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.

Hyd/UBR5 defines a tumor suppressor pathway that links Polycomb repressive complex to regulated protein degradation in tissue growth control and tumorigenesis.

Tumor suppressor genes play critical roles in normal tissue homeostasis, and their dysregulation underlies human diseases including cancer. Besides human genetics, model organisms such as Drosophila have been instrumental in discovering tumor suppressor pathways that were subsequently shown to be highly relevant in human cancer. Here we show that hyperplastic disc (Hyd), one of the first tumor suppressors isolated genetically in Drosophila and encoding an E3 ubiquitin ligase with hitherto unknown substrates, and Lines (Lin), best known for its role in embryonic segmentation, define an obligatory tumor suppressor protein complex (Hyd-Lin) that targets the zinc finger-containing oncoprotein Bowl for ubiquitin-mediated degradation, with Lin functioning as a substrate adaptor to recruit Bowl to Hyd for ubiquitination. Interestingly, the activity of the Hyd-Lin complex is directly inhibited by a micropeptide encoded by another zinc finger gene, drumstick (drm), which functions as a pseudosubstrate by displacing Bowl from the Hyd-Lin complex, thus stabilizing Bowl. We further identify the epigenetic regulator Polycomb repressive complex1 (PRC1) as a critical upstream regulator of the Hyd-Lin-Bowl pathway by directly repressing the transcription of the micropeptide drm Consistent with these molecular studies, we show that genetic inactivation of Hyd, Lin, or PRC1 resulted in Bowl-dependent hyperplastic tissue overgrowth in vivo. We also provide evidence that the mammalian homologs of Hyd (UBR5, known to be recurrently dysregulated in various human cancers), Lin (LINS1), and Bowl (OSR1/2) constitute an analogous protein degradation pathway in human cells, and that OSR2 promotes prostate cancer tumorigenesis. Altogether, these findings define a previously unrecognized tumor suppressor pathway that links epigenetic program to regulated protein degradation in tissue growth control and tumorigenesis.

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.

Dominance analysis to assess solute contributions to multicomponent phase equilibria.

Phase separation in aqueous solutions of macromolecules underlies the generation of biomolecular condensates in cells. Condensates are membraneless bodies, representing dense, macromolecule-rich phases that coexist with the dilute, macromolecule-deficient phases. In cells, condensates comprise hundreds of different macromolecular and small molecule solutes. How do different solutes contribute to the driving forces for phase separation? To answer this question, we introduce a formalism we term energy dominance analysis. This approach rests on analysis of shapes of the dilute phase boundaries, slopes of tie lines, and changes to dilute phase concentrations in response to perturbations of concentrations of different solutes. The framework is based solely on conditions for phase equilibria in systems with arbitrary numbers of macromolecules and solution components. Its practical application relies on being able to measure dilute phase concentrations of the components of interest. The dominance framework is both theoretically facile and experimentally applicable. We present the formalism that underlies dominance analysis and establish its accuracy and flexibility by deploying it to analyze phase diagrams probed in simulations and in experiments.

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.

A kinetic model for solving a combination optimization problem in ab-initio Cryo-EM 3D reconstruction.

Cryo-Electron Microscopy (cryo-EM) is a widely used and effective method for determining the three-dimensional (3D) structure of biological molecules. For ab-initio Cryo-EM 3D reconstruction using single particle analysis (SPA), estimating the projection direction of the projection image is a crucial step. However, the existing SPA methods based on common lines are sensitive to noise. The error in common line detection will lead to a poor estimation of the projection directions and thus may greatly affect the final reconstruction results. To improve the reconstruction results, multiple candidate common lines are estimated for each pair of projection images. The key problem then becomes a combination optimization problem of selecting consistent common lines from multiple candidates. To solve the problem efficiently, a physics-inspired method based on a kinetic model is proposed in this work. More specifically, hypothetical attractive forces between each pair of candidate common lines are used to calculate a hypothetical torque exerted on each projection image in the 3D reconstruction space, and the rotation under the hypothetical torque is used to optimize the projection direction estimation of the projection image. This way, the consistent common lines along with the projection directions can be found directly without enumeration of all the combinations of the multiple candidate common lines. Compared with the traditional methods, the proposed method is shown to be able to produce more accurate 3D reconstruction results from high noise projection images. Besides the practical value, the proposed method also serves as a good reference for solving similar combinatorial optimization problems.

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.

Mutations in the genes responsible for the synthesis of furan fatty acids resolve the light-induced off-odor in soybean oil.

Soybean oil is the second most produced edible vegetable oil and is used for many edible and industrial materials. Unfortunately, it has the disadvantage of 'reversion flavor' under photooxidative conditions, which produces an off-odor and decreases the quality of edible oil. Reversion flavor and off-odor are caused by minor fatty acids in the triacylglycerol of soybean oil known as furan fatty acids, which produce 3-methyl-2,4-nonanedione (3-MND) upon photooxidation. As a solution to this problem, a reduction in furan fatty acids leads to a decrease in 3-MND, resulting in a reduction in the off-odor induced by light exposure. However, there are no reports on the genes related to the biosynthesis of furan fatty acids in soybean oil. In this study, four mutant lines showing low or no furan fatty acid levels in soybean seeds were isolated from a soybean mutant library. Positional cloning experiments and homology search analysis identified two genes responsible for furan fatty acid biosynthesis in soybean: Glyma.20G201400 and Glyma.04G054100. Ectopic expression of both genes produced furan fatty acids in transgenic soybean hairy roots. The structure of these genes is different from that of the furan fatty acid biosynthetic genes in photosynthetic bacteria. Homologs of these two group of genes are widely conserved in the plant kingdom. The purified oil from the furan fatty acid mutant lines had lower amounts of 3-MND and reduced off-odor after light exposure, compared with oil from the wild-type.

Solanum pennellii (LA5240) backcross inbred lines (BILs) for high resolution mapping in tomato.

Wild species are an invaluable source of new traits for crop improvement. Over the years, the tomato community bred cultivated lines that carry introgressions from different species of the tomato tribe to facilitate trait discovery and mapping. The next phase in such projects is to find the genes that drive the identified phenotypes. This can be achieved by genotyping a few thousand individuals resulting in fine mapping that can potentially identify the causative gene. To couple trait discovery and fine mapping, we are presenting large, recombination-rich, Backcross Inbred Line (BIL) populations involving an unexplored accession of the wild, green-fruited species Solanum pennellii (LA5240; the 'Lost' Accession) with two modern tomato inbreds: LEA, determinate, and TOP, indeterminate. The LEA and TOP BILs are in BC2F6-8 generation and include 1400 and 500 lines, respectively. The BILs were genotyped with 5000 SPET markers, showing that in the euchromatic regions there was one recombinant every 17-18 Kb while in the heterochromatin a recombinant every 600-700 Kb (TOP and LEA respectively). To gain perspective on the topography of recombination we compared five independent members of the Self-pruning gene family with their respective neighboring genes; based on PCR markers, in all cases we found recombinants. Further mapping analysis of two known morphological mutations that segregated in the BILs (self-pruning and hairless) showed that the maximal delimited intervals were 73 Kb and 210 Kb, respectively, and included the known causative genes. The 'Lost'_BILs provide a solid framework to study traits derived from a drought-tolerant wild tomato.

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.

Mosaicism in Cutaneous Disorders.

Genetic mosaicism arises when a zygote harbors two or more distinct genotypes, typically due to de novo, somatic mutation during embryogenesis. The clinical manifestations largely depend on the differentiation status of the mutated cell; earlier mutations target pluripotent cells and generate more widespread disease affecting multiple organ systems. If gonadal tissue is spared-as in somatic genomic mosaicism-the mutation and its effects are limited to the proband, whereas mosaicism also affecting the gametes, such as germline or gonosomal mosaicism, is transmissible. Mosaicism is easily appreciated in cutaneous disorders, as phenotypically distinct mutant cells often give rise to lesions in patterns determined by the affected cell type. Genetic investigation of cutaneous mosaic disorders has identified pathways central to disease pathogenesis, revealing novel therapeutic targets. In this review, we discuss examples of cutaneous mosaicism, approaches to gene discovery in these disorders, and insights into molecular pathobiology that have potential for clinical translation.

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.