Single-cell genetic analysis reveals insights into clonal development of prostate cancers and indicates loss of PTEN as a marker of poor prognosis

Single-cell resolved ploidy and chromosomal aberrations in nonalcoholic steatohepatitis-(NASH) induced hepatocellular carcinoma and its precursor lesions

Nonalcoholic steatohepatitis (NASH)-induced hepatocellular carcinoma (HCC) and its precursor, nonalcoholic fatty liver disease (NAFLD) are an unmet health issue due to widespread obesity. We assessed copy number changes of genes associated with hepatocarcinogenesis and oxidative pathways at a single-cell level. Eleven patients with NASH-HCC and 11 patients with NAFLD were included. Eight probes were analyzed using multiplex interphase fluorescence in situ hybridization (miFISH), single-cell imaging and phylogenetic tree modelling: Telomerase reverse transcriptase (TERT), C-Myc (MYC), hepatocyte growth factor receptor tyrosine kinase (MET), tumor protein 53 (TP53), cyclin D1 (CCND1), human epidermal growth factor receptor 2 (HER2), the fragile histidine triad gene (FHIT) and FRA16D oxidoreductase (WWOX). Each NASH-HCC tumor had up to 14 distinct clonal signal patterns indicating multiclonality, which correlated with high tumor grade. Changes frequently observed were TP53 losses, 45%; MYC gains, 36%; WWOX losses, 36%; and HER2 gains, 18%. Whole-genome duplications were frequent (82%) with aberrant tetraploid cells evolving from diploid ancestors. Non-tumorous NAFLD/NASH biopsies did not harbor clonal copy number changes. Fine mapping of NASH-HCC using single-cell multiplex FISH shows that branched tumor evolution involves genome duplication and that multiclonality increases with tumor grade. The loss of oxidoreductase WWOX and HER2 gains could be potentially associated with NASH-induced hepatocellular carcinoma.

Tumor heterogeneity assessed by sequencing and fluorescence in situ hybridization (FISH) data

MOTIVATION

Computational reconstruction of clonal evolution in cancers has become a crucial tool for understanding how tumors initiate and progress and how this process varies across patients. The field still struggles, however, with special challenges of applying phylogenetic methods to cancers, such as the prevalence and importance of copy number alteration (CNA) and structural variation (SV) events in tumor evolution, which are difficult to profile accurately by prevailing sequencing methods in such a way that subsequent reconstruction by phylogenetic inference algorithms is accurate.

RESULTS

In the present work, we develop computational methods to combine sequencing with multiplex interphase fluorescence in situ hybridization (miFISH) to exploit the complementary advantages of each technology in inferring accurate models of clonal CNA evolution accounting for both focal changes and aneuploidy at whole-genome scales. By integrating such information in an integer linear programming (ILP) framework, we demonstrate on simulated data that incorporation of FISH data substantially improves accurate inference of focal CNA and ploidy changes in clonal evolution from deconvolving bulk sequence data. Analysis of real glioblastoma data for which FISH, bulk sequence, and single cell sequence are all available confirms the power of FISH to enhance accurate reconstruction of clonal copy number evolution in conjunction with bulk and optionally single-cell sequence data.

AVAILABILITY

Source code is available on Github at https://github.com/CMUSchwartzLab/FISH_deconvolution.

Involvement of the MEN1 Gene in Hormone-Related Cancers: Clues from Molecular Studies, Mouse Models, and Patient Investigations

MEN1 mutation predisposes patients to multiple endocrine neoplasia type 1 (MEN1), a genetic syndrome associated with the predominant co-occurrence of endocrine tumors. Intriguingly, recent evidence has suggested that MEN1 could also be involved in the development of breast and prostate cancers, two major hormone-related cancers. The first clues as to its possible role arose from the identification of the physical and functional interactions between the menin protein, encoded by MEN1, and estrogen receptor α and androgen receptor. In parallel, our team observed that aged heterozygous Men1 mutant mice developed cancerous lesions in mammary glands of female and in the prostate of male mutant mice at low frequencies, in addition to endocrine tumors. Finally, observations made both in MEN1 patients and in sporadic breast and prostate cancers further confirmed the role played by menin in these two cancers. In this review, we present the currently available data concerning the complex and multifaceted involvement of MEN1 in these two types of hormone-dependent cancers.

Genetic alterations in the 3q26.31-32 locus confer an aggressive prostate cancer phenotype

Large-scale genetic aberrations that underpin prostate cancer development and progression, such as copy-number alterations (CNAs), have been described but the consequences of specific changes in many identified loci is limited. Germline SNPs in the 3q26.31 locus are associated with aggressive prostate cancer, and is the location of NAALADL2, a gene overexpressed in aggressive disease. The closest gene to NAALADL2 is TBL1XR1, which is implicated in tumour development and progression. Using publicly-available cancer genomic data we report that NAALADL2 and TBL1XR1 gains/amplifications are more prevalent in aggressive sub-types of prostate cancer when compared to primary cohorts. In primary disease, gains/amplifications occurred in 15.99% (95% CI: 13.02–18.95) and 14.96% (95% CI: 12.08–17.84%) for NAALADL2 and TBL1XR1 respectively, increasing in frequency in higher Gleason grade and stage tumours. Gains/amplifications result in transcriptional changes and the development of a pro-proliferative and aggressive phenotype. These results support a pivotal role for copy-number gains in this genetic region.

Benjamin Simpson et al. use publicly available cancer genomic data to investigate copy number changes at the 3q26.31–32 locus, which has been associated with aggressive prostate cancer based on single-nucleotide polymorphisms. They find that gains of NAALADL2 and TBL1XR1 in this locus are associated with more aggressive subtypes of prostate cancer and the transcription of pro-proliferative signalling processes.

High Levels of Chromosomal Copy Number Alterations and TP53 Mutations Correlate with Poor Outcome in Younger Breast Cancer Patients

Prognosis in young patients with breast cancer is generally poor, yet considerable differences in clinical outcomes between individual patients exist. To understand the genetic basis of the disparate clinical courses, tumors were collected from 34 younger women, 17 with good and 17 with poor outcomes, as determined by disease-specific survival during a follow-up period of 17 years. The clinicopathologic parameters of the tumors were complemented with DNA image cytometry profiles, enumeration of copy numbers of eight breast cancer genes by multicolor fluorescence in situ hybridization, and targeted sequence analysis of 563 cancer genes. Both groups included diploid and aneuploid tumors. The degree of intratumor heterogeneity was significantly higher in aneuploid versus diploid cases, and so were gains of the oncogenes MYC and ZNF217. Significantly more copy number alterations were observed in the group with poor outcome. Almost all tumors in the group with long survival were classified as luminal A, whereas triple-negative tumors predominantly occurred in the short survival group. Mutations in PIK3CA were more common in the group with good outcome, whereas TP53 mutations were more frequent in patients with poor outcomes. This study shows that TP53 mutations and the extent of genomic imbalances are associated with poor outcome in younger breast cancer patients and thus emphasize the central role of genomic instability vis-a-vis tumor aggressiveness.

Cellular and Molecular Mechanisms Underlying Prostate Cancer Development: Therapeutic Implications

Prostate cancer is the most frequent nonskin cancer and second most common cause of cancer-related deaths in man. Prostate cancer is a clinically heterogeneous disease with many patients exhibiting an aggressive disease with progression, metastasis, and other patients showing an indolent disease with low tendency to progression. Three stages of development of human prostate tumors have been identified: intraepithelial neoplasia, adenocarcinoma androgen-dependent, and adenocarcinoma androgen-independent or castration-resistant. Advances in molecular technologies have provided a very rapid progress in our understanding of the genomic events responsible for the initial development and progression of prostate cancer. These studies have shown that prostate cancer genome displays a relatively low mutation rate compared with other cancers and few chromosomal loss or gains. The ensemble of these molecular studies has led to suggest the existence of two main molecular groups of prostate cancers: one characterized by the presence of ERG rearrangements (~50% of prostate cancers harbor recurrent gene fusions involving ETS transcription factors, fusing the 5' untranslated region of the androgen-regulated gene TMPRSS2 to nearly the coding sequence of the ETS family transcription factor ERG) and features of chemoplexy (complex gene rearrangements developing from a coordinated and simultaneous molecular event), and a second one characterized by the absence of ERG rearrangements and by the frequent mutations in the E3 ubiquitin ligase adapter SPOP and/or deletion of CDH1, a chromatin remodeling factor, and interchromosomal rearrangements and SPOP mutations are early events during prostate cancer development. During disease progression, genomic and epigenomic abnormalities accrued and converged on prostate cancer pathways, leading to a highly heterogeneous transcriptomic landscape, characterized by a hyperactive androgen receptor signaling axis.

Single-cell genetic analysis of clonal dynamics in colorectal adenomas indicates CDX2 gain as a predictor of recurrence

Colorectal adenomas are common precancerous lesions with the potential for malignant transformation to colorectal adenocarcinoma. Endoscopic polypectomy provides an opportunity for cancer prevention; however, recurrence rates are high. We collected formalin-fixed paraffin-embedded tissue of 15 primary adenomas with recurrence, 15 adenomas without recurrence, and 14 matched pair samples (primary adenoma and the corresponding recurrent adenoma). The samples were analysed by array-comparative genomic hybridisation (aCGH) and single-cell multiplex interphase fluorescence in situ hybridisation (miFISH) to understand clonal evolution, to examine the dynamics of copy number alterations (CNAs) and to identify molecular markers for recurrence prediction. The miFISH probe panel consisted of 14 colorectal carcinogenesis-relevant genes (COX2, PIK3CA, APC, CLIC1, EGFR, MYC, CCND1, CDX2, CDH1, TP53, HER2, SMAD7, SMAD4 and ZNF217), and a centromere probe (CEP10). The aCGH analysis confirmed the genetic landscape typical for colorectal tumorigenesis, that is, CNAs of chromosomes 7, 13q, 18 and 20q. Focal aberrations (≤10 Mbp) were mapped to chromosome bands 6p22.1-p21.33 (33.3%), 7q22.1 (31.4%) and 16q21 (29.4%). MiFISH detected gains of EGFR (23.6%), CDX2 (21.8%) and ZNF217 (18.2%). Most adenomas exhibited a major clone population which was accompanied by multiple smaller clone populations. Gains of CDX2 were exclusively seen in primary adenomas with recurrence (25%) compared to primary adenomas without recurrence (0%). Generation of phylogenetic trees for matched pair samples revealed four distinct patterns of clonal dynamics. In conclusion, adenoma development and recurrence are complex genetic processes driven by multiple CNAs whose evaluations by miFISH, with emphasis on CDX2, might serve as a predictor of recurrence.

The Heterogeneity of Prostate Cancer: A Practical Approach

Prostate cancer is a paradigm tumor model for heterogeneity in almost every sense. Its clinical, spatial, and morphological heterogeneity divided by the high-level molecular genetic diversity outline the complexity of this disease in the clinical and research settings. In this review, we summarize the main aspects of prostate cancer heterogeneity at different levels, with special attention given to the spatial heterogeneity within the prostate, and to the standard morphological heterogeneity, with respect to tumor grading and modern classifications. We also cover the complex issue of molecular genetic heterogeneity, discussing it in the context of the current evidence of the genetic characterization of prostate carcinoma; the interpatient, intertumoral (multifocal disease), and intratumoral heterogeneity; tumor clonality; and metastatic disease. Clinical and research implications are summarized and serve to address the most pertinent problems stemming from the extreme heterogeneity of prostate cancer.

Identification of fluorescence in situ hybridization assay markers for prediction of disease progression in prostate cancer patients on active surveillance

BACKGROUND

Prostate Cancer (PCa) is the second most prevalent cancer among U.S. males. In recent decades many men with low risk PCa have been over diagnosed and over treated. Given significant co-morbidities associated with definitive treatments, maximizing patient quality of life while recognizing early signs of aggressive disease is essential. There remains a need to better stratify newly diagnosed men according to the risk of disease progression, identifying, with high sensitivity and specificity, candidates for active surveillance versus intervention therapy. The objective of this study was to select fluorescence in situ hybridization (FISH) panels that differentiate non-progressive from progressive disease in patients with low and intermediate risk PCa.

METHODS

We performed a retrospective case-control study to evaluate FISH biomarkers on specimens from PCa patients with clinically localised disease (T1c-T2c) enrolled in Watchful waiting (WW)/Active Surveillance (AS). The patients were classified into cases (progressed to clinical intervention within 10 years), and controls (did not progress in 10 years). Receiver Operating Characteristic (ROC) curve analysis was performed to identify the best 3-5 probe combinations. FISH parameters were then combined with the clinical parameters ─ National Comprehensive Cancer Network (NNCN) risk categories ─ in the logistic regression model.

RESULTS

Seven combinations of FISH parameters with the highest sensitivity and specificity for discriminating cases from controls were selected based on the ROC curve analysis. In the logistic regression model, these combinations contributed significantly to the prediction of PCa outcome. The combination of NCCN risk categories and FISH was additive to the clinical parameters or FISH alone in the final model, with odds ratios of 5.1 to 7.0 for the likelihood of the FISH-positive patients in the intended population to develop disease progression, as compared to the FISH-negative group.

CONCLUSIONS

Combinations of FISH parameters discriminating progressive from non-progressive PCa were selected based on ROC curve analysis. The combination of clinical parameters and FISH outperformed clinical parameters alone, and was complimentary to clinical parameters in the final model, demonstrating potential utility of multi-colour FISH panels as an auxiliary tool for PCa risk stratification. Further studies with larger cohorts are planned to confirm these findings.

Application of Single Cell Sequencing in Cancer

Cancer is a heterogenetic disease at both the level of clinical manifestation and the level of the genome. Single-cell sequencing provides an unprecedented means of characterizing the intra-tumor heterogeneity and detecting and analyzing the genomes of cancer cells. These data will help to reconstruct the understanding of the evolutionary lineage of cancer cells. In the future, single-cell technology is believed to be a useful tool in diagnostic and prognostic application in oncology. The application of single cell technology in clinics will make it possible to detect cancer non-invasively at early stages and to develop precision medicine. In this chapter, we review the research and application status of the single cell technology in cancer.

The oncogenic transcription factor ERG represses the transcription of the tumour suppressor gene PTEN in prostate cancer cells

The oncogene ETS-related gene (ERG) encodes a transcription factor with roles in the regulation of haematopoiesis, angiogenesis, vasculogenesis, inflammation, migration and invasion. The ERG oncogene is activated in >50% of prostate cancer cases, generally through a gene fusion with the androgen-responsive promoter of transmembrane protease serine 2. Phosphatase and tensin homologue (PTEN) is an important tumour suppressor gene that is often inactivated in cancer. ERG overexpression combined with PTEN inactivation or loss is often associated with aggressive prostate cancer. The present study aimed to determine whether or not ERG regulates PTEN transcription directly. ERG was demonstrated to bind to the PTEN promoter and repress its transcription. ERG overexpression reduced endogenous PTEN expression, whereas ERG knockdown increased PTEN expression. The ability of ERG to repress PTEN may contribute to a more cancer-permissive environment.

Application of single-cell technology in cancer research

In this review, we have outlined the application of single-cell technology in cancer research. Single-cell technology has made encouraging progress in recent years and now provides the means to detect rare cancer cells such as circulating tumor cells and cancer stem cells. We reveal how this technology has advanced the analysis of intratumor heterogeneity and tumor epigenetics, and guided individualized treatment strategies. The future prospects now are to bring single-cell technology into the clinical arena. We believe that the clinical application of single-cell technology will be beneficial in cancer diagnostics and treatment, and ultimately improve survival in cancer patients.

The evolution of tumour phylogenetics: principles and practice

Rapid advances in high-throughput sequencing and a growing realization of the importance of evolutionary theory to cancer genomics have led to a proliferation of phylogenetic studies of tumour progression. These studies have yielded not only new insights but also a plethora of experimental approaches, sometimes reaching conflicting or poorly supported conclusions. Here, we consider this body of work in light of the key computational principles underpinning phylogenetic inference, with the goal of providing practical guidance on the design and analysis of scientifically rigorous tumour phylogeny studies. We survey the range of methods and tools available to the researcher, their key applications, and the various unsolved problems, closing with a perspective on the prospects and broader implications of this field.

Microfluidics-assisted fluorescence in situ hybridization for advantageous human epidermal growth factor receptor 2 assessment in breast cancer

Fluorescence in situ hybridization (FISH) is one of the recommended techniques for human epidermal growth factor receptor 2 (HER2) status assessment on cancer tissues. Here we develop microfluidics-assisted FISH (MA-FISH), in which hybridization of the FISH probes with their target DNA strands is obtained by applying square-wave oscillatory flows of diluted probe solutions in a thin microfluidic chamber of 5 μl volume. By optimizing the experimental parameters, MA-FISH decreases the consumption of the expensive probe solution by a factor 5 with respect to the standard technique, and reduces the hybridization time to 4 h, which is four times faster than in the standard protocol. To validate the method, we blindly conducted HER2 MA-FISH on 51 formalin-fixed paraffin-embedded tissue slides of 17 breast cancer samples, and compared the results with standard HER2 FISH testing. HER2 status classification was determined according to published guidelines, based on average number of HER2 copies per cell and average HER2/CEP17 ratio. Excellent agreement was observed between the two methods, supporting the validity of MA-FISH and further promoting its short hybridization time and reduced reagent consumption.

A Perspective on Implementing a Quantitative Systems Pharmacology Platform for Drug Discovery and the Advancement of Personalized Medicine

Drug candidates exhibiting well-defined pharmacokinetic and pharmacodynamic profiles that are otherwise safe often fail to demonstrate proof-of-concept in phase II and III trials. Innovation in drug discovery and development has been identified as a critical need for improving the efficiency of drug discovery, especially through collaborations between academia, government agencies, and industry. To address the innovation challenge, we describe a comprehensive, unbiased, integrated, and iterative quantitative systems pharmacology (QSP)-driven drug discovery and development strategy and platform that we have implemented at the University of Pittsburgh Drug Discovery Institute. Intrinsic to QSP is its integrated use of multiscale experimental and computational methods to identify mechanisms of disease progression and to test predicted therapeutic strategies likely to achieve clinical validation for appropriate subpopulations of patients. The QSP platform can address biological heterogeneity and anticipate the evolution of resistance mechanisms, which are major challenges for drug development. The implementation of this platform is dedicated to gaining an understanding of mechanism(s) of disease progression to enable the identification of novel therapeutic strategies as well as repurposing drugs. The QSP platform will help promote the paradigm shift from reactive population-based medicine to proactive personalized medicine by focusing on the patient as the starting and the end point.

FISHtrees 3.0: Tumor Phylogenetics Using a Ploidy Probe

Advances in fluorescence in situ hybridization (FISH) make it feasible to detect multiple copy-number changes in hundreds of cells of solid tumors. Studies using FISH, sequencing, and other technologies have revealed substantial intra-tumor heterogeneity. The evolution of subclones in tumors may be modeled by phylogenies. Tumors often harbor aneuploid or polyploid cell populations. Using a FISH probe to estimate changes in ploidy can guide the creation of trees that model changes in ploidy and individual gene copy-number variations. We present FISHtrees 3.0, which implements a ploidy-based tree building method based on mixed integer linear programming (MILP). The ploidy-based modeling in FISHtrees includes a new formulation of the problem of merging trees for changes of a single gene into trees modeling changes in multiple genes and the ploidy. When multiple samples are collected from each patient, varying over time or tumor regions, it is useful to evaluate similarities in tumor progression among the samples. Therefore, we further implemented in FISHtrees 3.0 a new method to build consensus graphs for multiple samples. We validate FISHtrees 3.0 on a simulated data and on FISH data from paired cases of cervical primary and metastatic tumors and on paired breast ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC). Tests on simulated data show improved accuracy of the ploidy-based approach relative to prior ploidyless methods. Tests on real data further demonstrate novel insights these methods offer into tumor progression processes. Trees for DCIS samples are significantly less complex than trees for paired IDC samples. Consensus graphs show substantial divergence among most paired samples from both sets. Low consensus between DCIS and IDC trees may help explain the difficulty in finding biomarkers that predict which DCIS cases are at most risk to progress to IDC. The FISHtrees software is available at ftp://ftp.ncbi.nih.gov/pub/FISHtrees.

PTEN Loss as Determined by Clinical-grade Immunohistochemistry Assay Is Associated with Worse Recurrence-free Survival in Prostate Cancer

BACKGROUND

PTEN is the most commonly deleted tumor suppressor gene in primary prostate cancer (PCa) and its loss is associated with poor clinical outcomes and ERG gene rearrangement.

OBJECTIVE

We tested whether PTEN loss is associated with shorter recurrence-free survival (RFS) in surgically treated PCa patients with known ERG status.

DESIGN SETTING AND PARTICIPANTS

A genetically validated, automated PTEN immunohistochemistry (IHC) protocol was used for 1275 primary prostate tumors from the Canary Foundation retrospective PCa tissue microarray cohort to assess homogeneous (in all tumor tissue sampled) or heterogeneous (in a subset of tumor tissue sampled) PTEN loss. ERG status as determined by a genetically validated IHC assay was available for a subset of 938 tumors.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Associations between PTEN and ERG status were assessed using Fisher's exact test. Kaplan-Meier and multivariate weighted Cox proportional models for RFS were constructed.

RESULTS AND LIMITATIONS

When compared to intact PTEN, homogeneous (hazard ratio [HR] 1.66, p = 0.001) but not heterogeneous (HR 1.24, p = 0.14) PTEN loss was significantly associated with shorter RFS in multivariate models. Among ERG-positive tumors, homogeneous (HR 3.07, p < 0.0001) but not heterogeneous (HR 1.46, p = 0.10) PTEN loss was significantly associated with shorter RFS. Among ERG-negative tumors, PTEN did not reach significance for inclusion in the final multivariate models. The interaction term for PTEN and ERG status with respect to RFS did not reach statistical significance (p = 0.11) for the current sample size.

CONCLUSIONS

These data suggest that PTEN is a useful prognostic biomarker and that there is no statistically significant interaction between PTEN and ERG status for RFS.

PATIENT SUMMARY

We found that loss of the PTEN tumor suppressor gene in prostate tumors as assessed by tissue staining is correlated with shorter time to prostate cancer recurrence after radical prostatectomy.

Expression of PTEN and Its Correlation with Proliferation Marker Ki-67 in Head and Neck Cancer

Introduction

PTEN is part of large family of tyrosine phosphatases and has been found inactivated in a wide variety of human cancers.

Aims

In the present study we have tried to determine the association of the expression patterns of this gene with carcinogenesis.

Methods

First, a systematic review was carried out to ascertain the importance of the PTEN gene and its role in carcinogenesis. In the second phase, a case-control study was designed using different expression analysis techniques. Expression of PTEN mRNA was analyzed using reverse transcriptase polymerase chain reaction (RT-PCR).

Results

Significantly downregulated expression of PTEN was observed in patients with head and neck cancer (HNC) compared to adjacent normal-tissue controls. These results were confirmed with quantitative polymerase chain reaction (qPCR). Significant downregulation of the gene was observed in HNC patients compared to adjacent normal-tissue controls. PTEN expression was correlated with different histopathological parameters of the study cohort by Spearman's correlation coefficient and a significant negative correlation was observed with pT stage (r = −0.271*; p<0.02) and grade (r = −0.228*; p<0.02) of HNC tissues. Furthermore, the expression variations of PTEN were correlated with the expression pattern of the proliferation marker Ki-67. Significantly (p<0.008) upregulated expression of Ki-67 was observed in HNC patients compared with adjacent normal-tissue controls This upregulation of Ki-67 was confirmed at the protein level by immunohistochemistry in HNC patients. When Spearman's correlation was carried out a significant negative correlation was observed between PTEN and Ki-67 (r = −0.230*; p<0.03).

Conclusions

Our data suggest that downregulation of PTEN and overexpression of Ki-67 may contribute to the initiation and progression of HNC.

Prognostic and predictive biomarkers in prostate cancer

Prostate cancer (PCa) is one of the leading causes of cancer death among males, especially in more developed countries. Diagnosis is often achieved at an early stage of the disease with prostate biopsy, following a screening test showing elevated serum levels of prostate-specific antigen or a positive digital rectal examination. Early detection of PCa has led to a substantial decline in the number of metastatic patients. However, the prostate-specific antigen screening test has proved to be a double-edged sword so far, as it also accounts for PCa overdiagnosis. Due to the variability of PCa features, accurate prognosis of PCa patients is very important for determining treatment options. Therefore, this review focuses on the most promising prognostic and predictive biomarkers in PCa, which are likely to play a pivotal role, alone or in panels, in the personalized medicine era that has recently emerged.

Phylogenetic analysis of multiple FISH markers in oral tongue squamous cell carcinoma suggests that a diverse distribution of copy number changes is associated with poor prognosis

Oral tongue squamous cell carcinoma (OTSCC) is associated with poor prognosis. To improve prognostication, we analyzed four gene probes (TERC, CCND1, EGFR and TP53) and the centromere probe CEP4 as a marker of chromosomal instability, using fluorescence in situ hybridization (FISH) in single cells from the tumors of sixty-five OTSCC patients (Stage I, n = 15; Stage II, n = 30; Stage III, n = 7; Stage IV, n = 13). Unsupervised hierarchical clustering of the FISH data distinguished three clusters related to smoking status. Copy number increases of all five markers were found to be correlated to non-smoking habits, while smokers in this cohort had low-level copy number gains. Using the phylogenetic modeling software FISHtrees, we constructed models of tumor progression for each patient based on the four gene probes. Then, we derived test statistics on the models that are significant predictors of disease-free and overall survival, independent of tumor stage and smoking status in multivariate analysis. The patients whose tumors were modeled as progressing by a more diverse distribution of copy number changes across the four genes have poorer prognosis. This is consistent with the view that multiple genetic pathways need to become deregulated in order for cancer to progress.

Association of ERG and TMPRSS2-ERG with grade, stage, and prognosis of prostate cancer is dependent on their expression levels

BACKGROUND

There is controversy in the literature on the role of the fusion TMPRSS2-ERG in the pathogenesis and progression of prostate cancer. The quantitative differences in TMPRSS2-ERG fusion expression have received very limited attention in the literature.

METHODS

We have quantitatively analyzed the mRNA levels of TMPRSS2-ERG, ERG, PTEN, and AR (n = 83), as well as ERG immunostaining (n = 78) in a series of prostate tumors.

RESULTS

Among the TMPRSS2-ERG cases (n = 57), high fusion levels were associated with GS ≥8 (P = 0.025). ERG mRNA overexpression was associated with GS ≥8 (P = 0.047), and with stage T3-T4 tumors (P = 0.032). Among the ERG overexpressing cases (n = 54), higher expression levels were found in 92.3% of GS ≥8 tumors (P = 0.02). ERG immunostaining, regardless of staining intensity, was also associated with high stage (P = 0.05). There was a statistical association between ERG immunostaining and PSA progression-free survival (Log Rank test, P = 0.048). Decreased PTEN expression was associated with TMPRSS2-ERG (P = 0.01), ERG mRNA overexpression (P = 0.003) and ERG immunostaining (P = 0.007). Furthermore, decreased PTEN expression, alone (P = 0.041) and also combined with TMPRSS2-ERG (P = 0.04) or with ERG overexpression (P = 0.04) was associated with GS ≥7 tumors.

CONCLUSIONS

Although more studies are needed to further clarify their role, our findings emphasize that the expression levels of the TMPRSS2-ERG fusion and ERG mRNA, rather than their mere presence, are related to a more aggressive phenotype, have an effect on prognosis and could be molecular markers of progression for prostate cancer. Furthermore, ERG immunohistochemistry could be also a potentially useful prognostic factor.

TBL1XR1 in physiological and pathological states

Transducin (beta)-like 1X related protein 1 (TBL1XR1/TBLR1) is an integral subunit of the NCoR (nuclear receptor corepressor) and SMRT (silencing mediator of retinoic acid and thyroid hormone receptors) repressor complexes. It is an evolutionally conserved protein that shares high similarity across all species. TBL1XR1 is essential for transcriptional repression mediated by unliganded nuclear receptors (NRs) and othe regulated transcription factors (TFs). However, it can also act as a transcription activator through the recruitment of the ubiquitin-conjugating/19S proteasome complex that mediates the exchange of corepressors for coactivators. TBL1XR1 is required for the activation of multiple intracellular signaling pathways. TBL1XR1 germline mutations and recurrent mutations are linked to intellectual disability. Upregulation of TBL1XR1 is observed in a variety of solid tumors, which is associated with advanced tumor stage, metastasis and poor prognosis. A variety of genomic alterations, such as translocation, deletion and mutation have been identified in many types of neoplasms. Loss of TBL1XR1 in B-lymphoblastic leukemia disrupts glucocorticoid receptor recruitment to chromatin and results in glucocorticoid resistance. However, the mechanisms of other types of genomic changes in tumorogenesis are still not clear. A pre-clinical study has shown that the disruption of the interaction between TBL1X and β-catenin using a small molecule can inhibit the growth of AML stem and blast cells both in vitro and in vivo. These findings shed light on the therapeutic potentials of targeting TBL1XR1 related proteins in cancer treatment.