Mariam Jamal-Hanjani

Clonal neoantigens elicit T cell immunoreactivity and sensitivity to immune checkpoint blockade

The cellular ancestry of tumor antigens One contributing factor in antitumor immunity is the repertoire of neoantigens created by genetic mutations within tumor cells. Like the corresponding mutations, these neoantigens show intratumoral heterogeneity. Some are present in all tumor cells (clonal), and others are present in only a fraction of cells (subclonal). In a study of lung cancer and melanoma, McGranahan et al. found that a high burden of clonal tumor neoantigens correlated with improved patient survival, an increased presence of tumor-infiltrating lymphocytes, and a durable response to immunotherapy. Science, this issue p. 1463 Analysis of the cellular ancestry of tumor neoantigens can predict which are most likely to induce an immune response. As tumors grow, they acquire mutations, some of which create neoantigens that influence the response of patients to immune checkpoint inhibitors. We explored the impact of neoantigen intratumor heterogeneity (ITH) on antitumor immunity. Through integrated analysis of ITH and neoantigen burden, we demonstrate a relationship between clonal neoantigen burden and overall survival in primary lung adenocarcinomas. CD8+ tumor-infiltrating lymphocytes reactive to clonal neoantigens were identified in early-stage non–small cell lung cancer and expressed high levels of PD-1. Sensitivity to PD-1 and CTLA-4 blockade in patients with advanced NSCLC and melanoma was enhanced in tumors enriched for clonal neoantigens. T cells recognizing clonal neoantigens were detectable in patients with durable clinical benefit. Cytotoxic chemotherapy–induced subclonal neoantigens, contributing to an increased mutational load, were enriched in certain poor responders. These data suggest that neoantigen heterogeneity may influence immune surveillance and support therapeutic developments targeting clonal neoantigens.

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

Tracking the Evolution of Non–Small-Cell Lung Cancer

BACKGROUND Among patients with non‐small‐cell lung cancer (NSCLC), data on intratumor heterogeneity and cancer genome evolution have been limited to small retrospective cohorts. We wanted to prospectively investigate intratumor heterogeneity in relation to clinical outcome and to determine the clonal nature of driver events and evolutionary processes in early‐stage NSCLC. METHODS In this prospective cohort study, we performed multiregion whole‐exome sequencing on 100 early‐stage NSCLC tumors that had been resected before systemic therapy. We sequenced and analyzed 327 tumor regions to define evolutionary histories, obtain a census of clonal and subclonal events, and assess the relationship between intratumor heterogeneity and recurrence‐free survival. RESULTS We observed widespread intratumor heterogeneity for both somatic copy‐number alterations and mutations. Driver mutations in EGFR, MET, BRAF, and TP53 were almost always clonal. However, heterogeneous driver alterations that occurred later in evolution were found in more than 75% of the tumors and were common in PIK3CA and NF1 and in genes that are involved in chromatin modification and DNA damage response and repair. Genome doubling and ongoing dynamic chromosomal instability were associated with intratumor heterogeneity and resulted in parallel evolution of driver somatic copy‐number alterations, including amplifications in CDK4, FOXA1, and BCL11A. Elevated copy‐number heterogeneity was associated with an increased risk of recurrence or death (hazard ratio, 4.9; P=4.4×10‐4), which remained significant in multivariate analysis. CONCLUSIONS Intratumor heterogeneity mediated through chromosome instability was associated with an increased risk of recurrence or death, a finding that supports the potential value of chromosome instability as a prognostic predictor. (Funded by Cancer Research UK and others; TRACERx ClinicalTrials.gov number, NCT01888601.)

Translational Implications of Tumor Heterogeneity

Advances in next-generation sequencing and bioinformatics have led to an unprecedented view of the cancer genome and its evolution. Genomic studies have demonstrated the complex and heterogeneous clonal landscape of tumors of different origins and the potential impact of intratumor heterogeneity on treatment response and resistance, cancer progression, and the risk of disease relapse. However, the significance of subclonal mutations, in particular mutations in driver genes, and their evolution through time and their dynamics in response to cancer therapies, is yet to be determined. The necessary tools are now available to prospectively determine whether clonal heterogeneity can be used as a biomarker of clinical outcome and to what extent subclonal somatic alterations might influence clinical outcome. Studies that use longitudinal tissue sampling, integrating both genomic and clinical data, have the potential to reveal the subclonal composition and track the evolution of tumors to address these questions and to begin to define the breadth of genetic diversity in different tumor types and its relevance to patient outcome. Such studies may provide further evidence for drug-resistance mechanisms informing combinatorial, adaptive, and tumor immune therapies placed within the context of tumor evolution. Clin Cancer Res; 21(6); 1258–66. ©2015 AACR.

Tracking genomic cancer evolution for precision medicine: the lung TRACERx study.

TRACERx, a prospective study of patients with primary non-small cell lung cancer, aims to map the genomic landscape of lung cancer by tracking clonal heterogeneity and tumour evolution from diagnosis to relapse.

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. Copyright

Anticancer effects of metformin and its potential use as a therapeutic agent for breast cancer

Metformin is an orally available, biguanide derivative that is widely used in the treatment of Type 2 diabetes. Recent preclinical data have demonstrated that it can also act as an anticancer agent by activation of AMPK and subsequent inhibition of mTOR. Metformin is currently being investigated in several Phase II/III clinical trials. This article will review the current evidence for its mechanism of action, efficacy in preclinical and clinical models, and toxicity. Ongoing and planned studies evaluating the impact of metformin on breast cancer outcomes are also discussed.

Tumour heterogeneity and immune-modulation

Highlights • Intratumour heterogeneity (ITH) has been demonstrated in various tumour types.• Distinct clonal subpopulations can exist within different regions of a tumour.• ITH has evident implications for cancer diagnosis and treatment.• There is increasing evidence for the association between ITH and drug resistance.• ITH may allow the effective use of immunotherapeutics against tumour neo-antigens.

Tracking Cancer Evolution Reveals Constrained Routes to Metastases: TRACERx Renal

Summary Clear-cell renal cell carcinoma (ccRCC) exhibits a broad range of metastatic phenotypes that have not been systematically studied to date. Here, we analyzed 575 primary and 335 metastatic biopsies across 100 patients with metastatic ccRCC, including two cases sampledat post-mortem. Metastatic competence was afforded by chromosome complexity, and we identify 9p loss as a highly selected event driving metastasis and ccRCC-related mortality (p = 0.0014). Distinct patterns of metastatic dissemination were observed, including rapid progression to multiple tissue sites seeded by primary tumors of monoclonal structure. By contrast, we observed attenuated progression in cases characterized by high primary tumor heterogeneity, with metastatic competence acquired gradually and initial progression to solitary metastasis. Finally, we observed early divergence of primitive ancestral clones and protracted latency of up to two decades as a feature of pancreatic metastases.

Deterministic Evolutionary Trajectories Influence Primary Tumor Growth: TRACERx Renal

Summary The evolutionary features of clear-cell renal cell carcinoma (ccRCC) have not been systematically studied to date. We analyzed 1,206 primary tumor regions from 101 patients recruited into the multi-center prospective study, TRACERx Renal. We observe up to 30 driver events per tumor and show that subclonal diversification is associated with known prognostic parameters. By resolving the patterns of driver event ordering, co-occurrence, and mutual exclusivity at clone level, we show the deterministic nature of clonal evolution. ccRCC can be grouped into seven evolutionary subtypes, ranging from tumors characterized by early fixation of multiple mutational and copy number drivers and rapid metastases to highly branched tumors with >10 subclonal drivers and extensive parallel evolution associated with attenuated progression. We identify genetic diversity and chromosomal complexity as determinants of patient outcome. Our insights reconcile the variable clinical behavior of ccRCC and suggest evolutionary potential as a biomarker for both intervention and surveillance.