Using tumour phylogenetics to identify the roots of metastasis in humans

Nanoparticle-Mediated Drug Delivery Systems for Precision Targeting in Oncology

Nanotechnology has emerged as a transformative force in oncology, facilitating advancements in site-specific cancer therapy and personalized oncomedicine. The development of nanomedicines explicitly targeted to cancer cells represents a pivotal breakthrough, allowing the development of precise interventions. These cancer-cell-targeted nanomedicines operate within the intricate milieu of the tumour microenvironment, further enhancing their therapeutic efficacy. This comprehensive review provides a contemporary perspective on precision cancer medicine and underscores the critical role of nanotechnology in advancing site-specific cancer therapy and personalized oncomedicine. It explores the categorization of nanoparticle types, distinguishing between organic and inorganic variants, and examines their significance in the targeted delivery of anticancer drugs. Current insights into the strategies for developing actively targeted nanomedicines across various cancer types are also provided, thus addressing relevant challenges associated with drug delivery barriers. Promising future directions in personalized cancer nanomedicine approaches are delivered, emphasising the imperative for continued optimization of nanocarriers in precision cancer medicine. The discussion underscores translational research's need to enhance cancer patients' outcomes by refining nanocarrier technologies in nanotechnology-driven, site-specific cancer therapy.

Nonepithelial cancer dissemination: specificities and challenges

Epithelial cancers have served as a paradigm to study tumor dissemination but recent data have highlighted significant differences with nonepithelial cancers. Here, we review the current knowledge on nonepithelial tumor dissemination, drawing examples from the latest developments in melanoma, glioma, and sarcoma research. We underscore the importance of the reactivation of developmental processes during cancer progression and describe the nongenetic mechanisms driving nonepithelial tumor spread. We also outline therapeutic opportunities and ongoing clinical approaches to fight disseminating cancers. Finally, we discuss remaining challenges and emerging questions in the field. Defining the core principles underlying nonepithelial cancer dissemination may uncover actionable vulnerabilities of metastatic tumors and help improve the prognosis of patients with cancer.

Evolutionary mode and timing of dissemination of high-grade serous carcinomas

Dissemination within the peritoneal cavity is a main determinant of poor patient outcomes from high-grade serous carcinomas (HGSCs). The dissemination process is poorly understood from a cancer evolutionary perspective. We reconstructed the evolutionary trajectories across a median of 5 tumor sites and regions from each of 23 patients based on deep whole-exome sequencing. Polyclonal cancer origin was detected in 1 patient. Ovarian tumors had more complex subclonal architectures than other intraperitoneal tumors in each patient, which indicated that tumors developed earlier in the ovaries. Three common modes of dissemination were identified, including monoclonal or polyclonal dissemination of monophyletic (linear) or polyphyletic (branched) subclones. Mutation profiles of initial or disseminated clones varied greatly among cancers, but recurrent mutations were found in 7 cancer-critical genes, including TP53, BRCA1, BRCA2, and DNMT3A, and in the PI3K/AKT1 pathway. Disseminated clones developed late in the evolutionary trajectory models of most cancers, in particular in cancers with DNA damage repair deficiency. Polyclonal dissemination was predicted to occur predominantly as a single and rapid wave, but chemotherapy exposure was associated with higher genomic diversity of disseminated clones. In conclusion, we described three common evolutionary dissemination modes across HGSCs and proposed factors associated with dissemination diversity.

Strategic Approach to Heterogeneity Analysis of Cutaneous Adnexal Carcinomas Using Computational Pathology and Genomics

Cutaneous adnexal tumors are neoplasms that arise from skin appendages. Their morphologic diversity and phenotypic variability with rare progression to malignancy make them difficult to diagnose and classify, and there is currently no established treatment strategy. To overcome these difficulties, this study investigated the transcription factor SOX9 expression, morphology, and genetics of skin adnexal tumors for understanding their biology, especially their histogenesis. We showed that cutaneous adnexal tumors and their nontumor counterparts of skin and appendages exhibit expression patterns similar to that of SOX9. Its expression intensity and pattern, as well as histopathologic evaluation of tumors, were analyzed using digital images of 69 normal skin adnexal 9-type organs and 185 skin adnexal 29-type tumors as references. It was possible to distinguish basal cell carcinoma from squamous cell carcinoma, sebaceous carcinoma, and pilomatrixoma with significant differences, along with porocarcinoma from squamous cell carcinoma. Furthermore, unsupervised machine learning "computational pathology" was used to derive a multiregion whole-exome sequencing fusion method termed "genocomputed pathology." The genocomputed pathology of three representable adnexal carcinomas (porocarcinoma, hidradenocarcinoma, and spiradenocarcinoma) was evaluated for total nine cases. We showed that there was more heterogeneity than expected within the tumors as well as the coexistence of components lacking driver fusion genes. The presence or absence of potential driver genes, such as PIK3CA, YAP1, and PTEN, in each region was identified, highlighting a therapeutic strategy for cutaneous adnexal carcinoma encompassing heterogeneous tumors.

Unraveling the Drivers of Tumorigenesis in the Context of Evolution: Theoretical Models and Bioinformatics Tools

Cancer originates from somatic cells that have accumulated mutations. These mutations alter the phenotype of the cells, allowing them to escape homeostatic regulation that maintains normal cell numbers. The emergence of malignancies is an evolutionary process in which the random accumulation of somatic mutations and sequential selection of dominant clones cause cancer cells to proliferate. The development of technologies such as high-throughput sequencing has provided a powerful means to measure subclonal evolutionary dynamics across space and time. Here, we review the patterns that may be observed in cancer evolution and the methods available for quantifying the evolutionary dynamics of cancer. An improved understanding of the evolutionary trajectories of cancer will enable us to explore the molecular mechanism of tumorigenesis and to design tailored treatment strategies.

Distinct genomic features between osteosarcomas firstly metastasing to bone and to lung

Background

Osteosarcoma initially metastasing to bone only shows distinct biological features compared to osteosarcoma that firstly metastasizes to the lung, which suggests us underlying different genomic pathogenetic mechanism.

Methods

We analyzed whole-exome sequencing (WES) data for 38 osteosarcoma with paired samples in different relapse patterns. We also sought to redefine disease subclassifications for osteosarcoma based on genetic alterations and correlate these genetic profiles with clinical treatment courses to elucidate potential evolving cladograms.

Results

We investigated WES of 12/38 patients with high-grade osteosarcoma (31.6%) with initial bone metastasis (group A) and 26/38 (68.4%) with initial pulmonary metastasis (group B), of whom 15/38 (39.5%) had paired samples of primary lesions and metastatic lesions. We found that osteosarcoma in group A mainly carries single-nucleotide variations displaying higher tumor mutation burden and neoantigen load and more tertiary lymphoid structures, while those in group B mainly exhibits structural variants. High conservation of reported genetic sequencing over time in their evolving cladograms.

Conclusions

Osteosarcoma with mainly single-nucleotide variations other than structural variants might exhibit biological behavior predisposing toward bone metastases as well as better immunogenicity in tumor microenvironment.

Is it time for redefining oligometastatic disease? Analysis of lung metastases CT in ten tumor types

BACKGROUND

Oligometastatic disease (OD) is usually defined arbitrarily as a condition in which there are ≤ 5 metastases. Given limited disease, it is expected that patients with OD should have better prognosis compared to other metastatic patients and that they can potentially benefit from metastasis-directed therapy (MDT). In this study, we attempted to redefine OD based upon objective evidence that fulfill these assumptions.

METHODS

Chest CTSs of 773 patients with 15,947 lung metastases originating from ten malignancy types were evaluated. The number and largest diameter of each metastasis was recorded. Metastatic cluster was defined as a cluster of two or more metastases with diameter difference ≤ 1 mm. The prognostic power of seven statistical models on overall survival (OS) was analyzed.

FINDINGS

Both the number of metastases and metastatic clusters had a highly significant impact on OS (p < 0.0001, p = 0.003 respectively). Patients with a single metastasis or a single cluster of metastases (regardless of metastases number), equaling 16.2% of all patients, had significantly better prognosis compared to other patients (p = 0.0002). If metastases diameter variability is ignored, as in the standard definition of OD, then patients with 2-5 and 6-10 metastases would have a similar prognosis.

INTERPRETATION

Patients with a single cluster of metastases, theoretically originating from a single clone, have significantly better prognosis compared to patients with more than one cluster. Using this definition can potentially improve the results of MDT. The upper limit of metastases number should be determined by the technical capabilities of the MDT used.

Biology, vulnerabilities and clinical applications of circulating tumour cells

In recent years, exceptional technological advances have enabled the identification and interrogation of rare circulating tumour cells (CTCs) from blood samples of patients, leading to new fields of research and fostering the promise for paradigm-changing, liquid biopsy-based clinical applications. Analysis of CTCs has revealed distinct biological phenotypes, including the presence of CTC clusters and the interaction between CTCs and immune or stromal cells, impacting metastasis formation and providing new insights into cancer vulnerabilities. Here we review the progress made in understanding biological features of CTCs and provide insight into exploiting these developments to design future clinical tools for improving the diagnosis and treatment of cancer.

Targeting SOST using a small-molecule compound retards breast cancer bone metastasis

BACKGROUND

Breast cancer metastasis to the bone can be exacerbated by osteoporosis, is associated with poor long-term survival, and has limited therapeutic options. Sclerostin (SOST) is an endogenous inhibitor of bone formation, and an attractive target for treatment of osteoporosis. However, it is unclear whether SOST can be used as a therapeutic target for bone metastases of breast cancer, and whether small molecule compounds that target SOST in breast cancer cells can inhibit breast cancer bone metastasis.

METHODS

SOST expression in 442 breast cancer tissues was characterized by immunohistochemistry and statistically analyzed for the association with breast cancer bone metastases. Bone metastatic breast cancer SCP2 cells were induced for SOST silencing or overexpression and their bone metastatic behaviors were tested in vitro and in vivo. To identify potential therapeutics, we screened inhibitors of the interaction of SOST with STAT3 from a small chemical molecule library and tested the inhibitory effects of one inhibitor on breast cancer growth and bone metastasis in vitro and in vivo.

RESULTS

We found that up-regulated SOST expression was associated with breast cancer bone metastases and worse survival of breast cancer patients. SOST silencing significantly reduced the bone metastatic capacity of SCP2 cells. SOST interacted with STAT3 to enhance the TGF-β/KRAS signaling, increasing both tumor growth and bone metastasis. Treatment with one lead candidate, S6, significantly inhibited the growth of breast-cancer organoids and bone metastasis in mice.

CONCLUSIONS

Our findings highlight a new class of potential therapeutics for treatment of bone metastasis in breast cancer.

The significance of glycolysis in tumor progression and its relationship with the tumor microenvironment

It is well known that tumor cells rely mainly on aerobic glycolysis for energy production even in the presence of oxygen, and glycolysis is a known modulator of tumorigenesis and tumor development. The tumor microenvironment (TME) is composed of tumor cells, various immune cells, cytokines, and extracellular matrix, among other factors, and is a complex niche supporting the survival and development of tumor cells and through which they interact and co-evolve with other tumor cells. In recent years, there has been a renewed interest in glycolysis and the TME. Many studies have found that glycolysis promotes tumor growth, metastasis, and chemoresistance, as well as inhibiting the apoptosis of tumor cells. In addition, lactic acid, a metabolite of glycolysis, can also accumulate in the TME, leading to reduced extracellular pH and immunosuppression, and affecting the TME. This review discusses the significance of glycolysis in tumor development, its association with the TME, and potential glycolysis-targeted therapies, to provide new ideas for the clinical treatment of tumors.

Patterns of metastases progression- The linear parallel ratio

BACKGROUND

Linear and parallel are the two leading models of metastatic progression. In this study we propose a simple way to differentiate between them. While the linear model predicts accumulation of genetic and epigenetic alterations within the primary tumor by founder cells before spreading as waves of metastases, the parallel model suggests preclinical distribution of less advanced disseminated tumor cells with independent selection and expansion at the ectopic sites. Due to identical clonal origin and time of dispatching, linear metastases are expected to have comparable diameters in any specific organ while parallel metastases are expected to appear in variable sizes.

METHODS AND FINDINGS

Retrospective revision of chest CT of oncological patients with lung metastases was performed. Metastasis number and largest diameters were recorded. The sum number of metastases with a similar diameter (c) and those without (i) was counted and the linear/parallel ratio (LPR) was calculated for each patient using the formula (∑c-∑i)/(∑c+∑i). A LPR ratio of 1 implies pure linear progression pattern and -1 pure parallel. 12,887 metastases were measured in 503 patients with nine malignancy types. The median LPR of the entire group was 0.71 (IQR 0.14-0.93). In carcinomas of the pancreas, prostate, and thyroid the median LPR was 1. Median LPRs were 0.91, 0.65, 0.60, 0.58, 0.50 and 0.43 in renal cell carcinomas, melanomas, colorectal, breast, bladder, and sarcomas, respectively.

CONCLUSIONS

Metastatic spread of thyroid, pancreas, and prostate tumors is almost exclusively by a linear route. The spread of kidney, melanoma, colorectal, breast, bladder and sarcoma is both linear and parallel with increasing dominance of the parallel route in this order. These findings can explain and predict the clinical and genomic features of these tumors and can potentially be used for evaluation of metastatic origin in the individual patient.

Tumour Stem Cells in Breast Cancer

Tumour stem cells (CSCs) are a self-renewing population that plays important roles in tumour initiation, recurrence, and metastasis. Although the medical literature is extensive, problems with CSC identification and cancer therapy remain. This review provides the main mechanisms of CSC action in breast cancer (BC): CSC markers and signalling pathways, heterogeneity, plasticity, and ecological behaviour. The dynamic heterogeneity of CSCs and the dynamic transitions of CSC⁻ non-CSCs and their significance for metastasis are considered.

CellPhy: accurate and fast probabilistic inference of single-cell phylogenies from scDNA-seq data

We introduce CellPhy, a maximum likelihood framework for inferring phylogenetic trees from somatic single-cell single-nucleotide variants. CellPhy leverages a finite-site Markov genotype model with 16 diploid states and considers amplification error and allelic dropout. We implement CellPhy into RAxML-NG, a widely used phylogenetic inference package that provides statistical confidence measurements and scales well on large datasets with hundreds or thousands of cells. Comprehensive simulations suggest that CellPhy is more robust to single-cell genomics errors and outperforms state-of-the-art methods under realistic scenarios, both in accuracy and speed. CellPhy is freely available at https://github.com/amkozlov/cellphy .

OUP accepted manuscript

Motivation

Identifying cell types and their abundances and how these evolve during tumor progression is critical to understanding the mechanisms of metastasis and identifying predictors of metastatic potential that can guide the development of new diagnostics or therapeutics. Single-cell RNA sequencing (scRNA-seq) has been especially promising in resolving heterogeneity of expression programs at the single-cell level, but is not always feasible, e.g. for large cohort studies or longitudinal analysis of archived samples. In such cases, clonal subpopulations may still be inferred via genomic deconvolution, but deconvolution methods have limited ability to resolve fine clonal structure and may require reference cell type profiles that are missing or imprecise. Prior methods can eliminate the need for reference profiles but show unstable performance when few bulk samples are available.

Results

In this work, we develop a new method using reference scRNA-seq to interpret sample collections for which only bulk RNA-seq is available for some samples, e.g. clonally resolving archived primary tissues using scRNA-seq from metastases. By integrating such information in a Quadratic Programming framework, our method can recover more accurate cell types and corresponding cell type abundances in bulk samples. Application to a breast tumor bone metastases dataset confirms the power of scRNA-seq data to improve cell type inference and quantification in same-patient bulk samples.

Availability and implementation

Source code is available on Github at https://github.com/CMUSchwartzLab/RADs.

Engineering Chameleon Prodrug Nanovesicles to Increase Antigen Presentation and Inhibit PD-L1 Expression for Circumventing Immune Resistance of Cancer

Immune evasion is the major obstacle for T-cell-based cancer immunotherapy. The insufficient expression of the tumor-rejection antigen causes the intrinsic immune resistance and high expression of programmed death ligand 1 (PD-L1) induced by interferon gamma (IFN-γ), which accounts for the inducible immune resistance. To deal with both the intrinsic and inducible immune resistance of cancer, a multifunctional prodrug nanovesicle is sequentially developed. It is first sorted out that doxycycline (Doxy) efficiently inhibits autophagy of the tumor cells, and increases the surface level of major histocompatibility complex class I (MHC-I). Then, chameleon-inspired prodrug nanovesicles are engineered for tumor-targeted delivery of Doxy. The prodrug nanovesicles integrating a sheddable poly(ethylene glycol) shell and CRGDK ligand are kept stable during blood circulation, while exposing the targeting ligand in the tumor, which significantly inhibits autophagy, elicits MHC-I expression, increases tumor antigen presentation, recruits more tumor-infiltrating T lymphocytes, and suppresses FN-γ-induced intratumoral PD-L1 expression. After a proof of concept for overcoming intrinsic and inducible immune evasion, the prodrug nanovesicles are applied to validate the efficacy of cancer immunotherapy in two tumor-bearing mouse models. This research thus provides a novel targeting strategy for reducing tumor immune resistance and potentiating tumor immunotherapy.

Single-cell lineage tracing of metastatic cancer reveals selection of hybrid EMT states

The underpinnings of cancer metastasis remain poorly understood, in part due to a lack of tools for probing their emergence at high resolution. Here we present macsGESTALT, an inducible CRISPR-Cas9-based lineage recorder with highly efficient single-cell capture of both transcriptional and phylogenetic information. Applying macsGESTALT to a mouse model of metastatic pancreatic cancer, we recover ∼380,000 CRISPR target sites and reconstruct dissemination of ∼28,000 single cells across multiple metastatic sites. We find that cells occupy a continuum of epithelial-to-mesenchymal transition (EMT) states. Metastatic potential peaks in rare, late-hybrid EMT states, which are aggressively selected from a predominately epithelial ancestral pool. The gene signatures of these late-hybrid EMT states are predictive of reduced survival in both human pancreatic and lung cancer patients, highlighting their relevance to clinical disease progression. Finally, we observe evidence for in vivo propagation of S100 family gene expression across clonally distinct metastatic subpopulations.

Metastatic Breast Cancer, Organotropism and Therapeutics: A Review

The final stage of breast cancer involves spreading breast cancer cells to the vital organs like the brain, liver lungs and bones in the process called metastasis. Once the target organ is overtaken by the metastatic breast cancer cells, its usual function is compromised causing organ dysfunction and death. Despite the significant research on breast cancer metastasis, it's still the main culprit of breast cancer-related deaths. Exploring the complex molecular pathways associated with the initiation and progression of breast cancer metastasis could lead to the discovery of more effective ways of treating the devastating phenomenon. The present review article highlights the recent advances to understand the complexity associated with breast cancer metastases, organotropism and therapeutic advances.

Hypoxia and the Tumor Microenvironment

Hypoxia is an important feature of the tumor microenvironment, and is closely associated with cell proliferation, angiogenesis, metabolism and the tumor immune response. All these factors can further promote tumor progression, increase tumor aggressiveness, enhance tumor metastatic potential and lead to poor prognosis. In this review, these effects of hypoxia on tumor biology will be discussed, along with their significance for tumor detection and treatment.

Is There One Key Step in the Metastatic Cascade?

Simple Summary

To successfully metastasize, cancer cells must complete a sequence of obligatory steps called the metastatic cascade. To model the metastatic cascade, we used the framework of the Drake equation, initially created to describe the emergence of intelligent life in the Milky way, using a similar logic of a sequence of obligatory steps. Then within this framework, we used simulations on breast cancer to investigate the contribution of each step to the metastatic cascade. We show that the half-life of circulating tumor cells is one of the most important parameters in the cascade, suggesting that therapies reducing the survival of those cells in the vascular system could significantly reduce the risk of metastasis.

Abstract

The majority of cancer-related deaths are the result of metastases (i.e., dissemination and establishment of tumor cells at distant sites from the origin), which develop through a multi-step process classically termed the metastatic cascade. The respective contributions of each step to the metastatic process are well described but are also currently not completely understood. Is there, for example, a critical phase that disproportionately affects the probability of the development of metastases in individual patients? Here, we address this question using a modified Drake equation, initially formulated by the astrophysicist Frank Drake to estimate the probability of the emergence of intelligent civilizations in the Milky Way. Using simulations based on realistic parameter values obtained from the literature for breast cancer, we examine, under the linear progression hypothesis, the contribution of each component of the metastatic cascade. Simulations demonstrate that the most critical parameter governing the formation of clinical metastases is the survival duration of circulating tumor cells (CTCs).

Whole-exome sequencing in osteosarcoma with distinct prognosis reveals disparate genetic heterogeneity

The genomic profiles of osteosarcoma (OS) patients have been extensively investigated; however, the genetic prognostic biomarkers still remain unclear. In the present study, we analyzed the mutational profiles of pre-treatment primary tumor samples from 33 OS patients using whole exome sequencing (WES). These 33 OS patients were divided into two groups according to clinical outcomes: a good prognosis group involving 21 patients with tumor free survival, and a poor prognosis group involving the remaining12 patients who had lung metastases at initial diagnosis. Overall we found that the MAPK signaling pathway may play an important role in determining a good prognosis, while the PI3K-Akt signaling pathway may be an important factor leading to a poor prognosis. Significant differences were observed in the number of somatic copy number alterations, including del (3p), amp (4q), del (7p) and amp (8q), between the two groups. Moreover, significant differences were observed in mutation sites and frequencies between these two groups. The good prognosis group exhibited a significantly higher mutation frequency in somatic JAK-STAT and germline base excision repair pathways than the poor prognosis group. Furthermore, significant difference was also observed in the frequency of potentially actionable alterations between the two groups, suggesting that patients with a poor prognosis potentially have access to a larger number of treatment options. These findings highlight the importance of evaluating genomic disparities in OS, and provide a novel insight into the potential prognostic biomarkers.

Heterogeneity of Colorectal Cancer Progression: Molecular Gas and Brakes

The review begins with molecular genetics, which hit the field unveiling the involvement of oncogenes and tumor suppressor genes in the pathogenesis of colorectal cancer (CRC) and uncovering genetic predispositions. Then the notion of molecular phenotypes with different clinical behaviors was introduced and translated in the clinical arena, paving the way to next-generation sequencing that captured previously unrecognized heterogeneity. Among other molecular regulators of CRC progression, the extent of host immune response within the tumor micro-environment has a critical position. Translational sciences deeply investigated the field, accelerating the pace toward clinical transition, due to its strong association with outcomes. While the perturbation of gut homeostasis occurring in inflammatory bowel diseases can fuel carcinogenesis, micronutrients like vitamin D and calcium can act as brakes, and we discuss underlying molecular mechanisms. Among the components of gut microbiota, Fusobacterium nucleatum is over-represented in CRC, and may worsen patient outcome. However, any translational knowledge tracing the multifaceted evolution of CRC should be interpreted according to the prognostic and predictive frame of the TNM-staging system in a perspective of clinical actionability. Eventually, we examine challenges and promises of pharmacological interventions aimed to restrain disease progression at different disease stages.

Whole-exome sequencing identifies somatic mutations associated with lung cancer metastasis to the brain

Background

Lung cancer is the most aggressive cancer, resulting in one-quarter of all cancer-related deaths, and its metastatic spread accounts for >70% of these deaths, especially metastasis to the brain. Metastasis-associated mutations are important biomarkers for metastasis prediction and outcome improvement.

Methods

In this study, we applied whole-exome sequencing (WES) to identify potential metastasis-related mutations in 12 paired lung cancer and brain metastasis samples.

Results

We identified 1,702 single nucleotide variants (SNVs) and 6,131 mutation events among 1,220 genes. Furthermore, we identified several lung cancer metastases associated genes (KMT2C, AHNAK2). A mean of 3.1 driver gene mutation events per tumor with the dN/dS (non-synonymous substitution rate/synonymous substitution rate) of 2.13 indicating a significant enrichment for cancer driver gene mutations. Mutation spectrum analysis found lung-brain metastasis samples have a more similar Ti/Tv (transition/transversion) profile with brain cancer in which C to T transitions are more frequent while lung cancer has more C to A transversion. We also found the most important tumor onset and metastasis pathways, such as chronic myeloid leukemia, ErbB signaling pathway, and glioma pathway. Finally, we identified a significant survival associated mutation gene ERF in both The Cancer Genome Atlas (TCGA) (P=0.01) and our dataset (P=0.012).

Conclusions

In summary, we conducted a pairwise lung-brain metastasis based exome-wide sequencing and identified some novel metastasis-related mutations which provided potential biomarkers for prognosis and targeted therapeutics.

Molecular features and gene expression signature of metastatic colorectal cancer (Review)

Uncontrollable metastatic outgrowth process is the leading cause of mortality worldwide, even in the case of colorectal cancer. Colorectal cancer (CRC) accounts for approximately 10% of all annually diagnosed cancers and 50% of CRC patients will develop metastases in the course of disease. Most patients with metastatic CRC have incurable disease. Even if patients undergo resection of liver metastases, the 5‑year survival rate ranges from 25 to 58%. Next‑generation sequencing of tumour specimens from large colorectal cancer patient cohorts has led to major advances in elucidating the genomic landscape of these tumours and paired metastases. The expression profiles of primary CRC and their metastatic lesions at both the gene and pathway levels were compared and led to the selection of early driver genes responsible for carcinogenesis and metastasis‑specific genes that increased the metastatic process. The genetic, transcriptional and epigenetic alteration encoded by these genes and their combination influence many pivotal signalling pathways, enabling the dissemination and outgrowth in distant organs. Therapeutic regimens affecting several different active pathways may have important implications for therapeutic efficacy.

CellCoal: Coalescent Simulation of Single-Cell Sequencing Samples

Our capacity to study individual cells has enabled a new level of resolution for understanding complex biological systems such as multicellular organisms or microbial communities. Not surprisingly, several methods have been developed in recent years with a formidable potential to investigate the somatic evolution of single cells in both healthy and pathological tissues. However, single-cell sequencing data can be quite noisy due to different technical biases, so inferences resulting from these new methods need to be carefully contrasted. Here, I introduce CellCoal, a software tool for the coalescent simulation of single-cell sequencing genotypes. CellCoal simulates the history of single-cell samples obtained from somatic cell populations with different demographic histories and produces single-nucleotide variants under a variety of mutation models, sequencing read counts, and genotype likelihoods, considering allelic imbalance, allelic dropout, amplification, and sequencing errors, typical of this type of data. CellCoal is a flexible tool that can be used to understand the implications of different somatic evolutionary processes at the single-cell level, and to benchmark dedicated bioinformatic tools for the analysis of single-cell sequencing data. CellCoal is available at https://github.com/dapogon/cellcoal.

Metastatic Spread in Prostate Cancer Patients Influencing Radiotherapy Response

Radiotherapy and surgery are curative treatment options for localized prostate cancer (PCa) with a 5-year survival rate of nearly 100%. Once PCa cells spread into distant organs, such as bone, the overall survival rate of patients drops dramatically. The metastatic cascade and organotropism of PCa cells are regulated by different cellular subtypes, organ microenvironment, and their interactions. This cross-talk leads to pre-metastatic niche formation that releases chemo-attractive factors enforcing the formation of distant metastasis. Biological characteristics of PCa metastasis impacting on metastatic sites, burden, and latency is of clinical relevance. Therefore, the implementation of modern hybrid imaging technologies into clinical routine increased the sensitivity to detect metastases at earlier stages. This enlarged the number of PCa patients diagnosed with a limited number of metastases, summarized as oligometastatic disease. These patients can be treated with androgen deprivation in combination with local-ablative radiotherapy or radiopharmaceuticals directed to metastatic sites. Unfortunately, the number of patients with disease recurrence is high due to the enormous heterogeneity within the oligometastatic patient population and the lack of available biomarkers with predictive potential for metastasis-directed radiotherapy. Another, so far unmet clinical need is the diagnosis of minimal residual disease before onset of clinical manifestation and/or early relapse after initial therapy. Here, monitoring of circulating and disseminating tumor cells in PCa patients during the course of radiotherapy may give us novel insight into how metastatic spread is influenced by radiotherapy and vice versa. In summary, this review critically compares current clinical concepts for metastatic PCa patients and discuss the implementation of recent preclinical findings improving our understanding of metastatic dissemination and radiotherapy resistance into standard of care.

Characterization of evolution trajectory and immune profiling of brain metastasis in lung adenocarcinoma

Characterizing the evolutionary trajectory and immune profiling of brain metastasis (BM) may provide insights in the development of novel therapeutic strategies. Here, we performed whole-exome sequencing and multiplex immunofluorescence (MIF) of 40 samples from 12 lung adenocarcinoma (LUAD) patients with BM and compared to their paired primary tumors. We observed significantly higher intertumor heterogeneity between paired primary tumors and BMs, with only a median of 8.3% of genetic mutations identified as shared. Phylogenetic analysis revealed that BM-competent clones genetically diverged from their primary tumors at relatively early stage, suggesting that the parallel progression model is dominant. In cases with synchronous lymph node metastasis (LNM), phylogenetic analysis suggested that BM is a later event than LNM. MIF analysis found that BMs exhibited significantly lower CD8+ T cell infiltration (P = 0.048), and elevated CD4+Foxp3+ T cell infiltration (P = 0.036) and PD-1 expression (P = 0.047) in comparison to the matched primary tumors, indicating an immunosuppressive microenvironment in BMs. The current study revealed the discrepancy of mutational landscape as well as tumor immune microenvironment between BM and its primary tumor - such findings shall help us better understand the unique biological features of BM and develop innovative strategies accordingly for our patients with LUAD.

Phylodynamics for cell biologists

Multicellular organisms are composed of cells connected by ancestry and descent from progenitor cells. The dynamics of cell birth, death, and inheritance within an organism give rise to the fundamental processes of development, differentiation, and cancer. Technical advances in molecular biology now allow us to study cellular composition, ancestry, and evolution at the resolution of individual cells within an organism or tissue. Here, we take a phylogenetic and phylodynamic approach to single-cell biology. We explain how "tree thinking" is important to the interpretation of the growing body of cell-level data and how ecological null models can benefit statistical hypothesis testing. Experimental progress in cell biology should be accompanied by theoretical developments if we are to exploit fully the dynamical information in single-cell data.

Inferring Tumor Proliferative Organization from Phylogenetic Tree Measures in a Computational Model

We use a computational modeling approach to explore whether it is possible to infer a solid tumor's cellular proliferative hierarchy under the assumptions of the cancer stem cell hypothesis and neutral evolution. We work towards inferring the symmetric division probability for cancer stem cells, since this is believed to be a key driver of progression and therapeutic response. Motivated by the advent of multiregion sampling and resulting opportunities to infer tumor evolutionary history, we focus on a suite of statistical measures of the phylogenetic trees resulting from the tumor's evolution in different regions of parameter space and through time. We find strikingly different patterns in these measures for changing symmetric division probability which hinge on the inclusion of spatial constraints. These results give us a starting point to begin stratifying tumors by this biological parameter and also generate a number of actionable clinical and biological hypotheses regarding changes during therapy, and through tumor evolutionary time. [Cancer; evolution; phylogenetics.].

Increased chromosomal instability characterizes metastatic renal cell carcinoma

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The clonal origin and parallel evolution of the metastatic lesions and primary tumour.

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The evolutionary branches of primary and metastatic clones diverge early in the development of the tumour.

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Increased genome instability and specific enriched somatic copy number alteration (SCNAs) in metastatic lesions compared to primary tumour.

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LOH at 14q, loss of 14q32.31 and gain of 6p22.2 are highly selected events during metastatic evolution.

The evolutionary trajectories of treatment-naïve metastatic tumour are largely unknown. Such knowledge is crucial for cancer prevention and therapeutic interventions. Herein, we performed whole genome or exome sequencing of 19 tumour specimens and 8 matched normal kidney tissues from 8 clear cell renal cell carcinoma (ccRCC) patients.

The clonal origin and parallel evolution of the metastatic lesions and primary tumour is identified in all 8 patients. But the evolutionary branches of primary and metastatic clones diverge early in the development of the tumour. More importantly, larger scale genomic aberrations including somatic copy number alteration (SCNA) or loss of heterozygosity (LOH) differentiate the metastasis lesions from primary tumour. Based on it, we identify that LOH at 14q, loss of 14q32.31 and gain of 6p22.2 are highly selected events during metastatic evolution. Further functional validations of multiple genes within the SCNA regions indicated that these selected events interact to drive metastatic risk with potential therapeutic relevance. Collectively, we described increased genome instability in metastatic ccRCC and validated it via molecular biology, providing an evolution pattern which may facilitate the translation of basic finding.

A Perspective on Therapeutic Pan-Resistance in Metastatic Cancer

Metastatic spread represents the leading cause of disease-related mortality among cancer patients. Many cancer patients suffer from metastatic relapse years or even decades after radical surgery for the primary tumor. This clinical phenomenon is explained by the early dissemination of cancer cells followed by a long period of dormancy. Although dormancy could be viewed as a window of opportunity for therapeutic interventions, dormant disseminated cancer cells and micrometastases, as well as emergent outgrowing macrometastases, exhibit a generalized, innate resistance to chemotherapy and even immunotherapy. This therapeutic pan-resistance, on top of other adaptive responses to targeted agents such as acquired mutations and lineage plasticity, underpins the current difficulties in eradicating cancer. In the present review, we attempt to provide a framework to understand the underlying biology of this major issue.

Tracing Tumor Evolution in Sarcoma Reveals Clonal Origin of Advanced Metastasis

Cellular heterogeneity is frequently observed in cancer, but the biological significance of heterogeneous tumor clones is not well defined. Using multicolor reporters and CRISPR-Cas9 barcoding, we trace clonal dynamics in a mouse model of sarcoma. We show that primary tumor growth is associated with a reduction in clonal heterogeneity. Local recurrence of tumors following surgery or radiation therapy is driven by multiple clones. In contrast, advanced metastasis to the lungs is driven by clonal selection of a single metastatic clone (MC). Using RNA sequencing (RNA-seq) and in vivo assays, we identify candidate suppressors of metastasis, namely, Rasd1, Reck, and Aldh1a2. These genes are downregulated in MCs of the primary tumors prior to the formation of metastases. Overexpression of these suppressors of metastasis impair the ability of sarcoma cells to colonize the lungs. Overall, this study reveals clonal dynamics during each step of tumor progression, from initiation to growth, recurrence, and distant metastasis.

Somatic Mitochondrial DNA Point Mutations Used as Biomarkers to Demonstrate Genomic Heterogeneity in Primary Prostate Cancer

Primary prostate tumor heterogeneity is poorly understood, leaving research efforts with challenges regarding the initiation and advancement of the disease. The growth of tumor cells is accompanied by mutations in nuclear and in mitochondrial genomes. Thus, mitochondrial DNA mutations may be used as tumor cell markers. By the use of laser capture microdissection coupled with assays for mitochondrial point mutation detection, mtDNA mutations were used to trace mutated cells at a histological level. Point mutations in mtDNA were determined in 12 primary prostate cancers. The tumors represent different pathology-prognostic grade groups. Known mutational hotspots of the mtDNA were scanned for heteroplasmy. All specimens with mtDNA heteroplasmy were subsequently subsampled by laser capture microdissection. From a total number of 1728 microsamples, mitochondrial DNA target sequences were amplified and base substitutions detected by cycling temperature capillary electrophoresis. Real-time PCR was used as a quantitative assay to determine the relative mtDNA copy number of 12 tumors studied, represented by two samples from each (N = 24); a high degree (75%) demonstrated tumor specimen heterogeneity. A grid of 96 spots isolated by laser capture microdissection demonstrated interfocal sample heterogeneity and increased the limit of detection. The spots demonstrated a wide range of mutant fractions from 0 to 100% mutant copies. The mitochondrial DNA copy number in the samples was determined by real-time PCR. No correlation between copy number and pathology-prognostic grade groups was observed. Somatic mitochondrial DNA point mutations represent traceable biomarkers demonstrating heterogeneity in primary prostate cancer. Mutations can be detected in areas before changes in tissue histopathology are evident to the pathologist.

Intratumor heterogeneity: A new perspective on colorectal cancer research

Colorectal cancers generally consist of multiple subclones. These subclones have their own unique characteristics, resulting in intratumor heterogeneity (ITH). As the discussion of ITH has advanced, a model describing the relationship of ITH to the tumor has gradually emerged. ITH can be divided into two types of intraprimary tumor heterogeneity and intraindividual tumor heterogeneity, the former for further understanding of tumor composition, and the latter for providing more information about evolutionary patterns. With the rapid development of new methods, such as next‐generation, polyguanine region sequencing, and Image detection, researchers may unravel the secrets underlying ITH. The higher the ITH of the tumor, the richer the interaction between the subclones maybe, or the greater the chance of the tumor getting more powerful subclones may be, thus increasing the malignant potential of the tumor. Existing evidence suggests that ITH may increase the ability of tumors to resist treatment and can be used as an independent influence on the prognosis of colorectal cancer. We reviewed 80 recent studies to give researchers a new perspective on colorectal cancer. There is still a limited amount of research in this area. Further study of the relationship between ITH and clinical endpoints may lead to the development of new treatment strategies.

Anesthesia Options and the Recurrence of Cancer: What We Know so Far?

Surgery is a critical period in the survival of patients with cancer. While resective surgery of primary tumors has shown to prolong the life of these patients, it can also promote mechanisms associated with metastatic progression. During surgery, patients require general and sometimes local anesthetics that also modulate mechanisms that can favor or reduce metastasis. In this narrative review, we summarized the evidence about the impact of local, regional and general anesthesia on metastatic mechanisms and the survival of patients. The available evidence suggests that cancer recurrence is not significantly impacted by neither regional anesthesia nor volatile or total intravenous anesthesia.

Cancer of Unknown Primary (CUP): genetic evidence for a novel nosological entity? A case report

Cancer of unknown primary (CUP) is an obscure disease characterized by multiple metastases in the absence of a primary tumor. No consensus has been reached whether CUPs are simply generated from cancers that cannot be detected or whether they are the manifestation of a still unknown nosological entity. Here, we report the complete expression and genetic analysis of multiple synchronous metastases harvested at warm autopsy of a patient with CUP. The expression profiles were remarkably similar and astonishingly singular. The whole exome analysis yielded a high number of mutations present in all metastases (fully shared), additional mutations (partially shared) accumulated one after another in a series, and few private mutations were unique to each metastasis. Surprisingly, the phylogenetic trajectory linking CUP metastases was atypical, depicting a common "stream", sprouting a series of linear "brooks", at variance from the extensive branched evolution observed in metastases from most cancers of known origin. The distinctive genetic and evolutionary features depicted suggest that CUP is a novel nosological entity.

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.

Multi-cancer analysis of clonality and the timing of systemic spread in paired primary tumors and metastases

Metastasis is the primary cause of cancer-related deaths, but the natural history, clonal evolution and impact of treatment are poorly understood. We analyzed whole-exome sequencing data from 457 paired primary tumor and metastatic samples from 136 breast, colorectal and lung cancer patients, including untreated (n=99) and treated (n=100) metastases. Treated metastases often harbored private ‘driver’ mutations whereas untreated metastases did not, suggesting that treatment promotes clonal evolution. Polyclonal seeding was common in untreated lymph node metastases (n=17/29, 59%) and distant metastases (n=20/70, 29%), but less frequent in treated distant metastases (n=9/94, 10%). The low number of metastasis-private clonal mutations is consistent with early metastatic seeding, which we estimated occurred 2–4 years prior to diagnosis across these cancers. Further, these data suggest that the natural course of metastasis is selectively relaxed relative to early tumorigenesis and that metastasis-private mutations are not drivers of cancer spread but instead associated with drug resistance.

Prognosis following surgical resection versus local excision of stage pT1 colorectal cancer: A population-based cohort study

AIMS

To evaluate patient management following stage pT1 colorectal cancer (CRC) diagnosis, and to determine if surgical resection improved outcome compared with local excision, within a population-based study.

METHODS

Data were collected from the Northern Ireland Cancer Registry. Cases of stage pT1 CRC diagnosed from 2007 to 2012 were identified. Analyses were conducted using Cox proportional hazard models to calculate hazard ratios (HR) and 95% confidence intervals (CI) for cancer-specific and all-cause mortality for individuals undergoing formal surgery versus local excision.

RESULTS

394 patients with pT1 CRC were included. Of these, 37.1% were treated by local resection, 36.8% had biopsy followed by surgery and 26.1% had local excision followed by surgery. There were 60 deaths over a mean 4.8 years of follow-up, including 10 CRC-specific deaths. An additional 12 patients had a CRC recurrence or metastases during follow-up. Of the CRC-specific deaths or recurrences, 27.3% had local excision only. Individuals treated by formal surgery did not have a reduced risk of CRC-specific death (adjusted HR = 1.51, 95% CI 0.29, 7.89), but did have a reduced risk of all-cause mortality (adjusted HR = 0.51 95% CI 0.30, 0.87) compared with those undergoing local excision only.

CONCLUSIONS

Patients with stage pT1 CRC undergoing formal surgery had a reduced risk of all-cause mortality compared with those treated by local excision only. However, this was not explained by a reduced risk of recurrence/disease-free survival or CRC death, and suggests that the observed benefits may simply reflect selection of a healthier patient population in the formal surgery group.

Chromosome Instability; Implications in Cancer Development, Progression, and Clinical Outcomes

Chromosome instability (CIN) refers to an ongoing rate of chromosomal changes and is a driver of genetic, cell-to-cell heterogeneity. It is an aberrant phenotype that is intimately associated with cancer development and progression. The presence, extent, and level of CIN has tremendous implications for the clinical management and outcomes of those living with cancer. Despite its relevance in cancer, there is still extensive misuse of the term CIN, and this has adversely impacted our ability to identify and characterize the molecular determinants of CIN. Though several decades of genetic research have provided insight into CIN, the molecular determinants remain largely unknown, which severely limits its clinical potential. In this review, we provide a definition of CIN, describe the two main types, and discuss how it differs from aneuploidy. We subsequently detail its impact on cancer development and progression, and describe how it influences metastatic potential with reference to cancer prognosis and outcomes. Finally, we end with a discussion of how CIN induces genetic heterogeneity to influence the use and efficacy of several precision medicine strategies, including patient and risk stratification, as well as its impact on the acquisition of drug resistance and disease recurrence.

Association of tumor genomic factors and efficacy for metastasis-directed stereotactic body radiotherapy for oligometastatic colorectal cancer

PURPOSE/OBJECTIVE(S)

To report tumor genomic factors associated with overall survival (OS) and local failure (LF) for patients with colorectal cancer (CRC) who received metastasis-directed stereotactic body radiation therapy (SBRT).

MATERIALS/METHODS

This was a retrospective review of patients with CRC who received metastasis-directed SBRT. Tumor genomic alterations were identified through KRAS, BRAF, or a 50-gene next generation sequencing panel. OS and LF were estimated using Kaplan-Meier and competing-risk methods.

RESULTS

Eighty-five patients and 109 lesions were treated between 2008 and 2018. The median patient follow-up was 50 months (IQR: 28-107). The median and 5-year OS was 34 months and 26% (95% CI: 16-41%), respectively. The 2-year cumulative incidence of LF was 30% (95% CI: 23-41%). Univariate associates with OS included patient age ≥60 years, bone metastasis, increasing tumor size, KRAS mutation, and combined KRAS and TP53 mutation, while increasing tumor size, bone metastasis, biologically effective dose <100 Gy, and combined KRAS and TP53 mutation were associated with LF. Multivariate associates with OS included patient age ≥60 years (HR: 2.4, 95% CI: 1.2-4.8, p = 0.01), lesion size per 1 cm (HR: 1.3, 95% CI: 1.1-1.5, p < 0.01), and KRAS mutation (HR: 2.2, 95% CI: 1.2-4.3, p < 0.01), while no multivariable model for LF retained more than a single variable.

CONCLUSION

Genomic factors, in particular KRAS and TP53 mutation, may assist in patient selection and radiotherapeutic decision-making for patients with oligometastatic CRC. Prospective validation, ideally with genomic correlation of all irradiated metastases, is warranted.

Power and pitfalls of computational methods for inferring clone phylogenies and mutation orders from bulk sequencing data

Tumors harbor extensive genetic heterogeneity in the form of distinct clone genotypes that arise over time and across different tissues and regions in cancer. Many computational methods produce clone phylogenies from population bulk sequencing data collected from multiple tumor samples from a patient. These clone phylogenies are used to infer mutation order and clone origins during tumor progression, rendering the selection of the appropriate clonal deconvolution method critical. Surprisingly, absolute and relative accuracies of these methods in correctly inferring clone phylogenies are yet to consistently assessed. Therefore, we evaluated the performance of seven computational methods. The accuracy of the reconstructed mutation order and inferred clone groupings varied extensively among methods. All the tested methods showed limited ability to identify ancestral clone sequences present in tumor samples correctly. The presence of copy number alterations, the occurrence of multiple seeding events among tumor sites during metastatic tumor evolution, and extensive intermixture of cancer cells among tumors hindered the detection of clones and the inference of clone phylogenies for all methods tested. Overall, CloneFinder, MACHINA, and LICHeE showed the highest overall accuracy, but none of the methods performed well for all simulated datasets. So, we present guidelines for selecting methods for data analysis.

Genetic heterogeneity and evolutionary history of high-grade ovarian carcinoma and matched distant metastases

BACKGROUND

High-grade serous ovarian carcinoma (HGSOC) is the most frequent type of ovarian carcinoma, associated with poor clinical outcome and metastatic disease. Although metastatic processes are becoming more understandable, the genomic landscape and metastatic progression in HGSOC has not been elucidated.

METHODS

Multi-region whole-exome sequencing was performed on HGSOC primary tumours and their metastases (n = 33 tumour regions) from six patients. The resulting somatic variants were analysed to delineate tumour evolution and metastatic dissemination, and to compare the repertoire of events between primary HGSOC and metastasis.

RESULTS

All cases presented branching evolution patterns in primary HGSOC, with three cases further showing parallel evolution in which different mutations on separate branches of a phylogenetic tree converge on the same gene. Furthermore, linear metastatic progression was observed in 67% of cases with late dissemination, in which the metastatic tumour mostly acquires the same mutational process active in primary tumour, and parallel metastatic progression, with early dissemination in the remaining 33.3% of cases. Metastatic-specific SNVs were further confirmed as late dissemination events. We also found the involvement of metastatic-specific driver events in the Wnt/β-catenin pathway, and identified potential clinically actionable events in individual patients of the metastatic HGSOC cohort.

CONCLUSIONS

This study provides deeper insights into clonal evolution and mutational processes that can pave the way to new therapeutic targets.

The pan-therapeutic resistance of disseminated tumor cells: Role of phenotypic plasticity and the metastatic microenvironment

Cancer metastasis is the leading cause of mortality in patients with solid tumors. The majority of these deaths are associated with metastatic disease that occurs after a period of clinical remission, anywhere from months to decades following removal of the primary mass. This dormancy is prominent in cancers of the breast and prostate among others, leaving the survivors uncertain about their longer-term prognosis. The most daunting aspect of this dormancy and re-emergence is that the micrometastases in particular, and even large lethal outgrowths are often show resistance to agents to which they have not been exposed. This suggests that in addition to specific mutations that target single agents, there also exist adaptive mechanisms that provide this pan-resistance. Potential molecular underpinnings of which are the topic of this review.

Delineation of Tumor Migration Paths by Using a Bayesian Biogeographic Approach

Understanding tumor progression and metastatic potential are important in cancer biology. Metastasis is the migration and colonization of clones in secondary tissues. Here, we posit that clone migration events between tumors resemble the dispersal of individuals between distinct geographic regions. This similarity makes Bayesian biogeographic analysis suitable for inferring cancer cell migration paths. We evaluated the accuracy of a Bayesian biogeography method (BBM) in inferring metastatic patterns and compared it with the accuracy of a parsimony-based approach (metastatic and clonal history integrative analysis, MACHINA) that has been specifically developed to infer clone migration patterns among tumors. We used computer-simulated datasets in which simple to complex migration patterns were modeled. BBM and MACHINA were effective in reliably reconstructing simple migration patterns from primary tumors to metastases. However, both of them exhibited a limited ability to accurately infer complex migration paths that involve the migration of clones from one metastatic tumor to another and from metastasis to the primary tumor. Therefore, advanced computational methods are still needed for the biologically realistic tracing of migration paths and to assess the relative preponderance of different types of seeding and reseeding events during cancer progression in patients.