Cancer evolution: Darwin and beyond

Cetuximab chemotherapy resistance: Insight into the homeostatic evolution of head and neck cancer (Review)

The complex evolution of genetic alterations in cancer that occurs in vivo is a selective process involving numerous factors and mechanisms. Chemotherapeutic agents that prevent the growth and spread of cancer cells induce selective pressure, leading to rapid artificial selection of resistant subclones. This rapid evolution is possible because antineoplastic drugs promote alterations in tumor‑cell metabolism, thus creating a bottleneck event. The few resistant cells that survive in this new environment obtain differential reproductive success that enables them to pass down the newly selected resistant gene pool. The present review aims to summarize key findings of tumor evolution, epithelial‑mesenchymal transition and resistance to cetuximab therapy in head and neck squamous cell carcinoma.

Genomic progression for local invasion of cutaneous squamous cell carcinoma from the superficial to the deep portion

Cutaneous squamous cell carcinoma (cSCC) is the second most common skin cancer. While many treatments exist, our understanding of its genomic progression, especially from the epidermis to the deep dermis, remains limited. This study aims to identify genetic mutations associated with the progression of cSCC into the deep dermis, providing insights into its aggressive behavior and high-risk features. We performed high-depth whole-exome sequencing on 12 cSCC tissues, along with paired normal tissues from six patients, using microdissection techniques. The mutational analysis focused on identifying alterations enriched during cSCC progression. Gene Ontology enrichment analysis, immunohistochemical assays, and external single-cell RNA data were utilized for validation. A total of 8863 non-synonymous somatic mutations were identified in 4092 genes across the superficial and deep portions of cSCCs. Analysis of deep portion mutations revealed a significant correlation with gene ontology biological processes, particularly cell junction organization, and cell-cell adhesion. Clonal mutations in these processes were more prevalent in the deep portions, indicating their impact on the cSCC mutation landscape. Genetic evolution analysis identified 29 causal genes associated with dermal invasion in cSCC. We highlight somatic mutations in cSCC, revealing heterogeneity between superficial and deep regions. Altered genes in cell junction organization and cell-cell adhesion emerged as pivotal in dermal invasion. We identified 29 causal genes primarily in deep tumor regions. Our findings emphasize analyzing multiple tumor regions to capture varied mutational landscapes. These insights advance our understanding of cSCC progression, emphasizing genetic and cellular changes during tumor evolution.

Progression-free survival after front line, second line and third line in patients with follicular lymphoma treated in clinical practice

BACKGROUND

The modern-day therapeutic landscape for follicular lymphoma (FL) includes a number of highly effective therapies.

PATIENTS AND METHODS

We set out to determine progression-free survival (PFS) after front line, second line, and third line of therapy on the basis of relevant biological characteristics and therapeutic choices. Patients (n = 743, 51% females, median 60 years old) diagnosed with grade 1-2 FL between 1997 and 2016 in nine institutions were included.

RESULTS

The median PFS1, PFS2, and PFS3 were 8.1 years (95% confidence interval [CI]: 7-9.3 years), 4.2 years (95% CI: 2.8-5.6 years) and 2.2 years (95% CI 1.7-2.8 years). We found longer PFS1 for (1) females, (2) younger age, (3) lower-risk follicular lymphoma international prognostic index (FLIPI), (4) standard intensity (over low intensity) regimens and (5) immunochemotherapy strategies and (6) maintenance rituximab. We found a shorter PFS2 for patients who received front-line immunochemotherapy. Older age at diagnosis correlated with a shorter PFS3. Intensity of front-line chemotherapy, maintenance, or POD24 status did not correlate with PFS2 or PFS3 in this dataset.

INTERPRETATION

With current immunochemotherapy strategies, the natural course of FL is characterized by shorter-lasting remissions after each relapse. It will be interesting to see whether new therapies can alter this pattern.

Unveiling Alterations of Epigenetic Modifications and Chromatin Architecture Leading to Lipid Metabolic Reprogramming during the Evolutionary Trastuzumab Adaptation of HER2-Positive Breast Cancer

Secondary trastuzumab resistance represents an evolutionary adaptation of HER2-positive breast cancer during anti-HER2 treatment. Most current studies have tended to prioritize HER2 and its associated signaling pathways, often overlooking broader but seemingly less relevant cellular processes, along with their associated genetic and epigenetic mechanisms. Here, transcriptome data is not only characterized but also examined epigenomic and 3D genome architecture information in both trastuzumab-sensitive and secondary-resistant breast cancer cells. The findings reveal that the global metabolic reprogramming associated with trastuzumab resistance may stem from genome-wide alterations in both histone modifications and chromatin structure. Specifically, the transcriptional activities of key genes involved in lipid metabolism appear to be regulated by variant promoter H3K27me3 and H3K4me3 modifications, as well as promoter-enhancer interactions. These discoveries offer valuable insights into how cancer cells adapt to anti-tumor drugs and have the potential to impact future diagnostic and treatment strategies.

Spatiotemporally resolved colorectal oncogenesis in mini-colons ex vivo

Three-dimensional organoid culture technologies have revolutionized cancer research by allowing for more realistic and scalable reproductions of both tumour and microenvironmental structures1-3. This has enabled better modelling of low-complexity cancer cell behaviours that occur over relatively short periods of time4. However, available organoid systems do not capture the intricate evolutionary process of cancer development in terms of tissue architecture, cell diversity, homeostasis and lifespan. As a consequence, oncogenesis and tumour formation studies are not possible in vitro and instead require the extensive use of animal models, which provide limited spatiotemporal resolution of cellular dynamics and come at a considerable cost in terms of resources and animal lives. Here we developed topobiologically complex mini-colons that are able to undergo tumorigenesis ex vivo by integrating microfabrication, optogenetic and tissue engineering approaches. With this system, tumorigenic transformation can be spatiotemporally controlled by directing oncogenic activation through blue-light exposure, and emergent colon tumours can be tracked in real-time at the single-cell resolution for several weeks without breaking the culture. These induced mini-colons display rich intratumoural and intertumoural diversity and recapitulate key pathophysiological hallmarks displayed by colorectal tumours in vivo. By fine-tuning cell-intrinsic and cell-extrinsic parameters, mini-colons can be used to identify tumorigenic determinants and pharmacological opportunities. As a whole, our study paves the way for cancer initiation research outside living organisms.

Assessment of cancer cell-expressed HLA class I molecules and their immunopathological implications

Immunotherapy using immune checkpoint inhibitors (ICIs) has shown superior efficacy compared with conventional chemotherapy in certain cancer types, establishing immunotherapy as the fourth standard treatment alongside surgical intervention, chemotherapy, and radiotherapy. In cancer immunotherapy employing ICIs, CD8-positive cytotoxic T lymphocytes are recognized as the primary effector cells. For effective clinical outcomes, it is essential that the targeted cancer cells express HLA class I molecules to present antigenic peptides derived from the tumor. However, cancer cells utilize various mechanisms to downregulate or lose HLA class I molecules from their surface, resulting in evasion from immune surveillance. Correlations between prognosis and the integrity of HLA class I molecules expressed by cancer cells have been consistently found across different types of cancer. This paper provides an overview of the regulatory mechanisms of HLA class I molecules and their role in cancer immunotherapy, with a particular emphasis on the significance of utilizing pathological tissues to evaluate HLA class I molecules expressed in cancer cells.

A glycolytic metabolite bypasses "two-hit" tumor suppression by BRCA2

Knudson's "two-hit" paradigm posits that carcinogenesis requires inactivation of both copies of an autosomal tumor suppressor gene. Here, we report that the glycolytic metabolite methylglyoxal (MGO) transiently bypasses Knudson's paradigm by inactivating the breast cancer suppressor protein BRCA2 to elicit a cancer-associated, mutational single-base substitution (SBS) signature in nonmalignant mammary cells or patient-derived organoids. Germline monoallelic BRCA2 mutations predispose to these changes. An analogous SBS signature, again without biallelic BRCA2 inactivation, accompanies MGO accumulation and DNA damage in Kras-driven, Brca2-mutant murine pancreatic cancers and human breast cancers. MGO triggers BRCA2 proteolysis, temporarily disabling BRCA2's tumor suppressive functions in DNA repair and replication, causing functional haploinsufficiency. Intermittent MGO exposure incites episodic SBS mutations without permanent BRCA2 inactivation. Thus, a metabolic mechanism wherein MGO-induced BRCA2 haploinsufficiency transiently bypasses Knudson's two-hit requirement could link glycolysis activation by oncogenes, metabolic disorders, or dietary challenges to mutational signatures implicated in cancer evolution.

Educate, not kill: treating cancer without triggering its defenses

Traditionally, anticancer therapies focus on restraining uncontrolled proliferation. However, these cytotoxic therapies expose cancer cells to direct killing, instigating the process of natural selection favoring survival of resistant cells that become the foundation for tumor progression and therapy failure. Recognizing this phenomenon has prompted the development of alternative therapeutic strategies. Here we propose strategies targeting cancer hallmarks beyond proliferation, aiming at re-educating cancer cells towards a less malignant phenotype. These strategies include controlling cell dormancy, transdifferentiation therapy, normalizing the cancer microenvironment, and using migrastatic therapy. Adaptive resistance to these educative strategies does not confer a direct proliferative advantage to resistant cells, as non-resistant cells are not subject to eradication, thereby delaying or preventing the development of therapy-resistant tumors.

Stochastic modelling of single-cell gene expression adaptation reveals non-genomic contribution to evolution of tumor subclones

Cancer progression is an evolutionary process driven by the selection of cells adapted to gain growth advantage. We present the first formal study on the adaptation of gene expression in subclonal evolution. We model evolutionary changes in gene expression as stochastic Ornstein-Uhlenbeck processes, jointly leveraging the evolutionary history of subclones and single-cell expression data. Applying our model to sublines derived from single cells of a mouse melanoma revealed that sublines with distinct phenotypes are underlined by different patterns of gene expression adaptation, indicating non-genetic mechanisms of cancer evolution. Interestingly, sublines previously observed to be resistant to anti-CTLA-4 treatment showed adaptive expression of genes related to invasion and non-canonical Wnt signaling, whereas sublines that responded to treatment showed adaptive expression of genes related to proliferation and canonical Wnt signaling. Our results suggest that clonal phenotypes emerge as the result of specific adaptivity patterns of gene expression.

A novel multiscale framework for delineating cancer evolution from subclonal compositions

OBJECTIVE

Owing to the heterogeneity in the evolution of cancer, distinguishing between diverse growth patterns and predicting long-term outcomes based on short-term measurements poses a great challenge.

METHODS

A novel multiscale framework is proposed to unravel the connections between the population dynamics of cancer growth (i.e., aggressive, bounded, and indolent) and the cellular-subclonal dynamics of cancer evolution. This framework employs the non-negative lasso (NN-LASSO) algorithm to forge a link between an ordinary differential equation (ODE)-based population model and a cellular evolution model.

RESULTS

The findings of our current work not only affirm the impact of subclonal composition on growth dynamics but also identify two significant subclones within heterogeneous growth patterns. Moreover, the subclonal compositions at the initial time are able to accurately discriminate diverse growth patterns through a machine learning algorithm.

CONCLUSION

The proposed multiscale framework successfully delineates the intricate landscape of cancer evolution, bridging the gap between long-term growth dynamics and short-term measurements, both in simulated and real-world data. This methodology provides a novel avenue for thorough exploration into the realm of cancer evolution.

Extrachromosomal DNA in cancer

Extrachromosomal DNA (ecDNA) has recently been recognized as a major contributor to cancer pathogenesis that is identified in most cancer types and is associated with poor outcomes. When it was discovered over 60 years ago, ecDNA was considered to be rare, and its impact on tumour biology was not well understood. The application of modern imaging and computational techniques has yielded powerful new insights into the importance of ecDNA in cancer. The non-chromosomal inheritance of ecDNA during cell division results in high oncogene copy number, intra-tumoural genetic heterogeneity and rapid tumour evolution that contributes to treatment resistance and shorter patient survival. In addition, the circular architecture of ecDNA results in altered patterns of gene regulation that drive elevated oncogene expression, potentially enabling the remodelling of tumour genomes. The generation of clusters of ecDNAs, termed ecDNA hubs, results in interactions between enhancers and promoters in trans, yielding a new paradigm in oncogenic transcription. In this Review, we highlight the rapid advancements in ecDNA research, providing new insights into ecDNA biogenesis, maintenance and transcription and its role in promoting tumour heterogeneity. To conclude, we delve into a set of unanswered questions whose answers will pave the way for the development of ecDNA targeted therapeutic approaches.

Characterization of tumor evolution by functional clonality and phylogenetics in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a molecularly heterogeneous solid malignancy, and its fitness may be shaped by how its tumor cells evolve. However, ability to monitor tumor cell evolution is hampered by the presence of numerous passenger mutations that do not provide any biological consequences. Here we develop a strategy to determine the tumor clonality of three independent HCC cohorts of 524 patients with diverse etiologies and race/ethnicity by utilizing somatic mutations in cancer driver genes. We identify two main types of tumor evolution, i.e., linear, and non-linear models where non-linear type could be further divided into classes, which we call shallow branching and deep branching. We find that linear evolving HCC is less aggressive than other types. GTF2IRD2B mutations are enriched in HCC with linear evolution, while TP53 mutations are the most frequent genetic alterations in HCC with non-linear models. Furthermore, we observe significant B cell enrichment in linear trees compared to non-linear trees suggesting the need for further research to uncover potential variations in immune cell types within genomically determined phylogeny types. These results hint at the possibility that tumor cells and their microenvironment may collectively influence the tumor evolution process.

Cellular senescence is associated with the spatial evolution toward a higher metastatic phenotype in colorectal cancer

In this study, we explore the dynamic process of colorectal cancer progression, emphasizing the evolution toward a more metastatic phenotype. The term "evolution" as used in this study specifically denotes the phenotypic transition toward a higher metastatic potency from well-formed glandular structures to collective invasion, ultimately resulting in the development of cancer cell buddings at the invasive front. Our findings highlight the spatial correlation of this evolution with tumor cell senescence, revealing distinct types of senescent tumor cells (types I and II) that play different roles in the overall cancer progression. Type I senescent tumor cells (p16INK4A+/CXCL12+/LAMC2-/MMP7-) are identified in the collective invasion region, whereas type II senescent tumor cells (p16INK4A+/CXCL12+/LAMC2+/MMP7+), representing the final evolved form, are prominently located in the partial-EMT region. Importantly, type II senescent tumor cells associate with local invasion and lymph node metastasis in colorectal cancer, potentially affecting patient prognosis.

Fast and flexible profiling of chromatin accessibility and total RNA expression in single nuclei using Microwell-seq3

Single cell chromatin accessibility profiling and transcriptome sequencing are the most widely used technologies for single-cell genomics. Here, we present Microwell-seq3, a high-throughput and facile platform for high-sensitivity single-nucleus chromatin accessibility or full-length transcriptome profiling. The method combines a preindexing strategy and a penetrable chip-in-a-tube for single nucleus loading and DNA amplification and therefore does not require specialized equipment. We used Microwell-seq3 to profile chromatin accessibility in more than 200,000 single nuclei and the full-length transcriptome in ~50,000 nuclei from multiple adult mouse tissues. Compared with the existing polyadenylated transcript capture methods, integrative analysis of cell type-specific regulatory elements and total RNA expression uncovered comprehensive cell type heterogeneity in the brain. Gene regulatory networks based on chromatin accessibility profiling provided an improved cell type communication model. Finally, we demonstrated that Microwell-seq3 can identify malignant cells and their specific regulons in spontaneous lung tumors of aged mice. We envision a broad application of Microwell-seq3 in many areas of research.

The antagonistic relationship between apoptosis and polyploidy in development and cancer

One of the important functions of regulated cell death is to prevent cells from inappropriately acquiring extra copies of their genome, a state known as polyploidy. Apoptosis is the primary cell death mechanism that prevents polyploidy, and defects in this apoptotic response can result in polyploid cells whose subsequent error-prone chromosome segregation are a major contributor to genome instability and cancer progression. Conversely, some cells actively repress apoptosis to become polyploid as part of normal development or regeneration. Thus, although apoptosis prevents polyploidy, the polyploid state can actively repress apoptosis. In this review, we discuss progress in understanding the antagonistic relationship between apoptosis and polyploidy in development and cancer. Despite recent advances, a key conclusion is that much remains unknown about the mechanisms that link apoptosis to polyploid cell cycles. We suggest that drawing parallels between the regulation of apoptosis in development and cancer could help to fill this knowledge gap and lead to more effective therapies.

Editorial for the Special Issue "Latest Review Papers in Molecular Oncology 2023"

Human cancers are products of multistep processes resulting in abnormal cell growth and differentiation, along with a loss of apoptotic function, leading to the uncontrolled expansion of neoplastic cells and their spread to surrounding tissues and, ultimately, distant parts of the body [...].

A binary trait model reveals the fitness effects of HIV-1 escape from T cell responses

Natural selection often acts on multiple traits simultaneously. For example, the virus HIV-1 faces pressure to evade host immunity while also preserving replicative fitness. While past work has studied selection during HIV-1 evolution, it is challenging to quantitatively separate different contributions to fitness. This task is made more difficult because a single mutation can affect both immune escape and replication. Here, we develop an evolutionary model that disentangles the effects of escaping CD8+ T cell-mediated immunity, which we model as a binary trait, from other contributions to fitness. After validation in simulations, we applied this model to study within-host HIV-1 evolution in a clinical data set. We observed strong selection for immune escape, sometimes greatly exceeding past estimates, especially early in infection. Conservative estimates suggest that roughly half of HIV-1 fitness gains during the first months to years of infection can be attributed to T cell escape. Our approach is not limited to HIV-1 or viruses, and could be adapted to study the evolution of quantitative traits in other contexts.

Moving toward precision medicine to predict drug sensitivity in patients with metastatic breast cancer

Tumor heterogeneity represents a major challenge in breast cancer, being associated with disease progression and treatment resistance. Precision medicine has been extensively applied to dissect tumor heterogeneity and, through a deeper molecular understanding of the disease, to personalize therapeutic strategies. In the last years, technological advances have widely improved the understanding of breast cancer biology and several trials have been developed to translate these new insights into clinical practice, with the ultimate aim of improving patients' outcomes. In the era of molecular oncology, genomics analyses and other methodologies are shaping a new treatment algorithm in breast cancer care. In this manuscript, we review the main steps of precision medicine to predict drug sensitivity in breast cancer from a translational point of view. Genomic developments and their clinical implications are discussed, along with technological advancements that could broaden precision medicine applications. Current achievements are put into perspective to provide an overview of the state-of-art of breast cancer precision oncology as well as to identify future research directions.

Deep quantitative proteomics of North American Pacific coast star tunicate (Botryllus schlosseri)

Botryllus schlosseri, is a model marine invertebrate for studying immunity, regeneration, and stress-induced evolution. Conditions for validating its predicted proteome were optimized using nanoElute® 2 deep-coverage LCMS, revealing up to 4930 protein groups and 20,984 unique peptides per sample. Spectral libraries were generated and filtered to remove interferences, low-quality transitions, and only retain proteins with >3 unique peptides. The resulting DIA assay library enabled label-free quantitation of 3426 protein groups represented by 22,593 unique peptides. Quantitative comparisons of single systems from a laboratory-raised with two field-collected populations revealed (1) a more unique proteome in the laboratory-raised population, and (2) proteins with high/low individual variabilities in each population. DNA repair/replication, ion transport, and intracellular signaling processes were distinct in laboratory-cultured colonies. Spliceosome and Wnt signaling proteins were the least variable (highly functionally constrained) in all populations. In conclusion, we present the first colonial tunicate's deep quantitative proteome analysis, identifying functional protein clusters associated with laboratory conditions, different habitats, and strong versus relaxed abundance constraints. These results empower research on B. schlosseri with proteomics resources and enable quantitative molecular phenotyping of changes associated with transfer from in situ to ex situ and from in vivo to in vitro culture conditions.

Malignant tumor cells engender second membrane-lined organelles for self-protection and tumor progression

Cancer is a leading cause of mortality in humans, but the efficacy of current treatments for many cancers is limited, as they lack unique mechanistically defined targets. Here, we show that, upon malignant transformation, aggressive oncocells generate a second membrane exterior to their plasma membrane to form cytocapsulas (CCs) and cytocapsular tubes (CCTs), which all together constitute cytocapsular oncocells with pleotropic biological functions in cancer patient tissues in vivo. Proteomic and biochemical analyses revealed that the PMCA2 calcium pump is highly up-regulated in CCs and CCTs in malignant tumors but not in normal tissues, thus identifying a unique cancer biomarker and target for cancer therapy. Cytocapsular oncocells are universally present in solid cancers and appear in hematologic cancers in immune organs. Multi-cell malignant tumors are also enveloped by protective CC membranes. These cytocapsular tumors (CTs) generate numerous CCTs that form freeways for cancer cell metastasis to both neighboring and distant destinations. Entire cytocapsular tumor networks (CTNs) dominate physical cancer metastasis pathways in cancer patients in vivo. Later, CCTs invade micro blood vessels and release cytocapsular oncocells into the blood, providing a source of circulating tumor cells. CTNs interconnect cytocapsular tumors in primary and secondary cancer niches, creating larger cytocapsular tumor network systems (CTNSs). Primary and secondary CTNSs are in turn interconnected, forming dynamic and integrated CTNSs. Thus, interconnected cytocapsular oncocells, CTNs, and CTNSs coordinate cancer progression via the integrated cytocapsular membrane systems.

Epigenetic regulation of mRNA mediates the phenotypic plasticity of cancer cells during metastasis and therapeutic resistance (Review)

Plasticity, the ability of cancer cells to transition between differentiation states without genomic alterations, has been recognized as a major source of intratumoral heterogeneity. It has a crucial role in cancer metastasis and treatment resistance. Thus, targeting plasticity holds tremendous promise. However, the molecular mechanisms of plasticity in cancer cells remain poorly understood. Several studies found that mRNA, which acts as a bridge linking the genetic information of DNA and protein, has an important role in translating genotypes into phenotypes. The present review provided an overview of the regulation of cancer cell plasticity occurring via changes in the transcription and editing of mRNAs. The role of the transcriptional regulation of mRNA in cancer cell plasticity was discussed, including DNA‑binding transcriptional factors, DNA methylation, histone modifications and enhancers. Furthermore, the role of mRNA editing in cancer cell plasticity was debated, including mRNA splicing and mRNA modification. In addition, the role of non‑coding (nc)RNAs in cancer plasticity was expounded, including microRNAs, long intergenic ncRNAs and circular RNAs. Finally, different strategies for targeting cancer cell plasticity to overcome metastasis and therapeutic resistance in cancer were discussed.

Bacteria colonization in tumor microenvironment creates a favorable niche for immunogenic chemotherapy

The tumor microenvironment (TME) presents differential selective pressure (DSP) that favors the growth of cancer cells, and monovalent therapy is often inadequate in reversing the cancer cell dominance in the TME. In this work, we introduce bacteria as a foreign species to the TME and explore combinatorial treatment strategies to alter DSP for tumor eradication. We show that cancer-selective chemotherapeutic agents and fasting can provide a strong selection pressure against tumor growth in the presence of bacteria. Moreover, we show that an immunogenic drug (oxaliplatin), but not a non-immunogenic one (5-FU), synergizes with the bacteria to activate both the innate and adaptive immunity in the TME, resulting in complete tumor remission and a sustained anti-tumor immunological memory in mice. The combination of oxaliplatin and bacteria greatly enhances the co-stimulatory and antigen-presenting molecules on antigen-presenting cells, which in turn bridge the cytotoxic T cells for cancer-cell killing. Our findings indicate that rational combination of bacterial therapy and immunogenic chemotherapy can promote anticancer immunity against the immunosuppressive TME.

Onco-Breastomics: An Eco-Evo-Devo Holistic Approach

Known as a diverse collection of neoplastic diseases, breast cancer (BC) can be hyperbolically characterized as a dynamic pseudo-organ, a living organism able to build a complex, open, hierarchically organized, self-sustainable, and self-renewable tumor system, a population, a species, a local community, a biocenosis, or an evolving dynamical ecosystem (i.e., immune or metabolic ecosystem) that emphasizes both developmental continuity and spatio-temporal change. Moreover, a cancer cell community, also known as an oncobiota, has been described as non-sexually reproducing species, as well as a migratory or invasive species that expresses intelligent behavior, or an endangered or parasite species that fights to survive, to optimize its features inside the host's ecosystem, or that is able to exploit or to disrupt its host circadian cycle for improving the own proliferation and spreading. BC tumorigenesis has also been compared with the early embryo and placenta development that may suggest new strategies for research and therapy. Furthermore, BC has also been characterized as an environmental disease or as an ecological disorder. Many mechanisms of cancer progression have been explained by principles of ecology, developmental biology, and evolutionary paradigms. Many authors have discussed ecological, developmental, and evolutionary strategies for more successful anti-cancer therapies, or for understanding the ecological, developmental, and evolutionary bases of BC exploitable vulnerabilities. Herein, we used the integrated framework of three well known ecological theories: the Bronfenbrenner's theory of human development, the Vannote's River Continuum Concept (RCC), and the Ecological Evolutionary Developmental Biology (Eco-Evo-Devo) theory, to explain and understand several eco-evo-devo-based principles that govern BC progression. Multi-omics fields, taken together as onco-breastomics, offer better opportunities to integrate, analyze, and interpret large amounts of complex heterogeneous data, such as various and big-omics data obtained by multiple investigative modalities, for understanding the eco-evo-devo-based principles that drive BC progression and treatment. These integrative eco-evo-devo theories can help clinicians better diagnose and treat BC, for example, by using non-invasive biomarkers in liquid-biopsies that have emerged from integrated omics-based data that accurately reflect the biomolecular landscape of the primary tumor in order to avoid mutilating preventive surgery, like bilateral mastectomy. From the perspective of preventive, personalized, and participatory medicine, these hypotheses may help patients to think about this disease as a process governed by natural rules, to understand the possible causes of the disease, and to gain control on their own health.

Cancer Evolution: A Multifaceted Affair

Cancer cells adapt and survive through the acquisition and selection of molecular modifications. This process defines cancer evolution. Building on a theoretical framework based on heritable genetic changes has provided insights into the mechanisms supporting cancer evolution. However, cancer hallmarks also emerge via heritable nongenetic mechanisms, including epigenetic and chromatin topological changes, and interactions between tumor cells and the tumor microenvironment. Recent findings on tumor evolutionary mechanisms draw a multifaceted picture where heterogeneous forces interact and influence each other while shaping tumor progression. A comprehensive characterization of the cancer evolutionary toolkit is required to improve personalized medicine and biomarker discovery.

SIGNIFICANCE

Tumor evolution is fueled by multiple enabling mechanisms. Importantly, genetic instability, epigenetic reprogramming, and interactions with the tumor microenvironment are neither alternative nor independent evolutionary mechanisms. As demonstrated by findings highlighted in this perspective, experimental and theoretical approaches must account for multiple evolutionary mechanisms and their interactions to ultimately understand, predict, and steer tumor evolution.

Concurrent Tissue and Circulating Tumor DNA Molecular Profiling to Detect Guideline-Based Targeted Mutations in a Multicancer Cohort

Importance

Tissue-based next-generation sequencing (NGS) of solid tumors is the criterion standard for identifying somatic mutations that can be treated with National Comprehensive Cancer Network guideline-recommended targeted therapies. Sequencing of circulating tumor DNA (ctDNA) can also identify tumor-derived mutations, and there is increasing clinical evidence supporting ctDNA testing as a diagnostic tool. The clinical value of concurrent tissue and ctDNA profiling has not been formally assessed in a large, multicancer cohort from heterogeneous clinical settings.

Objective

To evaluate whether patients concurrently tested with both tissue and ctDNA NGS testing have a higher rate of detection of guideline-based targeted mutations compared with tissue testing alone.

Design, Setting, and Participants

This cohort study comprised 3209 patients who underwent sequencing between May 2020, and December 2022, within the deidentified, Tempus multimodal database, consisting of linked molecular and clinical data. Included patients had stage IV disease (non-small cell lung cancer, breast cancer, prostate cancer, or colorectal cancer) with sufficient tissue and blood sample quantities for analysis.

Exposures

Received results from tissue and plasma ctDNA genomic profiling, with biopsies and blood draws occurring within 30 days of one another.

Main Outcomes and Measures

Detection rates of guideline-based variants found uniquely by ctDNA and tissue profiling.

Results

The cohort of 3209 patients (median age at diagnosis of stage IV disease, 65.3 years [2.5%-97.5% range, 43.3-83.3 years]) who underwent concurrent tissue and ctDNA testing included 1693 women (52.8%). Overall, 1448 patients (45.1%) had a guideline-based variant detected. Of these patients, 9.3% (135 of 1448) had variants uniquely detected by ctDNA profiling, and 24.2% (351 of 1448) had variants uniquely detected by solid-tissue testing. Although largely concordant with one another, differences in the identification of actionable variants by either assay varied according to cancer type, gene, variant, and ctDNA burden. Of 352 patients with breast cancer, 20.2% (71 of 352) with actionable variants had unique findings in ctDNA profiling results. Most of these unique, actionable variants (55.0% [55 of 100]) were found in ESR1, resulting in a 24.7% increase (23 of 93) in the identification of patients harboring an ESR1 mutation relative to tissue testing alone.

Conclusions and Relevance

This study suggests that unique actionable biomarkers are detected by both concurrent tissue and ctDNA testing, with higher ctDNA identification among patients with breast cancer. Integration of concurrent NGS testing into the routine management of advanced solid cancers may expand the delivery of molecularly guided therapy and improve patient outcomes.

Characterizing chromosomal instability-driven cancer evolution and cell fitness at a glance

Chromosomal instability (CIN), an increased rate of chromosome segregation errors during mitosis, is a hallmark of cancer cells. CIN leads to karyotype differences between cells and thus large-scale heterogeneity among individual cancer cells; therefore, it plays an important role in cancer evolution. Studying CIN and its consequences is technically challenging, but various technologies have been developed to track karyotype dynamics during tumorigenesis, trace clonal lineages and link genomic changes to cancer phenotypes at single-cell resolution. These methods provide valuable insight not only into the role of CIN in cancer progression, but also into cancer cell fitness. In this Cell Science at a Glance article and the accompanying poster, we discuss the relationship between CIN, cancer cell fitness and evolution, and highlight techniques that can be used to study the relationship between these factors. To that end, we explore methods of assessing cancer cell fitness, particularly for chromosomally unstable cancer.

In Vitro Evaluation of Cancer Cell Immunogenicity and Antigen-Specific T-Cell Cytotoxicity by Flow Cytometry

A cardinal principle of oncoimmunology is that cancer cells can be eliminated by tumor-infiltrating cytotoxic CD8 T lymphocytes. This has been widely demonstrated during the last 20 years and also recently harnessed for therapy. However, emerging evidence indicates that even neoplasms showing striking initial responses to conventional and targeted (immuno)therapies often acquire resistance, resulting in tumor relapse, increased aggressiveness, and metastatization. Indeed, tumors are complex ecosystems whose malignant and nonmalignant cells, constituting the tumor microenvironment, constantly interact and evolve in space and time. Together with patient's own genetic factors, such environmental interplays may curtail antitumor immune responses leading to cancer immune evasion and natural/acquired (immuno)therapy resistance. In this context, cancer stem cells (CSCs) are thought to be the roots of therapy failure. Flow cytometry is a powerful technology that finds extensive applications in cancer biology. It offers several unique advantages as it allows the rapid, quantitative, and multiparametric analysis of cell populations or functions at the single-cell level. In this chapter, we discuss a two-color flow cytometric protocol to evaluate cancer cell immunogenicity by analyzing the proliferative and tumor-killing potential of ovalbumin (OVA)-specific CD8 OT-1 T cells exposed to OVA-expressing MCA205 sarcoma cells and their CSC counterparts.

Interfacial Organization and Forces Arising from Epithelial-Cancerous Monolayer Interactions

The interfacial interactions between epithelia and cancer cells have profound relevance for tumor development and metastasis. Through monolayer confrontation of MCF10A (nontumorigenic human breast epithelial cells) and MDA-MB-231 (human epithelial breast cancer cells) cells, we investigate the epithelial-cancerous interfacial interactions at the tissue level. We show that the monolayer interaction leads to competitive interfacial morphodynamics and drives an intricate spatial organization of MCF10A cells into multicellular finger-like structures, which further branch into multiple subfinger-like structures. These hierarchical interfacial structures penetrate the cancer monolayer and can spontaneously segregate or even envelop cancer cell clusters, consistent with our theoretical prediction. By tracking the substrate displacements via embedded fluorescent nanobeads and implementing nanomechanical modeling that combines atomic force microscopy and finite element simulations, we computed mechanical force patterns, including traction forces and monolayer stresses, caused by the monolayer interaction. It is found that the heterogeneous mechanical forces accumulated in the monolayers are able to squeeze cancer cells, leading to three-dimensional interfacial bulges or cell extrusion, initiating the p53 apoptosis signaling pathways of cancer cells. We reveal that intercellular E-cadherin and P-cadherin of epithelial cells differentially regulate the interfacial organization including migration speed, directionality, spatial correlation, F-actin alignment, and subcellular protrusions of MCF10A cells; whereas E-cadherin governs interfacial geometry that is relevant to force localization and cancer cell extrusion, P-cadherin maintains interfacial integrity that enables long-range force transmission. Our findings suggest that the collaborative molecular and mechanical behaviors are crucial for preventing epithelial tissues from undergoing tumor invasion.

Circulating tumor DNA: current implementation issues and future challenges for clinical utility

Over the past decades, liquid biopsy, especially circulating tumor DNA (ctDNA), has received tremendous attention as a noninvasive detection approach for clinical applications, including early diagnosis of cancer and relapse, real-time therapeutic efficacy monitoring, potential target selection and investigation of drug resistance mechanisms. In recent years, the application of next-generation sequencing technology combined with AI technology has significantly improved the accuracy and sensitivity of liquid biopsy, enhancing its potential in solid tumors. However, the increasing integration of such promising tests to improve therapy decision making by oncologists still has complexities and challenges. Here, we propose a conceptual framework of ctDNA technologies and clinical utilities based on bibliometrics and highlight current challenges and future directions, especially in clinical applications such as early detection, minimal residual disease detection, targeted therapy, and immunotherapy. We also discuss the necessities of developing a dynamic field of translational cancer research and rigorous clinical studies that may support therapeutic strategy decision making in the near future.

Druggable growth dependencies and tumor evolution analysis in patient-derived organoids of neuroendocrine neoplasms from multiple body sites

Neuroendocrine neoplasms (NENs) comprise well-differentiated neuroendocrine tumors (NETs) and poorly differentiated neuroendocrine carcinomas (NECs). Treatment options for patients with NENs are limited, in part due to lack of accurate models. We establish patient-derived tumor organoids (PDTOs) from pulmonary NETs and derive PDTOs from an understudied subtype of NEC, large cell neuroendocrine carcinoma (LCNEC), arising from multiple body sites. PDTOs maintain the gene expression patterns, intra-tumoral heterogeneity, and evolutionary processes of parental tumors. Through hypothesis-driven drug sensitivity analyses, we identify ASCL1 as a potential biomarker for response of LCNEC to treatment with BCL-2 inhibitors. Additionally, we discover a dependency on EGF in pulmonary NET PDTOs. Consistent with these findings, we find that, in an independent cohort, approximately 50% of pulmonary NETs express EGFR. This study identifies an actionable vulnerability for a subset of pulmonary NETs, emphasizing the utility of these PDTO models.

Intratumor heterogeneity: models of malignancy emergence and evolution

Cancer is a complex and heterogeneous disease characterized by the accumulation of genetic alterations that drive uncontrolled cell growth and proliferation. Evolutionary dynamics plays a crucial role in the emergence and development of tumors, shaping the heterogeneity and adaptability of cancer cells. From the perspective of evolutionary theory, tumors are complex ecosystems that evolve through a process of microevolution influenced by genetic mutations, epigenetic changes, tumor microenvironment factors, and therapy-induced changes. This dynamic nature of tumors poses significant challenges for effective cancer treatment, and understanding it is essential for developing effective and personalized therapies. By uncovering the mechanisms that determine tumor heterogeneity, researchers can identify key genetic and epigenetic changes that contribute to tumor progression and resistance to treatment. This knowledge enables the development of innovative strategies for targeting specific tumor clones, minimizing the risk of recurrence and improving patient outcomes. To investigate the evolutionary dynamics of cancer, researchers employ a wide range of experimental and computational approaches. Traditional experimental methods involve genomic profiling techniques such as next-generation sequencing and fluorescence in situ hybridization. These techniques enable the identification of somatic mutations, copy number alterations, and structural rearrangements within cancer genomes. Furthermore, single-cell sequencing methods have emerged as powerful tools for dissecting intratumoral heterogeneity and tracing clonal evolution. In parallel, computational models and algorithms have been developed to simulate and analyze cancer evolution. These models integrate data from multiple sources to predict tumor growth patterns, identify driver mutations, and infer evolutionary trajectories. In this paper, we set out to describe the current approaches to address this evolutionary complexity and theories of its occurrence.

Neo-Darwinian Principles Exemplified in Cancer Genomics

Within the last two decades, the advent of next-generation sequencing accompanied by single-cell technologies has enabled cancer researchers to study in detail mutations and other genetic aberrations that transpire during transformation of cells to a neoplastic state. This article covers the insights gained through these extensive studies where neo-Darwinian principles can be inferred to play roles throughout neoplastic transformation. The cells promoted during cancer development exhibit cancer hallmarks combined with the related enabling characteristics as outlined by Hanahan and Weinberg, analogous to natural selection and survival of the fittest. Selection of driver mutations that inactivate proteins encoded by tumor suppressor genes differs in profound ways from mutations that activate tumor promoter proteins. In most cases, the later stages of cancer development are characterized by sudden, extensive damage to chromosomes in a process that is not Darwinian in nature. Nevertheless, cells that survive these cataclysmic events remain subject to Darwinian selection promoting clones exhibiting the greatest rates of progression. Duplications of chromosomal segments containing oncogenes, deletions of segments harboring tumor suppressor genes, or distinctive chromosomal rearrangements are often found in cells progressing into later stages of cancer. In summary, the technological developments in genome sequencing since the start of the century have given us clear insights into genomic alterations promoting tumor progression where neo-Darwinian mechanisms of clonal selection can be inferred to play a primary role.

Immunohistochemical markers as predictors of prognosis in multifocal prostate cancer

The impact of tumor focality on prostate cancer (PCa) prognosis has been addressed in several studies with conflicting results. Tumor foci from multifocal (MF) PCa can show highly heterogeneous molecular features. Our aim was to analyze the protein expression of PTEN, SPOP, SLC45A3, ETV1, ERG and the "triple hit" (ERG overexpression, PTEN plus SLC45A3 loss) in unifocal (UF) and MF PCa, to evaluate their value as prognostic markers according to focality, and the role of tumor heterogeneity in MF disease. PTEN, SPOP, SLC45A3, ETV1 and ERG immunohistochemical expression was evaluated in 185 PCa from 9 TMAs, 51 UF and 134 MF. In a subset of 69 MF cases, the dominant and secondary foci (DF and SF) were compared. Heterogeneity was considered when both tumor foci presented different expression patterns. Relationship with clinicopathological features was also analyzed. MF PCa was diagnosed in significantly younger patients when compared to UF ones (p = 0.007). ETV1 overexpression was associated with UF disease (p = 0.028). A shorter time to PSA recurrence was related to SLC45A3 wt expression in UF PCa (p = 0.052), and to SPOP expression loss (p = 0.043) or "triple hit" phenotype in MF PCa (p = 0.041). In MF cases, PTEN loss, SLC45A3 loss and "triple hit" phenotype were associated with the DF and had significant heterogeneity. In conclusion, our results indicate that UF and MF PCa have relevant and consistent molecular differences. The analysis of an immunohistochemical panel, composed by PTEN, SPOP, SLC45A3, ETV1 and ERG, could be useful to predict outcome in MF cases.

Subclonal Somatic Copy-Number Alterations Emerge and Dominate in Recurrent Osteosarcoma

Multiple large-scale genomic profiling efforts have been undertaken in osteosarcoma to define the genomic drivers of tumorigenesis, therapeutic response, and disease recurrence. The spatial and temporal intratumor heterogeneity could also play a role in promoting tumor growth and treatment resistance. We conducted longitudinal whole-genome sequencing of 37 tumor samples from 8 patients with relapsed or refractory osteosarcoma. Each patient had at least one sample from a primary site and a metastatic or relapse site. Subclonal copy-number alterations were identified in all patients except one. In 5 patients, subclones from the primary tumor emerged and dominated at subsequent relapses. MYC gain/amplification was enriched in the treatment-resistant clones in 6 of 7 patients with multiple clones. Amplifications in other potential driver genes, such as CCNE1, RAD21, VEGFA, and IGF1R, were also observed in the resistant copy-number clones. A chromosomal duplication timing analysis revealed that complex genomic rearrangements typically occurred prior to diagnosis, supporting a macroevolutionary model of evolution, where a large number of genomic aberrations are acquired over a short period of time followed by clonal selection, as opposed to ongoing evolution. A mutational signature analysis of recurrent tumors revealed that homologous repair deficiency (HRD)-related SBS3 increases at each time point in patients with recurrent disease, suggesting that HRD continues to be an active mutagenic process after diagnosis. Overall, by examining the clonal relationships between temporally and spatially separated samples from patients with relapsed/refractory osteosarcoma, this study sheds light on the intratumor heterogeneity and potential drivers of treatment resistance in this disease.

SIGNIFICANCE

The chemoresistant population in recurrent osteosarcoma is subclonal at diagnosis, emerges at the time of primary resection due to selective pressure from neoadjuvant chemotherapy, and is characterized by unique oncogenic amplifications.

Chromosome instability and aneuploidy in the mammalian brain

This review investigates the role of aneuploidy and chromosome instability (CIN) in the aging brain. Aneuploidy refers to an abnormal chromosomal count, deviating from the normal diploid set. It can manifest as either a deficiency or excess of chromosomes. CIN encompasses a broader range of chromosomal alterations, including aneuploidy as well as structural modifications in DNA. We provide an overview of the state-of-the-art methodologies utilized for studying aneuploidy and CIN in non-tumor somatic tissues devoid of clonally expanded populations of aneuploid cells.CIN and aneuploidy, well-established hallmarks of cancer cells, are also associated with the aging process. In non-transformed cells, aneuploidy can contribute to functional impairment and developmental disorders. Despite the importance of understanding the prevalence and specific consequences of aneuploidy and CIN in the aging brain, these aspects remain incompletely understood, emphasizing the need for further scientific investigations.This comprehensive review consolidates the present understanding, addresses discrepancies in the literature, and provides valuable insights for future research efforts.

Evaluating the dissemination of evolutionary biology concepts in medicine

Darwin's theory of evolution, which is based on variation, heredity, and selection, includes all biological fields and spreads to other areas such as philosophy. Medicine is an example of how the evolutionary perspective can greatly improve the understanding of concepts in an area, as human health and pathological conditions are under the effect of evolution. Evolutionary medicine is an emerging paradigm for understanding human heterogeneity, health, and diseases. Nevertheless, there are indications that medical research and practice are only marginally affected by these ideas. Here, we investigate how concepts of biological evolution are employed in medical research. We use a bibliometric approach to look for the presence and frequency of biological evolution-related concepts in medical articles. The distribution of these concepts over the years is analyzed according to the medical specialty and the impact of the journal. Our data showed that: i) only a small percentage of articles in medical journals have an evolutionary perspective; ii) medical journals where these evolution-based articles are published focus on basic science, theoretical medicine, and less frequently, on applied medicine; iii) these articles are mostly from the microbiology, immunology, neurology, psychology, behavior, and oncology fields; and iv) viruses are the most frequently covered microorganisms, followed by bacteria, fungi, and protozoans. The collection of our results, considering the importance of evolutionary medicine in the medical field, highlights the need for a decisive change in perspective in medical research.

Cancer origin tracing and timing in two high-risk prostate cancers using multisample whole genome analysis: prospects for personalized medicine

BACKGROUND

Prostate cancer (PrCa) genomic heterogeneity causes resistance to therapies such as androgen deprivation. Such heterogeneity can be deciphered in the context of evolutionary principles, but current clinical trials do not include evolution as an essential feature. Whether or not analysis of genomic data in an evolutionary context in primary prostate cancer can provide unique added value in the research and clinical domains remains an open question.

METHODS

We used novel processing techniques to obtain whole genome data together with 3D anatomic and histomorphologic analysis in two men (GP5 and GP12) with high-risk PrCa undergoing radical prostatectomy. A total of 22 whole genome-sequenced sites (16 primary cancer foci and 6 lymph node metastatic) were analyzed using evolutionary reconstruction tools and spatio-evolutionary models. Probability models were used to trace spatial and chronological origins of the primary tumor and metastases, chart their genetic drivers, and distinguish metastatic and non-metastatic subclones.

RESULTS

In patient GP5, CDK12 inactivation was among the first mutations, leading to a PrCa tandem duplicator phenotype and initiating the cancer around age 50, followed by rapid cancer evolution after age 57, and metastasis around age 59, 5 years prior to prostatectomy. In patient GP12, accelerated cancer progression was detected after age 54, and metastasis occurred around age 56, 3 years prior to prostatectomy. Multiple metastasis-originating events were identified in each patient and tracked anatomically. Metastasis from prostate to lymph nodes occurred strictly ipsilaterally in all 12 detected events. In this pilot, metastatic subclone content analysis appears to substantially enhance the identification of key drivers. Evolutionary analysis' potential impact on therapy selection appears positive in these pilot cases.

CONCLUSIONS

PrCa evolutionary analysis allows tracking of anatomic site of origin, timing of cancer origin and spread, and distinction of metastatic-capable from non-metastatic subclones. This enables better identification of actionable targets for therapy. If extended to larger cohorts, it appears likely that similar analyses could add substantial biological insight and clinically relevant value.

Characterization of Cancer Evolution Landscape Based on Accurate Detection of Somatic Mutations in Single Tumor Cells

Accurate detection of somatic mutations in single tumor cells is greatly desired as it allows us to quantify the single-cell mutation burden and construct the mutation-based phylogenetic tree. Here we developed scNanoSeq chemistry and profiled 842 single cells from 21 human breast cancer samples. The majority of the mutation-based phylogenetic trees comprise a characteristic stem evolution followed by the clonal sweep. We observed the subtype-dependent lengths in the stem evolution. To explain this phenomenon, we propose that the differences are related to different reprogramming required for different subtypes of breast cancer. Furthermore, we reason that the time that the tumor-initiating cell took to acquire the critical clonal-sweep-initiating mutation by random chance set the time limit for the reprogramming process. We refer to this model as a reprogramming and critical mutation co-timing (RCMC) subtype model. Next, in the sweeping clone, we observed that tumor cells undergo a branched evolution with rapidly decreasing selection. In the most recent clades, effectively neutral evolution has been reached, resulting in a substantially large number of mutational heterogeneities. Integrative analysis with 522-713X ultra-deep bulk whole genome sequencing (WGS) further validated this evolution mode. Mutation-based phylogenetic trees also allow us to identify the early branched cells in a few samples, whose phylogenetic trees support the gradual evolution of copy number variations (CNVs). Overall, the development of scNanoSeq allows us to unveil novel insights into breast cancer evolution.

Small extrachromosomal circular DNA harboring targeted tumor suppressor gene mutations supports intratumor heterogeneity in mouse liver cancer induced by multiplexed CRISPR/Cas9

BACKGROUND

Primary liver cancer has significant intratumor genetic heterogeneity (IGH), which drives cancer evolution and prevents effective cancer treatment. CRISPR/Cas9-induced mouse liver cancer models can be used to elucidate how IGH is developed. However, as CRISPR/Cas9 could induce chromothripsis and extrachromosomal DNA in cells in addition to targeted mutations, we wondered whether this effect contributes to the development of IGH in CRISPR/Cas9-induced mouse liver cancer.

METHODS

CRISPR/Cas9-based targeted somatic multiplex-mutagenesis was used to target 34 tumor suppressor genes (TSGs) for induction of primary liver tumors in mice. Target site mutations in tumor cells were analyzed and compared between single-cell clones and their subclones, between different time points of cell proliferation, and between parental clones and single-cell clones derived from mouse subcutaneous allografts. Genomic instability and generation of extrachromosomal circular DNA (eccDNA) was explored as a potential mechanism underlying the oscillation of target site mutations in these liver tumor cells.

RESULTS

After efficiently inducing autochthonous liver tumors in mice within 30-60 days, analyses of CRISPR/Cas9-induced tumors and single-cell clones derived from tumor nodules revealed multiplexed and heterogeneous mutations at target sites. Many target sites frequently displayed more than two types of allelic variations with varying frequencies in single-cell clones, indicating increased copy number of these target sites. The types and frequencies of targeted TSG mutations continued to change at some target sites between single-cell clones and their subclones. Even the proliferation of a subclone in cell culture and in mouse subcutaneous graft altered the types and frequencies of targeted TSG mutations in the absence of continuing CRISPR/Cas9 genome editing, indicating a new source outside primary chromosomes for the development of IGH in these liver tumors. Karyotyping of tumor cells revealed genomic instability in these cells manifested by high levels of micronuclei and chromosomal aberrations including chromosomal fragments and chromosomal breaks. Sequencing analysis further demonstrated the generation of eccDNA harboring targeted TSG mutations in these tumor cells.

CONCLUSIONS

Small eccDNAs carrying TSG mutations may serve as an important source supporting intratumor heterogeneity and tumor evolution in mouse liver cancer induced by multiplexed CRISPR/Cas9.

Game-theoretical description of the go-or-grow dichotomy in tumor development for various settings and parameter constellations

A medically important feature of several types of tumors is their ability to "decide" between staying at a primary site in the body or leaving it and forming metastases. The present theoretical study aims to provide a better understanding of the ultimate reasons for this so-called "go-or-grow" dichotomy. To that end, we use game theory, which has proven to be useful in analyzing the competition between tumors and healthy tissues or among different tumor cells. We begin by determining the game types in the Basanta-Hatzikirou-Deutsch model, depending on the parameter values. Thereafter, we suggest and analyze five modified variants of the model. For example, in the basic model, the deadlock game, Prisoner's Dilemma, and hawk-dove game can occur. The modified versions lead to several additional game types, such as battle of the sexes, route-choice, and stag-hunt games. For some game types, all cells are predicted to stay on their original site ("grow phenotype"), while for other types, only a certain fraction stay and the other cells migrate away ("go phenotype"). If the nutrient supply at a distant site is high, all the cells are predicted to go. We discuss our predictions in terms of the pros and cons of caloric restriction and limitations of the supply of vitamins or methionine. Our results may help devise treatments to prevent metastasis.

Multi-omics integration analysis unveils heterogeneity in breast cancer at the individual level

Identifying robust breast cancer subtypes will help to reveal the cancer heterogeneity. However, previous breast cancer subtypes were based on population-level quantitative gene expression, which is affected by batch effects and cannot be applied to individuals. We detected differential gene expression, genomic, and epigenomic alterations to identify driver differential expression at the individual level. The individual driver differential expression reflected the breast cancer patients' heterogeneity and revealed four subtypes. Mesenchymal subtype as the most aggressive subtype harbored deletion and downregulated expression of genes in chromosome 11q23 region. Specifically, silencing of the SDHD gene in 11q23 promoted the invasion and migration of breast cancer cells in vitro by the epithelial-mesenchymal transition. The immunologically hot subtype displayed an immune-hot microenvironment, including high T-cell infiltration and upregulated PD-1 and CTLA4. Luminal and genomic-unstable subtypes showed opposite macrophage polarization, which may be regulated by the ligand-receptor pairs of CD99. The integration of multi-omics data at the individual level provides a powerful framework for elucidating the heterogeneity of breast cancer.

Decoding Cancer Evolution: Integrating Genetic and Non-Genetic Insights

The development of cancer begins with cells transitioning from their multicellular nature to a state akin to unicellular organisms. This shift leads to a breakdown in the crucial regulators inherent to multicellularity, resulting in the emergence of diverse cancer cell subpopulations that have enhanced adaptability. The presence of different cell subpopulations within a tumour, known as intratumoural heterogeneity (ITH), poses challenges for cancer treatment. In this review, we delve into the dynamics of the shift from multicellularity to unicellularity during cancer onset and progression. We highlight the role of genetic and non-genetic factors, as well as tumour microenvironment, in promoting ITH and cancer evolution. Additionally, we shed light on the latest advancements in omics technologies that allow for in-depth analysis of tumours at the single-cell level and their spatial organization within the tissue. Obtaining such detailed information is crucial for deepening our understanding of the diverse evolutionary paths of cancer, allowing for the development of effective therapies targeting the key drivers of cancer evolution.

Cracking the pattern of tumor evolution based on single-cell copy number alterations

Copy number alterations (CNAs) are a key characteristic of tumor development and progression. The accumulation of various CNAs during tumor development plays a critical role in driving tumor evolution. Heterogeneous clones driven by distinct CNAs have different selective advantages, leading to differential patterns of tumor evolution that are essential for developing effective cancer therapies. Recent advances in single-cell sequencing technology have enabled genome-wide copy number profiling of tumor cell populations at single-cell resolution. This has made it possible to explore the evolutionary patterns of CNAs and accurately discover the mechanisms of intra-tumor heterogeneity. Here, we propose a two-step statistical approach that distinguishes neutral, linear, branching and punctuated evolutionary patterns for a tumor cell population based on single-cell copy number profiles. We assessed our approach using a variety of simulated and real single-cell genomic and transcriptomic datasets, demonstrating its high accuracy and robustness in predicting tumor evolutionary patterns. We applied our approach to single-cell DNA sequencing data from 20 breast cancer patients and observed that punctuated evolution is the dominant evolutionary pattern in breast cancer. Similar conclusions were drawn when applying the approach to single-cell RNA sequencing data obtained from 132 various cancer patients. Moreover, we found that differential immune cell infiltration is associated with specific evolutionary patterns. The source code of our study is available at https://github.com/FangWang-SYSU/PTEM.

Disentangling the roles of aneuploidy, chromosomal instability and tumour heterogeneity in developing resistance to cancer therapies

Aneuploidy is defined as the cellular state of having a number of chromosomes that deviates from a multiple of the normal haploid chromosome number of a given organism. Aneuploidy can be present in a static state: Down syndrome individuals stably maintain an extra copy of chromosome 21 in their cells. In cancer cells, however, aneuploidy is usually present in combination with chromosomal instability (CIN) which leads to a continual generation of new chromosomal alterations and the development of intratumour heterogeneity (ITH). The prevalence of cells with specific chromosomal alterations is further shaped by evolutionary selection, for example, during the administration of cancer therapies. Aneuploidy, CIN and ITH have each been individually associated with poor prognosis in cancer, and a wealth of evidence suggests they contribute, either alone or in combination, to cancer therapy resistance by providing a reservoir of potential resistant states, or the ability to rapidly evolve resistance. A full understanding of the contribution and interplay between aneuploidy, CIN and ITH is required to tackle therapy resistance in cancer patients. However, these characteristics often co-occur and are intrinsically linked, presenting a major challenge to defining their individual contributions. Moreover, their accurate measurement in both experimental and clinical settings is a technical hurdle. Here, we attempt to deconstruct the contribution of the individual and combined roles of aneuploidy, CIN and ITH to therapy resistance in cancer, and outline emerging approaches to measure and disentangle their roles as a step towards integrating these principles into cancer therapeutic strategy.

Single-cell phylogenies reveal changes in the evolutionary rate within cancer and healthy tissues

Cell lineages accumulate somatic mutations during organismal development, potentially leading to pathological states. The rate of somatic evolution within a cell population can vary due to multiple factors, including selection, a change in the mutation rate, or differences in the microenvironment. Here, we developed a statistical test called the Poisson Tree (PT) test to detect varying evolutionary rates among cell lineages, leveraging the phylogenetic signal of single-cell DNA sequencing (scDNA-seq) data. We applied the PT test to 24 healthy and cancer samples, rejecting a constant evolutionary rate in 11 out of 15 cancer and five out of nine healthy scDNA-seq datasets. In six cancer datasets, we identified subclonal mutations in known driver genes that could explain the rate accelerations of particular cancer lineages. Our findings demonstrate the efficacy of scDNA-seq for studying somatic evolution and suggest that cell lineages often evolve at different rates within cancer and healthy tissues.

Clinical and translational relevance of intratumor heterogeneity

Intratumor heterogeneity (ITH) is a driver of tumor evolution and a main cause of therapeutic resistance. Despite its importance, measures of ITH are still not incorporated into clinical practice. Consequently, standard treatment is frequently ineffective for patients with heterogeneous tumors as changes to treatment regimens are made only after recurrence and disease progression. More effective combination therapies require a mechanistic understanding of ITH and ways to assess it in clinical samples. The growth of technologies enabling the spatially intact analysis of tumors at the single-cell level and the development of sophisticated preclinical models give us hope that ITH will not simply be used as a predictor of a poor outcome but will guide treatment decisions from diagnosis through treatment.

Genomic and evolutionary characteristics of metastatic gastric cancer by routes

BACKGROUND

In gastric cancer (GC) patients, metastatic progression through the lymphatic, hematogenous, peritoneal, and ovarian routes, is the ultimate cause of death. However, the genomic and evolutionary characteristics of metastatic GC have not been widely evaluated.

METHODS

Whole-exome sequencing data were analyzed for 99 primary and paired metastatic gastric cancers from 15 patients who underwent gastrectomy and metastasectomy.

RESULTS

Hematogenous metastatic tumors were associated with increased chromosomal instability and de novo gain/amplification in cancer driver genes, whereas peritoneal/ovarian metastasis was linked to sustained chromosomal stability and de novo somatic mutations in driver genes. The genomic distance of the hematogenous and peritoneal metastatic tumors was found to be closer to the primary tumors than lymph node (LN) metastasis, while ovarian metastasis was closer to LN and peritoneal metastasis than the primary tumor. Two migration patterns for metastatic GCs were identified; branched and diaspora. Both molecular subtypes of the metastatic tumors, rather than the primary tumor, and their migration patterns were related to patient survival.

CONCLUSIONS

Genomic characteristics of metastatic gastric cancer is distinctive by routes and associated with patients' prognosis along with genomic evolution pattenrs, indicating that both primary and metastatic gastric cancers require genomic evaluation.

Specificity of cancer-related chromosomal translocations is linked to proximity after the DNA double-strand break and subsequent selection

Most cancer-related chromosomal translocations appear to be cell type specific. It is currently unknown why different chromosomal translocations occur in different cells. This can be due to either the occurrence of particular translocations in specific cell types or adaptive survival advantage conferred by translocations only in specific cells. We experimentally addressed this question by double-strand break (DSB) induction at MYC, IGH, AML and ETO loci in the same cell to generate chromosomal translocations in different cell lineages. Our results show that any translocation can potentially arise in any cell type. We have analyzed different factors that could affect the frequency of the translocations, and only the spatial proximity between gene loci after the DSB induction correlated with the resulting translocation frequency, supporting the 'breakage-first' model. Furthermore, upon long-term culture of cells with the generated chromosomal translocations, only oncogenic MYC-IGH and AML-ETO translocations persisted over a 60-day period. Overall, the results suggest that chromosomal translocation can be generated after DSB induction in any type of cell, but whether the cell with the translocation would persist in a cell population depends on the cell type-specific selective survival advantage that the chromosomal translocation confers to the cell.

Dissecting Intra-tumor Heterogeneity in the Glioblastoma Microenvironment Using Fluorescence-Guided Multiple Sampling

The treatment of the most aggressive primary brain tumor in adults, glioblastoma (GBM), is challenging due to its heterogeneous nature, invasive potential, and poor response to chemo- and radiotherapy. As a result, GBM inevitably recurs and only a few patients survive 5 years post-diagnosis. GBM is characterized by extensive phenotypic and genetic heterogeneity, creating a diversified genetic landscape and a network of biological interactions between subclones, ultimately promoting tumor growth and therapeutic resistance. This includes spatial and temporal changes in the tumor microenvironment, which influence cellular and molecular programs in GBM and therapeutic responses. However, dissecting phenotypic and genetic heterogeneity at spatial and temporal levels is extremely challenging, and the dynamics of the GBM microenvironment cannot be captured by analysis of a single tumor sample. In this review, we discuss the current research on GBM heterogeneity, in particular, the utility and potential applications of fluorescence-guided multiple sampling to dissect phenotypic and genetic intra-tumor heterogeneity in the GBM microenvironment, identify tumor and non-tumor cell interactions and novel therapeutic targets in areas that are key for tumor growth and recurrence, and improve the molecular classification of GBM.