Mutation-selection balance and compensatory mechanisms in tumour evolution

Surviving the Storm: The Role of Poly- and Depolyploidization in Tissues and Tumors

Polyploidization and depolyploidization are critical processes in the normal development and tissue homeostasis of diploid organisms. Recent investigations have revealed that polyaneuploid cancer cells (PACCs) exploit this ploidy variation as a survival strategy against anticancer treatment and for the repopulation of tumors. Unscheduled polyploidization and chromosomal instability in PACCs enhance malignancy and treatment resistance. However, their inability to undergo mitosis causes catastrophic cellular death in most PACCs. Adaptive ploid reversal mechanisms, such as multipolar mitosis, centrosome clustering, meiosis-like division, and amitosis, counteract this lethal outcome and drive cancer relapse. The purpose of this work is to focus on PACCs induced by cytotoxic therapy, highlighting the latest discoveries in ploidy dynamics in physiological and pathological contexts. Specifically, by emphasizing the role of "poly-depolyploidization" in tumor progression, the aim is to identify novel therapeutic targets or paradigms for combating diseases associated with aberrant ploidies.

Synergistic epistasis among cancer drivers can rescue early tumors from the accumulation of deleterious passengers

Epistasis among driver mutations is pervasive and explains relevant features of cancer, such as differential therapy response and convergence towards well-characterized molecular subtypes. Furthermore, a growing body of evidence suggests that tumor development could be hampered by the accumulation of slightly deleterious passenger mutations. In this work, we combined empirical epistasis networks, computer simulations, and mathematical models to explore how synergistic interactions among driver mutations affect cancer progression under the burden of slightly deleterious passengers. We found that epistasis plays a crucial role in tumor development by promoting the transformation of precancerous clones into rapidly growing tumors through a process that is analogous to evolutionary rescue. The triggering of epistasis-driven rescue is strongly dependent on the intensity of epistasis and could be a key rate-limiting step in many tumors, contributing to their unpredictability. As a result, central genes in cancer epistasis networks appear as key intervention targets for cancer therapy.

Machine learning-based extrachromosomal DNA identification in large-scale cohorts reveals its clinical implications in cancer

The clinical implications of extrachromosomal DNA (ecDNA) in cancer therapy remain largely elusive. Here, we present a comprehensive analysis of ecDNA amplification spectra and their association with clinical and molecular features in multiple cohorts comprising over 13,000 pan-cancer patients. Using our developed computational framework, GCAP, and validating it with multifaceted approaches, we reveal a consistent pan-cancer pattern of mutual exclusivity between ecDNA amplification and microsatellite instability (MSI). In addition, we establish the role of ecDNA amplification as a risk factor and refine genomic subtypes in a cohort from 1015 colorectal cancer patients. Importantly, our investigation incorporates data from four clinical trials focused on anti-PD-1 immunotherapy, demonstrating the pivotal role of ecDNA amplification as a biomarker for guiding checkpoint blockade immunotherapy in gastrointestinal cancer. This finding represents clinical evidence linking ecDNA amplification to the effectiveness of immunotherapeutic interventions. Overall, our study provides a proof-of-concept of identifying ecDNA amplification from cancer whole-exome sequencing (WES) data, highlighting the potential of ecDNA amplification as a valuable biomarker for facilitating personalized cancer treatment.

Molecular and immunohistochemical study of APC exon 16 and its possible role in colorectal carcinoma development

Background

Colorectal cancer ranks second as a cause of cancer deaths. Mutations in the adenomatous polyposis coli (APC) gene, especially in exon 16, could contribute to colorectal carcinoma development. This study explored the correlations between APC gene exon 16 variations/expression and colorectal carcinoma progression.

Methods

In a case-control study, blood samples from 150 colorectal carcinoma patients and 50 healthy volunteers were analyzed by PCR and sequencing for APC exon 16 variations. The APC protein expression on tissue samples was evaluated by immunohistochemistry and statistical analyses were used to examine clinicopathological correlations.

Results

The sequencing analysis revealed a mutation in exon 16 of the APC gene (rs459552) in 36 % of colorectal cancer cases while absent in all non-cancer controls. Subgroup analysis by tumor grade showed higher prevalence of mutant allele in Grade II and Grade III cases, with frequencies reaching 60.0 % and 69.2 %, respectively, compared to a substantially lower prevalence of 29.4 % in Grade I patients. Immunohistochemistry showed no significant correlation between this mutation and APC expression. APC positivity proportions were 25.5 % in Grade I tumors (n = 26/102) versus 17.1 % in Grade II (n = 6/35) and 46.2 % in Grade III (n = 6/13), showing a non-significant trend of reduced positivity in higher grade tumors (p>0.05).

Conclusions

The frequency of APC exon 16 mutation (rs459552) rose significantly with increasing tumor grade. Similarly, although not statistically significant, the percentage of APC positive staining increased with poorer tumor differentiation, rather than declining. Therefore, the APC exon 16 mutation and expression analysis provides insights into colorectal cancer progression, with the rs459552 mutation correlating with grade and may promoting aggression.

Treatment of Central Nervous System Tumors on Combination MR-Linear Accelerators: Review of Current Practice and Future Directions

Magnetic resonance imaging (MRI) provides excellent visualization of central nervous system (CNS) tumors due to its superior soft tissue contrast. Magnetic resonance-guided radiotherapy (MRgRT) has historically been limited to use in the initial treatment planning stage due to cost and feasibility. MRI-guided linear accelerators (MRLs) allow clinicians to visualize tumors and organs at risk (OARs) directly before and during treatment, a process known as online MRgRT. This novel system permits adaptive treatment planning based on anatomical changes to ensure accurate dose delivery to the tumor while minimizing unnecessary toxicity to healthy tissue. These advancements are critical to treatment adaptation in the brain and spinal cord, where both preliminary MRI and daily CT guidance have typically had limited benefit. In this narrative review, we investigate the application of online MRgRT in the treatment of various CNS malignancies and any relevant ongoing clinical trials. Imaging of glioblastoma patients has shown significant changes in the gross tumor volume over a standard course of chemoradiotherapy. The use of adaptive online MRgRT in these patients demonstrated reduced target volumes with cavity shrinkage and a resulting reduction in radiation dose to uninvolved tissue. Dosimetric feasibility studies have shown MRL-guided stereotactic radiotherapy (SRT) for intracranial and spine tumors to have potential dosimetric advantages and reduced morbidity compared with conventional linear accelerators. Similarly, dosimetric feasibility studies have shown promise in hippocampal avoidance whole brain radiotherapy (HA-WBRT). Next, we explore the potential of MRL-based multiparametric MRI (mpMRI) and genomically informed radiotherapy to treat CNS disease with cutting-edge precision. Lastly, we explore the challenges of treating CNS malignancies and special limitations MRL systems face.

Human APOBEC3B promotes tumor development in vivo including signature mutations and metastases

The antiviral DNA cytosine deaminase APOBEC3B has been implicated as a source of mutation in many cancers. However, despite years of work, a causal relationship has yet to be established in vivo. Here, we report a murine model that expresses tumor-like levels of human APOBEC3B. Animals expressing full-body APOBEC3B appear to develop normally. However, adult males manifest infertility, and older animals of both sexes show accelerated rates of carcinogenesis, visual and molecular tumor heterogeneity, and metastasis. Both primary and metastatic tumors exhibit increased frequencies of C-to-T mutations in TC dinucleotide motifs consistent with the established biochemical activity of APOBEC3B. Enrichment for APOBEC3B-attributable single base substitution mutations also associates with elevated levels of insertion-deletion mutations and structural variations. APOBEC3B catalytic activity is required for all of these phenotypes. Together, these studies provide a cause-and-effect demonstration that human APOBEC3B is capable of driving both tumor initiation and evolution in vivo.

Deep mutational scanning reveals the molecular determinants of RNA polymerase-mediated adaptation and tradeoffs

RNA polymerase (RNAP) is emblematic of complex biological systems that control multiple traits involving trade-offs such as growth versus maintenance. Laboratory evolution has revealed that mutations in RNAP subunits, including RpoB, are frequently selected. However, we lack a systems view of how mutations alter the RNAP molecular functions to promote adaptation. We, therefore, measured the fitness of thousands of mutations within a region of rpoB under multiple conditions and genetic backgrounds, to find that adaptive mutations cluster in two modules. Mutations in one module favor growth over maintenance through a partial loss of an interaction associated with faster elongation. Mutations in the other favor maintenance over growth through a destabilized RNAP-DNA complex. The two molecular handles capture the versatile RNAP-mediated adaptations. Combining both interaction losses simultaneously improved maintenance and growth, challenging the idea that growth-maintenance tradeoff resorts only from limited resources, and revealing how compensatory evolution operates within RNAP.

The recent progress of deep-learning-based in silico prediction of drug combination

Drug combination therapy has become a common strategy for the treatment of complex diseases. There is an urgent need for computational methods to efficiently identify appropriate drug combinations owing to the high cost of experimental screening. In recent years, deep learning has been widely used in the field of drug discovery. Here, we provide a comprehensive review on deep-learning-based drug combination prediction algorithms from multiple aspects. Current studies highlight the flexibility of this technology in integrating multimodal data and the ability to achieve state-of-art performance; it is expected that deep-learning-based prediction of drug combinations should play an important part in future drug discovery.

Human APOBEC3B promotes tumor heterogeneity in vivo including signature mutations and metastases

The antiviral DNA cytosine deaminase APOBEC3B has been implicated as a source of mutation in many different cancers. Despite over 10 years of work, a causal relationship has yet to be established between APOBEC3B and any stage of carcinogenesis. Here we report a murine model that expresses tumor-like levels of human APOBEC3B after Cre-mediated recombination. Animals appear to develop normally with full-body expression of APOBEC3B. However, adult males manifest infertility and older animals of both sexes show accelerated rates of tumorigenesis (mostly lymphomas or hepatocellular carcinomas). Interestingly, primary tumors also show overt heterogeneity, and a subset spreads to secondary sites. Both primary and metastatic tumors exhibit increased frequencies of C-to-T mutations in TC dinucleotide motifs consistent with the established biochemical activity of APOBEC3B. Elevated levels of structural variation and insertion-deletion mutations also accumulate in these tumors. Together, these studies provide the first cause-and-effect demonstration that human APOBEC3B is an oncoprotein capable of causing a wide range of genetic changes and driving tumor formation in vivo .

Protein degradation: expanding the toolbox to restrain cancer drug resistance

Despite significant progress in clinical management, drug resistance remains a major obstacle. Recent research based on protein degradation to restrain drug resistance has attracted wide attention, and several therapeutic strategies such as inhibition of proteasome with bortezomib and proteolysis-targeting chimeric have been developed. Compared with intervention at the transcriptional level, targeting the degradation process seems to be a more rapid and direct strategy. Proteasomal proteolysis and lysosomal proteolysis are the most critical quality control systems responsible for the degradation of proteins or organelles. Although proteasomal and lysosomal inhibitors (e.g., bortezomib and chloroquine) have achieved certain improvements in some clinical application scenarios, their routine application in practice is still a long way off, which is due to the lack of precise targeting capabilities and inevitable side effects. In-depth studies on the regulatory mechanism of critical protein degradation regulators, including E3 ubiquitin ligases, deubiquitylating enzymes (DUBs), and chaperones, are expected to provide precise clues for developing targeting strategies and reducing side effects. Here, we discuss the underlying mechanisms of protein degradation in regulating drug efflux, drug metabolism, DNA repair, drug target alteration, downstream bypass signaling, sustaining of stemness, and tumor microenvironment remodeling to delineate the functional roles of protein degradation in drug resistance. We also highlight specific E3 ligases, DUBs, and chaperones, discussing possible strategies modulating protein degradation to target cancer drug resistance. A systematic summary of the molecular basis by which protein degradation regulates tumor drug resistance will help facilitate the development of appropriate clinical strategies.

Genetic and microenvironmental intra-tumor heterogeneity impacts colorectal cancer evolution and metastatic development

Colorectal cancer (CRC) is a highly diverse disease, where different genomic instability pathways shape genetic clonal diversity and tumor microenvironment. Although intra-tumor heterogeneity has been characterized in primary tumors, its origin and consequences in CRC outcome is not fully understood. Therefore, we assessed intra- and inter-tumor heterogeneity of a prospective cohort of 136 CRC samples. We demonstrate that CRC diversity is forged by asynchronous forms of molecular alterations, where mutational and chromosomal instability collectively boost CRC genetic and microenvironment intra-tumor heterogeneity. We were able to depict predictor signatures of cancer-related genes that can foresee heterogeneity levels across the different tumor consensus molecular subtypes (CMS) and primary tumor location. Finally, we show that high genetic and microenvironment heterogeneity are associated with lower metastatic potential, whereas late-emerging copy number variations favor metastasis development and polyclonal seeding. This study provides an exhaustive portrait of the interplay between genetic and microenvironment intra-tumor heterogeneity across CMS subtypes, depicting molecular events with predictive value of CRC progression and metastasis development.

Pervasive conditional selection of driver mutations and modular epistasis networks in cancer

Cancer driver mutations often display mutual exclusion or co-occurrence, underscoring the key role of epistasis in carcinogenesis. However, estimating the magnitude of epistasis and quantifying its effect on tumor evolution remains a challenge. We develop a method (Coselens) to quantify conditional selection on the excess of nonsynonymous substitutions in cancer genes. Coselens infers the number of drivers per gene in different partitions of a cancer genomics dataset using covariance-based mutation models and determines whether coding mutations in a gene affect selection for drivers in any other gene. Using Coselens, we identify 296 conditionally selected gene pairs across 16 cancer types in the TCGA dataset. Conditional selection affects 25%-50% of driver substitutions in tumors with >2 drivers. Conditionally co-selected genes form modular networks, whose structures challenge the traditional interpretation of within-pathway mutual exclusivity and across-pathway synergy, suggesting a more complex scenario where gene-specific across-pathway epistasis shapes differentiated cancer subtypes.

Transcriptional variability accelerates preleukemia by cell diversification and perturbation of protein synthesis

Transcriptional variability facilitates stochastic cell diversification and can in turn underpin adaptation to stress or injury. We hypothesize that it may analogously facilitate progression of premalignancy to cancer. To investigate this, we initiated preleukemia in mouse cells with enhanced transcriptional variability due to conditional disruption of the histone lysine acetyltransferase gene Kat2a. By combining single-cell RNA sequencing of preleukemia with functional analysis of transformation, we show that Kat2a loss results in global variegation of cell identity and accumulation of preleukemic cells. Leukemia progression is subsequently facilitated by destabilization of ribosome biogenesis and protein synthesis, which confer a transient transformation advantage. The contribution of transcriptional variability to early cancer evolution reflects a generic role in promoting cell fate transitions, which, in the case of well-adapted malignancies, contrastingly differentiates and depletes cancer stem cells. That is, transcriptional variability confers forward momentum to cell fate systems, with differential multistage impact throughout cancer evolution.

Repositioning of Old Drugs for Novel Cancer Therapies: Continuous Therapeutic Perfusion of Aspirin and Oseltamivir Phosphate with Gemcitabine Treatment Disables Tumor Progression, Chemoresistance, and Metastases

Simple Summary

Repositioning old drugs in combination with clinical standard chemotherapeutics opens a promising clinical treatment approach for patients with pancreatic cancer. This report presents a therapeutic repositioning of continuous perfusion of aspirin and oseltamivir phosphate in combination with gemcitabine treatment as an effective treatment option for pancreatic cancer. The data suggest that repositioning these drugs with continuous perfusion with gemcitabine disables chemoresistance, tumor progression, EMT program, cancer stem cells, and metastases in a preclinical mouse model of human pancreatic cancer. These promising results warrant additional investigation to assess the potential of translating into the clinical setting to improve the cancer patient prognosis for an otherwise fatal disease.

Abstract

Metastatic pancreatic cancer has an invariably fatal outcome, with an estimated median progression-free survival of approximately six months employing our best combination chemotherapeutic regimens. Once drug resistance develops, manifested by increased primary tumor size and new and growing metastases, patients often die rapidly from their disease. Emerging evidence indicates that chemotherapy may contribute to the development of drug resistance through the upregulation of epithelial–mesenchymal transition (EMT) pathways and subsequent cancer stem cell (CSC) enrichment. Neuraminidase-1 (Neu-1) regulates the activation of several receptor tyrosine kinases implicated in EMT induction, angiogenesis, and cellular proliferation. Here, continuous therapeutic targeting of Neu-1 using parenteral perfusion of oseltamivir phosphate (OP) and aspirin (ASA) with gemcitabine (GEM) treatment significantly disrupts tumor progression, critical compensatory signaling mechanisms, EMT program, CSC, and metastases in a preclinical mouse model of human pancreatic cancer. ASA- and OP-treated xenotumors significantly inhibited the metastatic potential when transferred into animals.

SETD2 Haploinsufficiency Enhances Germinal Center-Associated AICDA Somatic Hypermutation to Drive B-cell Lymphomagenesis

SETD2 is the sole histone methyltransferase responsible for H3K36me3, with roles in splicing, transcription initiation, and DNA damage response. Homozygous disruption of SETD2 yields a tumor suppressor effect in various cancers. However, SETD2 mutation is typically heterozygous in diffuse large B-cell lymphomas. Here we show that heterozygous Setd2 deficiency results in germinal center (GC) hyperplasia and increased competitive fitness, with reduced DNA damage checkpoint activity and apoptosis, resulting in accelerated lymphomagenesis. Impaired DNA damage sensing in Setd2-haploinsufficient germinal center B (GCB) and lymphoma cells associated with increased AICDA-induced somatic hypermutation, complex structural variants, and increased translocations including those activating MYC. DNA damage was selectively increased on the nontemplate strand, and H3K36me3 loss was associated with greater RNAPII processivity and mutational burden, suggesting that SETD2-mediated H3K36me3 is required for proper sensing of cytosine deamination. Hence, Setd2 haploinsufficiency delineates a novel GCB context-specific oncogenic pathway involving defective epigenetic surveillance of AICDA-mediated effects on transcribed genes.

SIGNIFICANCE

Our findings define a B cell-specific oncogenic effect of SETD2 heterozygous mutation, which unleashes AICDA mutagenesis of nontemplate strand DNA in the GC reaction, resulting in lymphomas with heavy mutational burden. GC-derived lymphomas did not tolerate SETD2 homozygous deletion, pointing to a novel context-specific therapeutic vulnerability. This article is highlighted in the In This Issue feature, p. 1599.

Effect of LOXL2 on metastasis through remodeling of the cell surface matrix in non-small cell lung cancer cells

Lung cancer is the prominent cause of cancer-associated death primarily because of distant metastatic disease. The metastatic potential of non-small cell lung cancer (NSCLC) is associated with tumor cell aggregation. However, the systemic mechanotransduction mechanism by which tumor cells dynamically aggregate and disseminate is poorly understood, especially in NSCLC. In this study, we examine whether the cell surface matrix plays an important role in metastasis. We used poly-2-hydroxyethyl methacrylate-based 3D spheroid formation methods to mimic in vivo metastatic lesions. Supra-structural analysis of human NSCLC A549 cells stained with ruthenium red for transmission electron microscopy (TEM) showed that glycocalyx surrounding the cell surface in 2D culture decreases in 3D culture. Comprehensive gene expression analysis revealed that the genes associated with cell adhesion were distinctly enriched in A549 cell spheroids. Of these, downregulation of the tumor metastatic microenvironment facilitator LOXL2, a copper-dependent enzyme catalyzing posttranslational oxidative deamination of peptidyl lysine, was of special interest. Knockdown of LOXL2 thickened the cell surface matrix in 2D culture and impaired compact aggregate formation in 3D culture. Moreover, A549 cell spheroids with endogenous overexpression of LOXL2 increased their dissemination on basement extracellular matrix Matrigel. Overall, these data imply that cell detachment-downregulated LOXL2 contributes to cell surface matrix remodeling, leading to collective dissemination of free-floating aggregates.

Tumour immunotherapy: lessons from predator-prey theory

With the burgeoning use of immune-based treatments for cancer, never has there been a greater need to understand the tumour microenvironment within which immune cells function and how it can be perturbed to inhibit tumour growth. Yet, current challenges in identifying optimal combinations of immunotherapies and engineering new cell-based therapies highlight the limitations of conventional paradigms for the study of the tumour microenvironment. Ecology has a rich history of studying predator-prey dynamics to discern factors that drive prey to extinction. Here, we describe the basic tenets of predator-prey theory as applied to 'predation' by immune cells and the 'extinction' of cancer cells. Our synthesis reveals fundamental mechanisms by which antitumour immunity might fail in sometimes counterintuitive ways and provides a fresh yet evidence-based framework to better understand and therapeutically target the immune-cancer interface.

Targeting IL8 as a sequential therapy strategy to overcome chemotherapy resistance in advanced gastric cancer

Systemic chemotherapy with multiple drug regimens is the main therapy option for advanced gastric cancer (GC) patients. However, many patients develop relapse soon. Here, we evaluated the therapeutic potential of targeting interleukin-8 (IL8) to overcome resistance to chemotherapy in advanced GC. RNA sequencing revealed crucial molecular changes after chemotherapy resistance, in which the expression of IL8 was significantly activated with the increase in drug resistance. Subsequently, the clinical significance of IL8 expression was determined in GC population specimens. IL8-targeted by RNA interference or reparixin reversed chemotherapy resistance with limited toxicity in vivo and vitro experiments. Sequential treatment with first-line, second-line chemotherapy and reparixin inhibited GC growth, reduced toxicity and prolonged survival. Collectively, our study provides a therapeutic strategy that targeting IL8 as a sequential therapy after chemotherapy resistance in advanced GC.

Combinatorial CRISPR/Cas9 Screening Reveals Epistatic Networks of Interacting Tumor Suppressor Genes and Therapeutic Targets in Human Breast Cancer

The majority of cancers are driven by multiple genetic alterations, but how these changes collaborate during tumorigenesis remains largely unknown. To gain mechanistic insights into tumor-promoting genetic interactions among tumor suppressor genes (TSG), we conducted combinatorial CRISPR screening coupled with single-cell transcriptomic profiling in human mammary epithelial cells. As expected, different driver gene alterations in mammary epithelial cells influenced the repertoire of tumor suppressor alterations capable of inducing tumor formation. More surprisingly, TSG interaction networks were comprised of numerous cliques-sets of three or four genes such that each TSG within the clique showed oncogenic cooperation with all other genes in the clique. Genetic interaction profiling indicated that the predominant cooperating TSGs shared overlapping functions rather than distinct or complementary functions. Single-cell transcriptomic profiling of CRISPR double knockouts revealed that cooperating TSGs that synergized in promoting tumorigenesis and growth factor independence showed transcriptional epistasis, whereas noncooperating TSGs did not. These epistatic transcriptional changes, both buffering and synergistic, affected expression of oncogenic mediators and therapeutic targets, including CDK4, SRPK1, and DNMT1. Importantly, the epistatic expression alterations caused by dual inactivation of TSGs in this system, such as PTEN and TP53, were also observed in patient tumors, establishing the relevance of these findings to human breast cancer. An estimated 50% of differentially expressed genes in breast cancer are controlled by epistatic interactions. Overall, our study indicates that transcriptional epistasis is a central aspect of multigenic breast cancer progression and outlines methodologies to uncover driver gene epistatic networks in other human cancers. SIGNIFICANCE: This study provides a roadmap for moving beyond discovery and development of therapeutic strategies based on single driver gene analysis to discovery based on interactions between multiple driver genes.See related commentary by Fong et al., p. 6078.

Analysis of Mutations and Dysregulated Pathways Unravels Carcinogenic Effect and Clinical Actionability of Mutational Processes

Somatic mutations accumulate over time in cancer cells as a consequence of mutational processes. However, the role of mutational processes in carcinogenesis remains poorly understood. Here, we infer the causal relationship between mutational processes and somatic mutations in 5,828 samples spanning 34 cancer subtypes. We found most mutational processes cause abundant recurrent mutations in cancer genes, while exceptionally ultraviolet exposure and altered activity of the error-prone polymerase bring a large number of recurrent non-driver mutations. Furthermore, some mutations are specifically induced by a certain mutational process, such as IDH1 p.R132H which is mainly caused by spontaneous deamination of 5-methylcytosine. At the pathway level, clock-like mutational processes extensively trigger mutations to dysregulate cancer signal transduction pathways. In addition, APOBEC mutational process destroys DNA double-strand break repair pathway, and bladder cancer patients with high APOBEC activity, though with homologous recombination proficient, show a significantly longer overall survival with platinum regimens. These findings help to understand how mutational processes act on the genome to promote carcinogenesis, and further, presents novel insights for cancer prevention and treatment, as our results showing, APOBEC mutagenesis and HRD synergistically contributed to the clinical benefits of platinum-based treatment.

What do cellular responses to acidity tell us about cancer?

The notion that invasive cancer is a product of somatic evolution is a well-established theory that can be modelled mathematically and demonstrated empirically from therapeutic responses. Somatic evolution is by no means deterministic, and ample opportunities exist to steer its trajectory towards cancer cell extinction. One such strategy is to alter the chemical microenvironment shared between host and cancer cells in a way that no longer favours the latter. Ever since the first description of the Warburg effect, acidosis has been recognised as a key chemical signature of the tumour microenvironment. Recent findings have suggested that responses to acidosis, arising through a process of selection and adaptation, give cancer cells a competitive advantage over the host. A surge of research efforts has attempted to understand the basis of this advantage and seek ways of exploiting it therapeutically. Here, we review key findings and place these in the context of a mathematical framework. Looking ahead, we highlight areas relating to cellular adaptation, selection, and heterogeneity that merit more research efforts in order to close in on the goal of exploiting tumour acidity in future therapies.

Activatable Biomineralized Nanoplatform Remodels the Intracellular Environment of Multidrug-Resistant Tumors for Enhanced Ferroptosis/Apoptosis Therapy

Ferroptosis is a new form of regulated cell death with significant therapeutic prospect, but its application against drug-resistant tumor cells is challenging due to their ability to effuse antitumor agents via p-glycoprotein (P-gp) and anti-lipid peroxidation alkaline intracellular environment. Herein, an amorphous calcium phosphate (ACP)-based nanoplatform is reported for the targeted combinational ferroptosis/apoptosis therapy of drug resistant tumor cells by blocking the MCT4-mediated efflux of lactic acid (LA). The nanoplatform is fabricated through the biomineralization of doxorubicin-Fe²⁺ (DOX-Fe²⁺ ) complex and MCT4-inhibiting siRNAs (siMCT4) and can release them to the tumor cytoplasm after the hydrolysis of ACP and dissociation of DOX-Fe²⁺ in the acidic lysosomes. siMCT4 can inhibit MCT4 expression and force the glycolysis-generated lactic acid (LA) to remain in cytoplasm for rapid acidification. The nanoplatform-induced remodeling of the tumor intracellular environment can not only interrupt the ATP supply required for P-gp-dependent DOX effusion to enhance H₂ O₂ production, but also increase the overall catalytic efficiency of Fe²⁺ for the initiation and propagation of lipid peroxidation. These features could act in concert to enhance the efficacy of the combinational ferroptosis/chemotherapy and prolong the survival of tumor-bearing mice. This study may provide new avenues for the treatment of multidrug-resistant tumors.

Maintenance of genome sequence integrity in long- and short-lived rodent species

DNA mutations in somatic cells have been implicated in the causation of aging, with longer-lived species having a higher capacity to maintain genome sequence integrity than shorter-lived species. In an attempt to directly test this hypothesis, we used single-cell whole-genome sequencing to analyze spontaneous and bleomycin-induced somatic mutations in lung fibroblasts of four rodent species with distinct maximum life spans, including mouse, guinea pig, blind mole-rat, and naked mole-rat, as well as humans. As predicted, the mutagen-induced mutation frequencies inversely correlated with species-specific maximum life span, with the greatest difference observed between the mouse and all other species. These results suggest that long-lived species are capable of processing DNA damage in a more accurate way than short-lived species.

Allele-specific genomic data elucidate the role of somatic gain and copy-number neutral loss of heterozygosity in cancer

Pan-cancer studies sketched the genomic landscape of the tumor types spectrum. We delineated the purity- and ploidy-adjusted allele-specific profiles of 4,950 patients across 27 tumor types from the Cancer Genome Atlas (TCGA). Leveraging allele-specific data, we reclassified as loss of heterozygosity (LOH) 9% and 7% of apparent copy-number wild-type and gain calls, respectively, and overall observed more than 18 million allelic imbalance somatic events at the gene level. Reclassification of copy-number events revealed associations between driver mutations and LOH, pointing out the timings between the occurrence of point mutations and copy-number events. Integrating allele-specific genomics and matched transcriptomics, we observed that allele-specific gene status is relevant in the regulation of TP53 and its targets. Further, we disclosed the role of copy-neutral LOH in the impairment of tumor suppressor genes and in disease progression. Our results highlight the role of LOH in cancer and contribute to the understanding of tumor progression.

Genetic alteration and clonal evolution of primary glioblastoma into secondary gliosarcoma

Aims

Secondary gliosarcoma (SGS) rarely arises post treatment of primary glioblastoma multiforme (GBM), and contains gliomatous and sarcomatous components. The origin and clonal evolution of SGS sarcomatous components remain uncharacterized. Therapeutic radiation is mutagenic and can induce sarcomas in patients with other tumor phenotypes, but possible causal relationships between radiotherapy and induction of SGS sarcomatous components remain unexplored. Herein, we investigated the clonal origin of SGS in a patient with primary GBM progressing into SGS post‐radiochemotherapy.

Methods

Somatic mutation profile in GBM and SGS was examined using whole‐genome sequencing and deep‐whole‐exome sequencing. Mutation signatures were characterized to investigate relationships between radiochemotherapy and SGS pathogenesis.

Results

A mutation cluster containing two founding mutations in tumor‐suppressor genes NF1 (variant allele frequency [VAF]: 50.0% in GBM and 51.1% in SGS) and TP53 (VAF: 26.7% in GBM and 50.8% in SGS) was shared in GBM and SGS. SGS exhibited an overpresented C>A (G>T) transversion (oxidative DNA damage signature) but no signature 11 mutations (alkylating‐agents – exposure signature). Since radiation induces DNA lesions by generating reactive oxygen species, the mutations observed in this case of SGS were likely the result of radiotherapy rather than chemotherapy.

Conclusions

Secondary gliosarcoma components likely have a monoclonal origin, and the clone possessing mutations in NF1 and TP53 was likely the founding clone in this case of SGS.

Bridging Tumorigenesis and Therapy Resistance With a Non-Darwinian and Non-Lamarckian Mechanism of Adaptive Evolution

Although neo-Darwinian (and less often Lamarckian) dynamics are regularly invoked to interpret cancer's multifarious molecular profiles, they shine little light on how tumorigenesis unfolds and often fail to fully capture the frequency and breadth of resistance mechanisms. This uncertainty frames one of the most problematic gaps between science and practice in modern times. Here, we offer a theory of adaptive cancer evolution, which builds on a molecular mechanism that lies outside neo-Darwinian and Lamarckian schemes. This mechanism coherently integrates non-genetic and genetic changes, ecological and evolutionary time scales, and shifts the spotlight away from positive selection towards purifying selection, genetic drift, and the creative-disruptive power of environmental change. The surprisingly simple use-it or lose-it rationale of the proposed theory can help predict molecular dynamics during tumorigenesis. It also provides simple rules of thumb that should help improve therapeutic approaches in cancer.

Darwinian Approaches for Cancer Treatment: Benefits of Mathematical Modeling

One of the major problems of traditional anti-cancer treatments is that they lead to the emergence of treatment-resistant cells, which results in treatment failure. To avoid or delay this phenomenon, it is relevant to take into account the eco-evolutionary dynamics of tumors. Designing evolution-based treatment strategies may help overcoming the problem of drug resistance. In particular, a promising candidate is adaptive therapy, a containment strategy which adjusts treatment cycles to the evolution of the tumors in order to keep the population of treatment-resistant cells under control. Mathematical modeling is a crucial tool to understand the dynamics of cancer in response to treatments, and to make predictions about the outcomes of these treatments. In this review, we highlight the benefits of in silico modeling to design adaptive therapy strategies, and to assess whether they could effectively improve treatment outcomes. Specifically, we review how two main types of models (i.e., mathematical models based on Lotka-Volterra equations and agent-based models) have been used to model tumor dynamics in response to adaptive therapy. We give examples of the advances they permitted in the field of adaptive therapy and discuss about how these models can be integrated in experimental approaches and clinical trial design.

Extreme value theory as a framework for understanding mutation frequency distribution in cancer genomes

Currently, the population dynamics of preclonal cancer cells before clonal expansion of tumors has not been sufficiently addressed thus far. By focusing on preclonal cancer cell population as a Darwinian evolutionary system, we formulated and analyzed the observed mutation frequency among tumors (MFaT) as a proxy for the hypothesized sequence read frequency and beneficial fitness effect of a cancer driver mutation. Analogous to intestinal crypts, we assumed that sample donor patients are separate culture tanks where proliferating cells follow certain population dynamics described by extreme value theory (EVT). To validate this, we analyzed three large-scale cancer genome datasets, each harboring > 10000 tumor samples and in total involving > 177898 observed mutation sites. We clarified the necessary premises for the application of EVT in the strong selection and weak mutation (SSWM) regime in relation to cancer genome sequences at scale. We also confirmed that the stochastic distribution of MFaT is likely of the Fréchet type, which challenges the well-known Gumbel hypothesis of beneficial fitness effects. Based on statistical data analysis, we demonstrated the potential of EVT as a population genetics framework to understand and explain the stochastic behavior of driver-mutation frequency in cancer genomes as well as its applicability in real cancer genome sequence data.

Three-Dimensional Culture Models to Study Innate Anti-Tumor Immune Response: Advantages and Disadvantages

Several approaches have shown that the immune response against tumors strongly affects patients' clinical outcome. Thus, the study of anti-tumor immunity is critical to understand and potentiate the mechanisms underlying the elimination of tumor cells. Natural killer (NK) cells are members of innate immunity and represent powerful anti-tumor effectors, able to eliminate tumor cells without a previous sensitization. Thus, the study of their involvement in anti-tumor responses is critical for clinical translation. This analysis has been performed in vitro, co-incubating NK with tumor cells and quantifying the cytotoxic activity of NK cells. In vivo confirmation has been applied to overcome the limits of in vitro testing, however, the innate immunity of mice and humans is different, leading to discrepancies. Different activating receptors on NK cells and counter-ligands on tumor cells are involved in the antitumor response, and innate immunity is strictly dependent on the specific microenvironment where it takes place. Thus, three-dimensional (3D) culture systems, where NK and tumor cells can interact in a tissue-like architecture, have been created. For example, tumor cell spheroids and primary organoids derived from several tumor types, have been used so far to analyze innate immune response, replacing animal models. Herein, we briefly introduce NK cells and analyze and discuss in detail the properties of 3D tumor culture systems and their use for the study of tumor cell interactions with NK cells.

Acid-base transporters and pH dynamics in human breast carcinomas predict proliferative activity, metastasis, and survival

Breast cancer heterogeneity in histology and molecular subtype influences metabolic and proliferative activity and hence the acid load on cancer cells. We hypothesized that acid-base transporters and intracellular pH (pH_i) dynamics contribute inter-individual variability in breast cancer aggressiveness and prognosis. We show that Na⁺,HCO₃^- cotransport and Na⁺/H⁺ exchange dominate cellular net acid extrusion in human breast carcinomas. Na⁺/H⁺ exchange elevates pH_i preferentially in estrogen receptor-negative breast carcinomas, whereas Na⁺,HCO₃^- cotransport raises pH_i more in invasive lobular than ductal breast carcinomas and in higher malignancy grade breast cancer. HER2-positive breast carcinomas have elevated protein expression of Na⁺/H⁺ exchanger NHE1/SLC9A1 and Na⁺,HCO₃^- cotransporter NBCn1/SLC4A7. Increased dependency on Na⁺,HCO₃^- cotransport associates with severe breast cancer: enlarged CO₂/HCO₃^--dependent rises in pH_i predict accelerated cell proliferation, whereas enhanced CO₂/HCO₃^--dependent net acid extrusion, elevated NBCn1 protein expression, and reduced NHE1 protein expression predict lymph node metastasis. Accordingly, we observe reduced survival for patients suffering from luminal A or basal-like/triple-negative breast cancer with high SLC4A7 and/or low SLC9A1 mRNA expression. We conclude that the molecular mechanisms of acid-base regulation depend on clinicopathological characteristics of breast cancer patients. NBCn1 expression and dependency on Na⁺,HCO₃^- cotransport for pH_i regulation, measured in biopsies of human primary breast carcinomas, independently predict proliferative activity, lymph node metastasis, and patient survival.

Linking Tumor Microenvironment to Plasticity of Cancer Stem Cells: Mechanisms and Application in Cancer Therapy

Cancer stem cells (CSCs) are a minority subset of cancer cells that can drive tumor initiation, promote tumor progression, and induce drug resistance. CSCs are difficult to eliminate by conventional therapies and eventually mediate tumor relapse and metastasis. Moreover, recent studies have shown that CSCs display plasticity that renders them to alter their phenotype and function. Consequently, the varied phenotypes result in varied tumorigenesis, dissemination, and drug-resistance potential, thereby adding to the complexity of tumor heterogeneity and further challenging clinical management of cancers. In recent years, tumor microenvironment (TME) has become a hotspot in cancer research owing to its successful application in clinical tumor immunotherapy. Notably, emerging evidence shows that the TME is involved in regulating CSC plasticity. TME can activate stemness pathways and promote immune escape through cytokines and exosomes secreted by immune cells or stromal cells, thereby inducing non-CSCs to acquire CSC properties and increasing CSC plasticity. However, the relationship between TME and plasticity of CSCs remains poorly understood. In this review, we discuss the emerging investigations on TME and CSC plasticity to illustrate the underlying mechanisms and potential implications in suppressing cancer progression and drug resistance. We consider that this review can help develop novel therapeutic strategies by taking into account the interlink between TME and CSC plasticity.

Superlinear growth reveals the Allee effect in tumors

Integrating experimental data into ecological models plays a central role in understanding biological mechanisms that drive tumor progression where such knowledge can be used to develop new therapeutic strategies. While the current studies emphasize the role of competition among tumor cells, they fail to explain recently observed superlinear growth dynamics across human tumors. Here we study tumor growth dynamics by developing a model that incorporates evolutionary dynamics inside tumors with tumor-microenvironment interactions. Our results reveal that tumor cells' ability to manipulate the environment and induce angiogenesis drives superlinear growth-a process compatible with the Allee effect. In light of this understanding, our model suggests that, for high-risk tumors that have a higher growth rate, suppressing angiogenesis can be the appropriate therapeutic intervention.