line analyses (MCF7-vs-MCF10A) and analysis of TCGA clinical samples , to understand the adequacy of cell lines as models for LumA BC. Unlike past methods which directly considered the differences between tumours and cancer cell lines, our method considers the differences-of-differences between cell lines and clinical BC  were conducted in R version 4.1.2Our differences-of-differences approach first finds the differences between LumA (or MCF7) and normal (or MCF10A) samples via three separate analyses of the TCGA, 3D culture and 2D culture datasets  were maintained as monolayer in Dulbecco’s Modified Eagle’s Medium—high glucose  supplemented with 10% Fetal Bovine Serum , 1% Penicillin/Streptomycin . The ATCC-originated MCF10A cells (CRL-10317) were maintained in Dulbecco’s Modified Eagle Medium: Nutrient Mixture F-12 (D-MEM/F-12)  supplemented with 5% horse serum , 20 ng/ml Epidermal Growth Factor , 0.5 mg/ml hydrocortisone , 10 μg/ml insulin , 100 nM (−)-Isoproterenol hydrochloride  and 1% Penicillin/Streptomycin . All cells were passaged or changed with fresh medium every other day, and grown in 37 °C humidified incubator supplemented with 5% CO2.37. Briefly, 8-well chamber slide  were coated with 50 μl of growth factor-reduced Matrigel  and left to solidify in the incubator for at least 30 min. MCF7 and MCF10A cells (6500 and 5000 cells respectively) were seeded on top of the solidified Matrigel coating and overlayed with cell medium supplemented with 2% Matrigel . MCF10A spheroids were cultured in assayed Dulbecco’s Modified Eagle Medium: Nutrient Mixture F-12 (D-MEM/F-12)  medium supplemented with 2% horse serum , 5 ng/ml Epidermal Growth Factor , 0.5 mg/ml hydrocortisone , 10 μg/ml insulin , 100 nM (−)-Isoproterenol hydrochloride  and 1% Penicillin/Streptomycin . Cells were refed with fresh assay medium supplemented with 2% Matrigel  every two days thereafter. MCF7 spheroids were harvested on day 10, while MCF10A spheroids were harvested on day 16.The spheroids were generated using the 3D ‘on-top’ methods as described previouslyTotal RNA was extracted from MCF7 and MCF10A cells in both 2D and 3D cultures using RNeasy plus kits  according to manufacturer’s instructions. Briefly, cells grown as monolayer were trypsinized and washed with PBS twice followed by RNA extraction using RNeasy Plus Kit. To collect spheroids, medium was removed from 3D cell culture followed by washing with PBS twice gently. Pre-chilled cell recovery solution  at the volume of 200 μl were added to 8-well chamber slide . Matrigel matrix was fully depolymerized, and spheroids were released after 30 min incubation at 4 °C. Suspended spheroids were collected and washed with PBS twice followed by RNA extraction using RNeasy Plus Kit (Qiagen). The integrity and quantity of RNA were determined with NanoDrop 2000 spectrophotometer  before sending out for RNA sequencing.RNA-sequencing was done in two batches with the first batch by BGI Group and the second batch by NovogeneAIT Genomics Singapore Pte Ltd. RNA samples were subjected to quality control (QC) after sample submission to the companies. Preliminary quantification of nucleic acid samples was performed using Qubit . RNA degradation and contamination were ruled out with agarose gel electrophoresis verification. RNA integrity and quantity were measured on 2100 Bioanalyzer . After sample QC, library construction was performed using NEBNext Ultra II RNA Library Prep Kit  according to manufacturer’s protocols. For the first batch, the libraries were run with BGI group’s in-house sequencing platform BGISEQ-500 (20 M single-end reads). For the second batch, libraries were run on NovaSeq PE150  to produce 6 GB of raw data per sample (20 M paired-end reads).28. Specifically, Kallisto version 0.46.038 with a precalculated human index from the ARCHS4 repository  was used to obtain transcript counts, which were then mapped to gene-level counts using tximport version 1.22.039 and the GrCH38.87 human genome annotation40.Raw RNA-seq data comprised of 9 biological replicates per class . Data from single-end and paired-end sequencing runs were recorded as separate batches. We harmonised the FASTQ file processing by applying the methods in the ARCHS4 documentation28, and a subset of MCF7 and MCF10A samples was manually selected based on metadata from the Gene Expression Omnibus (GEO). Only untransformed samples in control conditions were included for further analysis. This dataset was then combined with our RNA-seq data, and subset into 3D culture and 2D culture datasets.To improve the generalisability of our findings, we augmented our cell line data with ARCHS4 data. Raw RNA-seq counts from the ARCHS4 repository were downloaded on 21 May 2021TCGAbiolinks version 2.22.341. Sample collection and processing protocols are detailed in Ref.42. The RNA-seq data had been processed according to GDC’s harmonised pipeline43. We discarded formalin-fixed paraffin-embedded samples, as RNA crosslinking due to the fixation process might confound analyses of the higher quality fresh-frozen samples44, and discarded non-female samples as male BC are characterised by distinct molecular profiles from female BC45. Metadata from46 was used for BC subtype assignment. Given that MCF7 is a LumA cell line12 and MCF10A is a non-tumourigenic breast cell line10, only LumA tumours and normal samples were retained. The number of samples by class in the three datasets are summarized in Fig. For clinical RNA-seq data, level 3 unnormalised HTSeq mRNA counts data from the TCGA Breast Invasive Carcinoma (TCGA-BRCA) dataset for “primary tumour” and “solid tissue normal” samples were obtained from the Genomic Data Commons (GDC) on 17 January 2022 using 47, and log2-transformed the counts per million (CPM) values using EdgeR version 3.36.048, with default settings.On each dataset, we performed low-counts filtering, normalised counts using the trimmed mean of M-values (TMM) methodscikit-learn version 1.0.249. We selected the top principal components (PCs) which cumulatively account for at least 80% of total variation as input into the Uniform Manifold Approximation and Projection (UMAP) algorithm50. Selecting only the top PCs accounting for majority of variation helps suppress noise51, allowing better projection of the relationships between samples. We used the Python package UMAP version 0.5.2 with 50 to 200 neighbours, a minimum distance of between 0.05 and 0.3, and random initial embedding positions, to visualise sample relationships. To assess the presence of batch effects and outliers, we generated boxplots by batch along one-dimensional UMAP projections of the PCs (PCA-UMAP) and two-dimensional PCA-UMAP scatterplots. Absolute UMAP values were not provided as they were not intrinsically meaningful. Relative positions of points in UMAP space were more relevant.To visualise data structure, we first performed principal component analysis (PCA) on log-CPM data using 52 and GEO series IDs (defining separate experiments) were used to specify batch variables for the TCGA and ARCHS4 data respectively. We used the removeBatchEffect function in limma version 3.50.053 on log-CPM values, specifying the batch variable as described, and LumA (or MCF7) against normal (or MCF10A) samples as the grouping variable.One-dimensional PCA-UMAP boxplots of TMM-normalised log-CPM suggested mild batch effects in the TCGA dataset as relative distributions of samples within each class were not homogeneous across plates Fig. a, and suConsequent to batch correction, distributions across batches highlighted clear differences between LumA (or MCF7) and normal (or MCF10A) samples Figs. b, S4b, sTo understand sample relationships across the three datasets, we combined the outlier-removed unnormalised data and kept genes which were present in all three datasets. We then performed low-counts filtering, normalisation and batch correction as described above. We visualised this combined dataset with a PCA plot instead of using PCA-UMAP because the first two PCs had already accounted for over 80% of variation in this dataset.To each of the three separate datasets, we applied a random stratified train-test split with a test set size of 20%. Only the training set was used for model fitting.54. To correct for class imbalance, we applied synthetic minority oversampling technique (SMOTE) on the training sets, implemented in imbalanced-learn version 0.9.055, to generate synthetic samples for the minority class based on existing samples56. Briefly, SMOTE randomly selected a sample, randomly selected a neighbouring sample out of a specified number (30% of the minority class size) of nearest neighbours in feature space, and generated a random synthetic point between the two samples. This was repeated until the minority class was equivalent in size to the majority class. Two-dimensional PCA-UMAP plots were generated before and after SMOTE to ensure that synthetic datapoints retained data structure.The number of samples in each class were unequal in all three training datasets Fig. a. This w57 implemented in scikit-learn with 5000 trees using the GridSearchCV function, with a pre-specified set of hyperparameters  in classifying LumA (or MCF7) and normal (or MCF10A) samples. To ascertain that the Boruta-selected genes were cancer-related, we trained the tuned RFC on the Boruta-selected genes from the oversampled training set and used this to obtain an accuracy score in the test set.To select key genes involved in distinguishing cancer from normal samples, we used gprofiler2 version 0.2.160. We used the gene ontology (GO) biological process gene sets from the generic GO slims provided by The Gene Ontology Consortium61, downloaded on 11 April 2022. For each analysis, the respective list of genes passing low-counts filtering was used as the background gene list. Gene sets with a Benjamini–Hochberg false discovery rate (FDR) below 0.01 were considered significant.ORA was performed on the unordered lists of Boruta-selected genes for each of the three analyses using limma version 3.50.053 with voom transformation62 to compute log2-fold changes (LFCs) between LumA (or MCF7) and normal (or MCF10A) samples in each dataset, with batch as a covariate. LFCs were input into a pre-ranked gene set enrichment analysis63 implemented in clusterProfiler version 4.2.264, using the “DOSE” method with 1000 permutations, without limiting gene set size. We only considered the ORA-significant gene sets. A positive normalised enrichment score meant that the gene set was upregulated, and a negative normalised enrichment score meant that it was downregulated.To determine direction of regulation of the significant gene sets, we first used VennDiagram version 1.7.165. We selected the top gene sets (ranked by FDR) occurring in the LumA-vs-normal analysis only and the MCF7-vs-MCF10A analyses only for further discussion. Finally, we listed the top genes (ranked by absolute LFC) associated with the selected gene sets, as well as genes which were associated with common gene sets and selected by Boruta in both cell line and TCGA datasets.We compared the results of each analysis by visualising the number of Boruta-selected genes and significant gene sets identified in each analysis using 30, the key benefit of this approach is the focus on cancer-related processes which are more relevant for tumour-modelling. Comparing cell lines to tumours does not reveal insights about the cancer-modelling ability of cell lines because cancer-related gene expression differences cannot be divorced from general culture-related but cancer-invariant differences. Our comparisons of tumourigenic MCF7 against non-tumourigenic MCF10A would ensure that the identified processes were cancer-related, hence providing a commentary on whether the cell lines model cancer adequately.We took a differences-of-differences approach to assess the value of MCF7 and MCF10A cell lines as models for BC  from normal (or MCF10A) samples.We used an RFC-based feature selection approach  to select key cancer-related genes important for classifying cancer from non-cancer samples. Unlike typical differential expression analysis methods which perform independent gene-wise significance tests, RFC-based gene selection methods can demonstrate greater power in large RNA-seq datasets and account for relationships between genes by selecting genes in a multivariate manner58, allowing a better understanding of the mechanistic underpinnings of cancer. Table Unlike other minimal-optimal feature selection algorithms which find the smallest feature subset that maximises classifier performance, Boruta’s all-relevant approach identifies all genes relevant to the classification of cancer from normal samplesIf MCF7 and MCF10A are good models, then they should be distinguished by the same set of cancer-related genes as between LumA BC and normal samples. However, Venn analysis revealed that only 5.1% of genes in the LumA-vs-normal analysis were important in the 2D MCF7-vs-MCF10A analysis Fig. a, and a 69. We used the generic GO slim, a high-level GO subset intended to give a broad overview of the biological processes involved61, because our goal was to summarise the key biological processes differentiating LumA (or MCF7) and normal (or MCF10A) samples. Moreover, using the GO slim reduced redundancy in the gene sets, facilitating comparison across the three analyses.To understand the biological processes underlying the Boruta-selected genes, we performed ORA within each of the three analyses to identify significant GO slims (FDR < 0.01), and then compared these significant gene sets. Our study focused on gene set-level comparisons because investigations using gene sets are more robust than studies based on genesVenn analysis Fig.  of signiWe used two criteria to assess the ability of MCF7-vs-MCF10A to model LumA BC at the gene set level. A good model of clinical LumA BC (1) should not miss overrepresentations of cancer-related processes which were found in LumA-vs-normal and (2) should not identify spurious processes which were absent in LumA-vs-normal. Despite similarities in gene sets to the LumA-vs-normal analyses, we found gene sets along these criteria.Among the 10 cancer-related gene sets identified in the LumA-vs-normal analysis, the 3D MCF7-vs-MCF10A analysis failed to represent the upregulation of mitotic nuclear division . Silencing of these genes may help experimenters create experimental models that better represent non-cancerous tissue.MCF7 and MCF10A have been used to understand mechanisms of cell cycle regulation in BC88, the observed downregulation of cell adhesion may have been an artefact of using a cell line of metastatic origin. The loss of cell adhesion-related functions allows detachment from the primary tumour, promoting metastasis89. In contrast to MCF7’s metastatic origin, only 1.4% of the LumA samples in the TCGA dataset had been diagnosed as metastatic. Unlike metastatic cells, many primary tumours may retain normal cell adhesion functions, enabling collective cell migration in tumour invasion and facilitating intercellular interactions with other cancer and stromal cells91. Therefore, cell adhesion processes were intact in the mostly non-metastatic TCGA dataset, but downregulated in the MCF7-vs-MCF10A comparison due to MCF7’s metastatic lineage. Another possible reason is that the standard of care for luminal tumours involves endocrine therapy92. The patients in the TCGA were likely treated with anti-estrogen therapy. ER inhibitors like tamoxifen had been shown to restore cell–cell adhesion, reducing tumour invasion93. Consequently, this may have recovered cell adhesion in TCGA LumA samples.Our findings indicated that MCF7 showed downregulated cell adhesion compared to MCF10A samples, but cell adhesion was not dysregulated in LumA tumours compared to normal samples. This finding was consistent with literature reporting decreased cell adhesion in cancer cell lines compared to tumours (Table 94 or RNA interference-based translational silencing95. Candidate cell adhesion-related genes (Fig. KIRREL1, which is known to be overexpressed in BC96, and COL17A1, whose underexpression is associated with metastatic tumours97. Activating these genes may increase resemblance of MCF7’s gene expression profile to that of LumA tumours. Candidate cell adhesion-related genes for suppression include RET, which has no known prognostic significance in ER-positive BC98, and AGR2, whose overexpression is associated with metastasis rather than typical LumA BC, and is known to be inhibited by estrogen inhibitor therapy99. The absence of estrogen inhibitor-affected Boruta-selected genes like AGR2 in the LumA-vs-normal analysis further supports the conjecture that endocrine therapies resolved the dysregulation of cell adhesion-related genes in clinical samples. To further address the differences in cell adhesion due to treatment effects in clinical samples, cell lines modelling post-treatment LumA cancers could be cultured in tamoxifen-treated media, better modelling tumour behaviour under endocrine therapy exposure.To address the differences in cell adhesion due to the metastatic lineage of MCF7 compared to LumA tumours, researchers could use techniques like CRISPR/Cas9-mediated gene activationWith the compilation of RNA-seq data from the ARCHS4 and TCGA repositories to augment our RNA-seq dataset, we presented a list of putative biomarkers Fig. b which eSLC2A10. This gene had been demonstrated to be upregulated in clinical BC100. SLC2A10 encodes GLUT10, a facilitative glucose transporter whose role in cancers remains unclear102. Downregulation of SLC2A10 is tied to destabilisation of the extracellular matrix via deficiencies in ascorbic acid processing which are cofactors facilitating collagen and elastin production103, and impaired cardiovascular morphogenesis via alterations in respiration and TGFβ signalling104. However, less is known about the implications of SLC2A10 overexpression in cancer. The consistent overexpression of SLC2A10 in cell lines relative to clinical samples suggest that it is possible to further investigate the role of SLC2A10 overexpression using MCF7 and MCF10A. Future studies could further explore the role of this gene in cancer using experimental cell lines, to better understand its implications on extracellular matrix organisation in cancer cells compared to normal cells.We could also use this list of genes to pursue more specific questions of interest. For example, to understand the cancer-related morphogenic changes underlying BC, experimenters may be interested in understanding gene expression differences related to extracellular matrix organisation. Among the genes in Fig. CRYAB, which was the top cancer-related gene associated with cytoskeleton organisation in the analyses of 2D and 3D cultures of cell lines and clinical samples. CRYAB encodes a small heat-shock protein associated with maintaining cytoskeletal integrity under stresses to the cytoskeleton105, possibly by reducing the aggregation of F-actin106. Studies on CRYAB expression in BC were mixed. While CRYAB was overexpressed and associated with poorer prognosis in the basal BC subtype and metastasis109, CRYAB was shown to be strongly downregulated in all BC subtypes110. Interestingly, separate clusters of BC samples were identified to be varying in CRYAB expression, where CRYAB tended to be less expressed in ER-positive BC but more expressed in ER-negative BC111, suggesting a subtype-specific gene expression pattern in CRYAB. While the tumour-suppressive roles of CRYAB in LumA BC are less well-established, CRYAB has been shown to reduce progression in nasopharyngeal cancers by associating with membrane-bound β-catenin, preventing the release of β-catenin into the cytoplasm, thereby suppressing the oncogenic abilities of β-catenin by preventing it from interacting with complexes to facilitate transcription of genes involved in tumour progression112. MCF7 and MCF10A cell lines may be useful models to resolve the mixed findings of CRYAB expression in cancers and better understand the mechanisms underlying CRYAB in BC. Given how its underexpression in LumA BC was consistently reflected in both cell lines and clinical samples, future work could use MCF7 cell lines to examine the roles of CRYAB in LumA BC, such as via gene activation protocols. There is a need for such studies to identify downstream effects of CRYAB expression, identify CRYAB’s tumour-suppressive role in LumA BC, and better determine whether CRYAB is an effector in cytoskeletal organisation or disorganisation.To further explore cytoskeleton organisation, researchers could analyse Our cell line dataset was a collection of independent experiments with varying culture and sequencing protocols. Specifically, in the ARCHS4 data, many MCF7 samples were obtained from different experiments from the MCF10A samples. Despite our attempts to remove cancer-unrelated variation, batch effects may still exist. Nonetheless, our study aimed to look at the broad cancer-related processes distinguishing cell line models from clinical samples and was able to capture the general differences between analyses of clinical samples and cell lines irrespective of remaining batch effects.Deriving biological meaning from manually curated GO annotations also provides a limited view of tissue-specific functions. It would be worthwhile to seek an alternative method to impute knowledge for uncovering unannotated biological processes for less studied genes.115. Moreover, cell subpopulations have important implications on treatment efficacy. For instance, studies have found that tumour-associated macrophages are related to worse prognoses116 while tumour-infiltrating lymphocytes are associated with good prognoses117. These effects of intratumoral heterogeneity cannot be elucidated directly with bulk RNA-seq data. Future work could collate single cell RNA-seq data to compare specific cell subpopulations between tumours and cell lines. This would allow us to answer more specific questions, such as whether cell lines preferentially model certain cellular subpopulations or whether intratumoral heterogeneity in clinical samples introduces complexity that cannot be modelled in cell lines.BCs exhibit high intra-tumour heterogeneity consisting of different cell subpopulations, genetic heterogeneity and mixed morphologies118 and vascularised systems119, which were not represented in this study. Hence, the list of cancer-related genes and gene sets identified may not generalise well to the full range of 3D culture technology. As 3D culture systems gain popularity, there might be more available data in future which can be used to determine the key cancer-related processes more reliably in 3D MCF7-vs-MCF10A. Future work could amass a larger dataset and further consider the differences between 3D culture techniques, to better assess the modelling capacity of MCF7 and MCF10A.Furthermore, our 3D culture dataset was limited in size compared to the other datasets. There are also various sophisticated 3D culture systems which better model tumour-stromal interactions such as co-cultures with other cell typesFinally, our study focused on MCF7 and MCF10A, among the many available BC and non-tumourigenic cell lines. However, our method is scalable and can be easily extended to RNA-seq data mined for other cell lines. Future work can consider expanding implementation to other BC cell lines to obtain a comprehensive idea of the overall representativeness of cell line models to clinical BC data and assist cell line selection in experimental studies by ranking cell lines by similarities in cancer-related processes to relevant breast tissues.Supplementary Information.Supplementary Table 2.Supplementary Table 3.


Natural products have historically played an important role as a source of therapeutic drugs for various diseases, and the development of medicinal natural products is still a field with high potential. Although diverse drugs have been developed for incurable diseases for several decades, discovering safe and efficient anticancer drugs remains a formidable challenge. Reptiles, as one source of Asian traditional medicines, are known to possess anticancer properties and have been used for a long time without a clarified scientific background. Recently, it has been reported that extracts, crude peptides, sera, and venom isolated from reptiles could effectively inhibit the survival and proliferation of various cancer cells. In this article, we summarize recent studies applying ingredients derived from reptiles in cancer therapy and discuss the difficulties and prospective development of natural product research. Cancer, an intricate genetic disease triggered by mutations that create expression, functional, and/or structural abnormalities in major genes, remains an unconquered disease worldwide . Cancer Throughout human history, natural products have been used in various forms from a time when there was no clear scientific verification for their use to the present. Based on the knowledge acquired through experience, natural products have been used for the prevention and treatment of diverse disorders, such as inflammation, hyperpyrexia and infection ,23,24,25Here, we discuss the development of cancer therapeutic drugs that are based on bioactive natural products and derived from sources including plants, marine organisms and animals. Specifically, we focus on recent research that has uncovered anticancer components derived from reptiles that may help to overcome challenges in cancer therapy.Catharanthus roseus . Vincristine and vinblastine are effective against some types of cancer, such as acute leukemia, Hodgkin lymphoma, lymphosarcoma, testicular cancer and lung cancer [Taxus brevifolia, the pacific yew. Paclitaxel is an antiproliferative drug that promotes microtubule assembly and stability, and it has been reported to be effective in the treatment of ovarian, cervical, breast, lung and pancreatic cancer [Since ancient times, terrestrial plants have been a very important source of medicines used for preventing or treating various diseases. Several anticancer drugs currently in use are derived from terrestrial plants . Vincrisg cancer ,43. Theyc cancer . In addic cancer ,51,52,53Ecteinascidia turbinata that might promote cancer cell death by inhibiting gene transcription [Dolabella auricularia might induce apoptosis through cell cycle arrest by binding to the tissue factor (CD142) on the cancer cell surface and releasing monomethyl auristatin E (MMAE) in the cell [Marine compounds possess unlimited potential for drug discovery because there are likely to be many unknown organisms and untapped areas of research. Marine research for drug development has been underway since the 1980s. Various anticancer peptides have been isolated from diverse marine organisms such as algae, sponges and fish . Lurbinecription . Tisotumthe cell . Additiothe cell ,57,58,59the cell ,61,62. IDrugs derived from reptiles have long been widely used as a source of nourishment, nutritional tonics and disease treatment in Asia. In general, powders and other derivatives can be made from dried reptiles after the removal of the intestines, or extracts can be created by soaking the whole reptile in alcohol. Recently, the inflammatory and tumor-suppressive effects of components derived from reptiles have been experimentally proven, and anticancer research is being conducted with various formulations generated with different extraction methods. Typically, cancer therapeutic studies are performed using extracts, crude peptides, sera and/or venom isolated from reptiles through several extraction methods .Gekko swinhonis inhibited the proliferation and differentiation of human hepatic cancer cell lines such as L-02 and Bel-7402 [Gekko subpalmatus Gunther exhibited antitumor effects in vivo and inhibited the growth of the Bel-7402 cell line [Gekko japonicus showed antitumor effects against the human esophageal carcinoma EC9703 and mouse sarcoma S180 cell lines in experiments in vitro and in vivo [Cyrtopodion scabrum using ethanol and distilled water showed selective anticancer effects against the human breast cancer cell line MCF7 and human colon cancer cell line SW-742 through the inhibition of growth and migration, and they had no effect on normal mesenchymal stem cells [Eublepharis macularius induced apoptosis only in human cancer cell lines, such as bladder cancer 5637 and cervical cancer HeLa cells, via the inhibition of the PI3K/Akt signaling pathway, and without any effect on normal cells, including C2C12, NIH3T3, MEF, HEK293, Hs27 and NuFF cells [Eublepharis macularius might possess therapeutic effects against many types of human cancer cells via in vitro and in vivo experiments.Reptile-derived extracts, which are very similar to traditionally derived agents, have been proven to have excellent tumor-suppressive effects. According to the reported studies, aqueous extracts of Bel-7402 . Additioell line . Moreoveem cells . In addiFF cells ,77. JeonFF cells . FinallyCrocodylus siamensis, promoted cell death in gastric cancer cell lines, including the BGC823, MGC803, SGC7901 and MKN28 cell lines, without side effects on the normal gastric cell line GESI [Crocodylus palustris, such as the heart, lungs, intestine and brain, showed a high cytotoxicity against the human prostate cancer cell line PC3 [Crocodylus siamensis induced apoptosis in the human cervical cancer cell line HeLa through the mitochondria/caspase-3/caspase-9-mediated intrinsic pathway and effectively inhibited the proliferation, migration and invasion of cancer cells [Crocodile choline, a bioactive component derived from er cells ,82. Furter cells . These sChinemys reevesii, Cuora aurocapitata or Trachemys scripta promoted cell death in the human leukemia cell line HL60 and the human liver cancer cell line HepG2 [Aqueous extracts of turtle shell derived from ne HepG2 . AlthougGekko swinhonis Guenther using polar solvents. Several features of the protein complex were analyzed through high-performance liquid chromatography, gas chromatography–mass spectrometry, gas chromatography and NMR spectroscopy. Remarkably, the complex inhibited the proliferation and migration abilities of the human hepatocellular carcinoma cell line SMMC-7721 [Gekko japonicus suppressed the proliferation of the human liver carcinoma cell line HepG2 and promoted apoptosis through Bcl-2/Bax pathway regulation [Gekko japonicus powder effectively inhibited the proliferation and induced the apoptosis of the human liver carcinoma cell line HepG2 [Peptide mixtures or crude peptides isolated from reptiles may play an important role in drug development and might provide promising options for cancer therapy. Protein and functional peptides are safe drugs that have an excellent cell permeability and minimal potential to elicit an immune-rejection response. Therefore, peptides derived from reptiles could be key drug candidates. A sulfated polysaccharide–protein complex can be extracted from the dried whole body of MMC-7721 . Additiogulation . These cne HepG2 . InteresVaranus salvator blood showed cytotoxicity against HeLa cells without affecting the normal human keratinocyte cell line HaCaT [Malayopython reticulatus and Cuora amboinensis kamaroma also exerted anticancer effects against the human cancer cell lines HeLa, PC3 and MCF7 [Anticancer studies based on body fluids rather than whole-body-derived components of reptiles are rare because a relatively fresher sample is needed. Nevertheless, studies have verified the anticancer properties of reptile serum and bile. Serum isolated from ne HaCaT . The serand MCF7 . This stCrocodylus siamensis promoted apoptosis in the human non-small-cell lung cancer cell line NCI-H1299 through the mitochondria/caspase-3/caspase-9-mediated intrinsic pathway, and effectively suppressed tumorigenesis and growth in athymic nude mice [Animal bile has been used as a natural drug to strengthen stamina and immunity for thousands of years. Bile contains many bile acids, such as cholic acid and deoxycholic acid, that play a role in physiological functions. Bile juice squeezed from the gallbladders of ude mice . These fClostridium botulinum is a neurotoxic protein that blocks the release of acetylcholine from the axon terminal of neurons. Botulinum toxin types A and B are applied in the medical field to treat the hyperactive responses of muscles and neurons [Macrovipera lebetina, BnSP-6 and Lys-49 phospholipase A2 (PLA2) purified from Bothrops pauloensis, NN-3 purified from Naja naja oxiana, and chlorotoxin purified from Leiurus quinquestriatus were analyzed to determine their structure, amino acid sequence and anticancer effect against MDA-MB-231 cells [Macrovipera lebetina, suppressed the migration, invasion and proliferation of the human melanoma cell line SK-MEL-28 [Crotalus durissus terrificus and cytotoxin 2 derived from Naja naja oxiana decreased the viability of MCF7aro cells via the inhibition of the extracellular signal-regulated kinase (ERK) pathway, inhibited cell migration by inducing the apoptosis of MCF7 cells, and showed an anticancer effect on lung cancer cells in A549 cells through the activation of the caspase-3 and p38 pathways [Daboia russelii, effectively inhibited cell motility by promoting the cytoskeletal damage and apoptosis of A549 cells [Naja atra) caused the necroptosis of the leukemia cell lines HL-60 and KG1a [Echis multisquamatus exerted antiproliferative action against HeLa cells [Vipera latifii or Naja hage showed anticancer effects against the hepatocellular carcinoma cell lines HepG2 and Huh7.5 [Walterinnesia aegyptia induced apoptosis through the activation of the caspase-3 pathway in human breast cancer cell lines MDA-MB-231 and MCF7 [Naja naja oxiana inhibited the transforming growth factor/suppressor of mothers against the decapentaplegic (TGFβ/SMAD) signaling pathway, and the expression of matrix metalloproteinase 3 (MMP3) in the human melanoma cell line SK-MEL-03, without side effects on the normal fibroblast cell line HFF-2 [Bothrops jararaca reduced proliferative ability through the activation of the caspase-3 pathway in the murine melanoma cell line B16F10 [Cerastes vipera showed powerful cytotoxicity against MCF7, HepG2, A549, and PC3 cells and the human colon cancer cell line HCT116, compared with doxorubicin [Cerastes cerastes by irradiation (Co-60 gamma rays) induced apoptosis via G2/M phase cell cycle arrest in the human non-small-cell lung cancer cell line A549 and the human prostate cancer cell line PC3 [Effective therapeutic factors that have been diluted or purified from venom have been used to treat diseases. Bee venom, for example, is composed of approximately 40 factors, and among these, melittin and apamin may enhance the immune system through the promotion of hormone metabolism, blood circulation and immune cell activation. This occurs by stimulating the anterior pituitary or adrenal cortex ,110. Bot neurons ,112,113.31 cells ,91,92,93K-MEL-28 . Crotoxipathways ,96,97. D49 cells . Additioand KG1a . DisinteLa cells . The vend Huh7.5 ,102. Addand MCF7 . The novne HFF-2 . Jararhae B16F10 . L-Aminoorubicin ,107. Theline PC3 . These sCrotalus durissus terrificus venom for application in medicinal technology [Therapeutic bioactive components derived from various reptiles are valuable natural sources with the potential to overcome the shortcomings of current cancer therapies . In the chnology . Howeverchnology ,120,121.


With the increasing incidence of depression worldwide, antidepressant medications are commonly used in males of reproductive age for long-term treatment of depression, as well as other disordersin vitro 2-dimensional cellular models, however, cannot reflect the full interaction among different cell types of the testis. Encouragingly, the rapid development ofin vitro 3-dimensional organoids has provided a more complex modelling of the structure and function of organs, including tissue-specific progenitor and differentiated cells arranged in an organotypic structure resembling the original organ. Establishedin vitro three-dimensional stem cell models of organogenesis have enormous potential for modelling normal development and disease, as a tool for drug testing, and as a framework for therapeutic testingThe testis is a complex multicellular organ responsible for spermatogenesis. Cell‒cell interactions between somatic and germ cells are essential for normal testis function. Only a few clinical indicators can be used to monitor potential testicular toxicity in drug development; therefore, the evaluation is mainly carried out on animals. This implies high costs and has limitations and potential interfering factors. For example, animals may lose weight after taking the drug, and subsequent alterations in neuromuscular function and mood of the animal may affect mating behavior. Furthermore, animal models might have different pharmacokinetic characteristics, and the overall human translational value might be limited. The development of testicular organoids might save at least €6.7 billion and 48.6 million animalsHere, we presented an improved testicular organoid model composed of rat testicular cell homogenates to assess the reproductive toxicity of antidepressants, with special emphasis on mimicking the drugs on different aspects of spermatogenesis and uncovering the underlying mechanisms. The two most frequently used antidepressants, amitriptyline and mirtazapine, were chosen to evaluate their reproductive toxicity effects on spermatogenic cells.Testicular organoids are usually cultured by mixing cells and Matrigel directlySupplementary Figure S1).To verify our model, we evaluated spherical–tubular structures composed of Sertoli cells, germ cells, and spermatocytes using the relevant markers SRY-box transcription factor 9 (Sox9), DEAD-box helicase 4 (Ddx4) and synaptonemal complex protein 3 (Scp3), respectively B. Ddx4 ain vitro concentrations chosen by us were 100 nM and 1 μM for subsequentin vitro experiments. After 7 days of culture, organoids were treated with both drugs for 48 and 96 h and then stained with Hoechst (live cells) and propidium iodide (dead cells).Supplementary Figures S2,S3 show that testicular organoids treated with amitriptyline contained significantly more apoptotic cells than those treated with mirtazapine, while mirtazapine treatment resulted in significantly more live cells than treatment with amitriptyline, indicating that the reproductive toxicity of amitriptyline was significantly higher than that of mirtazapine. We further quantified these effects by measuring and calculating the ratio of the fluorescence intensity of PI and Hoechst with a confocal microscope . We measured the red fluorescence value represented by PI and the blue fluorescence value represented by Hoechst. After that, the ratio of red fluorescence to blue fluorescence was calculated, which indicated that the higher the R level was, the higher the cell death rate. The results showed that the R value of amitriptyline was higher than that of mirtazapine . Amitriptyline was significantly more cytotoxic to GC1, GC2, TM3 and TM4 cell lines than mirtazapine, which means amitriptyline would bring more damage to the testis. To determine the effects of both drugs on testicular organoids, we used RT-PCR to detect changes in markers related to germ cells after drug treatment. JQ1, a drug that blocks spermatogenesis, was used as a positive control. Stimulated by retinoic acid 8 (Stra8) and ubiquitin C-terminal hydrolase L1 (Uchl1) genes were detected . These results confirmed that in this cultured organoid system, amitriptyline has much worse effects than mirtazapine, which was probably related to spermatogenesis. However, when the dose of both drugs was increased to 1 μM, the mRNA expression of Stra8 was downregulated .According to the plasma concentrations of amitriptyline (FDA label) and mirtazapineazapine D. This retected . When thgulated . Moreovegulated , indicatgulated A, suggesgulated . Under tThe above results also suggested that the developed organoid can be used to assess the reproductive toxicity of antidepressants and uncover how the drugs affect spermatogonia. By detecting the mRNA of the organoid with the two drug treatments, we can summarize that both drugs can damage spermatogonia and primary spermatocytes in the early stage of differentiation, suggesting that both drugs may affect the proliferation and division of spermatogenic cells. In addition, in the spermatogenesis process, amitriptyline can have a more significant effect on the expressions of Sox9, Stra8, Uchl1, and Zo1 than mirtazapine, which might indicate a disruption of signalling pathways. Third, 96 h of treatment with amitriptyline could have profound effects on Sox9 and Zo1, which may indicate that the use of amitriptyline in clinical practice may cause more serious damage to the male reproductive system B.Supplementary Figure S6). After the cell lines were treated with amitriptyline and mirtazapine for 24 h, the expression levels of key genes such asSlc6a4,Slc6a2,Htr2c,Oprk1,Hrh1, andAdra2a changed dramatically . It has been reported that changes in the expression levels of the above genes could lead to impaired testosterone synthesis, arrest of spermatogenesis, and harmful effects on male fertilityin vivo effects of the drugs. In addition, the testicular organoids can reflect the key genes in the sperm pathway much closer to the environmentin vivo . Therefore, the organoid developed in this study can be used as an effective model for evaluating drug effects on sperm productionin vitro.Finally, we used mouse cell lines such as GC1 and TM4 to compare the reproductive toxicity of these two drugs with the results obtained on the organoid developed in this study (in vitro. Indeed, supporting cells and spermatocytes that are essential in the sperm production process were also present in the organoid models. Spermatogenesis has specific metabolic requirements, and the existence of the blood-testis barrier indicated that organoids could provide the regulatory microenvironment conditions required during spermatogenesis. The rat testicular organoids developed in this study have the potential to mimic sperm development and to be used to assess male reproductive toxicity.In short, the organoids that we cultured for 7 days contained spermatogonia, spermatocytes and Sertoli cells, and developed a blood-testis barrier, which indicated that the organoids have the potential to mimic sperm productionin vivo animal studies, it can hopefully reduce the number of animals used for reproductive toxicity studies of psychological drugs. Additionally, this organoid culture method has high repeatability and easy operability, and our study shows that this organoid model can discern the effect of different drugs in this cultured organoid system. This provides a powerful tool to obtain a more comprehensive picture of the dynamic process of spermatogenesis and to analyse key pathways in specific cell types differentially affected by the drugs. This type of evaluation of reproductive toxicity in rat testicular organoids might pave the way towards developing human testicular organoid models and to provide insights into the reproductive toxicity of clinically relevant drugs in humans.Of note, the current study is a preliminary study which has several limitations that need further improvement. First, the “organoid model” is still in the preliminary stage, with no specific testicular cytoarchitecture/morphology. Second, the present evidence is not convincing enough to support that this model replicates testis-specific structure and function. Third, although the marker expression of spermatogonia, Sertoli cells and other cell types can be determined, whether germ cells differentiate during spermatogenesis requires further investigation. Nevertheless, the current model is suitable for drug toxicity screening and could potentially be used for the mechanistic study of drugs on spermatogenesis. Although it cannot replace


Molecular subtypes of muscle-invasive bladder cancer (MIBC) display differential survival and drug sensitivities in clinical trials. To date, they have not been used as a paradigm for phenotypic drug discovery. This study aimed to discover novel subtype-stratified therapy approaches based on high-content screening (HCS) drug discovery. Transcriptome expression data of CCLE and BLA-40 cell lines were used for molecular subtype assignment in basal, luminal, and mesenchymal-like cell lines. Two independent HCSs, using focused compound libraries, were conducted to identify subtype-specific drug leads. We correlated lead drug sensitivity data with functional genomics, regulon analysis, and in-vitro drug response-based enrichment analysis. The basal MIBC subtype displayed sensitivity to HDAC and CHK inhibitors, while the luminal subtype was sensitive to MDM2 inhibitors. The mesenchymal-like cell lines were exclusively sensitive to the ITGAV inhibitor SB273005. The role of integrins within this mesenchymal-like MIBC subtype was confirmed via its regulon activity and gene essentiality based on CRISPR–Cas9 knock-out data. Patients with high ITGAV expression showed a significant decrease in the median overall survival. Phenotypic high-content drug screens based on bladder cancer cell lines provide rationales for novel stratified therapeutic approaches as a framework for further prospective validation in clinical trials. Over the past 40 years, the survival rate associated with bladder cancer (BLCA) has not significantly changed . MethotrBLCA cell lines play a pivotal role in drug discovery for several reasons. First, there exists a high number of well-characterized cell lines that reflect crucial genetic aberrations also found in MIBC patients  . Second,With the increased molecular genetic understanding of BLCA, novel-targeted therapies are emerging. Recent studies have shown promising preclinical data for EZH2 and BET inhibitors ,14. OngoTo identify subtype-specific lead drugs and gain insight into the molecular subtype biology, we utilized a high-content screening (HCS) phenotypic drug discovery approach, using two focused drug libraries screened independently. We classified existing BLCA cell lines into the major molecular muscle-invasive BLCA subtype taxonomies. By combining drug sensitivity data with functional genomics, regulon, and drug set enrichment analysis, we were able to identify and validate both established drugs and novel lead drugs effective against subtype-specific BLCA cell lines.A total of 36 BLCA CCLE cell lines and 36 cell lines of the BLA-40 panel were classified into the major known molecular subtype taxonomies based on the Lund, MDA, TCGA, and Consensus classifiers ,18,20. TSome cell lines were mainly characterized by mesenchymal and smooth muscle gene signatures . The LunA total of 1448 drugs of the CCLE HCS were grouped by their drug targets defining the “drug sets” . Based oThe most selective growth inhibition of luminal BLCA cells was mediated via the inhibition of MDM2, a negative regulator of p53 B 23]. A. A23]. AThe AUC value of the mesenchymal-like cell lines remained high even for the most selective agents, demonstrating a certain degree of resistance against most drugs C. The onThe findings based on the CCLE HCS demonstrate that BLCA cell lines represent a valid platform for subtype-specific drug discovery. Consequently, in contrast to the PCR-based CCLE HCS, we performed a multiplexed  high-content screen based on a focused Selleck Chem drug library including 616 novel clinical compounds. For this HCS, we used preselected representative cell lines belonging to the BLA-40 library . The assessment of the drug response was based on the percentage of viable cells after drug exposure. We clustered the selected cells based on their drug response to 616 clinical or pre-clinical drugs of the Selleck Chem library . We founp = 0.01, 50 values differed significantly between the basal and mesenchymal-like subtypes, with a less pronounced effect against the luminal subtype. The basal cell lines also displayed sensitivity to mTOR inhibitors in drug set enrichment analyses, but they did not represent lead hits .The mesenchymal-like cell lines displayed subtype-specific sensitivity to Aurora kinase (AURK) inhibitors and other cell cycle inhibitors B, but asectively . Within p < 0.001). RERE is known for its role in embryogenesis and histone deacetylation [p < 0.001). The Ras-related GTPases  are oncogenes known to be activated via integrin-mediated downstream signaling [To evaluate the inherent molecular biology of each subtype, we performed regulon analysis via VIPER, based on the RNA-seq data from the CCLE cell lines. VIPER allows a subtype-specific identification of relevant active and inactive proteins. In line with the sensitivity of basal urothelial carcinoma to HDAC inhibitors, we identified the arginine–glutamic acid dipeptide repeats gene (RERE) as a leading regulon active in basal BLCA cell lines .The sensitivity of mesenchymal-like cell lines to integrin inhibitors is reflected by a strong activation of the integrin regulons ITGB4 and ITGB6  and vimentin (VIM), well-characterized biomarkers of the epithelial and mesenchymal phenotype respectively [ITGAV showed a strong correlation with the mesenchymal biomarker VIM .Since the αgulators . In ordeectively . While Isubtypes B. PatienIn this study, we performed, for the first time, a systematic clustering of bladder cancer cell lines based on the major subtype taxonomies. We observed that a high number of well-characterized cell lines provide a strong tool for subtype-specific drug discovery in bladder cancer. Our phenotypic HCS drug discovery approach identified subtype-specific drug sensitivities that were consistent with clinical trials, as well as in vivo studies, and facilitated the discovery of novel subtype-specific lead drugs . ConversITGAV knock-down had a greater impact on UMUC3 cell migration than on the RT4 cells [ITGAV knock-down presented a markedly lower number of metastases and bone marrow infiltration than wild-type tumor-bearing mice [ITGAV expression  and MK-886 (lipoxygenase inhibitor) displayed no luminal-specific dose-dependent effect despite both pathways being known to be altered in BLCA ,48. The Finally, we demonstrated a novel approach using enrichment analysis based on in-vitro drug response data. To date, drug set enrichment analyses were mainly used for the assessment of drug-induced gene expression signatures . High-coIn conclusion, we demonstrated that phenotypic HCS drug discovery targeting BLCA subtypes can identify novel subtype-specific treatment options and reproduce known BLCA drug sensitivities . In partWhole transcriptome RNA-seq data of 36 CCLE bladder cancer cell lines were obtained via DepMap Portal  . TranscrBladder cancer cell lines were classified into the major molecular subtype taxonomies  using the R-packages “BLCAsubtyping” and “ConsensusClassifier” available on GitHub ,5,18,20.Drug set enrichment analysis was performed using the gene set enrichment analysis (GSEA) software 4.1.0  . All druNext, gene set enrichment analysis was performed with R package GSVA 1.44.2 , which cp-values and normalized enrichment scores give information about the inferred protein activity.Virtual inference of protein activity by enriched regulon analysis (Version 1.30.0)  was condWe assessed candidate genes for their role in bladder cancer cell viability based on the genome-scale CRISPR–Cas9 knock-out data from the Project Achilles. Dependency scores were calculated using the CERES algorithm. Candidate genes with a CERES score of <−1 were identified as essential for cell survival  .The drug response of 36 BLCA CCLE cell lines to 1448 compounds was assessed by the PRISM Repurposing 19Q4 drug screen (CCLE HCS) . The dru2. The cells were used in experiments within 6 weeks of thawing. The drug response curves  were set in quadruplets for the hit validation of five drugs in nine selected cell lines.For the focused in-house HCS, we used 616 novel clinical and pre-clinical inhibitors of the Selleck Chem Clinical Compound library. All compounds were diluted in DMSO. For each BLCA subtype, we screened 3 representative cell lines from the BLA-40 cell line library . The cells were incubated in 384-well black flat-bottom cell culture microplates . The cells and reagents were plated with the automated Janus Liquid Handler Workstation . Multiplexed imaging was performed in phenol red-free medium containing L-glutamine and supplemented with 10% FBS. The cells were plated on day 0, with 1000 cells per well. The drug library and CellTox™ Green Express (0.5X) reagent  were added on day 1 in singlets, with a final concentration of 10 µM and 0.5% DMSO. Lysis buffer was used as a positive control. After 72 h of incubation, the cells were stained with Hoechst 33342  for imaging and cell counting by the Opera Phenix HCS system . The remaining cells with high Celltox™ green  signal were considered dead. The assay quality was assessed by the Z-prime value . A Z-prin = 25), resulting in a cohort of 386 available MIBC patients [ITGAV cutoff for risk stratification based on overall survival was calculated by applying Youden’s index in conjunction with ROC analysis [p-value asterisks criteria were adapted to the New England Journal of Medicine (NEJM) guidelines (<0.033 (*), <0.002 (**), <0.001 (***)). Statistical analyses were performed using RStudio , GraphPad Prism 7.03 , SPSS 25 , and JMP 10 . The RNA-seq data from 411 muscle-invasive BLCA (MIBC) patients of the TCGA cohort were evaluated for in silico validation. Patients with incomplete clinical and molecular annotation were excluded n = 2, resultipatients . The genanalysis ,61. Over


TP53 mutations and widespread copy number alterations. These copy number alterations include deletion of tumour suppressors and amplification of driver oncogenes. Given their key oncogenic roles, amplified driver genes are often proposed as therapeutic targets. For example, development of anti-HER2 agents has been clinically successful in treatment of ERBB2-amplified tumours. A wide scope of preclinical work has since investigated numerous amplified genes as potential therapeutic targets in high-grade serous ovarian carcinoma. However, variable experimental procedures , ambiguous phenotypes or lack of validation hinders further clinical translation of many targets. In this review, we collate the genes proposed to be amplified therapeutic targets in high-grade serous ovarian carcinoma, and quantitatively appraise the evidence in support of each candidate gene. Forty-four genes are found to have evidence as amplified therapeutic targets; the five highest scoring genes are CCNE1, PAX8, URI1, PRKCI and FAL1. This review generates an up-to-date list of amplified therapeutic target candidates for further development and proposes comprehensive criteria to assist amplified therapeutic target discovery in the future.High-grade serous ovarian carcinoma is a unique cancer characterised by universal  TP53 mutations are near universal in HGSOC [TP53 and BRCA1/2 (associated with hereditary OC and HRD) are rare  in comparison to other cancers [BRAF V600E melanoma) [Ovarian cancer (OC) is a significant cause of global female mortality. Epithelial ovarian cancer (EOC) represents over 90% of cases, with high-grade serous ovarian carcinoma (HGSOC) being the most common 70% of EOC) and deadly subtype due to its predilection for recurrence after initial treatment . HGSOC iin HGSOC , with lo0% of EOCelanoma) . Poly ADelanoma) . Rucaparelanoma) . Niraparelanoma) . Niraparelanoma) . PARP inelanoma) .KRAS and ERBB2 copy number has been observed in a HGSOC resection specimen [CCNE1, one of the most prevalent and potentially actionable amplified targets in HGSOC [ERBB2-amplified breast and gastric cancers demonstrates the scope for translational research [Within CNDCs, clusters of amplified genes at restricted regions of the genome, referred to as amplicons, can vary greatly in both size and genome location between tumours of the same type. Amplicons may contain numerous genes (the commonly amplified 20q locus may contain 132 genes ) but onlspecimen , highligspecimen . 19q12 iresearch . More reresearch .Fig. 1ScThis review presents a collation of genes established to be amplified therapeutic targets in HGSOC from the literature, with quantitative appraisal of the supporting evidence. Genes will be scored based on relevant evidence with key experimental strengths and flaws highlighted. Knockdown or knockout of a candidate gene in an OC cell line causing phenotypic suppression was near universal in publications and deemed essential for inclusion, as was evidence of overexpression and gene or locus amplification in human tissue. We devised a scoring system for candidate genes based on cell lines utilised, method of knockdown, breadth of phenotypic characterisation, correlation of expression or amplification to knockdown sensitivity (gene addictivity), evidence of reverse phenotype with gene overexpression, correlation of expression or amplification in human tissue to patient survival, use of in vivo models, use of pharmacological agents, mechanistic interrogation, and any other insightful efforts to validate , MCL1, BCL2L1, BCL2, ERBB3, ID4, RSF1 and CDC42BPA . The three joint highest scoring genes were CCNE1, is a key regulator of the cell cycle, promoting G1/S-phase transition mainly in conjunction with cyclin-dependent kinase 2 (CDK2)  constructs against CCNE1 in eight OC cell lines. Gene amplification was present in the most cell lines overexpressing CCNE1. Only one line was deemed high quality, however the group demonstrated addictivity to CCNE1: cell lines overexpressing the gene were more sensitive to siRNA knockdown. Similarly, CCNE1-overexpressing lines were more susceptible to the CDK2 inhibitor SNS-032. SNS-032 also increased survival of athymic mice injected with intraperitoneal OCC1 cells, a CCNE1-overexpressing cell line, exposing potential translational relevance [CCNE1 on five cell lines, including three high-quality lines. Cell lines with 19q12 amplification were more susceptible to knockdown. Interestingly, knockdown attenuated sensitivity to cisplatin, suggesting combination platinum therapy and CDK2-inhibition may be antagonistic [CCNE1 by inducing overexpression in dominant negative TP53 mutant Fallopian tube secretory epithelial cells (FTSEC) using a viral vector. This increased clonogenicity and anchorage-independent growth, elegantly supporting a role for CCNE1 in HGSOC carcinogenesis. The group also confirmed correlation of CCNE1-amplification in patient tumour tissue with poorer OS, using The Cancer Genome Atlas (TCGA) data [Cyclin E1, encoded by 2) (ref. ). Two paelevance . Etemadmgonistic . DemonstGA) data .CCNE1-amplified HGSOC, with SNS-032  and din32  [PAX8 is amplified in 16% of HGSOCs [CCNE1 in our analysis. Its significance as an amplified therapeutic target was identified by Cheung et al. in a genome-wide shRNA screen performed on a large panel of cell lines, including five high-quality HGSOC lines. In this study, the anti-proliferative effect of PAX8 knockdown correlated with expression level, and the gene emerged as the highest-ranking dependency in OC cell lines [PAX8’s role in cellular migration by performing wound closure and Boyden chamber assays with CRISPR-generated PAX8−/− OVCAR4 and OVCAR8 cells. Mouse models revealed reduced proliferation rates in vivo and prolonged survival with PAX8 knockout. The group demonstrated that the thiopeptide antibiotic thiostrepton reduces PAX8 protein levels by an as yet unidentified mechanism and successfully used micellar thiostrepton to improve survival of mice with OVCAR8 xenografts [PAX8 has strong evidence as an amplified therapeutic target.um (FTE) . PAX8 maum (FTE) ) and tumum (FTE) ). PAX8 if HGSOCs , and wasll lines . Hardy enografts . CollectDespite micellar thiostrepton being used pre-clinically , we coulURI1, resides in the 19q12 locus adjacent to CCNE1, and was one of the top depleted genes in this robust and systematic study. URI1 copy number and expression in patient tissue were both found to correlate with OS and PFS from TCGA data [URI1 overexpressing cell lines were more sensitive to knockdown than cell lines with low expression and demonstrated that knockdown of URI1 reduced the in vivo tumorigenicity of URI1-amplified OVCAR3 cells. Validating evidence for URI1’s mechanism of effect was also revealed; it increases the threshold for apoptotic death under stress conditions such as growth factor depletion or presence of antitumour drugs such as rapamycin and cisplatin. Overexpressed URI1 constitutively inhibits PP1γ, reducing the negative feedback of S6K1-BAD survival signalling; a finding corroborated in human ovarian cancer tissue [URI1 is a member of the prefoldin family of molecular chaperones with roles in apoptotic signalling . Davis eCGA data . Theurilr tissue .URI1, or publications pertaining to development of inhibitors.We could not find clinical trials relevant to PRKCI encodes protein kinase C Iota (PKCι), an atypical member of the (serine/threonine) protein kinase C (PKC) family [PRKCI induces YAP1-dependent transformation of FTE cells [PRKCI overexpression [PRKCI as an amplified therapeutic target. They performed an siRNA knockdown in 12 OC lines , demonstrating greater growth inhibition in lines with PRKCI amplification. The group also validated an EpCAM aptamer-delivered siRNA as a potential therapeutic using cell line-derived mouse xenograft models [) family . AlthougTE cells , 40 and TE cells . PRKCI opression  but not pression  is assoct models . IntrapeThe gold compound aurothiomalate is known to inhibit PKCι, and has been evaluated in a phase 1 study, which included four patients with OC. Best response was SD in 13.3% of patients . The comFAL1 from a panel of 37 lncRNA genes which were commonly amplified in at least one tumour tissue, commonly overexpressed in cell lines, and located in a focal amplicon. Amplification and overexpression of FAL1 in OC were associated with poorer OS. siRNA knockdown in a panel of OC cell lines reduced growth and anchorage-independent growth. Ectopic overexpression of the lncRNA induced colony formation in human ovarian surface epithelium (OSE) cells, supporting an oncogenic role for FAL1. Intraperitoneal injection of siRNA targeting FAL1 reduced growth of A2780 xenografts [FAL1, however A2780 cells are considered a poor model cell line for HGSOC. FAL1 was shown to associate with and stabilise BMI1, a known oncoprotein implicated in EOC and key component of the chromatin remodelling polycomb group complex 1 (PRC1)  (ref. ). FAL1 r regions .FAL1.We could not find clinical trials relevant to BCL2L1, MCL1, BCL2 and BCL2L2) extensively validated, including with use of BH3-mimetic drugs, such as navitoclax. These genes are amplified in HGSOC, albeit relatively infrequently (4–12%) [C12orf5 (now referred to as TIGAR) was identified from a second genome-wide CRISPR screen, which investigated genes causing olaparib resistance. This was however only performed in A2780 cells [BRD4  . While t80 cells , limitinD4 (ref. ). EffortMYC and PIK3CA, scored perhaps surprisingly low - 6 and 4 respectively. Coming from older bodies of work, the knockdown experiments supporting these genes as amplified therapeutic targets were less robustly performed, e.g., with only a single siRNA construct in both cases [Several lower ranked genes commonly derived evidence from older studies: use of CRISPR, screening methods and deeper knowledge of cell line quality were not established a decade ago. Some wider studied and acknowledged oncogenes, such as th cases , 53. RepERBB2 amplification in breast cancer has led to therapeutic success, but trials of drugs targeting HER2, including trastuzumab, pertuzumab and lapatinib, have yielded poor results in ovarian cancer [ERBB2 as an amplified therapeutic target in HGSOC (a modest score of 6 in this review). ERBB2 may have a more limited role in HGSOC carcinogenesis, or may be only a bystander amplification in such cases. The phosphoinositide 3-kinase (PI3K) pathway is one of the most commonly deregulated in OC [PIK3CA  is amplified in 18% of HGSOCs [PIK3CA amplifications were not detected in any of the evaluable patients [PIK3CA as an amplified therapeutic target (score 4), the low prevalence of AKT1, AKT2 and AKT3 amplifications (as downstream nodes of the pathway) in HGSOC [In this review, we have quantitatively appraised the evidence supporting genes as amplified therapeutic targets in HGSOC. As clinical investigation of the disease becomes more extensive, copy number analysis of validated oncogenes as standard of care could lead to improved prognostication and tailored treatments. The literature suggests several promising targets. To date however, trials of drugs targeting amplified genes in HGSOC have been disappointing. Interrogation of n cancer . This pef HGSOCs . Severalf HGSOCs , 56. Howin HGSOC , or the in HGSOC . FurtherIn our effort to score and rank individual genes as HGSOC amplified targets, limitations to our approach should be acknowledged. Firstly, we could not easily lend weight to prevalence of amplifications due to non-standardised definitions of ‘amplified’. Secondly, in pooled studies, candidate genes may have been quantitatively compared with each other for weight of effect, however these comparisons are difficult to merit with differential scores due to breadth of work and experimental techniques. Lastly, standard in vitro knockdown experiments are unable to reflect the influence of amplified driver gene signalling on the tumour microenvironment (TME) , which mConventional methods, including siRNA screens and shRNA/siRNA targeting single genes to investigate functions of amplified genes are limited by relative low-throughput and off-target effects. Recent advances in whole genome functional genomics including CRISPR/Cas9 and pooled shRNA screens have produced robust and high-throughput data. Project Achilles is an ongoing shRNA and CRISPR/Cas9 screening effort, now incorporating over 700 cancer cell lines, integrated with CNA and other genomic data . In paraPIK3CA, PI3, ERBB3, ERBB2, FOXM1 and SKIL in a large panel of high-quality cell lines will give a better representation of their oncogenic roles. Several prominent oncogenes such as KRAS, TERT, AKT1 and AKT3, were not found to have sufficient evidence as amplified therapeutic targets from our secondary search. A systemic investigation of such known oncogenes from other cancer types may be required for HGSOC specifically.Several genes scored relatively low in our analysis due to experimental use of poor-quality cell lines. Knockdown studies for PRKCI is implicated in HGSOC immune suppression [HGSOC is characterised by an immunosuppressive TME, attributed to low tumour mutational burden with consequent low neo-antigen expression, epigenetic silencing of Th1-cytokines, and tumour endothelial Fas ligand and endothelin B receptor expression . While Ppression , the sigpression , 63.Intratumoral heterogeneity is likely to represent a major challenge in the development of HGSOC therapeutics. Clonal evolution yielding variations in chromosome and gene copy number occur through disease progression and following treatment with chemotherapy , 64. HowCCNE1-amplified or overexpressing HGSOC does not appear to have been investigated and could be considered in phase 2/3 trials. Fadraciclib could prove a more efficacious agent given its greater CDK2 selectivity [CCNE1-amplification may also yield other therapeutic vulnerabilities. Wee1, a serine-threonine kinase, inhibits CDK1 and CDK2 in response to DNA damage, thereby halting G2 and G1/S phase cell cycle progression respectively. Cancers often depend on the G2-M checkpoint to prevent mitotic catastrophe, hence Wee1 inhibitors can induce cancer cell apoptosis. Wee1 inhibition also enhances detection of DNA damage at G2/M phase [CCNE1-amplification and one with overexpression responded to therapy, while CCNE1 overexpression was not seen in non-responders [CCNE1 overexpression predicts sensitivity to adavosertib [CCNE1 amplifications to Wee1 inhibition should be further explored with both pre-clinical and clinical studies. Given their somewhat opposing effects on the cell cycle, CDK2 and Wee1 inhibition may not be synergistic, however this could be first explored with in vitro cytotoxicity studies. CDK2 is amplified in 6.4% of ovarian tumours; [PRKCI may be vulnerable to existing compounds. Selective small molecule PKCι inhibitors such as ICA-1 have been investigated in prostate cancer cell lines [PRKCI-amplified HGSOC.Evidence is mounting that several established drugs may be of benefit in HGSOCs with the relevant gene amplification. SNS-032 and dinaciclib have undergone clinical evaluation, however specific activity in ectivity . BLU-222/M phase . Adavosesponders . Pre-clivosertib . The reltumours;  althoughll lines . FollowiERBB3 amplification) in phase 2 studies. Development of antibody-drug conjugates and small molecule inhibitors targeting HER3 can also be considered. Several BCL2 family genes scored highly, and BH3-mimetics have therefore been proposed as treatments, particularly in the context of synergising with chemotherapy or re-sensitising resistant cancers to chemotherapy: [CDC42BPA, encoding MRCKA, scored 9 in this study. MRCKA was successfully targeted in vitro with the small molecule inhibitor BDP9066 . This aPAX8, URI1 and FAL1 may be the most lucrative targets to explore with such approaches given their strong supportive evidence, however more druggable targets can also be considered.Given the number of high-scoring targets which are deemed either ‘undruggable’ or difficult to drug, the development of RNAi or even CRISPR/Cas9 based therapeutics against such oncogenes should be explored. This is an appealing direction given recent successes in the clinic for RNA therapies, including covid-19 vaccines and patisiran, an siRNA therapeutic for hereditary transthyretin-mediated amyloidosis, both utilising lipid nanoparticle vectors . LiposomA final clinical consideration, beyond validation of single-drug approaches to individual amplified therapeutic targets, is combining such agents with existing therapies, as well as eventually other prospective agents in a strategic manner. Pre-clinical studies are an important first step to this end since inhibitors of amplified therapeutic targets may be cytostatic and therefore potentially antagonistic with conventional cytotoxic drugs such as paclitaxel . This isWith sluggish progress in drug approvals and many patients still fated to poor prognoses, HGSOC is a disease in urgent need of superior therapeutics. Given the heterogeneity of the disease, successes are likely to depend on tailoring treatments to the individual; identifying amplified therapeutic targets represents a logical step forward in this respect. In this literature review we have collated and appraised the genes which drive HGSOC carcinogenesis through amplification to give insight into the genomic disorder underpinning the disease and potential avenues for drug development.Research interrogates OC non-selectively or HGSOC (other subtypes excluded)Knockdown experiments are performed on at least one human OC cell lineGene of interest is either known or demonstrated to be overexpressed in human OC tissueGene or gene locus is either known or demonstrated to be amplified in human OC tissueWe initially conducted a PubMed search of the Medline database using the following search terms: (ovarian cancer) AND ((gene) OR (target)) AND ((driver) OR (addicted) OR (amplified)) AND ((rna interference) OR (shrna) OR (sirna) OR (crispr)). This yielded 93 results (as of 17th April 2022). Essential criteria for inclusion were:Where a criterion was not evidenced in a paper, a basic PubMed search of the Medline database was conducted to identify if this had been established elsewhere. Thirty papers studying 36 genes met these criteria; 63 papers were excluded. A further search was conducted for each gene of interest to collate additional evidence where this was lacking from the hits of the primary search. An additional search was conducted for some well-established oncogenes which did not appear in papers from the primary search, which added a further 8 genes. These were likely missed from the primary search because more historical work in this field was less integrated and, where these genes have been identified from screening techniques, researchers may favour novel genes for validation. This supplementary search is noted as a potential source of bias in this review but needed to avoid omission of key genes.See Supplementary Table 1 for the full gene scoring criteria. We lent a large score weight to the choice of cell lines used for knockdown studies. EOC encompasses distinct histological subtypes with different mutational and copy number landscapes, leading to different vulnerabilities. Mounting evidence suggests HGSOC arises from the FTE rather than the OSE, which may be distinct from other OC subtypes . The morTP53 wildtype, both have ARID1A and PIK3CA mutations and both have poor CNA correlation with HGSOC, implying they were more likely derived from clear cell or endometrioid cancers and diminishing their validity as HGSOC models. As a further example, IGROV1 is hypermutated compared to patient HGSOC tissue [TP53 wildtype, derived from a non-HGSOC subtype, wrong tissue of origin, or non-human.The availability of public datasets has permitted interrogation of cell line quality: in 2013, Domcke et al. performed a genomic comparison of patient specimens in TCGA repository and cell lines from the Cancer Cell Line Encyclopedia (CCLE). As well as identifying several high-quality HGSOC model cell lines, they revealed that some commonly used cell lines are poorly representative. SKOV3 and A2780 were then the two most frequently used cell lines for OC research: both are The next experimental factor in knockdown studies is method of knockdown. RNA interference (RNAi) involves neutralisation of specific messenger RNA (mRNA) leading to reduced translation. This can be performed experimentally with siRNA and shRNA, both of which offer greater activity than antisense oligonucleotides (ASO). While siRNA can be synthesised and administered exogenously, shRNA requires nuclear expression through a vector . Due to continuous expression, shRNA gives a more stable and durable knockdown . ConversThe next consideration in knockdown studies is the phenotype(s) being investigated. The most common in this review was cell growth or apoptosis, measured with various assays. Other cancer phenotypes investigated included migration and invasiveness, metabolism, drug sensitivity and anchorage independence/anoikis escape. Proof of a driver’s role in multiple phenotypes was rewarded an additional score. Demonstrating increased phenotypic suppression with knockdown in amplified or overexpressing cell lines relative to unamplified or lower expressing cell lines adds weight to an amplified oncogene being a driver; it implies dependence on or addiction to that gene . AnotherClinical evidence supporting a gene as a driver is also valuable. If gene amplification is contributing to malignant phenotype, poorer patient survival might be expected when this is present , 38. AddSupplementary Table 1Supplementary Table 2References for Supplementary Material


Protein disulphide isomerases (PDIs) play an important role in cancer progression. However, the relative contribution of the various isoforms of PDI in tumorigenesis is not clear.The content of PDI isoforms in 22 cancer cells lines was investigated using LC–MS/MS-based proteomic analysis. The effects of PDIA1, PDIA3 and PDIA17 inhibition on the proliferation, migration and adhesion of MCF-7 and MDA-MB-231 cells, identified as high and low PDIA17 expressing cells, respectively, were assessed using novel aromatic N-sulphonamides of aziridine-2-carboxylic acid derivatives as PDI inhibitors.PDIA1 and PDIA3 were the most abundant in cancer cell lysates and were also detected extracellularly in breast cancer cells (MDA-MB-231 and MCF-7). Some cancer cell lines  showed upregulated expression of PDIA17, whereas in others , PDIA17 was not detected. The simultaneous inhibition of PDIA1 and PDIA3 showed similar anti-proliferative effects in MCF-7 and MDA-MB-231 breast cancer cells. However, the inhibition of PDIA1 and PDIA17 in the MCF-7 cell line resulted in more effective anti-adhesive and anti-proliferative effects.PDIA1 and PDIA3 represent major isoforms of multiple cancer cells, and their non-selective inhibition displays significant anti-proliferative effects irrespective of whether or not PDIA17 is present. The more pronounced anti-adhesive effects of PDI inhibition in hormone-sensitive MCF-7 cells featured by higher levels of PDIs when compared to triple-negative MDA-MB-231 cells suggests that targeting extracellular PDIA1 and PDIA3 with or without additional PDIA17 inhibition may represent a strategy for personalized anti-adhesive, anti-metastatic therapy in cancers with high PDI expression.The online version contains supplementary material available at 10.1186/s12935-022-02631-w. Protein disulphide isomerases (PDIs) are highly expressed proteins present predominantly in the endoplasmic reticulum but also in the cytosol, nucleus, on the cell surface and extracellularly . PDIs weThe best described PDI isoforms in cancer cells are PDIA1 P4HB) and PDIA3 (ERP57) HB and PD. SuppresIt is still inconclusive which PDI isoform should be targeted in anti-cancer treatment and whether targeting single rather than a formulation of ‘PDI-pan inhibition’ is a better strategy –18. It i2). Cells were regularly tested for mycoplasma contamination using the MycoAlert mycoplasma detection kit . Cells in two to five passages were seeded in equal amounts and grown to 90–95% confluence. The medium from cell cultures was collected and clarified from debris by centrifugation ). The cells were detached using Acutase solution  and washed twice with Dulbecco's phosphate-buffered saline  and centrifuged at 200g for 5 min. at RT. The material was frozen at − 80 °C until analysis.The studies were performed using 22 human and mouse cancer cell lines, representative for breast , colon , urinary bladder (5637), prostate , lung  and ovarian (A2780) cancer as well as two normal cell lines . The type of culture medium, cell culture conditions and number of passages are shown in Additional file g, 15 min., 4 °C), and the supernatant was collected [Cells were lysed in lysis buffer  containing 7 M urea , 2 M thiourea , mass spectrometry safe protease and phosphatase inhibitor cocktail   and 30 mM Tris-HCl, pH 8.0 , sonicated on ice and centrifuged , the pellet was dissolved in 50 mM ammonium bicarbonate (ABC) .The medium was lyophilized, resuspended in 1 ml of MilliQ water, and 10 mg protein was processed using a ProteoMiner Protein Enrichment Kit  according to the procedure of Boschetti and Righetti  .The cell lysates and cell medium for proteomic analysis of PDIs were prepared according to a procedure provided by Sitek et al.  with sliThe proteomic analysis of cell lysates was conducted using Dionex UltiMate™ 3000 RSLC System  coupled to LTQ XL hybrid ion trap-Orbitrap Discovery mass spectrometer  as described by Kurpinska et al. .For the detection and semi-quantitation of PDI isoforms in cell lysates, the exponentially modified protein abundance index (emPAI) calculation was performed using an in-built tool of the Mascot search engine based on protein coverage by the peptide matches in a database search result , 25. TheThe repertoire of released PDIs was characterized in the two lines selected for further studies. To define the PDIs secreted by MDA-MB-231 (negative/low PDIA17 expression) and MCF-7 (high PDIA17 expression), cell media were subjected to enhanced proteomic analysis in the Mass Spectrometry Laboratory at the Institute of Biochemistry and Biophysics, Polish Academy of Sciences, Warsaw, Poland , 26. TheDetailed procedures for the proteomic studies are described in Additional file Lysates of all cell lines used in the study were checked for PDIA17 presence using Western blotting  and C-3353 that also displayed PDIA17 inhibition properties were described previously , 20. Det50)  causing aggregation of its β-chain, analyzed by turbidimetry as presented earlier by Kalvins et al.  and Chlo50 parameter was determined as previously described [The proliferation rate of the cells was measured using an MTT assay.  was analyzed using a functional adhesion assay according to the procedure reported by Stojak et al.  with minThe migration of MCF-7 and MDA-MB-231 cells was monitored using real-time quantitative wound healing assays and 96W1E + ECIS arrays  according to the procedure reported by Stojak et al.  with minThe PDI repertoire detected by LC–MS/MS-based label-free semi-quantitative proteomic analysis in 22 cancer cell line lysates to some extent was specific to the cell type Table  and inclInterestingly, PDIA17 was expressed in some cancer cell lines  with comparable expression levels to that of PDIA1 and PDIA3. However, PDIA17 was not detected in other investigated cell lines .The presence of PDIA17 was confirmed by Western blot analysis in MCF-7, PC-3, HT-29, T47D, NCIH358 and A549 cell lines . PDIA3 expression was similar in both cell lines .50 values for C-3380 reached 80.45  ± 3.18 µM in MDA-MB-231 and 78.61 ± 7.20 µM in the MCF-7 cell line. For C-3389, the IC50 was 74.77 ± 3.17 µM in MDA-MB-231 and 85.86  ± 14.5 µM in MCF-7, whereas the IC50 of C-3399 was lower: 8.69  ± 0.89 µM in MDA-MB-231 and 11.06  ± 0.78 µM in MCF-7.As shown in Fig. . 50% of control) by C-3380 and C-3399 at a concentration of 3 µM and by C-3389 at a concentration of 50 µM. In turn, the adhesion of MDA-MB-231 to collagen was reduced (ca. 75% of control) by C-3399 at a concentration of 10 µM and weakly by C-3389 at a higher concentration (100 µM)   as compared with MDA-MB-231 cell adhesion, which was inhibited by C-3353 at a concentration of 50 µM Fig. C.50 values for C-3380, C-3389, C-3399 and C-3353 were 90.89  ±  17.18 µM, 34.34  ±  13.09 µM, 38.16  ±  10.33 µM and higher than 360 µM, respectively. In MCF10A cells, IC50 values were: 59.29  ±  8.3 µM, 20.42  ±  5.35 µM, 17.85  ±  1.15 µM and 75.60  ±  4.05 µM, respectively.To test cytotoxicity of compounds used in this study against regular cell lines, BALB/3T3 and MCF10A cells were used, mouse fibroblast and human breast epithelial cell line, respectively. In BALB/3T3 cells the ICIn the present work, we characterized PDI isoform contents in various cancer cell lines and provided evidence that PDIA1 and PDIA3 represent major isoforms of multiple cancer cells, and the non-selective inhibition of PDIA1 and PDIA3 displayed significant anti-proliferative effects irrespective of whether or not PDIA17 was present. On the other hand, PDIA17 was highly expressed in the hormone-sensitive MCF-7 breast cancer cell line when compared to the triple-negative MDA-MB-231 cell line, and PDIA17 inhibition displayed additional anti-proliferative effects in the MCF-7 but not in the MDA-MB-231 breast cancer cell line. Interestingly, the anti-adhesive effects in the hormone-sensitive MCF-7 cells featured by higher levels of PDIs were clearly more pronounced when compared to triple-negative MDA-MB-231 cells, suggesting that PDIA1-, PDIA3- and PDIA17-based therapy may represent a novel strategy for personalized anti-metastatic therapy in cancers with high PDI expression.In previous studies, the overexpression of the PDIs in comparison to normal tissue was demonstrated , and there is a general agreement on the important role of PDIs in cancer survival . The datThe major contribution of PDIA1 and PDIA3 to the total PDI profile of various cancer cells, their secretion and important role outside the cell agrees with growing evidence for the involvement of PDIA1 and PDIA3 in cancer progression , 30–35.., prostate, breast cancer) and cell lines within the same type of cancer. For example, among lung cancers, the NCIH1299 cell line had very low expression of PDIA1, whereas in the NCIH358 cell line, this expression was 14 folds higher. In particular, in breast cancer cell lines, PDIA17 expression was high in the hormone-sensitive MCF-7 cell line but not detectable in the triple-negative MDA-MB-231 cell line. This was an important finding of our work in the context of the suggested role of PDIA17 in genomic integrity, proliferation, apoptosis, angiogenesis, adhesion, migration, stemness and inflammation [Importantly, independent of this general rule, the profile of individual PDIs did vary to some extent between cancer types (e.gammation , 36, indammation . Increasammation . In our ammation , suggestammation , 40–42. ammation –45.In the context of the emerging literature on the role of PDIA17 in tumorigenesis, based on our proteomic analysis confirmed by Western blotting, we were able to clearly define MCF-7 as a breast cancer cell line with high PDIA17 expression, whereas MDA-MB-231 had very low PDIA17 expression, and we used these two cell lines for pharmacological studies. Importantly, the intercellular expression of PDIA1 and PDIA3 in these two cell lines displayed only modest differences in their relative intracellular abundance; therefore, these two lines were well suited to delineate the relative functional importance of PDIA1 and PDIA3 as compared with PDIA17. As pharmacological tools to inhibit PDIA1, PDIA3 or PDIA17, we used recently developed aromatic N-sulphonamides of aziridine-2-carboxylic acid derivatives , 20. TheHere, we demonstrated in the anti-proliferative assays that MCF-7 and MDA-MB-231 exhibited similar responses to the PDI inhibitors used, suggesting that targeting the most abundant PDI isoforms regardless of PDIA17 levels may be an effective strategy to inhibit the proliferation of cancer cells.In turn, the anti-adhesive properties of the tested PDIA1 and PDIA3 inhibitors were more pronounced in the MCF-7 cell line, a result that might be attributed to higher expression of PDIA1 on the surface membrane of the cells in comparison to the MDA-MB-231 cell line because extracellular PDIA1 seemed more abundant in the cell line. The role of PDIA1 in cancer cell adhesion was in accordance with our recent work demonstrating that extracellular PDIA1 plays an important role in regulating the adhesion of cancer cells to matrix proteins, endothelium and their transendothelial migration . SimilarNoteworthy, the majority of available inhibitors of PDIs are non-selective sulfhydryl-reactive compounds that mostly target intracellular PDIs. For example, the irreversible PDIA1 inhibitor—PACMA31—efficiently suppressed ovarian tumour growth, suggesting non-selective intracellular PDI inhibition as a major target for anti-cancer PACMA 31 action , 47. SimIn conclusion, PDIA1 and PDIA3 represent the most abundant isoforms in multiple cancer cell lines and are also bound to membranes and released extracellularly providing the rationale of the development of anti-PDIA1 and anti-PDIA3 therapy targeted to extracellular PDIs. PDIA17 expression appears to be cell specific and related to cancer cell malignancy, and its inhibition could present additional benefits in cancer cells expressing PDIA17. In particular, it seems that PDIA17 targeting might be of importance in some ER-positive cancers. Targeting extracellular PDIA1-, PDIA- and PDI17-dependent regulation of cancer cell adhesion may represent a novel, effective, personalized anti-adhesive and anti-metastatic therapy in cancers with high PDI expression. This notion agrees with an increasing interest in the molecular mechanisms of action of extracellular PDIs . FurtherAdditional file 1: Methods. Contains all additional information on methods used in the study.Additional file 2: Table S1. The origin and conditions of maintenance of cell cultures.Additional file 3: Table S2. The half maximal inhibitory concentration for selected PDIA1, PDIA3 and PDIA17 inhibitors.


Decreased α-Klotho, a geroprotective factor, and increased senescent cell burden are both associated with early onset of physical disability, cognitive impairment, and premature all-cause mortality. It has been demonstrated that eliminating senescent cells can enhance physical function, cognition, and survival in mice, as does overexpressing α-Klotho. Mice with low α-Klotho exhibit accelerated senescent cell accumulation, recombinant α-Klotho decreases senescent cell burden and restores lifespan in these mice, and senescent epidermal cells are reduced in mice overexpressing α-Klotho. Here, we tested the hypothesis that senescent cells cause decreased α-Klotho and hence that reducing senescent cells can increase α-Klotho. Senescent cell conditioned medium (CM) reduced α-Klotho in cultured non-senescent human umbilical vein endothelial cells (HUVECs), renal tubular endothelial cells, and astrocytes. These effects of senescent CM were partially attenuated by neutralizing antibodies against the senescence-associated secretory phenotype (SASP) factors, activin A and IL-1α. Transplanting senescent cells into younger mice caused decreased urine and brain α-Klotho. Genetically reducing highly p16Ink4a-expressing cells in old INK-ATTAC mice or administering the senolytics, Dasatinib plus Quercetin (D+Q) or Fisetin (F), to young mice transplanted with senescent cells, young diet-induced obese (DIO) mice, or naturally-aged mice increased urine, kidney, and/or brain α-Klotho. Treating patients with idiopathic pulmonary fibrosis (IPF), a cellular senescence-related disease, with D+Q led to increased urinary α-Klotho. Thus, targeting senescent cells causes increases in the geroprotective factor α-Klotho, potentially amplifying the beneficial effects of senolytic drugs.