Cancer screening with multicancer detection tests: A translational science review.

Multicancer detection (MCD) tests use a single, easily obtainable biospecimen, such as blood, to screen for more than one cancer concurrently. MCD tests can potentially be used to improve early cancer detection, including cancers that currently lack effective screening methods. However, these tests have unknown and unquantified benefits and harms. MCD tests differ from conventional cancer screening tests in that the organ responsible for a positive test is unknown, and a broad diagnostic workup may be necessary to confirm the location and type of underlying cancer. Among two prospective studies involving greater than 16,000 individuals, MCD tests identified those who had some cancers without currently recommended screening tests, including pancreas, ovary, liver, uterus, small intestine, oropharyngeal, bone, thyroid, and hematologic malignancies, at early stages. Reported MCD test sensitivities range from 27% to 95% but differ by organ and are lower for early stage cancers, for which treatment toxicity would be lowest and the potential for cure might be highest. False reassurance from a negative MCD result may reduce screening adherence, risking a loss in proven public health benefits from standard-of-care screening. Prospective clinical trials are needed to address uncertainties about MCD accuracy to detect different cancers in asymptomatic individuals, whether these tests can detect cancer sufficiently early for effective treatment and mortality reduction, the degree to which these tests may contribute to cancer overdiagnosis and overtreatment, whether MCD tests work equally well across all populations, and the appropriate diagnostic evaluation and follow-up for patients with a positive test.

Revisiting the standard blueprint for biomarker development to address emerging cancer early detection technologies.

Novel liquid biopsy technologies are creating a watershed moment in cancer early detection. Evidence supporting population screening is nascent, but a rush to market the new tests is prompting cancer early detection researchers to revisit the standard blueprint that the Early Detection Research Network established to evaluate novel screening biomarkers. In this commentary, we review the Early Detection Research Network's Phases of Biomarker Development (PBD) for rigorous evaluation of novel early detection biomarkers and discuss both hazards and opportunities involved in expedited evaluation. According to the PBD, for a biomarker-based test to be considered for population screening, 1) test sensitivity in a prospective screening setting must be adequate, 2) the shift to early curable stages must be meaningful, and 3) any stage shift must translate into clinically significant mortality benefit. In the past, determining mortality benefit has required lengthy randomized screening trials, but interest is growing in expedited trial designs with shorter-term endpoints. Whether and how best to use such endpoints in a manner that retains the rigor of the PBD remains to be determined. We discuss how computational disease modeling can be harnessed to learn about screening impact and meet the needs of the moment.

Study design considerations for trials to evaluate multicancer early detection assays for clinical utility.

Blood-based assays using various technologies and biomarkers are in commercial development for the purpose of detecting multiple cancer types concurrently at an early stage of disease. These multicancer early detection (MCED) assays have the potential to improve the detection of cancers, particularly those for which no current screening modality exists. However, the unknown clinical benefits and harms of using MCED assays for cancer screening necessitate the development and implementation of a randomized controlled trial (RCT) to ascertain their clinical effectiveness. This was the consensus of experts at a National Cancer Institute-hosted workshop to discuss initial design concepts for such a trial. Using these assays to screen simultaneously for multiple cancers poses novel uncertainties for patient care compared with conventional screening tests for single cancers, such as establishing the diagnostic workup to confirm the presence of cancer at any organ site; clarifying appropriate follow-up for a positive assay for which there is no definitive diagnosis; identifying potential harms such as overdiagnosis of indolent disease; determining clinically effective and efficient strategies for disseminating MCED screening in real-world practice; and understanding the ethical implications, such as potentially alleviating or exacerbating existing health disparities. These assays present new and complex challenges for designing an RCT. Issues that emerged from the meeting centered around the need for a flexibly designed, clinical utility RCT to rigorously capture the evidence required to fully understand the net benefit of this promising technology. Specific topic areas were endpoints, screening protocols, recruitment, diagnostic pathway, pilot phase, data elements, specimen collection, and ethical considerations.

Synthetic biomarkers: a twenty-first century path to early cancer detection.

Detection of cancer at an early stage when it is still localized improves patient response to medical interventions for most cancer types. The success of screening tools such as cervical cytology to reduce mortality has spurred significant interest in new methods for early detection (for example, using non-invasive blood-based or biofluid-based biomarkers). Yet biomarkers shed from early lesions are limited by fundamental biological and mass transport barriers - such as short circulation times and blood dilution - that limit early detection. To address this issue, synthetic biomarkers are being developed. These represent an emerging class of diagnostics that deploy bioengineered sensors inside the body to query early-stage tumours and amplify disease signals to levels that could potentially exceed those of shed biomarkers. These strategies leverage design principles and advances from chemistry, synthetic biology and cell engineering. In this Review, we discuss the rationale for development of biofluid-based synthetic biomarkers. We examine how these strategies harness dysregulated features of tumours to amplify detection signals, use tumour-selective activation to increase specificity and leverage natural processing of bodily fluids (for example, blood, urine and proximal fluids) for easy detection. Finally, we highlight the challenges that exist for preclinical development and clinical translation of synthetic biomarker diagnostics.

Cancer Biomarkers and Big Data: A Planetary Science Approach.

Cancer biomarker research has become a data-intensive discipline requiring innovative approaches for data analysis that can combine traditional and data-driven methods. Significant leveraging can be done transferring methodologies and capabilities across scientific disciplines, such as planetary science and astronomy, each of which are grappling with and developing similar solutions for the analysis of massive scientific data.

Association Between Benign Breast Disease in African American and White American Women and Subsequent Triple-Negative Breast Cancer.

IMPORTANCE: Compared with white American (WA) women, African American (AA) women have a 2-fold higher incidence of breast cancers that are negative for estrogen receptor, progesterone receptor, and ERBB2 (triple-negative breast cancer [TNBC]). Triple-negative breast cancer, compared with non-TNBC, likely arises from different pathogenetic pathways, and benign breast disease (BBD) predicts future non-TNBC. OBJECTIVE: To determine whether AA identity remains associated with TNBC for women with a prior diagnosis of BBD. DESIGN, SETTING, AND PARTICIPANTS: This study is a retrospective analysis of data of a cohort of 2588 AA and 3566 WA women aged between 40 and 70 years with a biopsy-proven BBD diagnosis. The data-obtained from the Pathology Information System of Henry Ford Health System (HFHS), an integrated multihospital and multispecialty health care system headquartered in Detroit, Michigan-include specimens of biopsies performed between January 1, 1994, and December 31, 2005. Data analysis was performed from November 1, 2015, to June 15, 2016. MAIN OUTCOMES AND MEASURES: Subsequent breast cancer was stratified on the basis of combinations of hormone receptor and ERBB2 expression. RESULTS: Case management, follow-up, and outcomes received or obtained by our cohort of 2588 AA and 3566 WA patients were similar, demonstrating that HFHS delivered care equitably. Subsequent breast cancers developed in 103 (4.1%) of AA patients (mean follow-up interval of 6.8 years) and 143 (4.0%) of WA patients (mean follow-up interval of 6.1 years). More than three-quarters of subsequent breast cancers in each subset were ductal carcinoma in situ or stage I. The 10-year probability estimate for developing TNBC was 0.56% (95% CI, 0.32%-1.0%) for AA patients and 0.25% (95% CI, 0.12%-0.53%) for WA patients. Among the 66 AA patients who developed subsequent invasive breast cancer, 16 (24.2%) developed TNBC compared with 7 (7.4%) of the 94 WA patients who developed subsequent invasive breast cancers and had complete biomarker data (P = .01). CONCLUSIONS AND RELEVANCE: This study is the largest analysis to date of TNBC in the context of racial/ethnic identity and BBD as risk factors. The study found that AA identity persisted as a significant risk factor for TNBC. This finding suggests that AA identity is associated with inherent susceptibility for TNBC pathogenetic pathways.

Construction and analysis of the NCI-EDRN breast cancer reference set for circulating markers of disease.

BACKGROUND: Many circulating biomarkers have been reported for the diagnosis of breast cancer, but few, if any, have undergone rigorous credentialing using prospective cohorts and blinded evaluation. METHODS: The NCI Early Detection Research Network (EDRN) has created a prospective, multicenter collection of plasma and serum samples from 832 subjects designed to evaluate circulating biomarkers for the detection and diagnosis of breast cancer. These samples are available to investigators who wish to evaluate their biomarkers using a set of blinded samples. The breast cancer reference set is composed of blood samples collected using a standard operating procedure at four U.S. medical centers from 2008 to 2010 from women undergoing either tissue diagnosis for breast cancer or routine screening mammography. The reference set contains samples from women with incident invasive cancer (n = 190), carcinoma in situ (n = 55), benign pathology with atypia (n = 63), benign disease with no atypia (n = 231), and women with no evidence of breast disease by screening mammography (BI-RADS 1 or 2, n = 276). Using a subset of plasma samples (n = 505) from the reference set, we analyzed 90 proteins by multiplexed immunoassays for their potential utility as diagnostic markers. RESULTS: We found that none of these markers is useful for distinguishing cancer from benign controls. However, elevated CA-125 does appear to be a candidate marker for estrogen receptor-negative cancers. CONCLUSIONS: Markers that can distinguish benign breast conditions from invasive cancer have not yet been found. IMPACT: Availability of prospectively collected samples should improve future validation efforts.

The Early Detection Research Network's Specimen reference sets: paving the way for rapid evaluation of potential biomarkers.

BACKGROUND: The mission of the National Cancer Institute's Early Detection Research Network (EDRN) is to identify and validate cancer biomarkers for clinical use. Since its inception, EDRN investigators have learned a great deal about the process of validating biomarkers for clinical use. Translational research requires a broad spectrum of research expertise, and coordinating collaborative activities can be challenging. The EDRN has developed a robust triage and validation system that serves the roles of both "facilitator" and "brake." CONTENT: The system consists of (a) establishing a reference set of specimens collected under PRoBE (Prospective Specimen Collection Retrospective Blinded Evaluation) design criteria; (b) using the reference set to prevalidate candidate biomarkers before committing to full-scale validation; (c) performing full-scale validation for those markers that pass prevalidation testing; and (d) ensuring that the reference set is sufficiently large in numbers and volumes of sample that it can also be used to study future candidate biomarkers. This system provides rigorous and efficient evaluation of candidate biomarkers and biomarker panels. Reference sets should also be constructed to enable high-quality biomarker-discovery research. SUMMARY: We describe the process of establishing our system in the hope that it will serve as an example of how to validate biomarkers for clinical application. We also hope that this description of the biospecimen reference sets available from the EDRN will encourage the biomarker research community--from academia or industry--to use this resource to advance biomarkers into clinical use.

Ovarian cancer biomarker performance in prostate, lung, colorectal, and ovarian cancer screening trial specimens.

Establishing a cancer screening biomarker's intended performance requires "phase III" specimens obtained in asymptomatic individuals before clinical diagnosis rather than "phase II" specimens obtained from symptomatic individuals at diagnosis. We used specimens from the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial to evaluate ovarian cancer biomarkers previously assessed in phase II sets. Phase II specimens from 180 ovarian cancer cases and 660 benign disease or general population controls were assembled from four Early Detection Research Network or Ovarian Cancer Specialized Program of Research Excellence sites and used to rank 49 biomarkers. Thirty-five markers, including 6 additional markers from a fifth site, were then evaluated in PLCO proximate specimens from 118 women with ovarian cancer and 474 matched controls. Top markers in phase II specimens included CA125, HE4, transthyretin, CA15.3, and CA72.4 with sensitivity at 95% specificity ranging from 0.73 to 0.40. Except for transthyretin, these markers had similar or better sensitivity when moving to phase III specimens that had been drawn within 6 months of the clinical diagnosis. Performance of all markers declined in phase III specimens more remote than 6 months from diagnosis. Despite many promising new markers for ovarian cancer, CA125 remains the single-best biomarker in the phase II and phase III specimens tested in this study.

A framework for evaluating biomarkers for early detection: validation of biomarker panels for ovarian cancer.

A panel of biomarkers may improve predictive performance over individual markers. Although many biomarker panels have been described for ovarian cancer, few studies used prediagnostic samples to assess the potential of the panels for early detection. We conducted a multisite systematic evaluation of biomarker panels using prediagnostic serum samples from the Prostate, Lung, Colorectal, and Ovarian Cancer (PLCO) screening trial. Using a nested case-control design, levels of 28 biomarkers were measured laboratory-blinded in 118 serum samples obtained before cancer diagnosis and 951 serum samples from matched controls. Five predictive models, each containing 6 to 8 biomarkers, were evaluated according to a predetermined analysis plan. Three sequential analyses were conducted: blinded validation of previously established models (step 1); simultaneous split-sample discovery and validation of models (step 2); and exploratory discovery of new models (step 3). Sensitivity, specificity, sensitivity at 98% specificity, and AUC were computed for the models and CA125 alone among 67 cases diagnosed within one year of blood draw and 476 matched controls. In step 1, one model showed comparable performance to CA125, with sensitivity, specificity, and AUC at 69.2%, 96.6%, and 0.892, respectively. Remaining models had poorer performance than CA125 alone. In step 2, we observed a similar pattern. In step 3, a model derived from all 28 markers failed to show improvement over CA125. Thus, biomarker panels discovered in diagnostic samples may not validate in prediagnostic samples; utilizing prediagnostic samples for discovery may be helpful in developing validated early detection panels.

Characterization of a carcinogenesis rat model of ovarian preneoplasia and neoplasia.

Animal models of ovarian cancer are crucial for understanding the pathogenesis of the disease and for testing new treatment strategies. A model of ovarian carcinogenesis in the rat was modified and improved to yield ovarian preneoplastic and neoplastic lesions that pathogenetically resemble human ovarian cancer. A significantly lower dose (2 to 5 mug per ovary) of 7,12-dimethylbenz(a)anthracene (DMBA) was applied to the one ovary to maximally preserve its structural integrity. DMBA-induced mutagenesis was additionally combined with repetitive gonadotropin hormone stimulation to induce multiple cycles of active proliferation of the ovarian surface epithelium. Animals were treated in three arms of different doses of DMBA alone or followed by hormone administration. Comparison of the DMBA-treated ovaries with the contralateral control organs revealed the presence of epithelial cell origin lesions at morphologically distinct stages of preneoplasia and neoplasia. Their histopathology and path of dissemination to other organs are very similar to human ovarian cancer. Hormone cotreatment led to an increased lesion severity, indicating that gonadotropins may promote ovarian cancer progression. Point mutations in the Tp53 and Ki-Ras genes were detected that are also characteristic of human ovarian carcinomas. Additionally, an overexpression of estrogen and progesterone receptors was observed in preneoplastic and early neoplastic lesions, suggesting a role of these receptors in ovarian cancer development. These data indicate that this DMBA animal model gives rise to ovarian lesions that closely resemble human ovarian cancer and it is adequate for additional studies on the mechanisms of the disease and its clinical management.

Use of RNA amplification in the optimal characterization of global gene expression using cDNA microarrays.

Microarray analysis of human tissue is frequently hindered by the limited amount of RNA available. Although amplification protocols can be utilized, the relative representation of transcripts present in the starting material must remain unaltered. In this study, 200 ng of total RNA derived from cultured renal epithelial cells from tuberous sclerosis complex (TSC) carriers and control individuals was amplified by in vitro transcription with T7 RNA polymerase. The resulting Cy-labeled cDNAs (from total or amplified RNA (aRNA)) were analyzed as direct replicates and dye-flips on slides containing 10,000 human cDNAs. The Pearson correlation coefficients for the direct replicate experiments were 0.80 (20 microg total RNA), 0.85 (40 microg total RNA), and 0.93 (2 microg of aRNA). Comparisons between the array data revealed that the majority of genes expressed in total RNA (97% for 20 microg and 85% for 40 microg) were also detected in aRNA. The correlation coefficient of the expression ratios for genes detected in both total RNA (40 microg) and aRNA was 0.63. Further, Student's t-test indicated no significant difference (P = 0.83) between these ratios. These results indicate that the number of expressed genes detected with total RNA is proportional to the amount of RNA used and underscore the requirement of large amounts of total RNA for a comprehensive characterization of gene expression profiles. RNA amplification allows the detection of a large number of genes expressed in the starting RNA population without altering their relative intensities significantly. Thus, an RNA amplification step improves the quality of gene expression results obtained by microarray analysis. This study indicates that high quality microarray data can be generated from small amounts of RNA, including those extracted from limiting clinical samples and microdissected histological specimens.

Optimized procedures for microarray analysis of histological specimens processed by laser capture microdissection.

Analysis of cell-specific gene expression patterns using microarrays can reveal genes that are differentially expressed in diseased and normal tissue, as well as identify genes associated with specialized cellular functions. However, the cellular heterogeneity of the tissues precludes the resolution of expression profiles of specific cell types. While laser capture microdissection (LCM) can be used to obtain purified cell populations, the limited quantity of RNA isolated makes it necessary to perform an RNA amplification step prior to microarray analysis. The linearity and reproducibility of two RNA amplification protocols--the Baugh protocol (Baugh et al., 2001, Nucleic Acids Res 29:E29) and an in-house protocol have been assessed by conducting microarray analyses. Cy3-labeled total RNA from the colorectal cell line Colo-205 was compared to Cy5-labeled Colo-205 amplified RNA (aRNA) generated with each of the two protocols, using a human 10K cDNA array. The correlation of the gene intensities between amplified and total RNA measured in the two channels of each microarray was 0.72 and 0.61 for the Baugh protocol and the in-house protocol, respectively. The two protocols were further evaluated using aRNA obtained from normal colonic crypt cross-sections isolated via LCM. In both cases a microarray profile representative of colonic mucosa was obtained; statistically, the Baugh protocol was superior. Furthermore, a substantial overlap between highly expressed genes in the Colo-205 cells and colonic crypts underscores the reliability of the microarray analysis of LCM-derived material. Taken together, these results demonstrate that LCM-derived tissue from histological specimens can generate abundant amounts of high-quality aRNA for subsequent microarray analysis.

A novel approach for increasing sensitivity and correcting saturation artifacts of radioactively labeled cDNA arrays.

MOTIVATION: The radioactivity labeled DNA array platform is a robust and accurate way for a high-throughput measurement of gene expression levels in biological samples. Despite its high degree of sensitivity and reproducibility, this platform has several sources of variation. These are related to the presence of saturation effects in the array images and impede the degree of accuracy at which gene expression levels are determined. RESULTS: Here we describe a simple, but effective, approach for combining expression data from a series of autoradiographic exposures of variable length. This technique increases the sensitivity of this array platform by detecting low-expressed genes at longer exposures. It also improves the measurement accuracy of highly abundant genes by considering only values from the linear portion of dependency between the exposure times and gene intensities. As a result, the described approach improves the outcome of the subsequent steps of array data normalization and mining.

Normalization of single-channel DNA array data by principal component analysis.

MOTIVATION: Detailed comparison and analysis of the output of DNA gene expression arrays from multiple samples require global normalization of the measured individual gene intensities from the different hybridizations. This is needed for accounting for variations in array preparation and sample hybridization conditions. RESULTS: Here, we present a simple, robust and accurate procedure for the global normalization of datasets generated with single-channel DNA arrays based on principal component analysis. The procedure makes minimal assumptions about the data and performs well in cases where other standard procedures produced biased estimates. It is also insensitive to data transformation, filtering (thresholding) and pre-screening.

Gonadotropin and steroid hormones stimulate proliferation of the rat ovarian surface epithelium.

The ovarian surface epithelium (OSE) is a single layer of flattened or cuboidal cells covering the ovary. Ninety percent of all human ovarian malignancies arise from this layer of cells. Incessant ovulation, hyperovulation induced by infertility treatment, and hormone replacement therapy have been suggested as risk factors for ovarian cancer. In this study, two groups of rats, with and without surgically induced injury to the ovary, were treated with 17beta-estradiol, pregnant mare's serum gonadotropin (PMSG), human chorionic gonadotropin (hCG), or the combination PMSG/hCG, and the proliferative response of the OSE cells was measured using bromodeoxyuridne (BrdU) and (3)H-thymidine. All hormones, alone or in combination with ovarian surgery, were found to increase significantly the rate of proliferation of the rat OSE. These data demonstrate that hormones associated with infertility treatments and hormone replacement therapy, as well as injury- or ovulation-induced rupture of the ovarian surface, stimulate the rat OSE, and hence could have a role in the development of ovarian cancer via proliferation-associated mutagenesis, or alternatively, by promoting the rapid selection of OSE cells with accumulated mutations.

Identification of epidermal growth factor-responsive genes in normal rat ovarian surface epithelial cells.

Alteration in epidermal growth factor receptor (EGFR) family signaling is among the most frequently implicated effectors of human oncogenesis. Overexpression of members of this family of receptors has often been detected in many epithelial tumors and is believed to be associated with an overall poor prognosis in patients with cancer. Therefore, we hypothesized that identification of potential EGF target genes in normal cells will provide a basis for unbiased genetic analysis of this signaling pathway in cancer. We utilized Atlas Rat 1.2 nylon cDNA arrays (Clontech) to determine gene expression changes in normal rat ovarian surface epithelial (ROSE) cells following EGF treatment. The results indicate activation of genes involved in a wide variety of cellular mechanisms, including regulation of cell cycle and proliferation, apoptosis, and protein turnover. In addition, using an in vitro model of ovarian cancer, we demonstrated that malignant transformation of ROSE cells resulted in alteration of downstream effectors of the EGFR pathway, as exemplified by aberrant expression of p66Shc, c-Jun, c-Myc, c-Fos, Lot1, p21Cip/Waf, and cdc25A. These data suggest that knowledge of the downstream genetic lesions, which may result in loss of growth factor requirement of the affected cells, will be crucial for the selection of the EGFR pathway as an effective target for cancer therapy.

Molecular events associated with dysplastic morphologic transformation and initiation of ovarian tumorigenicity.

BACKGROUND: Disabled-2 (Dab2), a candidate tumor suppressor of ovarian carcinoma, frequently (around 80%) loses its expression in ovarian tumors. Expression of exogenous Dab2 in tumor cell lines negatively regulates growth and suppresses the downstream signal of the Ras/mitogen activated protein kinase mitogenic pathway. The inactivation of Dab2 is believed to be an early event in ovarian tumorigenicity. METHODS: The authors analyzed the correlation among expression of Dab2, presence of basement membrane (collagen IV and laminin), morphologic alteration of the surface epithelial cells, and expression of the mitotic index marker Mib-1 in 50 archived ovarian tumors by an immunohistochemical approach. The stainings of Dab2, Mib-1, collagen IV, and laminin in premalignant lesions bordering both normal and neoplastic ovarian surface epithelium from adjacent slides were analyzed in 50 ovarian tumors. RESULTS: In these 50 ovarian tumors, the percentage of Mib-1 positive tumor cells distributed in a wide range, from 1% to 75%, and there has no strong correlation with the expression of Dab2. However, in the premalignant regions bordering tumor and normal ovarian surface epithelium, the loss of Dab2 expression closely correlated with the dysplastic morphologic transition and Mib-1 expression of the ovarian surface epithelial cells. In 20 foci in 12 out of the 50 tumors, a transition from normal to neoplastic morphology within a contiguous epithelium was observed, and in all cases the morphologic change correlated with the loss of Dab2 staining. In addition, the collagen and laminin staining of the basement membrane were absent or weakened in pre-malignant epithelium prior to loss of Dab2 expression in all these 20 cases. Nevertheless, collagen IV and laminin were detectable in established adenomas on the same tumor slides. CONCLUSIONS: The loss of Dab2 is closely associated with the transition of ovarian surface epithelial cells to premalignant states and is likely involved in the initiation of ovarian tumorigenicity. Transient loss of collagen IV and laminin in the basement membrane of the premalignant epithelium and subsequent inactivation of Dab2 are common early events associated with tumorigenicity of the ovarian surface epithelium.

Dissection of HEF1-dependent functions in motility and transcriptional regulation.

Cas-family proteins have been implicated as signaling intermediaries in diverse processes including cellular attachment, motility, growth factor response, apoptosis and oncogenic transformation. The three defined Cas-family members (p130Cas, HEF1/Cas-L and Efs/Sin) are subject to multiple forms of regulation (including cell-cycle- and cell-attachment-mediated post-translational modification and cleavage) that complicate elucidation of the function of specific Cas proteins in defined biological processes. To explore the biological role of HEF1 further, we have developed a series of cell lines in which HEF1 production is regulated by an inducible promoter. In this system, HEF1 production rapidly induces changes in cellular morphology and motility, enhancing cell speed and haptotaxis towards fibronectin in a process partially dependent on intact ERK and p38 MAPK signaling pathways. Finally, cDNA expression array analysis and subsequent studies indicate that HEF1 production increases levels of mRNA transcripts encoding proteins that are associated with motility, cell transformation and invasiveness, including several metalloproteinases, MLCK, p160ROCK and ErbB2. Upregulation of such proteins suggests mechanisms through which misregulation of HEF1 may be involved in cancer progression.