Parallel evolution of tumour subclones mimics diversity between tumours

Chromosomal defects track tumor subpopulations and change in progression in oligodendroglioma

To assess karyotypic changes and tumor subpopulations in progression of oligodendroglioma (ODG) we analyzed histologically diagnosed 1p/19q codeleted cases using single nucleotide polymorphism (SNP) microarray data. We separated cases according to grade, which was assigned blind to karyotype information beyond 1p/19q status. The 51 WHO grade II (O2) and 18 WHO grade III (O3) specimens showed frequent chromosomal locations and patterns of change including loss of heterozygosity (LOH), often copy-neutral, on 9p and LOH on 4p and 4q together. Analysis of co-occurrence indicated that most defects were independent but also suggested increased likelihood of defects on 11q, 13q, and 14q in the presence of defects on 18, 4, and 9, respectively. We used the relative degree of change in B-allele frequency as an indicator of an abnormality's extent, and we present simulated data to clarify how information on subpopulations was thus inferred. Among 9p defects, 89.3% involved the whole tumor, whereas only 47.6% of 4q defects did so. We modeled extent through the tumor as due to a karyotypic change's likelihood of occurring and the fitness it confers on its subpopulation, and used group data to estimate these values. To assess progression directly, we evaluated specimens from six patients who underwent multiple resections since 1996. Four of these patients had received no chemotherapy or radiation, permitting assessment of the natural history of the tumor karyotype in situ. Defects present throughout a tumor at first resection remained so, whereas among subpopulations, some expanded, some remained constant, and some disappeared. The rate of expansion among subpopulations that did so was not uniform, and estimates of fitness predicted subpopulation composition at recurrence. These results extend prior studies of increased karyotypic abnormality in progression of oligodendroglioma and reveal the complex dynamics of subpopulations in the tumor over time.

Fully automated fluorescence-based four-color multiplex assay for co-detection of microRNA and protein biomarkers in clinical tissue specimens

The application of locked nucleic acid chemistry for microRNA detection by in situ hybridization, and thereby visualization of microRNA expression at single-cell resolution, has contributed to our understanding of the roles that these short noncoding regulatory RNAs play during development, physiology, and disease. Several groups have implemented chromogenic-based and fluorescence-based protocols to detect microRNA expression in formalin-fixed paraffin-embedded clinical tissue specimens. These emerging robust and reproducible tissue slide-based assays are valid tools to bring about the clinical application of in situ microRNA detection for routine diagnostics. Here, I describe a fully automated fluorescence-based four-color multiplex assay for co-detection of a microRNA (e.g., let-7a, miR-10b, miR-21, miR-34a, miR-126, miR-145, miR-155, miR-205, miR-210), reference RNA (e.g., U6 snRNA, 18S rRNA), and protein markers (e.g., CD11b, CD20, CD45, collagen I, cytokeratin 7, cytokeratin 19, smooth muscle actin, tubulin, vimentin) in FDA-approved Leica Bond-MAX staining station.

Intratumour heterogeneity in urologic cancers: from molecular evidence to clinical implications

CONTEXT

Intratumour heterogeneity (ITH) can impair the precise molecular analysis of tumours and may contribute to difficulties encountered in cancer biomarker qualification and treatment personalisation.

OBJECTIVE

This review summarises the evidence for genetic ITH in renal, bladder, and prostate carcinomas and potential strategies to address the clinical and translational research challenges arising from ITH.

EVIDENCE ACQUISITION

Publications that assessed ITH in the relevant urologic cancers were identified in a literature review.

EVIDENCE SYNTHESIS

ITH with functionally distinct tumour subclones has been identified in all three tumour types. Heterogeneity of actionable genetic changes and of prognostic biomarkers between different tumour regions in the same patient suggests limitations of single biopsy-based molecular analyses for precision medicine approaches. Evolutionary constraints may differ between patients and may allow the prediction of specific evolutionary trajectories.

CONCLUSIONS

Assessment of multiple tumour regions for precision medicine purposes, monitoring of subclonal dynamics over time, and the preferential targeting of genetic alterations located on the trunk of the phylogenetic tree of individual cancers may accelerate the development of personalised medicine strategies and improve our understanding of treatment failure.

PATIENT SUMMARY

Genetic alterations can be heterogeneous within urologic tumours, complicating their use as biomarkers for treatment personalisation. We present novel strategies to address these challenges.

Diversity index of mucosal resident T lymphocyte repertoire predicts clinical prognosis in gastric cancer

A characteristic immunopathology of human cancers is the induction of tumor antigen-specific T lymphocyte responses within solid tumor tissues. Current strategies for immune monitoring focus on the quantification of the density and differentiation status of tumor-infiltrating T lymphocytes; however, properties of the TCR repertoire ‒ including antigen specificity, clonality, as well as its prognostic significance ‒ remain elusive. In this study, we enrolled 28 gastric cancer patients and collected tumor tissues, adjacent normal mucosal tissues, and peripheral blood samples to study the landscape and compartmentalization of these patients' TCR β repertoire by deep sequencing analyses. Our results illustrated antigen-driven expansion within the tumor compartment and the contracted size of shared clonotypes in mucosa and peripheral blood. Most importantly, the diversity of mucosal T lymphocytes could independently predict prognosis, which strongly underscores critical roles of resident mucosal T-cells in executing post-surgery immunosurveillance against tumor relapse.

Sequenza: allele-specific copy number and mutation profiles from tumor sequencing data

BACKGROUND

Exome or whole-genome deep sequencing of tumor DNA along with paired normal DNA can potentially provide a detailed picture of the somatic mutations that characterize the tumor. However, analysis of such sequence data can be complicated by the presence of normal cells in the tumor specimen, by intratumor heterogeneity, and by the sheer size of the raw data. In particular, determination of copy number variations from exome sequencing data alone has proven difficult; thus, single nucleotide polymorphism (SNP) arrays have often been used for this task. Recently, algorithms to estimate absolute, but not allele-specific, copy number profiles from tumor sequencing data have been described.

MATERIALS AND METHODS

We developed Sequenza, a software package that uses paired tumor-normal DNA sequencing data to estimate tumor cellularity and ploidy, and to calculate allele-specific copy number profiles and mutation profiles. We applied Sequenza, as well as two previously published algorithms, to exome sequence data from 30 tumors from The Cancer Genome Atlas. We assessed the performance of these algorithms by comparing their results with those generated using matched SNP arrays and processed by the allele-specific copy number analysis of tumors (ASCAT) algorithm.

RESULTS

Comparison between Sequenza/exome and SNP/ASCAT revealed strong correlation in cellularity (Pearson's r = 0.90) and ploidy estimates (r = 0.42, or r = 0.94 after manual inspecting alternative solutions). This performance was noticeably superior to previously published algorithms. In addition, in artificial data simulating normal-tumor admixtures, Sequenza detected the correct ploidy in samples with tumor content as low as 30%.

CONCLUSIONS

The agreement between Sequenza and SNP array-based copy number profiles suggests that exome sequencing alone is sufficient not only for identifying small scale mutations but also for estimating cellularity and inferring DNA copy number aberrations.

Cancer genomic research at the crossroads: realizing the changing genetic landscape as intratumoral spatial and temporal heterogeneity becomes a confounding factor

The US National Cancer Institute (NCI) and the National Human Genome Research Institute (NHGRI) created the Cancer Genome Atlas (TCGA) Project in 2006. The TCGA’s goal was to sequence the genomes of 10,000 tumors to identify common genetic changes among different types of tumors for developing genetic-based treatments. TCGA offered great potential for cancer patients, but in reality has little impact on clinical applications. Recent reports place the past TCGA approach of testing a small tumor mass at a single time-point at a crossroads. This crossroads presents us with the conundrum of whether we should sequence more tumors or obtain multiple biopsies from each individual tumor at different time points. Sequencing more tumors with the past TCGA approach of single time-point sampling can neither capture the heterogeneity between different parts of the same tumor nor catch the heterogeneity that occurs as a function of time, error rates, and random drift. Obtaining multiple biopsies from each individual tumor presents multiple logistical and financial challenges. Here, we review current literature and rethink the utility and application of the TCGA approach. We discuss that the TCGA-led catalogue may provide insights into studying the functional significance of oncogenic genes in reference to non-cancer genetic background. Different methods to enhance identifying cancer targets, such as single cell technology, real time imaging of cancer cells with a biological global positioning system, and cross-referencing big data sets, are offered as ways to address sampling discrepancies in the face of tumor heterogeneity. We predict that TCGA landmarks may prove far more useful for cancer prevention than for cancer diagnosis and treatment when considering the effect of non-cancer genes and the normal genetic background on tumor microenvironment. Cancer prevention can be better realized once we understand how therapy affects the genetic makeup of cancer over time in a clinical setting. This may help create novel therapies for gene mutations that arise during a tumor’s evolution from the selection pressure of treatment.

Intratumor heterogeneity in localized lung adenocarcinomas delineated by multiregion sequencing

Cancers are composed of populations of cells with distinct molecular and phenotypic features, a phenomenon termed intratumor heterogeneity (ITH). ITH in lung cancers has not been well studied. We applied multiregion whole-exome sequencing (WES) on 11 localized lung adenocarcinomas. All tumors showed clear evidence of ITH. On average, 76% of all mutations and 20 out of 21 known cancer gene mutations were identified in all regions of individual tumors, which suggested that single-region sequencing may be adequate to identify the majority of known cancer gene mutations in localized lung adenocarcinomas. With a median follow-up of 21 months after surgery, three patients have relapsed, and all three patients had significantly larger fractions of subclonal mutations in their primary tumors than patients without relapse. These data indicate that a larger subclonal mutation fraction may be associated with increased likelihood of postsurgical relapse in patients with localized lung adenocarcinomas.

Systematic evaluation of the prognostic impact and intratumour heterogeneity of clear cell renal cell carcinoma biomarkers

BACKGROUND

Candidate biomarkers have been identified for clear cell renal cell carcinoma (ccRCC) patients, but most have not been validated.

OBJECTIVE

To validate published ccRCC prognostic biomarkers in an independent patient cohort and to assess intratumour heterogeneity (ITH) of the most promising markers to guide biomarker optimisation.

DESIGN, SETTING, AND PARTICIPANTS

Cancer-specific survival (CSS) for each of 28 identified genetic or transcriptomic biomarkers was assessed in 350 ccRCC patients. ITH was interrogated in a multiregion biopsy data set of 10 ccRCCs.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Biomarker association with CSS was analysed by univariate and multivariate analyses.

RESULTS AND LIMITATIONS

A total of 17 of 28 biomarkers (TP53 mutations; amplifications of chromosomes 8q, 12, 20q11.21q13.32, and 20 and deletions of 4p, 9p, 9p21.3p24.1, and 22q; low EDNRB and TSPAN7 expression and six gene expression signatures) were validated as predictors of poor CSS in univariate analysis. Tumour stage and the ccB expression signature were the only independent predictors in multivariate analysis. ITH of the ccB signature was identified in 8 of 10 tumours. Several genetic alterations that were significant in univariate analysis were enriched, and chromosomal instability indices were increased in samples expressing the ccB signature. The study may be underpowered to validate low-prevalence biomarkers.

CONCLUSIONS

The ccB signature was the only independent prognostic biomarker. Enrichment of multiple poor prognosis genetic alterations in ccB samples indicated that several events may be required to establish this aggressive phenotype, catalysed in some tumours by chromosomal instability. Multiregion assessment may improve the precision of this biomarker.

PATIENT SUMMARY

We evaluated the ability of published biomarkers to predict the survival of patients with clear cell kidney cancer in an independent patient cohort. Only one molecular test adds prognostic information to routine clinical assessments. This marker showed good and poor prognosis results within most individual cancers. Future biomarkers need to consider variation within tumours to improve accuracy.

The potential of genome-wide analyses to improve non-small-cell lung cancer care

SUMMARY 

Genomic technologies have revolutionized the way we study and understand cancer. The advent of next-generation sequencing technology in particular is now starting to change the clinical management of non-small-cell lung cancer. These technologies have helped us to refine prognostication and identify new driver mutations that can allow subselection of patients for therapeutic intervention. However, several limitations and challenges must be overcome before these technologies are widely accepted in diagnostic laboratories. It will be important for clinicians and diagnostic laboratories to consider sample type, analytical platform, cost, data security and ethics, and the bioinformatics challenges associated with 'big data', before widespread integration to the clinic. If these challenges can be overcome, then genomics has the potential to change clinical management of lung cancer.

Tissue slide-based microRNA characterization of tumors: how detailed could diagnosis become for cancer medicine?

miRNAs are short, non-coding, regulatory RNAs that exert cell type-dependent, context-dependent, transcriptome-wide gene expression control under physiological and pathological conditions. Tissue slide-based assays provide qualitative (tumor compartment) and semi-quantitative (expression levels) information about altered miRNA expression at single-cell resolution in clinical tumor specimens. Reviewed here are key technological advances in the last 5 years that have led to implementation of fully automated, robust and reproducible tissue slide-based assays for in situ miRNA detection on US FDA-approved instruments; recent tissue slide-based discovery studies that suggest potential clinical applications of specific miRNAs in cancer medicine are highlighted; and the challenges in bringing tissue slide-based miRNA assays into the clinic are discussed, including clinical validation, biomarker performance, biomarker space and integration with other biomarkers.

Development of synchronous VHL syndrome tumors reveals contingencies and constraints to tumor evolution

BACKGROUND

Genomic analysis of multi-focal renal cell carcinomas from an individual with a germline VHL mutation offers a unique opportunity to study tumor evolution.

RESULTS

We perform whole exome sequencing on four clear cell renal cell carcinomas removed from both kidneys of a patient with a germline VHL mutation. We report that tumors arising in this context are clonally independent and harbour distinct secondary events exemplified by loss of chromosome 3p, despite an identical genetic background and tissue microenvironment. We propose that divergent mutational and copy number anomalies are contingent upon the nature of 3p loss of heterozygosity occurring early in tumorigenesis. However, despite distinct 3p events, genomic, proteomic and immunohistochemical analyses reveal evidence for convergence upon the PI3K-AKT-mTOR signaling pathway. Four germline tumors in this young patient, and in a second, older patient with VHL syndrome demonstrate minimal intra-tumor heterogeneity and mutational burden, and evaluable tumors appear to follow a linear evolutionary route, compared to tumors from patients with sporadic clear cell renal cell carcinoma.

CONCLUSIONS

In tumors developing from a germline VHL mutation, the evolutionary principles of contingency and convergence in tumor development are complementary. In this small set of patients with early stage VHL-associated tumors, there is reduced mutation burden and limited evidence of intra-tumor heterogeneity.

Chromosome 9p deletion in clear cell renal cell carcinoma predicts recurrence and survival following surgery

Background:

Wider clinical applications of 9p status in clear cell renal cell carcinoma (ccRCC) are limited owing to the lack of validation and consensus for interphase fluorescent in situ hybridisation (I-FISH) scoring technique. The aim of this study was to analytically validate the applicability of I-FISH in assessing 9p deletion in ccRCC and to clinically assess its long-term prognostic impact following surgical excision of ccRCC.

Methods:

Tissue microarrays were constructed from 108 renal cell carcinoma (RCC) tumour paraffin blocks. Interphase fluorescent in situ hybridisation analysis was undertaken based on preset criteria by two independent observers to assess interobserver variability. 9p status in ccRCC tumours was determined and correlated to clinicopathological variables, recurrence-free survival and disease-specific survival.

Results:

There were 80 ccRCCs with valid 9p scoring and a median follow-up of 95 months. Kappa statistic for interobserver variability was 0.71 (good agreement). 9p deletion was detected in 44% of ccRCCs. 9p loss was associated with higher stage, larger tumours, necrosis, microvascular and renal vein invasion, and higher SSIGN (stage, size, grade and necrosis) score. Patients with 9p-deleted ccRCC were at a higher risk of recurrence (P=0.008) and RCC-specific mortality (P=0.001). On multivariate analysis, 9p deletion was an independent predictor of recurrence (hazard ratio 4.323; P=0.021) and RCC-specific mortality (hazard ratio 4.603; P=0.007). The predictive accuracy of SSIGN score improved from 87.7% to 93.1% by integrating 9p status to the model (P=0.001).

Conclusions:

Loss of 9p is associated with aggressive ccRCC and worse prognosis in patients following surgery. Our findings independently confirm the findings of previous reports relying on I-FISH to detect 9p (CDKN2A) deletion.

The impact of genetic heterogeneity on biomarker development in kidney cancer assessed by multiregional sampling

Primary clear cell renal cell carcinoma (ccRCC) genetic heterogeneity may lead to an underestimation of the mutational burden detected from a single site evaluation. We sought to characterize the extent of clonal branching involving key tumor suppressor mutations in primary ccRCC and determine if genetic heterogeneity could limit the mutation profiling from a single region assessment. Ex vivo core needle biopsies were obtained from three to five different regions of resected renal tumors at a single institution from 2012 to 2013. DNA was extracted and targeted sequencing was performed on five genes associated with ccRCC (von-Hippel Lindau [VHL], PBRM1, SETD2, BAP1, and KDM5C). We constructed phylogenetic trees by inferring clonal evolution based on the mutations present within each core and estimated the predictive power of detecting a mutation for each successive tumor region sampled. We obtained 47 ex vivo biopsy cores from 14 primary ccRCC's (median tumor size 4.5 cm, IQR 4.0–5.9 cm). Branching patterns of various complexities were observed in tumors with three or more mutations. A VHL mutation was detected in nine tumors (64%), each time being present ubiquitously throughout the tumor. Other genes had various degrees of regional mutational variation. Based on the mutations' prevalence we estimated that three different tumor regions should be sampled to detect mutations in PBRM1, SETD2, BAP1, and/or KDM5C with 90% certainty. The mutational burden of renal tumors varies by region sampled. Single site assessment of key tumor suppressor mutations in primary ccRCC may not adequately capture the genetic predictors of tumor behavior.

Tumorigenicity and genetic profiling of circulating tumor cells in small-cell lung cancer

Small-cell lung cancer (SCLC), an aggressive neuroendocrine tumor with early dissemination and dismal prognosis, accounts for 15-20% of lung cancer cases and ∼200,000 deaths each year. Most cases are inoperable, and biopsies to investigate SCLC biology are rarely obtainable. Circulating tumor cells (CTCs), which are prevalent in SCLC, present a readily accessible 'liquid biopsy'. Here we show that CTCs from patients with either chemosensitive or chemorefractory SCLC are tumorigenic in immune-compromised mice, and the resultant CTC-derived explants (CDXs) mirror the donor patient's response to platinum and etoposide chemotherapy. Genomic analysis of isolated CTCs revealed considerable similarity to the corresponding CDX. Most marked differences were observed between CDXs from patients with different clinical outcomes. These data demonstrate that CTC molecular analysis via serial blood sampling could facilitate delivery of personalized medicine for SCLC. CDXs are readily passaged, and these unique mouse models provide tractable systems for therapy testing and understanding drug resistance mechanisms.

Genomics of pancreatic ductal adenocarcinoma

Pancreatic cancer is one of the worst prognostic cancers because of the late diagnosis and the absence of effective treatment. Within all subtypes of this disease, ductal adenocarcinoma has the shortest survival time. In recent years, global genomics profiling allowed the identification of hundreds of genes that are perturbed in pancreatic cancer. The integration of different omics sources in the study of pancreatic cancer has revealed several molecular mechanisms, indicating the complex history of its development. However, validation of these genes as biomarkers for early diagnosis, prognosis or treatment efficacy is still incomplete but should lead to new approaches for the treatment of the disease in the future.

Ultra-deep T cell receptor sequencing reveals the complexity and intratumour heterogeneity of T cell clones in renal cell carcinomas

The recognition of cancer cells by T cells can impact upon prognosis and be exploited for immunotherapeutic approaches. This recognition depends on the specific interaction between antigens displayed on the surface of cancer cells and the T cell receptor (TCR), which is generated by somatic rearrangements of TCR α- and β-chains (TCRb). Our aim was to assess whether ultra-deep sequencing of the rearranged TCRb in DNA extracted from unfractionated clear cell renal cell carcinoma (ccRCC) samples can provide insights into the clonality and heterogeneity of intratumoural T cells in ccRCCs, a tumour type that can display extensive genetic intratumour heterogeneity (ITH). For this purpose, DNA was extracted from two to four tumour regions from each of four primary ccRCCs and was analysed by ultra-deep TCR sequencing. In parallel, tumour infiltration by CD4, CD8 and Foxp3 regulatory T cells was evaluated by immunohistochemistry and correlated with TCR-sequencing data. A polyclonal T cell repertoire with 367-16 289 (median 2394) unique TCRb sequences was identified per tumour region. The frequencies of the 100 most abundant T cell clones/tumour were poorly correlated between most regions (Pearson correlation coefficient, -0.218 to 0.465). 3-93% of these T cell clones were not detectable across all regions. Thus, the clonal composition of T cell populations can be heterogeneous across different regions of the same ccRCC. T cell ITH was higher in tumours pretreated with an mTOR inhibitor, which could suggest that therapy can influence adaptive tumour immunity. These data show that ultra-deep TCR-sequencing technology can be applied directly to DNA extracted from unfractionated tumour samples, allowing novel insights into the clonality of T cell populations in cancers. These were polyclonal and displayed ITH in ccRCC. TCRb sequencing may shed light on mechanisms of cancer immunity and the efficacy of immunotherapy approaches.

Cancer evolution: the final frontier of precision medicine?

This editorial will review our current understanding of intratumour heterogeneity and cancer evolution and its potential impact on patient outcome and biomarker validation.

Genomic architecture and evolution of clear cell renal cell carcinomas defined by multiregion sequencing

Clear cell renal carcinomas (ccRCCs) can display intratumor heterogeneity (ITH). We applied multiregion exome sequencing (M-seq) to resolve the genetic architecture and evolutionary histories of ten ccRCCs. Ultra-deep sequencing identified ITH in all cases. We found that 73-75% of identified ccRCC driver aberrations were subclonal, confounding estimates of driver mutation prevalence. ITH increased with the number of biopsies analyzed, without evidence of saturation in most tumors. Chromosome 3p loss and VHL aberrations were the only ubiquitous events. The proportion of C>T transitions at CpG sites increased during tumor progression. M-seq permits the temporal resolution of ccRCC evolution and refines mutational signatures occurring during tumor development.

Implications of intratumour heterogeneity for treatment stratification

Despite advances in the diagnosis and treatment of cancer, the majority of advanced metastatic solid tumours remain incurable. Differential gene expression, somatic mutational status, tumour-specific genetic signatures and micro-environmental selection pressures within individual tumours have implications for the success of predictive assays to guide therapeutic intervention. In this review we discuss the evidence for genetic and phenotypic heterogeneity and its potential implications for clinical decision making. We highlight areas of research that could be improved in order to better stratify patient treatment. We also discuss the predictive potential of patient-derived models of tumour response, including xenograft and cell line-based systems within the context of intratumour heterogeneity.

Computational optimisation of targeted DNA sequencing for cancer detection

Despite recent progress thanks to next-generation sequencing technologies, personalised cancer medicine is still hampered by intra-tumour heterogeneity and drug resistance. As most patients with advanced metastatic disease face poor survival, there is need to improve early diagnosis. Analysing circulating tumour DNA (ctDNA) might represent a non-invasive method to detect mutations in patients, facilitating early detection. In this article, we define reduced gene panels from publicly available datasets as a first step to assess and optimise the potential of targeted ctDNA scans for early tumour detection. Dividing 4,467 samples into one discovery and two independent validation cohorts, we show that up to 76% of 10 cancer types harbour at least one mutation in a panel of only 25 genes, with high sensitivity across most tumour types. Our analyses demonstrate that targeting “hotspot” regions would introduce biases towards in-frame mutations and would compromise the reproducibility of tumour detection.

The causes and consequences of genetic heterogeneity in cancer evolution

Recent studies have revealed extensive genetic diversity both between and within tumours. This heterogeneity affects key cancer pathways, driving phenotypic variation, and poses a significant challenge to personalized cancer medicine. A major cause of genetic heterogeneity in cancer is genomic instability. This instability leads to an increased mutation rate and can shape the evolution of the cancer genome through a plethora of mechanisms. By understanding these mechanisms we can gain insight into the common pathways of tumour evolution that could support the development of future therapeutic strategies.

Integration of cancer genomics with treatment selection: from the genome to predictive biomarkers

The field of cancer genomics is rapidly advancing as new technology provides detailed genetic and epigenetic profiling of human cancers. The amount of new data available describing the genetic make-up of tumors is paralleled by rapid advances in drug discovery and molecular therapy currently under investigation to treat these diseases. This review summarizes the challenges and approaches associated with the integration of genomic data into the development of new biomarkers in the management of cancer.