Marco Gerlinger

Intratumor heterogeneity and branched evolution revealed by multiregion sequencing.

BACKGROUND Intratumor heterogeneity may foster tumor evolution and adaptation and hinder personalized-medicine strategies that depend on results from single tumor-biopsy samples. METHODS To examine intratumor heterogeneity, we performed exome sequencing, chromosome aberration analysis, and ploidy profiling on multiple spatially separated samples obtained from primary renal carcinomas and associated metastatic sites. We characterized the consequences of intratumor heterogeneity using immunohistochemical analysis, mutation functional analysis, and profiling of messenger RNA expression. RESULTS Phylogenetic reconstruction revealed branched evolutionary tumor growth, with 63 to 69% of all somatic mutations not detectable across every tumor region. Intratumor heterogeneity was observed for a mutation within an autoinhibitory domain of the mammalian target of rapamycin (mTOR) kinase, correlating with S6 and 4EBP phosphorylation in vivo and constitutive activation of mTOR kinase activity in vitro. Mutational intratumor heterogeneity was seen for multiple tumor-suppressor genes converging on loss of function; SETD2, PTEN, and KDM5C underwent multiple distinct and spatially separated inactivating mutations within a single tumor, suggesting convergent phenotypic evolution. Gene-expression signatures of good and poor prognosis were detected in different regions of the same tumor. Allelic composition and ploidy profiling analysis revealed extensive intratumor heterogeneity, with 26 of 30 tumor samples from four tumors harboring divergent allelic-imbalance profiles and with ploidy heterogeneity in two of four tumors. CONCLUSIONS Intratumor heterogeneity can lead to underestimation of the tumor genomics landscape portrayed from single tumor-biopsy samples and may present major challenges to personalized-medicine and biomarker development. Intratumor heterogeneity, associated with heterogeneous protein function, may foster tumor adaptation and therapeutic failure through Darwinian selection. (Funded by the Medical Research Council and others.).

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.

Spatial and temporal diversity in genomic instability processes defines lung cancer evolution

Spatial and temporal dissection of the genomic changes occurring during the evolution of human non–small cell lung cancer (NSCLC) may help elucidate the basis for its dismal prognosis. We sequenced 25 spatially distinct regions from seven operable NSCLCs and found evidence of branched evolution, with driver mutations arising before and after subclonal diversification. There was pronounced intratumor heterogeneity in copy number alterations, translocations, and mutations associated with APOBEC cytidine deaminase activity. Despite maintained carcinogen exposure, tumors from smokers showed a relative decrease in smoking-related mutations over time, accompanied by an increase in APOBEC-associated mutations. In tumors from former smokers, genome-doubling occurred within a smoking-signature context before subclonal diversification, which suggested that a long period of tumor latency had preceded clinical detection. The regionally separated driver mutations, coupled with the relentless and heterogeneous nature of the genome instability processes, are likely to confound treatment success in NSCLC. Different regions of a human lung tumor harbor different mutations, possibly explaining why the disease is so tough to treat. [Also see Perspective by Govindan] Space, time, and the lung cancer genome Lung cancer poses a formidable challenge to clinical oncologists. It is often detected at a late stage, and most therapies work for only a short time before the tumors resume their relentless growth. Two independent analyses of the human lung cancer genome may help explain why this disease is so resilient (see the Perspective by Govindan). Rather than take a single “snapshot” of the cancer genome, de Bruin et al. and Zhang et al. identified genomic alterations in spatially distinct regions of single lung tumors and used this information to infer the tumors evolutionary history. Each tumor showed tremendous spatial and temporal diversity in its mutational profiles. Thus, the efficacy of drugs may be short-lived because they destroy only a portion of the tumor. Science, this issue p. 251, p. 256; see also p. 169

Intratumor Heterogeneity: Seeing the Wood for the Trees

Intratumor genetic heterogeneity impedes development of new therapeutics and biomarkers that predict drug response. Most advanced solid tumors remain incurable, with resistance to chemotherapeutics and targeted therapies a common cause of poor clinical outcome. Intratumor heterogeneity may contribute to this failure by initiating phenotypic diversity enabling drug resistance to emerge and by introducing tumor sampling bias. Envisaging tumor growth as a Darwinian tree with the trunk representing ubiquitous mutations and the branches representing heterogeneous mutations may help in drug discovery and the development of predictive biomarkers of drug response.

How Darwinian models inform therapeutic failure initiated by clonal heterogeneity in cancer medicine

Carcinogenesis is an evolutionary process that establishes the ‘hallmarks of cancer’ by natural selection of cell clones that have acquired advantageous heritable characteristics. Evolutionary adaptation has also been proposed as a mechanism that promotes drug resistance during systemic cancer therapy. This review summarises the evidence for the evolution of resistance to cytotoxic and targeted anti-cancer drugs according to Darwinian models and highlights the roles of genomic instability and high intra-tumour genetic heterogeneity as major accelerators of this evolutionary process. Clinical implications and strategies that may prevent the evolution of resistance or target the origins of genetic heterogeneity are discussed. New technologies to measure intra-tumour heterogeneity and translational research on serial biopsies of cancer lesions during and after therapeutic intervention are identified as key areas to further the understanding of determinants and mechanisms of the evolution of drug resistance.

Cancer: Evolution Within a Lifetime

Subclonal cancer populations change spatially and temporally during the disease course. Studies are revealing branched evolutionary cancer growth with low-frequency driver events present in subpopulations of cells, providing escape mechanisms for targeted therapeutic approaches. Despite such complexity, evidence is emerging for parallel evolution of subclones, mediated through distinct somatic events converging on the same gene, signal transduction pathway, or protein complex in different subclones within the same tumor. Tumors may follow gradualist paths (microevolution) as well as major shifts in evolutionary trajectories (macroevolution). Although macroevolution has been subject to considerable controversy in post-Darwinian evolutionary theory, we review evidence that such nongradual, saltatory leaps, driven through chromosomal rearrangements or genome doubling, may be particularly relevant to tumor evolution. Adapting cancer care to the challenges imposed by tumor micro- and macroevolution and developing deeper insight into parallel evolutionary events may prove central to improving outcome and reducing drug development costs.

Assessment of an RNA interference screen-derived mitotic and ceramide pathway metagene as a predictor of response to neoadjuvant paclitaxel for primary triple-negative breast cancer: a retrospective analysis of five clinical trials.

BACKGROUND Addition of taxanes to preoperative chemotherapy in breast cancer increases the proportion of patients who have a pathological complete response (pCR). However, a substantial proportion of patients do not respond, and the prognosis is particularly poor for patients with oestrogen-receptor (ER)/progesterone-receptor (PR)/human epidermal growth factor receptor 2 (HER2; ERBB2)-negative (triple-negative) disease who do not achieve a pCR. Reliable identification of such patients is the first step in determining who might benefit from alternative treatment regimens in clinical trials. We previously identified genes involved in mitosis or ceramide metabolism that influenced sensitivity to paclitaxel, with an RNA interference (RNAi) screen in three cancer cell lines, including a triple-negative breast-cancer cell line. Here, we assess these genes as a predictor of pCR to paclitaxel combination chemotherapy in triple-negative breast cancer. METHODS We derived a paclitaxel response metagene based on mitotic and ceramide genes identified by functional genomics studies. We used area under the curve (AUC) analysis and multivariate logistic regression to retrospectively assess the metagene in six cohorts of patients with triple-negative breast cancer treated with neoadjuvant chemotherapy; two cohorts treated with paclitaxel (n=27, 30) and four treated without paclitaxel (n=88, 28, 48, 39). FINDINGS The metagene was associated with pCR in paclitaxel-treated cohorts (AUC 0.79 [95% CI 0.53-0.93], 0.72 [0.48-0.90]) but not in non-paclitaxel treated cohorts (0.53 [0.31-0.77], 0.59 [0.22-0.82], 0.53 [0.36-0.71], 0.64 [0.43-0.81]). In multivariate logistic regression, the metagene was associated with pCR (OR 19.92, 2.62-151.57; p=0.0039) with paclitaxel-containing chemotherapy. INTERPRETATION The paclitaxel response metagene shows promise as a paclitaxel-specific predictor of pCR in patients with triple-negative breast cancer. The metagene is suitable for development into a reverse transcription-PCR assay, for which clinically relevant thresholds could be established in randomised clinical trials. These results highlight the potential for functional genomics to accelerate development of drug-specific predictive biomarkers without the need for training clinical trial cohorts. FUNDING UK Medical Research Council; Cancer Research UK; the National Institute for Health Research (UK); the Danish Council for Independent Research-Medical Sciences (FSS); Breast Cancer Research Foundation (New York); Fondation Luxembourgeoise contre le Cancer; the Fonds National de la Recherche Scientifique; Brussels Region (IRSIB-IP, Life Sciences 2007) and Walloon Region (Biowin-Keymarker); Sally Pearson Breast Cancer Fund; and the European Commission.

Egr-1 Induces the Expression of Its Corepressor Nab2 by Activation of the Nab2 Promoter Thereby Establishing a Negative Feedback Loop

The transcription factor Egr-1 regulates the expression of numerous genes involved in differentiation, growth, and in response to environmental signals. Egr-1 activity is modulated in part through the binding of corepressors Nab1 and Nab2. Nab2 appears crucial for controlling Egr-1-mediated transactivation because it is a delayed early response gene, induced by the same stimuli that induce the immediate early gene Egr-1. To identify important elements regulating Nab2 expression, we cloned the human Nab2 gene and investigated the 5′-region. The TATA- and initiator-less Nab2 promoter, located from –679 to –74 bp, contains a total of 11 Egr binding sites, including a cluster of multiple overlapping Egr/Sp1 sites between –329 and –260 bp. This region is critical for basal promoter activity as well as for maximum induction by phorbol esters. Electromobility shifts show that Sp1 binds to this region in normal and stimulated cells, whereas stimulation induces binding of Egr-1. In addition Egr-1 activates the Nab2 promoter in a pattern similar to phorbol esters, suggesting that Egr-1 is a major inducer of protein kinase C-mediated Nab2 induction. Depletion of Egr-1 by each of two distinct Egr-1 short-interfering RNAs reduces Nab2 expression and inducibility, confirming that Egr-1 is an important regulator of Nab2 expression. Transfection experiments show that Egr-1-induced Nab2 promoter activity is itself repressed by Nab2. These results indicate that Egr-1 mediates the induction of its own repressor, thereby preventing a permanent transactivation of Egr-1 target genes and a damaging overreaction in response to environmental signals.

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.

Cancer Evolution and the Limits of Predictability in Precision Cancer Medicine.

The ability to predict the future behavior of an individual cancer is crucial for precision cancer medicine. The discovery of extensive intratumor heterogeneity and ongoing clonal adaptation in human tumors substantiated the notion of cancer as an evolutionary process. Random events are inherent in evolution and tumor spatial structures hinder the efficacy of selection, which is the only deterministic evolutionary force. This review outlines how the interaction of these stochastic and deterministic processes, which have been extensively studied in evolutionary biology, limits cancer predictability and develops evolutionary strategies to improve predictions. Understanding and advancing the cancer predictability horizon is crucial to improve precision medicine outcomes.