An analysis of genetic heterogeneity in untreated cancers

Mutational Landscape and Evolutionary Pattern of Liver and Brain Metastasis in Lung Adenocarcinoma

INTRODUCTION

A comprehensive genomic analysis of paired primary tumors and their metastatic lesions may provide new insights into the biology of metastatic processes and therefore guide the development of novel strategies for intervention. To date, our knowledge of the genetic divergence and phylogenetic relationships among diverse metastatic lesions from cancer remains limited.

METHODS

We performed whole-exome sequencing in 84 tissue and blood samples from 26 patients with lung adenocarcinoma having liver metastases (LiM) or brain metastases (BrM) before any systemic therapy, with the goal to molecularly characterize the metastatic process. Mutational landscape and evolutionary patterns were compared between paired primary lesions (primary lesion of LiM or BrM) and metastases (metastatic site of LiM or BrM).

RESULTS

We found that common driver mutations, including TP53 and EGFR, were highly consistent between paired primary and metastatic tumors. Although tumor mutational burden was comparable among groups, the LiM group had significantly higher mutational and copy number variational similarity than the BrM group between paired primary lesions and metastases (p = 0.019 and p = 0.035, respectively). Phylogenetic analysis further revealed that LiM-competent disseminations had a higher level of genetic similarity to their paired primary lesions and were genetically diverged from their primary tumors at a relatively later stage than those of BrM. These results suggest that LiM favorably followed the linear progression model, whereas BrM was more consistent with the parallel progression model.

CONCLUSIONS

This study suggests that the mutational landscape and evolutionary pattern was distinctly different between the LiM and BrM of lung adenocarcinoma.

Recurring urothelial carcinomas show genomic rearrangements incompatible with a direct relationship

We used the fact that patients with non-muscle invasive bladder tumors show local recurrences and multiple tumors to study re-initiation of tumor growth from the same urothelium. By extensive genomic analyses we show that tumors from the same patient are clonal. We show that gross genomic chromosomal aberrations may be detected in one tumor, only to be undetected in a recurrent tumor. By analyses of incompatible changes i.e., genomic alterations that cannot be reversed, we show that almost all tumors from a single patient may show such changes, thus the tumors cannot have originated from each other. As recurring tumors share both genomic alterations and driver gene mutations, these must have been present in the urothelium in periods with no tumor growth. We present a model that includes a growing and evolving field of urothelial cells that occasionally, and locally, produce bursts of cellular growth leading to overt tumors.

Breast Cancer Heterogeneity and Response to Novel Therapeutics

Simple Summary

Breast cancer is a heterogeneous disease that is driven by genetic, epigenetic and phenotypic modifications and is also affected by the microenvironment and the metabolism. In this article we review genetic and non-genetic causes of tumor heterogeneity focusing on the impact that heterogeneity has on resistance to therapy. We will provide examples of personalized medicines and their translation to the clinic.

Abstract

Targeted cancer therapies against oncogenic drivers are actively being developed and tested in clinical trials. Targeting an oncogenic driver may only prove effective if the mutation is present in most tumoral cells. Therefore, highly heterogeneous tumors may be refractory to these therapies. This makes tumor heterogeneity a major challenge in cancer therapy. Although heterogeneity has traditionally been attributed to genetic diversity within cancer cell populations, it is now widely recognized that human cancers are heterogeneous in almost all distinguishable phenotypic characteristics. Understanding the genetic variability and also the non-genetic influences of tumor heterogeneity will provide novel insights into how to reverse therapeutic resistance and improve cancer therapy.

Redefining Colorectal Cancer by Tumor Biology

Colorectal cancer treatment has undergone a paradigm shift. We no longer see this disease as a singular, anatomic tumor type but rather a set of disease subgroups. Largely because of a better understanding of cancer biology and the introduction and integration of molecular biomarkers-the premise of precision therapy-we are beginning to direct treatments toward the right tumor target(s) in the right patients. The field of molecular profiling is continually evolving, and new biomarkers are constantly being discovered that have investigational, therapeutic, and/or prognostic implications-negative or positive. To date, only a few biomarkers have sufficient actionable, clinical implication to earn international guideline-recommended routine testing. Hence, it is vital that the treating oncologist should know which biomarkers to assess, when in the treatment course to test for them, and how the test is to be done. Correct interpretation of profiling results is imperative. Herein, we focus on international guideline-recommended mutation testing for patients prior to their colorectal cancer treatment initiation. The clinical applications of circulating tumor DNA (ctDNA) in patients with metastatic disease, based on our current knowledge and capabilities, are also addressed.

The Tumor Microenvironment of Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) has a dismal prognosis along with rising incidence rates and will be responsible for many cancer deaths in the future [...].

Prognostic significance of postsurgery circulating tumor DNA in nonmetastatic colorectal cancer: Individual patient pooled analysis of three cohort studies

Studies in multiple solid tumor types have demonstrated the prognostic significance of ctDNA analysis after curative intent surgery. A combined analysis of data across completed studies could further our understanding of circulating tumor DNA (ctDNA) as a prognostic marker and inform future trial design. We combined individual patient data from three independent cohort studies of nonmetastatic colorectal cancer (CRC). Plasma samples were collected 4 to 10 weeks after surgery. Mutations in ctDNA were assayed using a massively parallel sequencing technique called SafeSeqS. We analyzed 485 CRC patients (230 Stage II colon, 96 Stage III colon, and 159 locally advanced rectum). ctDNA was detected after surgery in 59 (12%) patients overall (11.0%, 12.5% and 13.8% for samples taken at 4-6, 6-8 and 8-10 weeks; P = .740). ctDNA detection was associated with poorer 5-year recurrence-free (38.6% vs 85.5%; P < .001) and overall survival (64.6% vs 89.4%; P < .001). The predictive accuracy of postsurgery ctDNA for recurrence was higher than that of individual clinicopathologic risk features. Recurrence risk increased exponentially with increasing ctDNA mutant allele frequency (MAF) (hazard ratio, 1.2, 2.5 and 5.8 for MAF of 0.1%, 0.5% and 1%). Postsurgery ctDNA was detected in 3 of 20 (15%) patients with locoregional and 27 of 60 (45%) with distant recurrence (P = .018). This analysis demonstrates a consistent long-term impact of ctDNA as a prognostic marker across nonmetastatic CRC, where ctDNA outperforms other clinicopathologic risk factors and MAF further stratifies recurrence risk. ctDNA is a better predictor of distant vs locoregional recurrence.

A compendium of mutational cancer driver genes

A fundamental goal in cancer research is to understand the mechanisms of cell transformation. This is key to developing more efficient cancer detection methods and therapeutic approaches. One milestone towards this objective is the identification of all the genes with mutations capable of driving tumours. Since the 1970s, the list of cancer genes has been growing steadily. Because cancer driver genes are under positive selection in tumorigenesis, their observed patterns of somatic mutations across tumours in a cohort deviate from those expected from neutral mutagenesis. These deviations, which constitute signals of positive selection, may be detected by carefully designed bioinformatics methods, which have become the state of the art in the identification of driver genes. A systematic approach combining several of these signals could lead to a compendium of mutational cancer genes. In this Review, we present the Integrative OncoGenomics (IntOGen) pipeline, an implementation of such an approach to obtain the compendium of mutational cancer drivers. Its application to somatic mutations of more than 28,000 tumours of 66 cancer types reveals 568 cancer genes and points towards their mechanisms of tumorigenesis. The application of this approach to the ever-growing datasets of somatic tumour mutations will support the continuous refinement of our knowledge of the genetic basis of cancer.

High-metastatic cancer cells derived exosomal miR92a-3p promotes epithelial-mesenchymal transition and metastasis of low-metastatic cancer cells by regulating PTEN/Akt pathway in hepatocellular carcinoma

Exosomes play an important role in intercellular communication and metastatic progression of hepatocellular carcinoma (HCC). However, cellular communication between heterogeneous HCC cells with different metastatic potentials and the resultant cancer progression are not fully understood in HCC. Here, HCC cells with high-metastatic capacity (97hm and Huhm) were constructed by continually exerting selective pressure on primary HCC cells (MHCC-97H and Huh7). Through performing exosomal miRNA sequencing in HCC cells with different metastatic potentials (MHCC-97H and 97hm), many significantly different miRNA candidates were found. Among these miRNAs, miR-92a-3p was the most abundant miRNA in the exosomes of highly metastatic HCC cells. Exosomal miR92a-3p was also found enriched in the plasma of HCC patient-derived xenograft mice (PDX) model with high-metastatic potential. Exosomal miR-92a-3p promotes epithelial-mesenchymal transition (EMT) in recipient cancer cells via targeting PTEN and regulating its downstream Akt/Snail signaling. Furthermore, through mRNA sequencing in HCC cells with different metastatic potentials and predicting potential transcription factors of miR92a-3p, upregulated transcript factors E2F1 and c-Myc were found in high-metastatic HCC cells promote the expression of cellular and exosomal miR-92a-3p in HCC by directly binding the promoter of its host gene, miR17HG. Clinical data showed that a high plasma exosomal miR92a-3p level was correlated with shortened overall survival and disease-free survival, indicating poor prognosis in HCC patients. In conclusion, hepatoma-derived exosomal miR92a-3p plays a critical role in the EMT progression and promoting metastasis by inhibiting PTEN and activating Akt/Snail signaling. Exosomal miR92a-3p is a potential predictive biomarker for HCC metastasis, and this may provoke the development of novel therapeutic and preventing strategies against metastasis of HCC.

A systems biology approach to discovering pathway signaling dysregulation in metastasis

Total metastatic burden is the primary cause of death for many cancer patients. While the process of metastasis has been studied widely, much remains to be understood. Moreover, few agents have been developed that specifically target the major steps of the metastatic cascade. Many individual genes and pathways have been implicated in metastasis but a holistic view of how these interact and cooperate to regulate and execute the process remains somewhat rudimentary. It is unclear whether all of the signaling features that regulate and execute metastasis are yet fully understood. Novel features of a complex system such as metastasis can often be discovered by taking a systems-based approach. We introduce the concepts of systems modeling and define some of the central challenges facing the application of a multidisciplinary systems-based approach to understanding metastasis and finding actionable targets therein. These challenges include appreciating the unique properties of the high-dimensional omics data often used for modeling, limitations in knowledge of the system (metastasis), tumor heterogeneity and sampling bias, and some of the issues key to understanding critical features of molecular signaling in the context of metastasis. We also provide a brief introduction to integrative modeling that focuses on both the nodes and edges of molecular signaling networks. Finally, we offer some observations on future directions as they relate to developing a systems-based model of the metastatic cascade.

Facile Fabrication of Thin-Bottom Round-Well Plates Using the Deformation of PDMS Molds and Their Application for Single-Cell PCR

Recently, microdevices made of resins have been strongly supporting cell analysis in a range of fields, from fundamental life science research to medical applications. Many microdevices are fabricated by molding resin to a mold made precisely from rigid materials. However, because dimensional errors in the mold are also accurately printed to the products, the accuracy of the product is limited to less than the accuracy of the rigid mold. Therefore, we hypothesized that if dimensional errors could be self-corrected by elastic molds, microdevices could be facilely fabricated with precision beyond that of molds. In this paper, we report a novel processing strategy in which an elastic mold made of polymethylsiloxane (PDMS) deforms to compensate for the dimensional error on the products. By heat-press molding a polycarbonate plate using a mold that has 384 PDMS convexes with a large dimensional error of height of ± 15.6 µm in standard deviation, a 384-round-well plate with a bottom thickness 13.3 ± 2.3 µm (n = 384) was easily fabricated. Finally, single-cell observation and polymerase chain reactions (PCRs) demonstrated the application of the products made by elastic PDMS molds. Therefore, this processing method is a promising strategy for facile, low-cost, and higher precision microfabrication.

Chemosensitivity of Patient-Derived Cancer Stem Cells Identifies Colorectal Cancer Patients with Potential Benefit from FGFR Inhibitor Therapy

Some colorectal cancer patients harboring FGFR (fibroblast growth factor receptor) genetic alterations, such as copy number gain, mutation, and/or mRNA overexpression, were selected for enrollment in several recent clinical trials of FGFR inhibitor, because these genetic alterations were preclinically reported to be associated with FGFR inhibitor sensitivity as well as poor prognosis, invasiveness, and/or metastatic potential. However, few enrolled patients were responsive to FGFR inhibitors. Thus, practical strategies are eagerly awaited that can stratify patients for the subset that potentially responds to FGFR inhibitor chemotherapy. In the present study, we evaluated the sensitivity to FGFR inhibitor erdafitinib on 25 patient-derived tumor-initiating cell (TIC) spheroid lines carrying wild-type RAS and RAF genes, both in vitro and in vivo. Then, we assessed possible correlations between the sensitivity and the genetic/genomic data of the spheroid lines tested. Upon their exposure to erdafitinib, seven lines (7/25, 28%) responded significantly. Normal colonic epithelial stem cells were unaffected by the inhibitors. Moreover, the combination of erdafitinib with EGFR inhibitor erlotinib showed stronger growth inhibition than either drug alone, as efficacy was observed in 21 lines (84%) including 14 (56%) that were insensitive to erdafitinib alone. The in vitro erdafitinib response was accurately reflected on mouse xenografts of TIC spheroid lines. However, we found little correlation between their genetic/genomic alterations of TIC spheroids and the sensitivity to the FGFR inhibitor. Accordingly, we propose that direct testing of the patient-derived spheroids in vitro is one of the most reliable personalized methods in FGFR-inhibitor therapy of colorectal cancer patients.

Breakthrough concepts in immune-oncology: Cancer vaccines at the bedside

Clinical approval of the immune checkpoint blockade (ICB) agents for multiple cancer types has reinvigorated the long-standing work on cancer vaccines. In the pre-ICB era, clinical efforts focused on the Ag, the adjuvants, the formulation, and the mode of delivery. These translational efforts on therapeutic vaccines range from cell-based (e.g., dendritic cells vaccine Sipuleucel-T) to DNA/RNA-based platforms with various formulations (liposome), vectors (Listeria monocytogenes), or modes of delivery (intratumoral, gene gun, etc.). Despite promising preclinical results, cancer vaccine trials without ICB have historically shown little clinical activity. With the anticipation and expansion of combinatorial immunotherapeutic trials with ICB, the cancer vaccine field has entered the personalized medicine arena with recent advances in immunogenic neoantigen-based vaccines. In this article, we review the literature to organize the different cancer vaccines in the clinical space, and we will discuss their advantages, limits, and recent progress to overcome their challenges. Furthermore, we will also discuss recent preclinical advances and clinical strategies to combine vaccines with checkpoint blockade to improve therapeutic outcome and present a translational perspective on future directions.

Insights from the genetic and transcriptional characterization of a cancer of unknown primary (CUP)

Cancer of unknown primary (CUP) defines a heterogeneous group of metastatic tumors that lack an identifiable primary tumor, despite a standardized diagnostic work‐up (Fizazi et al, 2015). CUPs are characterized by an aggressive clinical course, unusual metastatic pattern, and poor prognosis. Research in this field has been encouraged to unravel the complexity of this enigmatic entity and improve clinical management and survival of CUP patients. In this issue of EMBO Molecular Medicine, Benvenuti et al (2020) describe the molecular characterization of multiple synchronous and spatially distinct metastases from a CUP patient, shedding light on the evolutionary dynamic and distinctive features of CUP.

Lymph node metastases develop through a wider evolutionary bottleneck than distant metastases

Genetic diversity among metastases is poorly understood but contains important information about disease evolution at secondary sites. Here we investigate inter- and intra-lesion heterogeneity for two types of metastases that associate with different clinical outcomes: lymph node and distant organ metastases in human colorectal cancer. We develop a rigorous mathematical framework for quantifying metastatic phylogenetic diversity. Distant metastases are typically monophyletic and genetically similar to each other. Lymph node metastases, in contrast, display high levels of inter-lesion diversity. We validate these findings by analyzing 317 multi-region biopsies from an independent cohort of 20 patients. We further demonstrate higher levels of intra-lesion heterogeneity in lymph node than in distant metastases. Our results show that fewer primary tumor lineages seed distant metastases than lymph node metastases, indicating that the two sites are subject to different levels of selection. Thus, lymph node and distant metastases develop through fundamentally different evolutionary mechanisms.

iWhale: a computational pipeline based on Docker and SCons for detection and annotation of somatic variants in cancer WES data

Whole exome sequencing (WES) is a powerful approach for discovering sequence variants in cancer cells but its time effectiveness is limited by the complexity and issues of WES data analysis. Here we present iWhale, a customizable pipeline based on Docker and SCons, reliably detecting somatic variants by three complementary callers (MuTect2, Strelka2 and VarScan2). The results are combined to obtain a single variant call format file for each sample and variants are annotated by integrating a wide range of information extracted from several reference databases, ultimately allowing variant and gene prioritization according to different criteria. iWhale allows users to conduct a complex series of WES analyses with a powerful yet customizable and easy-to-use tool, running on most operating systems (macOs, GNU/Linux and Windows).

iWhale code is freely available at https://github.com/alexcoppe/iWhale and the docker image is downloadable from https://hub.docker.com/r/alexcoppe/iwhale.

Whole-exome mutational landscape of metastasis in patient-derived hepatocellular carcinoma cells

In order to explore the genomic basis for liver cancer metastasis, whole-exome sequencing (WES) was performed on patient-derived hepatocellular carcinoma (HCC) cell lines with differential metastatic potentials and analyzed their clonal evolution relationships. An evolutionary tree based on genomic single nucleotide polymorphism (SNP) was constructed in MegaX software. The WES data showed that the average percentage of heterogeneous mutations in each HCC cell lines was 16.55% (range, 15.38%–18.17%). C: G > T: A and T: A > C: G somatic transitions were the two most frequent substitutions. In these metastatic HCC cell lines, non-silent gene mutations were found in 21.88% of known driver genes and 10 classical signaling pathways. The protein interaction network was constructed by STRING, and hub genes were found in the shared trunk mutation genes and the heterogeneous branch mutations respectively. In cBioPortal database, some of the selected hub genes were found to be associated with poor overall survival (OS) of HCC patients. Among the mutated HCC driver genes, a novel KEAP1 mutation with a homozygous frameshift truncation at the c-terminal Nrf2 binding region was detected and verified in MHCC97-H and HCC97LM3 cells. In conclusion, WES data demonstrate that HCC cell lines from tumor biopsy specimens of the same patient have obtained different metastatic potentials through repeated selection in rodents in vivo, and they do indeed have a genetic relationship at the genomic level.

Recent insights into the biology of pancreatic cancer

Pancreatic cancer (PDAC) is one of the deadliest types of human cancers, owing to late stage at presentation and pervasive therapeutic resistance. The extensive tumour heterogeneity, as well as substantial crosstalk between the neoplastic epithelium and components within the microenvironment are the defining features of PDAC biology that dictate the dismal natural history. Recent advances in genomic and molecular profiling have informed on the genetic makeup and evolutionary patterns of tumour progression, leading to treatment breakthroughs in minor subsets of patients with specific tumour mutational profiles. The nature and function of tumour heterogeneity, including stromal heterogeneity, in PDAC development and therapeutic resistance, are increasingly being elucidated. Deep insight has been gained regarding the metabolic and immunological deregulation, which further sheds light on the complex biology and the observed treatment recalcitrance. Here we will summarize these recent achievements and offer our perspective on the path forward.

Evaluation of the tumor-targeting efficiency and intratumor heterogeneity of anticancer drugs using quantitative mass spectrometry imaging

The development of improved or targeted drugs that discriminate between normal and tumor tissues is the key therapeutic issue in cancer research. However, the development of an analytical method with a high accuracy and sensitivity to achieve quantitative assessment of the tumor targeting of anticancer drugs and even intratumor heterogeneous distribution of these drugs at the early stages of drug research and development is a major challenge. Mass spectrometry imaging is a label-free molecular imaging technique that provides spatial-temporal information on the distribution of drugs and metabolites in organisms, and its application in the field of pharmaceutical development is rapidly increasing. Methods: The study presented here accurately quantified the distribution of paclitaxel (PTX) and its prodrug (PTX-R) in whole-body animal sections based on the virtual calibration quantitative mass spectrometry imaging (VC-QMSI) method, which is label-free and does not require internal standards, and then applied this technique to evaluate the tumor targeting efficiency in three treatment groups-the PTX-injection treatment group, PTX-liposome treatment group and PTX-R treatment group-in nude mice bearing subcutaneous A549 xenograft tumors. Results: These results indicated that PTX was widely distributed in multiple organs throughout the dosed body in the PTX-injection group and the PTX-liposome group. Notably, in the PTX-R group, both the prodrug and metabolized PTX were mainly distributed in the tumor tissue, and this group showed a significant difference compared with the PTX-liposome group, the relative targeting efficiency of PTX-R group was increased approximately 50-fold, leading to substantially decreased systemic toxicities. In addition, PTX-R showed a significant and specific accumulation in the poorly differentiated intratumor area and necrotic area. Conclusion: This method was demonstrated to be a reliable, feasible and easy-to-implement strategy to quantitatively map the absorption, distribution, metabolism and excretion (ADME) of a drug in the whole-body and tissue microregions and could therefore evaluate the tumor-targeting efficiency of anticancer drugs to predict drug efficacy and safety and provide key insights into drug disposition and mechanisms of action and resistance. Thus, this strategy could significantly facilitate the design and optimization of drugs at the early stage of drug research and development.

Molecular Biology and Evolution of Cancer: From Discovery to Action

Cancer progression is an evolutionary process. During this process, evolving cancer cell populations encounter restrictive ecological niches within the body, such as the primary tumor, circulatory system, and diverse metastatic sites. Efforts to prevent or delay cancer evolution-and progression-require a deep understanding of the underlying molecular evolutionary processes. Herein we discuss a suite of concepts and tools from evolutionary and ecological theory that can inform cancer biology in new and meaningful ways. We also highlight current challenges to applying these concepts, and propose ways in which incorporating these concepts could identify new therapeutic modes and vulnerabilities in cancer.