Ancestry matters: Building inclusivity into preclinical study design.

Human cell lines (CLs) are key assets for biomedicine but lack ancestral diversity. Here, we explore why genetic diversity among cell-based models is essential for making preclinical research more equitable and widely translatable. We lay out practical actions that can be taken to improve inclusivity in study design.

Quantitative Proteomics of the Cancer Cell Line Encyclopedia.

Proteins are essential agents of biological processes. To date, large-scale profiling of cell line collections including the Cancer Cell Line Encyclopedia (CCLE) has focused primarily on genetic information whereas deep interrogation of the proteome has remained out of reach. Here, we expand the CCLE through quantitative profiling of thousands of proteins by mass spectrometry across 375 cell lines from diverse lineages to reveal information undiscovered by DNA and RNA methods. We observe unexpected correlations within and between pathways that are largely absent from RNA. An analysis of microsatellite instable (MSI) cell lines reveals the dysregulation of specific protein complexes associated with surveillance of mutation and translation. These and other protein complexes were associated with sensitivity to knockdown of several different genes. These data in conjunction with the wider CCLE are a broad resource to explore cellular behavior and facilitate cancer research.

Characterizing Mutational Signatures in Human Cancer Cell Lines Reveals Episodic APOBEC Mutagenesis.

Multiple signatures of somatic mutations have been identified in cancer genomes. Exome sequences of 1,001 human cancer cell lines and 577 xenografts revealed most common mutational signatures, indicating past activity of the underlying processes, usually in appropriate cancer types. To investigate ongoing patterns of mutational-signature generation, cell lines were cultured for extended periods and subsequently DNA sequenced. Signatures of discontinued exposures, including tobacco smoke and ultraviolet light, were not generated in vitro. Signatures of normal and defective DNA repair and replication continued to be generated at roughly stable mutation rates. Signatures of APOBEC cytidine deaminase DNA-editing exhibited substantial fluctuations in mutation rate over time with episodic bursts of mutations. The initiating factors for the bursts are unclear, although retrotransposon mobilization may contribute. The examined cell lines constitute a resource of live experimental models of mutational processes, which potentially retain patterns of activity and regulation operative in primary human cancers.

Metabolic Diversity in Human Non-Small Cell Lung Cancer Cells.

Intermediary metabolism in cancer cells is regulated by diverse cell-autonomous processes, including signal transduction and gene expression patterns, arising from specific oncogenotypes and cell lineages. Although it is well established that metabolic reprogramming is a hallmark of cancer, we lack a full view of the diversity of metabolic programs in cancer cells and an unbiased assessment of the associations between metabolic pathway preferences and other cell-autonomous processes. Here, we quantified metabolic features, mostly from the 13C enrichment of molecules from central carbon metabolism, in over 80 non-small cell lung cancer (NSCLC) cell lines cultured under identical conditions. Because these cell lines were extensively annotated for oncogenotype, gene expression, protein expression, and therapeutic sensitivity, the resulting database enables the user to uncover new relationships between metabolism and these orthogonal processes.

Cell line authentication: a necessity for reproducible biomedical research.

Immortalized or continuous cell lines are invaluable tools in basic and preclinical research. However, the widespread use of misidentified cell lines is a serious threat to scientific reproducibility. Based on the experiences of mandatory cell line authentication at the International Journal of Cancer (IJC), we provide an overview of the issues pertinent to misidentified cell lines and discuss available solutions. We also summarize the lessons learned, revealing that at least 5% of the human cell lines used in manuscripts considered for peer review are misidentified. About 4% of the considered manuscripts are rejected for severe cell line problems, and most are subsequently published in other journals. In order to diminish such malpractice and its consequences for the scientific record, we postulate that strict multi-layered quality control is essential. Besides journals and publishers, we encourage scientists, research institutions, and funders to take action on the matter and revise their respective policies. Hence, we provide concrete recommendations on introducing regular authentication schemes and staff training, and discuss future steps for enhancing good cell culture practices.

A comprehensive benchmarking of machine learning algorithms and dimensionality reduction methods for drug sensitivity prediction.

A major challenge of precision oncology is the identification and prioritization of suitable treatment options based on molecular biomarkers of the considered tumor. In pursuit of this goal, large cancer cell line panels have successfully been studied to elucidate the relationship between cellular features and treatment response. Due to the high dimensionality of these datasets, machine learning (ML) is commonly used for their analysis. However, choosing a suitable algorithm and set of input features can be challenging. We performed a comprehensive benchmarking of ML methods and dimension reduction (DR) techniques for predicting drug response metrics. Using the Genomics of Drug Sensitivity in Cancer cell line panel, we trained random forests, neural networks, boosting trees and elastic nets for 179 anti-cancer compounds with feature sets derived from nine DR approaches. We compare the results regarding statistical performance, runtime and interpretability. Additionally, we provide strategies for assessing model performance compared with a simple baseline model and measuring the trade-off between models of different complexity. Lastly, we show that complex ML models benefit from using an optimized DR strategy, and that standard models-even when using considerably fewer features-can still be superior in performance.

Efficient tagging of endogenous proteins in human cell lines for structural studies by single-particle cryo-EM.

CRISPR/Cas9-based genome engineering has revolutionized our ability to manipulate biological systems, particularly in higher organisms. Here, we designed a set of homology-directed repair donor templates that enable efficient tagging of endogenous proteins with affinity tags by transient transfection and selection of genome-edited cells in various human cell lines. Combined with technological advancements in single-particle cryogenic electron microscopy, this strategy allows efficient structural studies of endogenous proteins captured in their native cellular environment and during different cellular processes. We demonstrated this strategy by tagging six different human proteins in both HEK293T and Jurkat cells. Moreover, analysis of endogenous glyceraldehyde 3-phosphate dehydrogenase (GAPDH) in HEK293T cells allowed us to follow its behavior spatially and temporally in response to prolonged oxidative stress, correlating the increased number of oxidation-induced inactive catalytic sites in GAPDH with its translocation from cytosol to nucleus.

Cell fate simulation reveals cancer cell features in the tumor microenvironment.

To elucidate the dynamic evolution of cancer cell characteristics within the tumor microenvironment (TME), we developed an integrative approach combining single-cell tracking, cell fate simulation, and 3D TME modeling. We began our investigation by analyzing the spatiotemporal behavior of individual cancer cells in cultured pancreatic (MiaPaCa2) and cervical (HeLa) cancer cell lines, with a focus on the α2-6 sialic acid (α2-6Sia) modification on glycans, which is associated with cell stemness. Our findings revealed that MiaPaCa2 cells exhibited significantly higher levels of α2-6Sia modification, correlating with enhanced reproductive capabilities, whereas HeLa cells showed less prevalence of this modification. To accommodate the in vivo variability of α2-6Sia levels, we employed a cell fate simulation algorithm that digitally generates cell populations based on our observed data while varying the level of sialylation, thereby simulating cell growth patterns. Subsequently, we performed a 3D TME simulation with these deduced cell populations, considering the microenvironment that could impact cancer cell growth. Immune cell landscape information derived from 193 cervical and 172 pancreatic cancer cases was used to estimate the degree of the positive or negative impact. Our analysis suggests that the deduced cells generated based on the characteristics of MiaPaCa2 cells are less influenced by the immune cell landscape within the TME compared to those of HeLa cells, highlighting that the fate of cancer cells is shaped by both the surrounding immune landscape and the intrinsic characteristics of the cancer cells.

Failure to progress: breast and prostate cancer cell lines in developing targeted therapies.

Developing anticancer drugs from preclinical to clinical takes approximately a decade in a cutting-edge biomedical lab and still 97% of most fail at clinical trials. Cell line usage is critical in expediting the advancement of anticancer therapies. Yet developing appropriate cell lines has been challenging and overcoming these obstacles whilst implementing a systematic approach of utilizing 3D models that recapitulate the tumour microenvironment is prudent. Using a robust and continuous supply of cell lines representing all ethnic groups from all locales is necessary to capture the evolving tumour landscape in culture. Next, the conversion of these models to systems on a chip that can by way of high throughput cytotoxic assays identify drug leads for clinical trials should fast-track drug development while markedly improving success rates. In this review, we describe the challenges that have hindered the progression of cell line models over seven decades and methods to overcome this. We outline the gaps in breast and prostate cancer cell line pathology and racial representation alongside their involvement in relevant drug development.

Incorporation of 53BP1 into phase-separated bodies in cancer cells during aberrant mitosis.

53BP1 (also known as TP53BP1) is a key mediator of the non-homologous end joining (NHEJ) DNA repair pathway, which is the primary repair pathway in interphase cells. However, the mitotic functions of 53BP1 are less well understood. Here, we describe 53BP1 mitotic stress bodies (MSBs) formed in cancer cell lines in response to delayed mitosis. These bodies displayed liquid-liquid phase separation characteristics, were close to centromeres, and included lamin A/C and the DNA repair protein RIF1. After release from mitotic arrest, 53BP1 MSBs decreased in number and moved away from the chromatin. Using GFP fusion constructs, we found that the 53BP1 oligomerization domain region was required for MSB formation, and that inclusion of the 53BP1 N terminus increased MSB size. Exogenous expression of 53BP1 did not increase MSB size or number but did increase levels of MSB-free 53BP1. This was associated with slower mitotic progression, elevated levels of DNA damage and increased apoptosis, which is consistent with MSBs suppressing a mitotic surveillance by 53BP1 through sequestration. The 53BP1 MSBs, which were also found spontaneously in a subset of normally dividing cancer cells but not in non-transformed cells (ARPE-19), might facilitate the survival of cancer cells following aberrant mitoses. This article has an associated First Person interview with the first author of the paper.

CCSynergy: an integrative deep-learning framework enabling context-aware prediction of anti-cancer drug synergy.

Combination therapy is a promising strategy for confronting the complexity of cancer. However, experimental exploration of the vast space of potential drug combinations is costly and unfeasible. Therefore, computational methods for predicting drug synergy are much needed for narrowing down this space, especially when examining new cellular contexts. Here, we thus introduce CCSynergy, a flexible, context aware and integrative deep-learning framework that we have established to unleash the potential of the Chemical Checker extended drug bioactivity profiles for the purpose of drug synergy prediction. We have shown that CCSynergy enables predictions of superior accuracy, remarkable robustness and improved context generalizability as compared to the state-of-the-art methods in the field. Having established the potential of CCSynergy for generating experimentally validated predictions, we next exhaustively explored the untested drug combination space. This resulted in a compendium of potentially synergistic drug combinations on hundreds of cancer cell lines, which can guide future experimental screens.

PALB2-mutated human mammary cells display a broad spectrum of morphological and functional abnormalities induced by increased TGFß signaling.

Heterozygous mutations in any of three major genes, BRCA1, BRCA2 and PALB2, are associated with high-risk hereditary breast cancer susceptibility frequently seen as familial disease clustering. PALB2 is a key interaction partner and regulator of several vital cellular activities of BRCA1 and BRCA2, and is thus required for DNA damage repair and alleviation of replicative and oxidative stress. Little is however known about how PALB2-deficiency affects cell function beyond that, especially in the three-dimensional setting, and also about its role during early steps of malignancy development. To answer these questions, we have generated biologically relevant MCF10A mammary epithelial cell lines with mutations that are comparable to certain clinically important PALB2 defects. We show in a non-cancerous background how both mono- and biallelically PALB2-mutated cells exhibit gross spontaneous DNA damage and mitotic aberrations. Furthermore, PALB2-deficiency disturbs three-dimensional spheroid morphology, increases the migrational capacity and invasiveness of the cells, and broadly alters their transcriptome profiles. TGFß signaling and KRT14 expression are enhanced in PALB2-mutated cells and their inhibition and knock down, respectively, lead to partial restoration of cell functions. KRT14-positive cells are also more abundant with DNA damage than KRT14-negative cells. The obtained results indicate comprehensive cellular changes upon PALB2 mutations, even in the presence of half dosage of wild type PALB2 and demonstrate how PALB2 mutations may predispose their carriers to malignancy.

BBS genes are involved in accelerated proliferation and early differentiation of BBS-related tissues.

Bardet-Biedl syndrome (BBS) is an inherited disorder primarily ciliopathy with pleiotropic multi-systemic phenotypic involvement, including adipose, nerve, retinal, kidney, Etc. Consequently, it is characterized by obesity, cognitive impairment and retinal, kidney and cutaneous abnormalities. Initial studies, including ours have shown that BBS genes play a role in the early developmental stages of adipocytes and ß-cells. However, this role in other BBS-related tissues is unknown. We investigated BBS genes involvement in the proliferation and early differentiation of different BBS cell types. The involvement of BBS genes in cellular proliferation were studied in seven in-vitro and transgenic cell models; keratinocytes (hHaCaT) and Ras-transfected keratinocytes (Ras-hHaCaT), neuronal cell lines (hSH-SY5Y and rPC-12), silenced BBS4 neural cell lines (siBbs4 hSH-SY5Y and siBbs4 rPC-12), adipocytes (m3T3L1), and ex-vivo transformed B-cells obtain from BBS4 patients, using molecular and biochemical methodologies. RashHaCaT cells showed an accelerated proliferation rate in parallel to significant reduction in the transcript levels of BBS1, 2, and 4. BBS1, 2, and 4 transcripts linked with hHaCaT cell cycle arrest (G1 phase) using both chemical (CDK4 inhibitor) and serum deprivation methodologies. Adipocyte (m3T3-L1) Bbs1, 2 and 4 transcript levels corresponded to the cell cycle phase (CDK4 inhibitor and serum deprivation). SiBBS4 hSH-SY5Y cells exhibited early cell proliferation and differentiation (wound healing assay) rates. SiBbs4 rPC-12 models exhibited significant proliferation and differentiation rate corresponding to Nestin expression levels. BBS4 patients-transformed B-cells exhibited an accelerated proliferation rate (LPS-induced methodology). In conclusions, the BBS4 gene plays a significant, similar and global role in the cellular proliferation of various BBS related tissues. These results highlight the universal role of the BBS gene in the cell cycle, and further deepen the knowledge of the mechanisms underlying the development of BBS.

Statistical Testing for Protein Equivalence Identifies Core Functional Modules Conserved across 360 Cancer Cell Lines and Presents a General Approach to Investigating Biological Systems.

Quantitative proteomics has enhanced our capability to study protein dynamics and their involvement in disease using various techniques, including statistical testing, to discern the significant differences between conditions. While most focus is on what is different between conditions, exploring similarities can provide valuable insights. However, exploring similarities directly from the analyte level, such as proteins, genes, or metabolites, is not a standard practice and is not widely adopted. In this study, we propose a statistical framework called QuEStVar (Quantitative Exploration of Stability and Variability through statistical hypothesis testing), enabling the exploration of quantitative stability and variability of features with a combined statistical framework. QuEStVar utilizes differential and equivalence testing to expand statistical classifications of analytes when comparing conditions. We applied our method to an extensive data set of cancer cell lines and revealed a quantitatively stable core proteome across diverse tissues and cancer subtypes. The functional analysis of this set of proteins highlighted the molecular mechanism of cancer cells to maintain constant conditions of the tumorigenic environment via biological processes, including transcription, translation, and nucleocytoplasmic transport.

O-Glycome Profiling of Breast Cancer Cell Lines to Understand Breast Cancer Brain Metastasis.

Breast cancer is the second leading cause of cancer-related death among women and a major source of brain metastases. Despite the increasing incidence of brain metastasis from breast cancer, the underlying mechanisms remain poorly understood. Altered glycosylation is known to play a role in various diseases including cancer metastasis. However, profiling studies of O-glycans and their isomers in breast cancer brain metastasis (BCBM) are scarce. This study analyzed the expression of O-glycans and their isomers in human breast cancer cell lines (MDA-MB-231, MDA-MB-361, HTB131, and HTB22), a brain cancer cell line (CRL-1620), and a brain metastatic breast cancer cell line (MDA-MB-231BR) using nanoLC-MS/MS, identifying 27 O-glycan compositions. We observed significant upregulation in the expression of HexNAc1Hex1NeuAc2 and HexNAc2Hex3, whereas the expression of HexNAc1Hex1NeuAc1 was downregulated in MDA-MB-231BR compared to other cell lines. In our isomeric analysis, we observed notable alterations in the isomeric forms of the O-glycan structure HexNAc1Hex1NeuAc1 in a comparison of different cell lines. Our analysis of O-glycans and their isomers in cancer cells demonstrated that changes in their distribution can be related to the metastatic process. We believe that our investigation will contribute to an enhanced comprehension of the significance of O-glycans and their isomers in BCBM.

PhoXplex: Combining Phospho-enrichable Cross-Linking with Isobaric Labeling for Quantitative Proteome-Wide Mapping of Protein Interfaces.

Integrating cross-linking mass spectrometry (XL-MS) into structural biology workflows provides valuable information about the spatial arrangement of amino acid stretches, which can guide elucidation of protein assembly architecture. Additionally, the combination of XL-MS with peptide quantitation techniques is a powerful approach to delineate protein interface dynamics across diverse conditions. While XL-MS is increasingly effective with isolated proteins or small complexes, its application to whole-cell samples poses technical challenges related to analysis depth and throughput. The use of enrichable cross-linkers has greatly improved the detectability of protein interfaces in a proteome-wide scale, facilitating global protein-protein interaction mapping. Therefore, bringing together enrichable cross-linking and multiplexed peptide quantification is an appealing approach to enable comparative characterization of structural attributes of proteins and protein interactions. Here, we combined phospho-enrichable cross-linking with TMT labeling to develop a streamline workflow (PhoXplex) for the detection of differential structural features across a panel of cell lines in a global scale. We achieved deep coverage with quantification of over 9000 cross-links and long loop-links in total including potentially novel interactions. Overlaying AlphaFold predictions and disorder protein annotations enables exploration of the quantitative cross-linking data set, to reveal possible associations between mutations and protein structures. Lastly, we discuss current shortcomings and perspectives for deep whole-cell profiling of protein interfaces at large-scale.

Modulation of aggregation and structural polymorphisms of ß-amyloid fibrils in cellular environments by pyroglutamate-3 variant cross-seeding.

Amyloidogenic deposition of ß-amyloid (Aß) peptides in human brain involves not only the wild-type Aß (wt-Aß) sequences, but also posttranslationally modified Aß (PTM-Aß) variants. Recent studies hypothesizes that the PTM-Aß variants may trigger the deposition of wt-Aß, which underlies the pathology of Sporadic Alzheimer's disease. Among PTM-Aß variants, the pyroglutamate-3-Aß (pyroE3-Aß) has attracted much attention because of their significant abundances and broad distributions in senile plaques and dispersible and soluble oligomers. pyroE3-specific antibodies are being tested as potential anti-Aß drugs in clinical trials. However, evidence that support the triggering effect of pyroE3-Aß on wt-Aß in cells remain lacking, which diminishes its pathological relevance. We show here that cross-seeding with pyroE3-Aß40 leads to accelerated extracellular and intracellular aggregation of wt-Aß40 in different neuronal cells. Cytotoxicity levels are elevated through the cross-seeded aggregation, comparing with the self-seeded aggregation of wt-Aß40 or the static presence of pyroE3-Aß40 seeds. For the extracellular deposition in mouse neuroblastoma Neuro2a (N2a) cells, the cytotoxicity elevation correlates positively with the seeding efficiency. Besides aggregation rates, cross-seeding with pyroE3-Aß40 also modulates the molecular level structural polymorphisms of the resultant wt-Aß40 fibrils. Using solid-state nuclear magnetic resonance (ssNMR) spectroscopy, we identified key structural differences between the parent pyroE3/ΔE3 and wt-Aß40 fibrils within their fibrillar cores. Structural propagation from seeds to daughter fibrils is demonstrated to be more pronounced in the extracellular seeding in N2a cells by comparing the ssNMR spectra from different seeded wt-Aß40 fibrils, but less significant in the intracellular seeding process in human neuroblastoma SH-SY5Y cells.

Building in vitro tools for livestock genomics: chromosomal variation within the PK15 cell line.

BACKGROUND: Cultured porcine cell lines are powerful tools for functional genomics and in vitro phenotypic testing of candidate causal variants. However, to be utilised for genomic or variant interrogation assays, the genome sequence and structure of cultured cell lines must be realised. In this work, we called variants and used read coverage in combination with within-sample allele frequency to detect potential aneuploidy in two immortalised porcine kidney epithelial (PK15) cell lines and in a pig embryonic fibroblast line. RESULTS: We compared two PK15 cultured cells samples: a new American Type Culture Collection (ATCC) sample and one that has been utilised and passaged within the laboratory for an extended period (> 10 years). Read coverage and within-sample allele frequencies showed that several chromosomes are fully or partially aneuploid in both PK15 lines, including potential trisomy of chromosome 4 and tetrasomy of chromosome 17. The older PK15 line showed evidence of additional structural variation and potentially clonal variation. By comparison, the pig embryonic fibroblast line was free from the gross aneuploidies seen in the PK15s. CONCLUSIONS: Our results show that the PK15 cell lines examined have aneuploidies and complex structural variants in their genomes. We propose that screening for aneuploidy should be considered for cell lines, and discuss implications for livestock genomics.

Transcription factor expression landscape in Drosophila embryonic cell lines.

BACKGROUND: Transcription factor (TF) proteins are a key component of the gene regulatory networks that control cellular fates and function. TFs bind DNA regulatory elements in a sequence-specific manner and modulate target gene expression through combinatorial interactions with each other, cofactors, and chromatin-modifying proteins. Large-scale studies over the last two decades have helped shed light on the complex network of TFs that regulate development in Drosophila melanogaster. RESULTS: Here, we present a detailed characterization of expression of all known and predicted Drosophila TFs in two well-established embryonic cell lines, Kc167 and S2 cells. Using deep coverage RNA sequencing approaches we investigate the transcriptional profile of all 707 TF coding genes in both cell types. Only 103 TFs have no detectable expression in either cell line and 493 TFs have a read count of 5 or greater in at least one of the cell lines. The 493 TFs belong to 54 different DNA-binding domain families, with significant enrichment of those in the zf-C2H2 family. We identified 123 differentially expressed genes, with 57 expressed at significantly higher levels in Kc167 cells than S2 cells, and 66 expressed at significantly lower levels in Kc167 cells than S2 cells. Network mapping reveals that many of these TFs are crucial components of regulatory networks involved in cell proliferation, cell-cell signaling pathways, and eye development. CONCLUSIONS: We produced a reference TF coding gene expression dataset in the extensively studied Drosophila Kc167 and S2 embryonic cell lines, and gained insight into the TF regulatory networks that control the activity of these cells.

Genomic dissection and mutation-specific target discovery for breast cancer PIK3CA hotspot mutations.

BACKGROUND: Recent advancements in high-throughput genomics and targeted therapies have provided tremendous potential to identify and therapeutically target distinct mutations associated with cancers. However, to date the majority of targeted therapies are used to treat all functional mutations within the same gene, regardless of affected codon or phenotype. RESULTS: In this study, we developed a functional genomic analysis workflow with a unique isogenic cell line panel bearing two distinct hotspot PIK3CA mutations, E545K and H1047R, to accurately identify targetable differences between mutations within the same gene. We performed RNA-seq and ATAC-seq and identified distinct transcriptomic and epigenomic differences associated with each PIK3CA hotspot mutation. We used this data to curate a select CRISPR knock out screen to identify mutation-specific gene pathway vulnerabilities. These data revealed AREG as a E545K-preferential target that was further validated through in vitro analysis and publicly available patient databases. CONCLUSIONS: Using our multi-modal genomics framework, we discover distinct differences in genomic regulation between PIK3CA hotspot mutations, suggesting the PIK3CA mutations have different regulatory effects on the function and downstream signaling of the PI3K complex. Our results demonstrate the potential to rapidly uncover mutation specific molecular targets, specifically AREG and a proximal gene regulatory region, that may provide clinically relevant therapeutic targets. The methods outlined provide investigators with an integrative strategy to identify mutation-specific targets for the treatment of other oncogenic mutations in an isogenic system.