Maria P. Alcolea

A Single Progenitor Population Switches Behavior to Maintain and Repair Esophageal Epithelium

Epithelial Defense Force The nature of the cells that maintain and heal the epithelium lining the esophagus has been controversial. Doupé et al. (p. 1091, published online 19 July; see the Perspective by Kushner) show that, unlike many other tissues, mouse esophagus is devoid of slow cycling stem cells. Instead, the epithelium is maintained and repaired by a single population of proliferating cells that can switch rapidly from homeostatic behavior into “repair mode” in the vicinity of a wound. Dividing cells in the mouse esophagus contribute to wound healing without the need for quiescent stem cells. Diseases of the esophageal epithelium (EE), such as reflux esophagitis and cancer, are rising in incidence. Despite this, the cellular behaviors underlying EE homeostasis and repair remain controversial. Here, we show that in mice, EE is maintained by a single population of cells that divide stochastically to generate proliferating and differentiating daughters with equal probability. In response to challenge with all-trans retinoic acid (atRA), the balance of daughter cell fate is unaltered, but the rate of cell division increases. However, after wounding, cells reversibly switch to producing an excess of proliferating daughters until the wound has closed. Such fate-switching enables a single progenitor population to both maintain and repair tissue without the need for a “reserve” slow-cycling stem cell pool.

Application of Label-free Quantitative Peptidomics for the Identification of Urinary Biomarkers of Kidney Chronic Allograft Dysfunction

The advent of quantitative proteomics opens new opportunities in biomedical and clinical research. Although quantitative proteomics methods based on stable isotope labeling are in general preferred for biomolecular research, biomarker discovery is a case example of a biomedical problem that may be better addressed by using label-free MS techniques. As a proof of concept of this paradigm, we report the use of label-free quantitative LC-MS to profile the urinary peptidome of kidney chronic allograft dysfunction (CAD). The aim was to identify predictive biomarkers that could be used to personalize immunosuppressive therapies for kidney transplant patients. We detected (by LC-M/MS) and quantified (by LC-MS) 6000 polypeptide ions in undigested urine specimens across 39 CAD patients and 32 control individuals. Although unsupervised hierarchical clustering differentiated between the groups when including all the identified peptides, specific peptides derived from uromodulin and kininogen were found to be significantly more abundant in control than in CAD patients and correctly identified the two groups. These peptides are therefore potential biomarkers that might be used for the diagnosis of CAD. In addition, ions at m/z 645.59 and m/z 642.61 were able to differentiate between patients with different forms of CAD with specificities and sensitivities of 90% in a training set and, significantly, of ∼70% in an independent validation set of samples. Interestingly low expression of uromodulin at m/z 638.03 coupled with high expression of m/z 642.61 diagnosed CAD in virtually all cases. Multiple reaction monitoring experiments further validated the results, illustrating the power of our label-free quantitative LC-MS approach for obtaining quantitative profiles of urinary polypeptides in a rapid, comprehensive, and precise fashion and for biomarker discovery.

Differentiation imbalance in single oesophageal progenitor cells causes clonal immortalization and field change

Multiple cancers may arise from within a clonal region of preneoplastic epithelium, a phenomenon termed ‘field change’. However, it is not known how field change develops. Here we investigate this question using lineage tracing to track the behaviour of scattered single oesophageal epithelial progenitor cells expressing a mutation that inhibits the Notch signalling pathway. Notch is frequently subject to inactivating mutation in squamous cancers. Quantitative analysis reveals that cell divisions that produce two differentiated daughters are absent from mutant progenitors. As a result, mutant clones are no longer lost by differentiation and become functionally immortal. Furthermore, mutant cells promote the differentiation of neighbouring wild-type cells, which are then lost from the tissue. These effects lead to clonal expansion, with mutant cells eventually replacing the entire epithelium. Notch inhibition in progenitors carrying p53 stabilizing mutations creates large confluent regions of doubly mutant epithelium. Field change is thus a consequence of imbalanced differentiation in individual progenitor cells.

Phosphoproteomic Analysis of Leukemia Cells under Basal and Drug-treated Conditions Identifies Markers of Kinase Pathway Activation and Mechanisms of Resistance

Protein kinase signaling is fundamental to cell homeostasis and is deregulated in all cancers but varies between patients. Understanding the mechanisms underlying this heterogeneity is critical for personalized targeted therapies. Here, we used a recently established LC-MS/MS platform to profile protein phosphorylation in acute myeloid leukemia cell lines with different sensitivities to kinase inhibitors. The compounds used in this study were originally developed to target Janus kinase, phosphatidylinositol 3-kinase, and MEK. After further validation of the technique, we identified several phosphorylation sites that were inhibited by these compounds but whose intensities did not always correlate with growth inhibition sensitivity. In contrast, several hundred phosphorylation sites that correlated with sensitivity/resistance were not in general inhibited by the compounds. These results indicate that markers of pathway activity may not always be reliable indicators of sensitivity of cancer cells to inhibitors that target such pathways, because the activity of parallel kinases can contribute to resistance. By mining our data we identified protein kinase C isoforms as one of such parallel pathways being more active in resistant cells. Consistent with the view that several parallel kinase pathways were contributing to resistance, inhibitors that target protein kinase C, MEK, and Janus kinase potentiated each other in arresting the proliferation of multidrug-resistant cells. Untargeted/unbiased approaches, such as the one described here, to quantify the activity of the intended target kinase pathway in concert with the activities of parallel kinase pathways will be invaluable to personalize therapies based on kinase inhibitors.

Tracking cells in their native habitat: lineage tracing in epithelial neoplasia.

For tumours to develop, mutations must disrupt tissue homeostasis in favour of deregulated proliferation. Genetic lineage tracing has uncovered the behaviour of proliferating cells that underpins the maintenance of epithelial tissues and the barriers that are broken in neoplastic transformation. In this Review, we focus on new insights revealed by quantifying the behaviour of normal, preneoplastic and tumour cells in epithelia in transgenic mice and consider their potential importance in humans.

Phosphoproteomics data classify hematological cancer cell lines according to tumor type and sensitivity to kinase inhibitors

BackgroundTumor classification based on their predicted responses to kinase inhibitors is a major goal for advancing targeted personalized therapies. Here, we used a phosphoproteomic approach to investigate biological heterogeneity across hematological cancer cell lines including acute myeloid leukemia, lymphoma, and multiple myeloma.ResultsMass spectrometry was used to quantify 2,000 phosphorylation sites across three acute myeloid leukemia, three lymphoma, and three multiple myeloma cell lines in six biological replicates. The intensities of the phosphorylation sites grouped these cancer cell lines according to their tumor type. In addition, a phosphoproteomic analysis of seven acute myeloid leukemia cell lines revealed a battery of phosphorylation sites whose combined intensities correlated with the growth-inhibitory responses to three kinase inhibitors with remarkable correlation coefficients and fold changes (> 100 between the most resistant and sensitive cells). Modeling based on regression analysis indicated that a subset of phosphorylation sites could be used to predict response to the tested drugs. Quantitative analysis of phosphorylation motifs indicated that resistant and sensitive cells differed in their patterns of kinase activities, but, interestingly, phosphorylations correlating with responses were not on members of the pathway being targeted; instead, these mainly were on parallel kinase pathways.ConclusionThis study reveals that the information on kinase activation encoded in phosphoproteomics data correlates remarkably well with the phenotypic responses of cancer cells to compounds that target kinase signaling and could be useful for the identification of novel markers of resistance or sensitivity to drugs that target the signaling network.

Increased confidence in large-scale phosphoproteomics data by complementary mass spectrometric techniques and matching of phosphopeptide data sets.

Large-scale phosphoproteomics studies are of great interest due to their potential for the dissection of signaling pathways controlled by protein kinases. Recent advances in mass spectrometry (MS)-based phosphoproteomic techniques offer new opportunities to profile protein kinase activities in a comprehensive manner. However, this increasingly used approach still poses many analytical challenges. On one hand, high stringency criteria for phosphopeptide identification based on MS/MS data are needed in order to avoid false positives; however, on the other hand, these stringent criteria also result in the introduction of many false negatives. In the current report, we employ different mass spectrometric techniques for large-scale phosphoproteomics in order to reduce the presence of false negatives and enhance data confidence. A LTQ-Orbitrap LC-MS/MS platform identified approximately 3 times more phosphopeptides than Q-TOF LC-MS/MS instrumentation (4308 versus 1485 identifications, respectively). In both cases, collision induced dissociation (CID) was used to fragment peptides. Interestingly, the two platforms produced complementary data as many of the low scoring phosphopeptide ions identified by LTQ-Orbitrap MS/MS gave rise to high score identifications by Q-TOF MS/MS analysis, and vice versa. In fact, approximately 450 phosphopeptides identified by the Q-TOF instrument were not identified by the LTQ-Orbitrap. Further data comparison revealed the extent of the problem: in one experiment, the estimated number of false negatives (1066) was close to the number of identified phosphopeptides (1485). This work demonstrates that by using standard procedures for phosphopeptide identification the number of false negatives can be even greater than the number of false positives. We propose using historical phosphoproteomic data and spectral matching algorithms in order to efficiently minimize false negative rates.

Cell competition: Winning out by losing notch

Cell competition where ‘loser’ cells are eliminated by neighbors with higher fitness is a widespread phenomenon in development. However, a growing body of evidence argues cells with somatic mutations compete with their wild type counterparts in the earliest stages of cancer development. Recent studies have begun to shed light on the molecular and cellular mechanisms that alter the competitiveness of cells carrying somatic mutations in adult tissues. Cells with a ‘winner’ phenotype create clones which may expand into extensive fields of mutant cells within normal appearing epithelium, favoring the accumulation of further genetic alterations and the evolution of cancer. Here we focus on how mutations which disrupt the Notch signaling pathway confer a ‘super competitor’ status on cells in squamous epithelia and consider the broader implications for cancer evolution.

Acute sensitivity of the oral mucosa to oncogenic K-ras

Mouse models of cancer represent powerful tools for analysing the role of genetic alterations in carcinogenesis. Using a mouse model that allows tamoxifen‐inducible somatic activation (by Cre‐mediated recombination) of oncogenic K‐rasG12D in a wide range of tissues, we observed hyperplasia of squamous epithelium located in moist or frequently abraded mucosa, with the most dramatic effects in the oral mucosa. This epithelium showed a sequence of squamous hyperplasia followed by squamous papilloma with dysplasia, in which some areas progressed to early invasive squamous cell carcinoma, within 14 days of widespread oncogenic K‐ras activation. The marked proliferative response of the oral mucosa to K‐rasG12D was most evident in the basal layers of the squamous epithelium of the outer lip with hair follicles and wet mucosal surface, with these cells staining positively for pAKT and cyclin D1, showing Ras/AKT pathway activation and increased proliferation with Ki‐67 and EdU positivity. The stromal cells also showed gene activation by recombination and immunopositivity for pERK indicating K‐Ras/ERK pathway activation, but without Ki‐67 positivity or increase in stromal proliferation. The oral neoplasms showed changes in the expression pattern of cytokeratins (CK6 and CK13), similar to those observed in human oral tumours. Sporadic activation of the K‐rasG12D allele (due to background spontaneous recombination in occasional cells) resulted in the development of benign oral squamous papillomas only showing a mild degree of dysplasia with no invasion. In summary, we show that oral mucosa is acutely sensitive to oncogenic K‐ras, as widespread expression of activated K‐ras in the murine oral mucosal squamous epithelium and underlying stroma can drive the oral squamous papilloma–carcinoma sequence. Copyright

In-Depth Analysis of Protein Phosphorylation by Multidimensional Ion Exchange Chromatography and Mass Spectrometry

Protein phosphorylation controls fundamental biological functions that are often deregulated in disease. Therefore, system-level understanding of complex pathophysiological processes requires methods that can be used to profile and quantify protein phosphorylation as comprehensively as possible. Here we present a detailed protocol to enrich phosphopeptides from total cell lysates in a form amenable to downstream analysis by mass spectrometry. Using these techniques, we have detected several thousands of phosphorylation sites in the NIH-3T3 cell line.