Implications of Tumor Clonal Heterogeneity in the Era of Next-Generation Sequencing

Diversity of Intercellular Communication Modes: A Cancer Biology Perspective

From the moment a cell is on the path to malignant transformation, its interaction with other cells from the microenvironment becomes altered. The flow of molecular information is at the heart of the cellular and systemic fate in tumors, and various processes participate in conveying key molecular information from or to certain cancer cells. For instance, the loss of tight junction molecules is part of the signal sent to cancer cells so that they are no longer bound to the primary tumors and are thus free to travel and metastasize. Upon the targeting of a single cell by a therapeutic drug, gap junctions are able to communicate death information to by-standing cells. The discovery of the importance of novel modes of cell-cell communication such as different types of extracellular vesicles or tunneling nanotubes is changing the way scientists look at these processes. However, are they all actively involved in different contexts at the same time or are they recruited to fulfill specific tasks? What does the multiplicity of modes mean for the overall progression of the disease? Here, we extend an open invitation to think about the overall significance of these questions, rather than engage in an elusive attempt at a systematic repertory of the mechanisms at play.

Deciphering the spectrum of cutaneous lymphomas expressing TFH markers

T-follicular helper (TFH) markers are expressed in the microenvironnement of marginal zone B-cell lymphoma (MZL), and in lymphomas arising from TFH-cells, sometimes making the differential diagnosis difficult. In the skin, the "TFH-spectrum" is poorly defined, going from primary cutaneous lymphoproliferative disorder with small/medium CD4+ T-cells (SMLPD) to cutaneous localizations of systemic angioimmunoblastic T-cell lymphoma (cAITL), and may pass through intermediate forms (primary cutaneous T-follicular helper derived lymphoma, not otherwise specified (PCTFHL,NOS)). We retrospectively analyzed 20 MZL, 13 SMLPD, 5 PCTFHL, and 11 cAITL clinically, histologically, and molecularly, to define tools to differentiate them. Characteristics that might favor the diagnosis of MZL over SMLPD are: multiple skin nodules (p < 0.001), nodular architecture (p < 0.01), residual germinal centers with follicular dendritic cell network (p < 0.001), monotypic plasma cells (p < 0.001), and few staining with PD1 (p = 0.016) or CXCL13 (p = 0.03). PCTFHL and cAITL presented as multiple (p < 0.01) lesions, in older patients (p < 0.01), with systemic symptoms and/or biological alterations (p < 0.01). Immunophenotypic loss of T-cell markers (p < 0.001), BCL6 (p = 0.023) and/or CD10 staining (p = 0.08), and a higher proliferative index (≥ 30%, p = 0.039) favoured these diagnoses over SMLPD. Pathogenic variants were observed by genomic sequencing in 47% of MZL (TNFAIP3 (32%), EP300 (21%), NOTCH2 (16%), KMT2D (16%), CARD11 (10.5%)), 8% of SMLPD (TET2), 40% of PCTFHL (SOCS1 (20%), ARID1A (20%)) and 64% of cAITL (TET2 (63.6%), RHOA (36.4%), NOTCH1 (9%)). This study characterizes the various clinical and histological features between cutaneous lymphomas expressing TFH markers and highlights the value of the interest of screening for genomic mutations in difficult cases.

Development and validation of a chromatin regulator prognostic signature in colon adenocarcinoma

Aberrant expression of chromatin regulators (CRs) could lead to the development of various diseases including cancer. However, the biological function and prognosis role of CRs in colon adenocarcinoma (COAD) remains unclear. We performed the clustering analyses for expression profiling of COAD downloaded from The Cancer Genome Atlas. We developed a chromatin regulator prognostic model, which was validated in an independent cohort data. Time-intendent receiver operating characteristics curve was used to evaluate predict ability of model. Univariate and multivariate cox regression were used to assess independence of risk score. Nomogram was established to assess individual risk. Gene ontology, and Kyoto Encyclopedia of genes and genomes, gene set variation analysis and gene set enrichment analysis were performed to explore the function of CRs. Immune infiltration and drug sensitivity were also performed to assess effect of CRs on treatment in COAD. COAD can be separated into two subtypes with different clinical characteristics and prognosis. The C2 had elevated immune infiltration levels and low tumor purity. Using 12 chromatin regulators, we developed and validated a prognostic model that can predict the overall survival of COAD patients. We built a risk score that can be an independent prognosis predictor of COAD. The nomogram score system achieved the best predict ability and were also confirmed by decision curve analysis. There were significantly different function and pathway enrichment, immune infiltration levels, and tumor mutation burden between high-risk and low-risk group. The external validation data also indicated that high-risk group had higher stable disease/progressive disease response rate and poorer prognosis than low-risk group. Besides, the signature genes included in the model could cause chemotherapy sensitivity to some small molecular compounds. Our integrative analyses for chromatin regulators could provide new insights for the risk management and individualized treatment in COAD.

Targeting CREB in Cancer Therapy: A Key Candidate or One of Many? An Update

Simple Summary

Only 5% of all drug-related targets currently move from preclinical to clinical in cancer, and just some of them achieve patient’s bedside. Among others, intratumor heterogeneity and preclinical cancer model limitations actually represent the main reasons for this failure. Cyclic-AMP response element-binding protein (CREB) has been defined as a proto-oncogene in different tumor types, being involved in maintenance and progression. Due to its relevance in tumor pathophysiology, many CREB inhibitor compounds have been developed and tested over the years. Herein, we examine the current state-of-the-art of both CREB and CREB inhibitors in cancer, retracing some of the most significant findings of the last years. While the scientific statement confers on CREB a proactive role in cancer, its therapeutic potential is still stuck at laboratory bench. Therefore, pursuing every concrete result to achieve CREB inhibition in clinical might give chance and future to cancer patients worldwide.

Abstract

Intratumor heterogeneity (ITH) is considered the major disorienting factor in cancer treatment. As a result of stochastic genetic and epigenetic alterations, the appearance of a branched evolutionary shape confers tumor plasticity, causing relapse and unfavorable clinical prognosis. The growing evidence in cancer discovery presents to us “the great paradox” consisting of countless potential targets constantly discovered and a small number of candidates being effective in human patients. Among these, cyclic-AMP response element-binding protein (CREB) has been proposed as proto-oncogene supporting tumor initiation, progression and metastasis. Overexpression and hyperactivation of CREB are frequently observed in cancer, whereas genetic and pharmacological CREB downregulation affects proliferation and apoptosis. Notably, the present review is designed to investigate the feasibility of targeting CREB in cancer therapy. In particular, starting with the latest CREB evidence in cancer pathophysiology, we evaluate the advancement state of CREB inhibitor design, including the histone lysine demethylases JMJD3/UTX inhibitor GSKJ4 that we newly identified as a promising CREB modulator in leukemia cells. Moreover, an accurate analysis of strengths and weaknesses is also conducted to figure out whether CREB can actually represent a therapeutic candidate or just one of the innumerable preclinical cancer targets.

Assembling and Validating Bioinformatic Pipelines for Next-Generation Sequencing Clinical Assays

CONTEXT.—

Clinical next-generation sequencing (NGS) is being rapidly adopted, but analysis and interpretation of large data sets prompt new challenges for a clinical laboratory setting. Clinical NGS results rely heavily on the bioinformatics pipeline for identifying genetic variation in complex samples. The choice of bioinformatics algorithms, genome assembly, and genetic annotation databases are important for determining genetic alterations associated with disease. The analysis methods are often tuned to the assay to maximize accuracy. Once a pipeline has been developed, it must be validated to determine accuracy and reproducibility for samples similar to real-world cases. In silico proficiency testing or institutional data exchange will ensure consistency among clinical laboratories.

OBJECTIVE.—

To provide molecular pathologists a step-by-step guide to bioinformatics analysis and validation design in order to navigate the regulatory and validation standards of implementing a bioinformatic pipeline as a part of a new clinical NGS assay.

DATA SOURCES.—

This guide uses published studies on genomic analysis, bioinformatics methods, and methods comparison studies to inform the reader on what resources, including open source software tools and databases, are available for genetic variant detection and interpretation.

CONCLUSIONS.—

This review covers 4 key concepts: (1) bioinformatic analysis design for detecting genetic variation, (2) the resources for assessing genetic effects, (3) analysis validation assessment experiments and data sets, including a diverse set of samples to mimic real-world challenges that assess accuracy and reproducibility, and (4) if concordance between clinical laboratories will be improved by proficiency testing designed to test bioinformatic pipelines.

Cancer systems immunology

Tumor immunology is undergoing a renaissance due to the recent profound clinical successes of tumor immunotherapy. These advances have coincided with an exponential growth in the development of -omics technologies. Armed with these technologies and their associated computational and modeling toolsets, systems biologists have turned their attention to tumor immunology in an effort to understand the precise nature and consequences of interactions between tumors and the immune system. Such interactions are inherently multivariate, spanning multiple time and size scales, cell types, and organ systems, rendering systems biology approaches particularly amenable to their interrogation. While in its infancy, the field of 'Cancer Systems Immunology' has already influenced our understanding of tumor immunology and immunotherapy. As the field matures, studies will move beyond descriptive characterizations toward functional investigations of the emergent behavior that govern tumor-immune responses. Thus, Cancer Systems Immunology holds incredible promise to advance our ability to fight this disease.

Genetics of progression from MDS to secondary leukemia

Our understanding of the genetics of acute myeloid leukemia (AML) development from myelodysplastic syndrome (MDS) has advanced significantly as a result of next-generation sequencing technology. Although differences in cell biology and maturation exist between MDS and AML secondary to MDS, these 2 diseases are genetically related. MDS and secondary AML cells harbor mutations in many of the same genes and functional categories, including chromatin modification, DNA methylation, RNA splicing, cohesin complex, transcription factors, cell signaling, and DNA damage, confirming that they are a disease continuum. Differences in the frequency of mutated genes in MDS and secondary AML indicate that the order of mutation acquisition is not random during progression. In almost every case, disease progression is associated with clonal evolution, typically defined by the expansion or emergence of a subclone with a unique set of mutations. Monitoring tumor burden and clonal evolution using sequencing provides advantages over using the blast count, which underestimates tumor burden, and could allow for early detection of disease progression prior to clinical deterioration. In this review, we outline advances in the study of MDS to secondary AML progression, with a focus on the genetics of progression, and discuss the advantages of incorporating molecular genetic data in the diagnosis, classification, and monitoring of MDS to secondary AML progression. Because sequencing is becoming routine in the clinic, ongoing research is needed to define the optimal assay to use in different clinical situations and how the data can be used to improve outcomes for patients with MDS and secondary AML.

What makes leader cells arise: Intrinsic properties and support from neighboring cells

Cancer cells collectively invading as a cohesive and polarized group is termed collective invasion, which is a fundamental property of many types of cancers. In this multicellular unit, cancer cells are heterogeneous, consisting of two morphologically and functionally distinct subpopulations, leader cells and follower cells. Leader cells at the invasive front are responsible for exploring the microenvironment, paving the way, and transmitting information to follower cells. Here, in this review, we will describe the important role of leader cells in collective invasion and the emerging underlying mechanisms of leader cell formation including intrinsic properties and the support from neighboring cells. It will help us to elucidate the essence of collective invasion and provide new anticancer therapeutic clues.

Identification of circulating tumor DNA using a targeted 545-gene next generation sequencing panel in patients with gastric cancer

Gastric cancer (GC) is characterized by unique genetic aberrations. Some of these mutations may be used to predict tumor prognosis or to guide patient therapy. Cell-free circulating tumor DNA (ctDNA) has been considered a promising alternative to biopsy to identify genome aberrations. However, no standardized methods to detect ctDNA variations in patients with GC are currently available. In the present study, the targeted sequencing of 545 genes was used to identify somatic alterations in tissues and matched plasma samples of nine patients with GC. Driver gene mutations were detected in matched tissues and plasma ctDNA. The mutated reads concordance rate of ctDNA in GC tissues with matched tissues was 45%. A true positive copy number gain of human epidermal growth factor receptor 2 in plasma from patients with GC was identified. Furthermore, the ctDNA fraction in plasma cell-free DNA (cfDNA) was positively correlated with metastasis lymph node number and with lactate dehydrogenase level. In conclusion, results from the present study suggested that targeted sequencing of plasma ctDNA may be considered a potential option for the clinical monitoring of GC.

Clonal relationship of synchronous head and neck cancer and esophageal cancer assessed by single nucleotide polymorphism-based loss of heterozygosity analysis

Background

The prognoses of head and neck squamous cell carcinoma (HNSCC) and esophageal squamous cell carcinoma (ESCC) are poor, especially when both tumors occur at the same time. We examined the clonal relatedness of HNSCCs with synchronous ESCCs to confirm whether the second tumors were metastasis or separate second primary malignancies (SPMs) using loss of heterozygosity (LOH) analysis.

Methods

Twenty-one pairs of formalin-fixed paraffin-embedded tissue from HNSCC patients with synchronous esophageal cancer were analyzed by single nucleotide polymorphism (SNP) array using the Illumina HumanCytoSNP FFPE-12 BeadChip (San Diego, CA), which contains approximately 300,000 probes. LOH was identified using Nexus Copy Number software (El Segundo, CA).

Results

Comparing the LOH pattern between HNSCC and paired ESCC, we found that 20 out of 21 paired tissues had a high number of discordant LOHs (LOH identified solely in the primary HNSCC but not in synchronous ESCC at the same genomic location) and a low number of concordant LOHs (LOH at the same genomic location in both HNSCC and ESCC). Only one case fell into the undetermined category. Therefore, these 20 ESCCs were classified as SPMs or second field tumors (SFTs). Moreover, the HNSCC patients with molecularly confirmed esophageal SPM had significantly poorer survival than the other patients.

Conclusions

We propose the use of a genome-wide SNP array as a tool to differentiate metastatic tumors from SPM/SFT. The SNP array offers genome-wide LOH information that earlier microsatellite analysis studies lack. The ability to accurately identify SPM should contribute to a better treatment plan and follow-up care of these patients.

Association of metabolic and genetic heterogeneity in head and neck squamous cell carcinoma with prognostic implications: integration of FDG PET and genomic analysis

Purpose

The linkage between the genetic and phenotypic heterogeneity of the tumor has not been thoroughly evaluated. Herein, we investigated how the genetic and metabolic heterogeneity features of the tumor are associated with each other in head and neck squamous cell carcinoma (HNSC). We further assessed the prognostic significance of those features.

Methods

The mutant-allele tumor heterogeneity (MATH) score (n = 508), a genetic heterogeneity feature, and tumor glycolysis feature (GlycoS) (n = 503) were obtained from the HNSC dataset in the cancer genome atlas (TCGA). We identified matching patients (n = 33) who underwent 18F-fluorodeoxyglucose positron emission tomography (FDG PET) from the cancer imaging archive (TCIA) and obtained the following information from the primary tumor: metabolic, metabolic-volumetric, and metabolic heterogeneity features. The association between the genetic and metabolic features and their prognostic values were assessed.

Results

Tumor metabolic heterogeneity and metabolic-volumetric features showed a mild degree of association with MATH (n = 25, ρ = 0.4~0.5, P < 0.05 for all features). The patients with higher FDG PET features and MATH died sooner. Combination of MATH and tumor metabolic heterogeneity features showed a better stratification of prognosis than MATH. Also, higher MATH and GlycoS were associated with significantly worse overall survival (n = 499, P = 0.002 and 0.0001 for MATH and GlycoS, respectively). Furthermore, both MATH and GlycoS independently predicted overall survival after adjusting for clinicopathologic features and the other (P = 0.015 and 0.006, respectively).

Conclusion

Both tumor metabolic heterogeneity and metabolic-volumetric features assessed by FDG PET showed a mild degree of association with genetic heterogeneity in HNSC. Both metabolic and genetic heterogeneity features were predictive of survival and there was an additive prognostic value when the metabolic and genetic heterogeneity features were combined. Also, MATH and GlycoS were independent prognostic factors in HNSC; they can be used for precise prognostication once validated.

Circulating tumor DNA analyses predict progressive disease and indicate trastuzumab-resistant mechanism in advanced gastric cancer

Background

Circulating tumor DNA (ctDNA) isolated from plasma contains genetic mutations that can be representative of those found in primary tumor tissue DNA. These samples can provide insights into tumoral heterogeneity in patients with advanced gastric cancer (AGC). Although trastuzumab has been shown to be effective in first-line therapy for patients with metastatic gastric cancer with overexpression of human epidermal growth factor receptor 2 (HER2), the mechanism of AGC resistance is incompletely understood.

Methods

In this prospective study, we used targeted capture sequencing to analyze 173 serial ctDNA samples from 39 AGC patients. We analyzed cancer cell fractions with PyClone to understand the clonal population structure in cancer, and monitored serial samples during therapy. Serial monitoring of ctDNA using the molecular tumor burden index (mTBI), identified progressive disease before imaging results (mean: 18 weeks).

Findings

We reconstructed the clonal structure of ctDNA during anti-HER2 treatment, and identified 32 expanding mutations potentially related to trastuzumab resistance. Multiple pathways activating in the same patients revealed heterogeneity in trastuzumab resistance mechanisms in AGC. In patients who received chemotherapy, mTBI was validated for the prediction of progressive disease, with a sensitivity of 94% (15/16). A higher mTBI (≥1%) in pretreatment ctDNA was also a risk factor for progression-free survival.

Conclusions

Analysis of ctDNA clones based on sequencing is a promising approach to clinical management, and may lead to improved therapeutic strategies for AGC patients.

Fund

This work was supported by grants from the National International Cooperation Grant (to J.X.; Project No. 2014DFB33160).

Cancer stem cell mobilization and therapeutic targeting of the 5T4 oncofetal antigen

Cancer stem cells (CSCs) can act as the cellular drivers of tumors harnessing stem cell properties that contribute to tumorigenesis either as founder elements or by the gain of stem cell traits by the malignant cells. Thus, CSCs can self-renew and generate the cellular heterogeneity of tumors including a hierarchical organization similar to the normal tissue. While the principle tumor growth contribution is often from the non-CSC components, it is the ability of small numbers of CSCs to avoid the effects of therapeutic strategies that can contribute to recurrence after treatment. However, identifying and characterizing CSCs for therapeutic targeting is made more challenging by their cellular potency being influenced by a particular tissue niche or by the capacity of more committed cells to regain stem cell functions. This review discusses the properties of CSCs including the limitations of the available cell surface markers, the assays that document tumor initiation and clonogenicity, the roles of epithelial mesenchymal transition and molecular pathways such as Notch, Wnt, Hippo and Hedgehog. The ability to target and eliminate CSCs is thought to be critical in the search for curative cancer treatments. The oncofetal tumor-associated antigen 5T4 (TBGP) has been linked with CSC properties in several different malignancies. 5T4 has functional attributes that are relevant to the spread of tumors including through EMT, CXCR4/CXCL12, Wnt, and Hippo pathways which may all contribute through the mobilization of CSCs. There are several different immunotherapies targeting 5T4 in development including antibody-drug conjugates, antibody-targeted bacterial super-antigens, a Modified Vaccinia Ankara-basedvaccine and 5T4-directed chimeric antigen receptor T-cells. These immune therapies would have the advantage of targeting both the bulk tumor as well as mobilized CSC populations.

Bioinformatics Analysis of Whole Exome Sequencing Data

This chapter contains a step-by-step protocol for identifying somatic SNPs and small Indels from next-generation sequencing data of tumor samples and matching normal samples. The workflow presented here is largely based on the Broad Institute's "Best Practices" guidelines and makes use of their Genome Analysis Toolkit (GATK) platform. Variants are annotated with population allele frequencies and curated resources such as GnomAD and ClinVar and curated effect predictions from dbNSFP using VCFtools, SnpEff, and SnpSift.

Reliability of algorithmic somatic copy number alteration detection from targeted capture data

Motivation

Whole exome and gene panel sequencing are increasingly used for oncological diagnostics. To investigate the accuracy of SCNA detection algorithms on simulated and clinical tumor samples, the precision and sensitivity of four SCNA callers were measured using 50 simulated whole exome and 50 simulated targeted gene panel datasets, and using 119 TCGA tumor samples for which SNP array data were available.

Results

On synthetic exome and panel data, VarScan2 mostly called false positives, whereas Control-FREEC was precise (>90% correct calls) at the cost of low sensitivity (<40% detected). ONCOCNV was slightly less precise on gene panel data, with similarly low sensitivity. This could be explained by low sensitivity for amplifications and high precision for deletions. Surprisingly, these results were not strongly affected by moderate tumor impurities; only contaminations with more than 60% non-cancerous cells resulted in strongly declining precision and sensitivity. On the 119 clinical samples, both Control-FREEC and CNVkit called 71.8% and 94%, respectively, of the SCNAs found by the SNP arrays, but with a considerable amount of false positives (precision 29% and 4.9%).

Discussion

Whole exome and targeted gene panel methods by design limit the precision of SCNA callers, making them prone to false positives. SCNA calls cannot easily be integrated in clinical pipelines that use data from targeted capture-based sequencing. If used at all, they need to be cross-validated using orthogonal methods.

Availability and implementation

Scripts are provided as supplementary information.

Supplementary information

Supplementary data are available at Bioinformatics online.

Recent Advances in Prostate Cancer Treatment and Drug Discovery

Novel drugs, drug sequences and combinations have improved the outcome of prostate cancer in recent years. The latest approvals include abiraterone acetate, enzalutamide and apalutamide which target androgen receptor (AR) signaling, radium-223 dichloride for reduction of bone metastases, sipuleucel-T immunotherapy and taxane-based chemotherapy. Adding abiraterone acetate to androgen deprivation therapy (ADT) in order to achieve complete androgen blockade has proven highly beneficial for treatment of locally advanced prostate cancer and metastatic hormone-sensitive prostate cancer (mHSPC). Also, ADT together with docetaxel treatment showed significant benefit in mHSPC. Ongoing clinical trials for different subgroups of prostate cancer patients include the evaluation of the second-generation AR antagonists enzalutamide, apalutamide and darolutamide, of inhibitors of the phosphatidylinositol-4,5-bisphosphate 3-kinase (PI3K) pathway, of inhibitors of DNA damage response, of targeted alpha therapy and of prostate-specific membrane antigen (PSMA) targeting approaches. Advanced clinical studies with immune checkpoint inhibitors have shown limited benefits in prostate cancer and more trials are needed to demonstrate efficacy. The identification of improved, personalized treatments will be much supported by the major progress recently made in the molecular characterization of early- and late-stage prostate cancer using “omics” technologies. This has already led to novel classifications of prostate tumors based on gene expression profiles and mutation status, and should greatly help in the choice of novel targeted therapies best tailored to the needs of patients.

Subclones dominate at MDS progression following allogeneic hematopoietic cell transplant

Allogeneic hematopoietic cell transplantation (alloHCT) is a potentially curative treatment for myelodysplastic syndromes (MDS), but patients who relapse after transplant have poor outcomes. In order to understand the contribution of tumor clonal evolution to disease progression,we applied exome and error-corrected targeted sequencing coupled with copy number analysis to comprehensively define changes in the clonal architecture of MDS in response to therapy using 51 serially acquired tumor samples from 9 patients who progressed after an alloHCT. We show that small subclones before alloHCT can drive progression after alloHCT. Notably, at least one subclone expanded or emerged at progression in all patients. Newly acquired structural variants (SVs) were present in an emergent/expanding subclone in 8 of 9 patients at progression, implicating the acquisition of SVs as important late subclonal progression events. In addition, pretransplant therapy with azacitidine likely influenced the mutation spectrum and evolution of emergent subclones after alloHCT. Although subclone evolution is common, founding clone mutations are always present at progression and could be detected in the bone marrow as early as 30 and/or 100 days after alloHCT in 6 of 8 (75%) patients, often prior to clinical progression. In conclusion, MDS progression after alloHCT is characterized by subclonal expansion and evolution, which can be influenced by pretransplant therapy.

Targeted sequencing reveals TP53 as a potential diagnostic biomarker in the post-treatment surveillance of head and neck cancer

Head and neck squamous cell carcinomas (HNSCC) form a large heterogeneous group of tumors and have a relatively poor outcome in advanced cases. Revealing the underlying genetic mutations in HNSCC facilitates the development of diagnostic biomarkers, which might lead to improved diagnosis and post treatment surveillance. We retrospectively analyzed mutational hotspots using targeted next-generation sequencing (NGS) of 239 HNSCC tumor samples in order to examine the mutational profile of HNSCC. Furthermore, we assessed prevalence, co-occurrence, and synonymy of gene mutations in (matched) tumor samples. TP53 was found mutated the most frequent with mutation rates of up to 83% in all tumors, compared to mutation rates of between 0 and 21% of CDKN2A, PIK3CA, HRAS, CDK4, FBXW7 and RB1. Mutational co-occurrence predominantly existed between TP53 and PIK3CA, TP53 and CDKN2A, and HRAS and PIK3CA. Mutational synonymy between primary tumor and associated metastasis and recurrence was present in respectively 88% and 89%. TP53 mutations were concordantly mutated in 95% of metastases and in 91% of recurrences. This indicates TP53 mutations to be highly prevalent and concordant in primary tumors and associated locoregional metastases and recurrences. In turn, this provides ground for further investigating the use of TP53 mutations as diagnostic biomarkers in HNSCC patients.

Comprehensive benchmarking of SNV callers for highly admixed tumor data

Precision medicine attempts to individualize cancer therapy by matching tumor-specific genetic changes with effective targeted therapies. A crucial first step in this process is the reliable identification of cancer-relevant variants, which is considerably complicated by the impurity and heterogeneity of clinical tumor samples. We compared the impact of admixture of non-cancerous cells and low somatic allele frequencies on the sensitivity and precision of 19 state-of-the-art SNV callers. We studied both whole exome and targeted gene panel data and up to 13 distinct parameter configurations for each tool. We found vast differences among callers. Based on our comprehensive analyses we recommend joint tumor-normal calling with MuTect, EBCall or Strelka for whole exome somatic variant calling, and HaplotypeCaller or FreeBayes for whole exome germline calling. For targeted gene panel data on a single tumor sample, LoFreqStar performed best. We further found that tumor impurity and admixture had a negative impact on precision, and in particular, sensitivity in whole exome experiments. At admixture levels of 60% to 90% sometimes seen in pathological biopsies, sensitivity dropped significantly, even when variants were originally present in the tumor at 100% allele frequency. Sensitivity to low-frequency SNVs improved with targeted panel data, but whole exome data allowed more efficient identification of germline variants. Effective somatic variant calling requires high-quality pathological samples with minimal admixture, a consciously selected sequencing strategy, and the appropriate variant calling tool with settings optimized for the chosen type of data.

Visualizing Clonal Evolution in Cancer

Rapid and inexpensive single-cell sequencing is driving new visualizations of cancer instability and evolution. Krzywinski discusses how to present clone evolution plots in order to visualize temporal, phylogenetic, and spatial aspects of a tumor in a single static image.

Image-guided genomics of phenotypically heterogeneous populations reveals vascular signalling during symbiotic collective cancer invasion

Phenotypic heterogeneity is widely observed in cancer cell populations. Here, to probe this heterogeneity, we developed an image-guided genomics technique termed spatiotemporal genomic and cellular analysis (SaGA) that allows for precise selection and amplification of living and rare cells. SaGA was used on collectively invading 3D cancer cell packs to create purified leader and follower cell lines. The leader cell cultures are phenotypically stable and highly invasive in contrast to follower cultures, which show phenotypic plasticity over time and minimally invade in a sheet-like pattern. Genomic and molecular interrogation reveals an atypical VEGF-based vasculogenesis signalling that facilitates recruitment of follower cells but not for leader cell motility itself, which instead utilizes focal adhesion kinase-fibronectin signalling. While leader cells provide an escape mechanism for followers, follower cells in turn provide leaders with increased growth and survival. These data support a symbiotic model of collective invasion where phenotypically distinct cell types cooperate to promote their escape.

The mechanisms linking phenotypic heterogeneity to collective cancer invasion are unclear. Here the authors develop an image-guided genomic technique to select and amplify leader and follower cells from in vitro invading cell packs and find a cooperative symbiotic relationship between these two cell populations.

Circulating biomarkers to monitor cancer progression and treatment

Tumor heterogeneity is a major challenge and the root cause of resistance to treatment. Still, the standard diagnostic approach relies on the analysis of a single tumor sample from a local or metastatic site that is obtained at a given time point. Due to intratumoral heterogeneity and selection of subpopulations in diverse lesions this will provide only a limited characterization of the makeup of the disease. On the other hand, recent developments of nucleic acid sequence analysis allows to use minimally invasive serial blood samples to assess the mutational status and altered gene expression patterns for real time monitoring in individual patients. Here, we focus on cell-free circulating tumor-specific mutant DNA and RNA (including mRNA and non-coding RNA), as well as current limitations and challenges associated with circulating nucleic acids biomarkers.