A novel RNA sequencing data analysis method for cell line authentication

Multiple approaches revealed MGc80-3 as a somatic hybrid with HeLa cells rather than a gastric cancer cell line

The short-tandem-repeats (STR) profiles of MGc80-3 and HeLa partially overlap, raising suspicion of contamination in the MGc80-3 cell line. However, there has not been any relevant study demonstrating whether MGc80-3 was fully replaced by HeLa cells, just mixed with HeLa cells (co-existing), or was a somatic hybrid with HeLa cells. In addition to STR profiling, various approaches, including single nucleotide polymorphisms genotyping, polymerase chain reaction, screening for human papillomaviruses type 18 (HPV-18) fragment, chromosome karyotyping, pathological examination of xenografts, tissue-specific-90-gene expression signature and high-throughput RNA sequencing were used to determine the nature of MGc80-3. Our study found that the abnormal STR profile, partially overlapping with that of HeLa cells (64.62% to 71.64%), could not verify MGc80-3 as a HeLa cell line. However, the STR 13.3 repeat allele in the D13S317 locus that seemed to be unique to HeLa cells was detected in MGc80-3. Almost all the MGc80-3 cells exhibited HPV-18 fragments in the genome as well as certain HeLa marker chromosomes, such as M7 and M12. The molecular assay of the 90-gene expression signature still considered MGc80-3 as a stomach cancer using an algorithmic analysis. The expression pattern of multiple genes in MGc80-3 was quite different from that in HeLa cells, which showed that certain characteristics belonged to gastric cancer cell lines. High throughput RNA sequencing showed the distinct patterns of gene expression in MGc80-3. In conclusion, MGc80-3 cell line is a somatic hybrid with HeLa cells rather than a pure gastric cancer cell line.

GenoPipe: identifying the genotype of origin within (epi)genomic datasets

Confidence in experimental results is critical for discovery. As the scale of data generation in genomics has grown exponentially, experimental error has likely kept pace despite the best efforts of many laboratories. Technical mistakes can and do occur at nearly every stage of a genomics assay (i.e. cell line contamination, reagent swapping, tube mislabelling, etc.) and are often difficult to identify post-execution. However, the DNA sequenced in genomic experiments contains certain markers (e.g. indels) encoded within and can often be ascertained forensically from experimental datasets. We developed the Genotype validation Pipeline (GenoPipe), a suite of heuristic tools that operate together directly on raw and aligned sequencing data from individual high-throughput sequencing experiments to characterize the underlying genome of the source material. We demonstrate how GenoPipe validates and rescues erroneously annotated experiments by identifying unique markers inherent to an organism's genome (i.e. epitope insertions, gene deletions and SNPs).

CCLHunter: An efficient toolkit for cancer cell line authentication

Cancer cell lines are essential in cancer research, yet accurate authentication of these cell lines can be challenging, particularly for consanguineous cell lines with close genetic similarities. We introduce a new Cancer Cell Line Hunter (CCLHunter) method to tackle this challenge. This approach utilizes the information of single nucleotide polymorphisms, expression profiles, and kindred topology to authenticate 1389 human cancer cell lines accurately. CCLHunter can precisely and efficiently authenticate cell lines from consanguineous lineages and those derived from other tissues of the same individual. Our evaluation results indicate that CCLHunter has a complete accuracy rate of 93.27%, with an accuracy of 89.28% even for consanguineous cell lines, outperforming existing methods. Additionally, we provide convenient access to CCLHunter through standalone software and a web server at https://ngdc.cncb.ac.cn/cclhunter.

GenoPipe: identifying the genotype of origin within (epi)genomic datasets

Confidence in experimental results is critical for discovery. As the scale of data generation in genomics has grown exponentially, experimental error has likely kept pace despite the best efforts of many laboratories. Technical mistakes can and do occur at nearly every stage of a genomics assay (i.e., cell line contamination, reagent swapping, tube mislabelling, etc.) and are often difficult to identify post-execution. However, the DNA sequenced in genomic experiments contains certain markers (e.g., indels) encoded within and can often be ascertained forensically from experimental datasets. We developed the Genotype validation Pipeline (GenoPipe), a suite of heuristic tools that operate together directly on raw and aligned sequencing data from individual high-throughput sequencing experiments to characterize the underlying genome of the source material. We demonstrate how GenoPipe validates and rescues erroneously annotated experiments by identifying unique markers inherent to an organism’s genome (i.e., epitope insertions, gene deletions, and SNPs).

Effect of TP53 deficiency and KRAS signaling on the bioenergetics of colon cancer cells in response to different substrates: A single cell study

Metabolic reprogramming is a hallmark of cancer. Somatic mutations in genes involved in oncogenic signaling pathways, including KRAS and TP53, rewire the metabolic machinery in cancer cells. We here set out to determine, at the single cell level, metabolic signatures in human colon cancer cells engineered to express combinations of activating KRAS gene mutations and TP53 gene deletions. Specifically, we explored how somatic mutations in these genes and substrate availability (lactate, glucose, substrate deprivation) from the extracellular microenvironment affect bioenergetic parameters, including cellular ATP, NADH and mitochondrial membrane potential dynamics. Employing cytosolic and mitochondrial FRET-based ATP probes, fluorescent NADH sensors, and the membrane-permeant cationic fluorescent probe TMRM in HCT-116 cells as a model system, we observed that TP53 deletion and KRAS mutations drive a shift in metabolic signatures enabling lactate to become an efficient metabolite to replenish both ATP and NADH following nutrient deprivation. Intriguingly, cytosolic, mitochondrial and overall cellular ATP measurements revealed that, in WT KRAS cells, TP53 deficiency leads to an enhanced ATP production in the presence of extracellular lactate and glucose, and to the greatest increase in ATP following a starvation period. On the other hand, oncogenic KRAS in TP53-deficient cells reversed the alterations in cellular ATP levels. Moreover, cell population measurements of mitochondrial and glycolytic metabolism using a Seahorse analyzer demonstrated that WT KRAS TP53-silenced cells display an increase of the basal respiration and tightly-coupled mitochondria, in the presence of glucose as substrate, compared to TP53 competent cells. Furthermore, cells possessing oncogenic KRAS, independently of TP53 status, showed less pronounced mitochondrial membrane potential changes in response to metabolic nutrients. Furthermore, analysis of cytosolic and mitochondrial NADH levels revealed that the simultaneous presence of TP53 deletion and oncogenic KRAS showed the most pronounced alteration in cytosolic and mitochondrial NADH during metabolic stress. In conclusion, our findings demonstrate how activating KRAS mutation and loss of TP53 remodel cancer metabolism and lead to alterations in bioenergetics under metabolic stress conditions by modulating cellular ATP production, NADH oxidation, mitochondrial respiration and function.

Using short tandem repeat profiling to validate cell lines in biobanks

Aim. To approve the COrDIS kit (Gordiz, Russia) for the authenticity of cell lines from the Bioresource Collection of the N.N. Blokhin National Medical Research Center of Oncology by the short tandem repeat (STR) profiling.

Material and methods. The chosen method proved to be a reliable and reproducible option. With this approach, a number of polymorphic STR loci are amplified using commercially available primer sets. Polymerase chain reaction (PCR) products are analyzed simultaneously with size standards using automated fluorescent detection methods. The results are presented as a simple number code corresponding to the lengths of the PCR products amplified at each locus. By applying this method to cell lines, the laboratory can both authenticate commercial cell lines and build a database of their lines. In the work, we used the COrDIS EXPERT 26 kit (Gordiz, Russia), validated for molecular genetic identification of personality based on multiplex PCR analysis of 26 highly polymorphic loci of human genomic deoxyribonucleic acid. PCR results were analyzed by capillary electrophoresis using an automatic genetic analyzer with laser-induced fluorescence detection (Applied Biosystems 3500xL).

Results. When testing the method, profiling of 37 cell lines was carried out, of which 18 were announced in international databases and 19 were unique, obtained at the N. N. Blokhin National Medical Research Center of Oncology, as well as a cell line mixture in order to determine the limits of contamination detection. The obtained results showed the correspondence of commercial cell lines with the data in international databases. Within the framework of this work, profiles of unique lines were obtained and the foundation of own genetic database was laid. Studies to identify the limit of contamination detection by another line have shown that even 4% of the contaminant culture in the total pool can be used to identify its individual alleles.

Conclusion. The results obtained indicate the possibility of using the method to identify samples of the collection and detect intraspecific contamination.

Recent Updates on the Significance of KRAS Mutations in Colorectal Cancer Biology

The most commonly mutated isoform of RAS among all cancer subtypes is KRAS. In this review, we focus on the special role of KRAS mutations in colorectal cancer (CRC), aiming to collect recent data on KRAS-driven enhanced cell signalling, in vitro and in vivo research models, and CRC development-related processes such as metastasis and cancer stem cell formation. We attempt to cover the diverse nature of the effects of KRAS mutations on age-related CRC development. As the incidence of CRC is rising in young adults, we have reviewed the driving forces of ageing-dependent CRC.

CCLA: an accurate method and web server for cancer cell line authentication using gene expression profiles

Cancer cell lines (CCLs) as important model systems play critical roles in cancer research. The misidentification and contamination of CCLs are serious problems, leading to unreliable results and waste of resources. Current methods for CCL authentication are mainly based on the CCL-specific genetic polymorphism, whereas no method is available for CCL authentication using gene expression profiles. Here, we developed a novel method and homonymic web server (CCLA, Cancer Cell Line Authentication, http://bioinfo.life.hust.edu.cn/web/CCLA/) to authenticate 1291 human CCLs of 28 tissues using gene expression profiles. CCLA showed an excellent speed advantage and high accuracy for CCL authentication, a top 1 accuracy of 96.58 or 92.15% (top 3 accuracy of 100 or 95.11%) for microarray or RNA-Seq validation data (719 samples, 461 CCLs), respectively. To the best of our knowledge, CCLA is the first approach to authenticate CCLs using gene expression data. Users can freely and conveniently authenticate CCLs using gene expression profiles or NCBI GEO accession on CCLA website.

Extensive rewiring of the EGFR network in colorectal cancer cells expressing transforming levels of KRASG13D

Protein-protein-interaction networks (PPINs) organize fundamental biological processes, but how oncogenic mutations impact these interactions and their functions at a network-level scale is poorly understood. Here, we analyze how a common oncogenic KRAS mutation (KRASG13D) affects PPIN structure and function of the Epidermal Growth Factor Receptor (EGFR) network in colorectal cancer (CRC) cells. Mapping >6000 PPIs shows that this network is extensively rewired in cells expressing transforming levels of KRASG13D (mtKRAS). The factors driving PPIN rewiring are multifactorial including changes in protein expression and phosphorylation. Mathematical modelling also suggests that the binding dynamics of low and high affinity KRAS interactors contribute to rewiring. PPIN rewiring substantially alters the composition of protein complexes, signal flow, transcriptional regulation, and cellular phenotype. These changes are validated by targeted and global experimental analysis. Importantly, genetic alterations in the most extensively rewired PPIN nodes occur frequently in CRC and are prognostic of poor patient outcomes.

Approaching RNA-seq for Cell Line Identification

Cancer cell lines serve as invaluable model systems for cancer biology research and help in evaluating the efficacy of new therapeutic agents. However, cell line contamination and misidentification have become one of the most pressing problems affecting biomedical research. Available methods of cell line authentication suffer from limited access, time-consuming and often costly for many researchers, hence a new and cost-effective approach for cell line authentication is needed. In this regard, we developed a new method called CeL-ID for cell line authentication using genomic variants as a byproduct derived from RNA-seq data. CeL-ID was trained and tested on publicly available more than 900 RNA-seq dataset derived from the Cancer Cell Line Encyclopedia (CCLE) project; including most frequently used adult and pediatric cancer cell lines. We generated cell line specific variant profiles from RNA-seq data using our in-house pipeline followed by pair-wise variant profile comparison between cell lines using allele frequencies and depth of coverage values of the entire variant set. Comparative analysis of variant profiles revealed that they differ significantly from cell line to cell line whereas identical, synonymous and derivative cell lines share high variant identity and their allelic fractions are highly correlated, which is the basis of this cell line authentication protocol. Additionally, CeL-ID also includes a method to estimate the possible cross-contamination using a linear mixture model with any possible CCLE cells in case no perfect match was detected.

seqCAT: a Bioconductor R-package for variant analysis of high throughput sequencing data

High throughput sequencing technologies are flourishing in the biological sciences, enabling unprecedented insights into e.g. genetic variation, but require extensive bioinformatic expertise for the analysis. There is thus a need for simple yet effective software that can analyse both existing and novel data, providing interpretable biological results with little bioinformatic prowess. We present seqCAT, a Bioconductor toolkit for analysing genetic variation in high throughput sequencing data. It is a highly accessible, easy-to-use and well-documented R-package that enables a wide range of researchers to analyse their own and publicly available data, providing biologically relevant conclusions and publication-ready figures. SeqCAT can provide information regarding genetic similarities between an arbitrary number of samples, validate specific variants as well as define functionally similar variant groups for further downstream analyses. Its ease of use, installation, complete data-to-conclusions functionality and the inherent flexibility of the R programming language make seqCAT a powerful tool for variant analyses compared to already existing solutions. A publicly available dataset of liver cancer-derived organoids is analysed herein using the seqCAT package, corroborating the original authors' conclusions that the organoids are genetically stable. A previously known liver cancer-related mutation is additionally shown to be present in a sample though it was not listed in the original publication. Differences between DNA- and RNA-based variant calls in this dataset are also analysed revealing a high median concordance of 97.5%. SeqCAT is an open source software under a MIT licence available at https://bioconductor.org/packages/release/bioc/html/seqCAT.html.

Single-cell RNA-seq variant analysis for exploration of genetic heterogeneity in cancer

Inter- and intra-tumour heterogeneity is caused by genetic and non-genetic factors, leading to severe clinical implications. High-throughput sequencing technologies provide unprecedented tools to analyse DNA and RNA in single cells and explore both genetic heterogeneity and phenotypic variation between cells in tissues and tumours. Simultaneous analysis of both DNA and RNA in the same cell is, however, still in its infancy. We have thus developed a method to extract and analyse information regarding genetic heterogeneity that affects cellular biology from single-cell RNA-seq data. The method enables both comparisons and clustering of cells based on genetic variation in single nucleotide variants, revealing cellular subpopulations corroborated by gene expression-based methods. Furthermore, the results show that lymph node metastases have lower levels of genetic heterogeneity compared to their original tumours with respect to variants affecting protein function. The analysis also revealed three previously unknown variants common across cancer cells in glioblastoma patients. These results demonstrate the power and versatility of scRNA-seq variant analysis and highlight it as a useful complement to already existing methods, enabling simultaneous investigations of both gene expression and genetic variation.

Transcriptional and metabolic rewiring of colorectal cancer cells expressing the oncogenic KRASG13D mutation

Background

Activating mutations in KRAS frequently occur in colorectal cancer (CRC) patients, leading to resistance to EGFR-targeted therapies.

Methods

To better understand the cellular reprogramming which occurs in mutant KRAS cells, we have undertaken a systems-level analysis of four CRC cell lines which express either wild type (wt) KRAS or the oncogenic KRAS^G13D allele (mtKRAS).

Results

RNAseq revealed that genes involved in ribosome biogenesis, mRNA translation and metabolism were significantly upregulated in mtKRAS cells. Consistent with the transcriptional data, protein synthesis and cell proliferation were significantly higher in the mtKRAS cells. Targeted metabolomics analysis also confirmed the metabolic reprogramming in mtKRAS cells. Interestingly, mtKRAS cells were highly transcriptionally responsive to EGFR activation by TGFα stimulation, which was associated with an unexpected downregulation of genes involved in a range of anabolic processes. While TGFα treatment strongly activated protein synthesis in wtKRAS cells, protein synthesis was not activated above basal levels in the TGFα-treated mtKRAS cells. This was likely due to the defective activation of the mTORC1 and other pathways by TGFα in mtKRAS cells, which was associated with impaired activation of PKB signalling and a transient induction of AMPK signalling.

Conclusions

We have found that mtKRAS cells are substantially rewired at the transcriptional, translational and metabolic levels and that this rewiring may reveal new vulnerabilities in oncogenic KRAS CRC cells that could be exploited in future.

Multi-omic measurements of heterogeneity in HeLa cells across laboratories

Reproducibility in research can be compromised by both biological and technical variation, but most of the focus is on removing the latter. Here we investigate the effects of biological variation in HeLa cell lines using a systems-wide approach. We determine the degree of molecular and phenotypic variability across 14 stock HeLa samples from 13 international laboratories. We cultured cells in uniform conditions and profiled genome-wide copy numbers, mRNAs, proteins and protein turnover rates in each cell line. We discovered substantial heterogeneity between HeLa variants, especially between lines of the CCL2 and Kyoto varieties, and observed progressive divergence within a specific cell line over 50 successive passages. Genomic variability has a complex, nonlinear effect on transcriptome, proteome and protein turnover profiles, and proteotype patterns explain the varying phenotypic response of different cell lines to Salmonella infection. These findings have implications for the interpretation and reproducibility of research results obtained from human cultured cells.

Subverted regulation of Nox1 NADPH oxidase-dependent oxidant generation by protein disulfide isomerase A1 in colon carcinoma cells with overactivated KRas

Protein disulfide isomerases including PDIA1 are implicated in cancer progression, but underlying mechanisms are unclear. PDIA1 is known to support vascular Nox1 NADPH oxidase expression/activation. Since deregulated reactive oxygen species (ROS) production underlies tumor growth, we proposed that PDIA1 is an upstream regulator of tumor-associated ROS. We focused on colorectal cancer (CRC) with distinct KRas activation levels. Analysis of RNAseq databanks and direct validation indicated enhanced PDIA1 expression in CRC with constitutive high (HCT116) vs. moderate (HKE3) and basal (Caco2) Ras activity. PDIA1 supported Nox1-dependent superoxide production in CRC; however, we first reported a dual effect correlated with Ras-level activity: in Caco2 and HKE3 cells, loss-of-function experiments indicate that PDIA1 sustains Nox1-dependent superoxide production, while in HCT116 cells PDIA1 restricted superoxide production, a behavior associated with increased Rac1 expression/activity. Transfection of Rac1G12V active mutant into HKE3 cells induced PDIA1 to become restrictive of Nox1-dependent superoxide, while in HCT116 cells treated with Rac1 inhibitor, PDIA1 became supportive of superoxide. PDIA1 silencing promoted diminished cell proliferation and migration in HKE3, not detectable in HCT116 cells. Screening of cell signaling routes affected by PDIA1 silencing highlighted GSK3β and Stat3. Also, E-cadherin expression after PDIA1 silencing was decreased in HCT116, consistent with PDIA1 support of epithelial-mesenchymal transition. Thus, Ras overactivation switches the pattern of PDIA1-dependent Rac1/Nox1 regulation, so that Ras-induced PDIA1 bypass can directly activate Rac1. PDIA1 may be a crucial regulator of redox-dependent adaptive processes related to cancer progression.

CeL-ID: cell line identification using RNA-seq data

BACKGROUND

Cell lines form the cornerstone of cell-based experimentation studies into understanding the underlying mechanisms of normal and disease biology including cancer. However, it is commonly acknowledged that contamination of cell lines is a prevalent problem affecting biomedical science and available methods for cell line authentication suffer from limited access as well as being too daunting and time-consuming for many researchers. Therefore, a new and cost effective approach for authentication and quality control of cell lines is needed.

RESULTS

We have developed a new RNA-seq based approach named CeL-ID for cell line authentication. CeL-ID uses RNA-seq data to identify variants and compare with variant profiles of other cell lines. RNA-seq data for 934 CCLE cell lines downloaded from NCI GDC were used to generate cell line specific variant profiles and pair-wise correlations were calculated using frequencies and depth of coverage values of all the variants. Comparative analysis of variant profiles revealed that variant profiles differ significantly from cell line to cell line whereas identical, synonymous and derivative cell lines share high variant identity and are highly correlated (ρ > 0.9). Our benchmarking studies revealed that CeL-ID method can identify a cell line with high accuracy and can be a valuable tool of cell line authentication in biomedical science. Finally, CeL-ID estimates the possible cross contamination using linear mixture model if no perfect match was detected.

CONCLUSIONS

In this study, we show the utility of an RNA-seq based approach for cell line authentication. Our comparative analysis of variant profiles derived from RNA-seq data revealed that variant profiles of each cell line are distinct and overall share low variant identity with other cell lines whereas identical or synonymous cell lines show significantly high variant identity and hence variant profiles can be used as a discriminatory/identifying feature in cell authentication model.

PDEδ inhibition impedes the proliferation and survival of human colorectal cancer cell lines harboring oncogenic KRas

Ras proteins, most notably KRas, are prevalent oncogenes in human cancer. Plasma membrane localization and thereby signaling of KRas is regulated by the prenyl‐binding protein PDEδ. Recently, we have reported the specific anti‐proliferative effects of PDEδ inhibition in KRas‐dependent human pancreatic ductal adenocarcinoma cell lines. Here, we investigated the proliferative dependence on the solubilizing activity of PDEδ of human colorectal cancer (CRC) cell lines with or without oncogenic KRas mutations. Our results show that genetic and pharmacologic interference with PDEδ specifically inhibits proliferation and survival of CRC cell lines harboring oncogenic KRas mutations whereas isogenic cell lines in which the KRas oncogene has been removed, or cell lines with oncogenic BRaf mutations or EGFR overexpression are not dependent on PDEδ. Pharmacological PDEδ inhibition is therefore a possible new avenue to target oncogenic KRas bearing CRC.

What's new?

Oncogenic KRas mutations are present in about 45% of colorectal cancers (CRCs), where they are associated with poor prognosis. While KRas is an appealing therapeutic target, it has repeatedly eluded small‐molecule inhibitors. Here, the authors chose instead to target PDEδ, a prenyl‐binding protein that regulates the plasma membrane localization of KRas. In experiments in human colorectal cancer cells, PDEδ inhibition limited proliferation and survival in cells harboring KRas mutations, with no effect on wild‐type KRas cells, providing a new therapeutiv opportunity for CRC harbouring oncogenic KRas. In addition, PDEδ protein expression was correlated with oncogenic KRas activity within the CRC cell panel, suggesting that PDEδ protein‐level determination may be of prognostic relevance for CRC patients.

Analysis of public RNA-sequencing data reveals biological consequences of genetic heterogeneity in cell line populations

Meta-analysis of datasets available in public repositories are used to gather and summarise experiments performed across laboratories, as well as to explore consistency of scientific findings. As data quality and biological equivalency across samples may obscure such analyses and consequently their conclusions, we investigated the comparability of 85 public RNA-seq cell line datasets. Thousands of pairwise comparisons of single nucleotide variants in 139 samples revealed variable genetic heterogeneity of the eight cell line populations analysed as well as variable data quality. The H9 and HCT116 cell lines were found to be remarkably stable across laboratories (with median concordances of 99.2% and 98.5%, respectively), in contrast to the highly variable HeLa cells (89.3%). We show that the genetic heterogeneity encountered greatly affects gene expression between same-cell comparisons, highlighting the importance of interrogating the biological equivalency of samples when comparing experimental datasets. Both the number of differentially expressed genes and the expression levels negatively correlate with the genetic heterogeneity. Finally, we demonstrate how comparing genetically heterogeneous datasets affect gene expression analyses and that high dissimilarity between same-cell datasets alters the expression of more than 300 cancer-related genes, which are often the focus of studies using cell lines.

Oncogenic KRAS suppresses store-operated Ca2+ entry and ICRAC through ERK pathway-dependent remodelling of STIM expression in colorectal cancer cell lines

The KRAS GTPase plays a fundamental role in transducing signals from plasma membrane growth factor receptors to downstream signalling pathways controlling cell proliferation, survival and migration. Activating KRAS mutations are found in 20% of all cancers and in up to 40% of colorectal cancers, where they contribute to dysregulation of cell processes underlying oncogenic transformation. Multiple KRAS-regulated cell functions are also influenced by changes in intracellular Ca2+ levels that are concurrently modified by receptor signalling pathways. Suppression of intracellular Ca2+ release mechanisms can confer a survival advantage in cancer cells, and changes in Ca2+ entry across the plasma membrane modulate cell migration and proliferation. However, inconsistent remodelling of Ca2+ influx and its signalling role has been reported in studies of transformed cells. To isolate the interaction between altered Ca2+ handling and mutated KRAS in colorectal cancer, we have previously employed isogenic cell line pairs, differing by the presence of an oncogenic KRAS allele (encoding KRASG13D), and have shown that reduced Ca2+ release from the ER and mitochondrial Ca2+ uptake contributes to the survival advantage conferred by oncogenic KRAS. Here we show in the same cell lines, that Store-Operated Ca2+ Entry (SOCE) and its underlying current, ICRAC are under the influence of KRASG13D. Specifically, deletion of the oncogenic KRAS allele resulted in enhanced STIM1 expression and greater Ca2+ influx. Consistent with the role of KRAS in the activation of the ERK pathway, MEK inhibition in cells with KRASG13D resulted in increased STIM1 expression. Further, ectopic expression of STIM1 in HCT 116 cells (which express KRASG13D) rescued SOCE, demonstrating a fundamental role of STIM1 in suppression of Ca2+ entry downstream of KRASG13D. These results add to the understanding of how ERK controls cancer cell physiology and highlight STIM1 as an important biomarker in cancerogenesis.

Transcriptome profiling of the interconnection of pathways involved in malignant transformation and response to hypoxia

In tumor tissues, hypoxia is a commonly observed feature resulting from rapidly proliferating cancer cells outgrowing their surrounding vasculature network. Transformed cancer cells are known to exhibit phenotypic alterations, enabling continuous proliferation despite a limited oxygen supply. The four-step isogenic BJ cell model enables studies of defined steps of tumorigenesis: the normal, immortalized, transformed, and metastasizing stages. By transcriptome profiling under atmospheric and moderate hypoxic (3% O₂) conditions, we observed that despite being highly similar, the four cell lines of the BJ model responded strikingly different to hypoxia. Besides corroborating many of the known responses to hypoxia, we demonstrate that the transcriptome adaptation to moderate hypoxia resembles the process of malignant transformation. The transformed cells displayed a distinct capability of metabolic switching, reflected in reversed gene expression patterns for several genes involved in oxidative phosphorylation and glycolytic pathways. By profiling the stage-specific responses to hypoxia, we identified ASS1 as a potential prognostic marker in hypoxic tumors. This study demonstrates the usefulness of the BJ cell model for highlighting the interconnection of pathways involved in malignant transformation and hypoxic response.