Phenotypic plasticity and genetic control in colorectal cancer evolution

Mechanisms of metastatic colorectal cancer

Despite extensive research and improvements in understanding colorectal cancer (CRC), its metastatic form continues to pose a substantial challenge, primarily owing to limited therapeutic options and a poor prognosis. This Review addresses the emerging focus on metastatic CRC (mCRC), which has historically been under-studied compared with primary CRC despite its lethality. We delve into two crucial aspects: the molecular and cellular determinants facilitating CRC metastasis and the principles guiding the evolution of metastatic disease. Initially, we examine the genetic alterations integral to CRC metastasis, connecting them to clinically marked characteristics of advanced CRC. Subsequently, we scrutinize the role of cellular heterogeneity and plasticity in metastatic spread and therapy resistance. Finally, we explore how the tumour microenvironment influences metastatic disease, emphasizing the effect of stromal gene programmes and the immune context. The ongoing research in these fields holds immense importance, as its future implications are projected to revolutionize the treatment of patients with mCRC, hopefully offering a promising outlook for their survival.

Profiling cell identity and tissue architecture with single-cell and spatial transcriptomics

Single-cell transcriptomics has broadened our understanding of cellular diversity and gene expression dynamics in healthy and diseased tissues. Recently, spatial transcriptomics has emerged as a tool to contextualize single cells in multicellular neighbourhoods and to identify spatially recurrent phenotypes, or ecotypes. These technologies have generated vast datasets with targeted-transcriptome and whole-transcriptome profiles of hundreds to millions of cells. Such data have provided new insights into developmental hierarchies, cellular plasticity and diverse tissue microenvironments, and spurred a burst of innovation in computational methods for single-cell analysis. In this Review, we discuss recent advancements, ongoing challenges and prospects in identifying and characterizing cell states and multicellular neighbourhoods. We discuss recent progress in sample processing, data integration, identification of subtle cell states, trajectory modelling, deconvolution and spatial analysis. Furthermore, we discuss the increasing application of deep learning, including foundation models, in analysing single-cell and spatial transcriptomics data. Finally, we discuss recent applications of these tools in the fields of stem cell biology, immunology, and tumour biology, and the future of single-cell and spatial transcriptomics in biological research and its translation to the clinic.

Cell states and neighborhoods in distinct clinical stages of primary and metastatic esophageal adenocarcinoma

Esophageal adenocarcinoma (EAC) is a highly lethal cancer of the upper gastrointestinal tract with rising incidence in western populations. To decipher EAC disease progression and therapeutic response, we performed multiomic analyses of a cohort of primary and metastatic EAC tumors, incorporating single-nuclei transcriptomic and chromatin accessibility sequencing, along with spatial profiling. We identified tumor microenvironmental features previously described to associate with therapy response. We identified five malignant cell programs, including undifferentiated, intermediate, differentiated, epithelial-to-mesenchymal transition, and cycling programs, which were associated with differential epigenetic plasticity and clinical outcomes, and for which we inferred candidate transcription factor regulons. Furthermore, we revealed diverse spatial localizations of malignant cells expressing their associated transcriptional programs and predicted their significant interactions with microenvironmental cell types. We validated our findings in three external single-cell RNA-seq and three bulk RNA-seq studies. Altogether, our findings advance the understanding of EAC heterogeneity, disease progression, and therapeutic response.

Detecting branching rate heterogeneity in multifurcating trees with applications in lineage tracing data

Understanding cellular birth rate differences is crucial for predicting cancer progression and interpreting tumor-derived genetic data. Lineage tracing experiments enable detailed reconstruction of cellular genealogies, offering new opportunities to measure branching rate heterogeneity. However, the lineage tracing process can introduce complex tree features that complicate this effort. Here, we examine tree characteristics in lineage tracing-derived genealogies and find that editing window placement leads to multifurcations at a tree's root or tips. We propose several ways in which existing tree topology-based metrics can be extended to test for rate heterogeneity on trees even in the presence of lineage-tracing associated distortions. Although these methods vary in power and robustness, a test based on theJ 1 statistic effectively detects branching rate heterogeneity in simulated lineage tracing data. Tests based on other common statistics ( s ^ and the Sackin index) show interior performance toJ 1 . We apply our validated methods to xenograft experimental data and find widespread rate heterogeneity across multiple study systems. Our results demonstrate the potential of tree topology statistics in analyzing lineage tracing data, and highlight the challenges associated with adapting phylogenetic methods to these systems.

Single-cell decoding of drug induced transcriptomic reprogramming in triple negative breast cancers

BACKGROUND

The encoding of cell intrinsic drug resistance states in breast cancer reflects the contributions of genomic and non-genomic variations and requires accurate estimation of clonal fitness from co-measurement of transcriptomic and genomic data. Somatic copy number (CN) variation is the dominant mutational mechanism leading to transcriptional variation and notably contributes to platinum chemotherapy resistance cell states. Here, we deploy time series measurements of triple negative breast cancer (TNBC) single-cell transcriptomes, along with co-measured single-cell CN fitness, identifying genomic and transcriptomic mechanisms in drug-associated transcriptional cell states.

RESULTS

We present scRNA-seq data (53,641 filtered cells) from serial passaging TNBC patient-derived xenograft (PDX) experiments spanning 2.5 years, matched with genomic single-cell CN data from the same samples. Our findings reveal distinct clonal responses within TNBC tumors exposed to platinum. Clones with high drug fitness undergo clonal sweeps and show subtle transcriptional reversion, while those with weak fitness exhibit dynamic transcription upon drug withdrawal. Pathway analysis highlights convergence on epithelial-mesenchymal transition and cytokine signaling, associated with resistance. Furthermore, pseudotime analysis demonstrates hysteresis in transcriptional reversion, indicating generation of new intermediate transcriptional states upon platinum exposure.

CONCLUSIONS

Within a polyclonal tumor, clones with strong genotype-associated fitness under platinum remained fixed, minimizing transcriptional reversion upon drug withdrawal. Conversely, clones with weaker fitness display non-genomic transcriptional plasticity. This suggests CN-associated and CN-independent transcriptional states could both contribute to platinum resistance. The dominance of genomic or non-genomic mechanisms within polyclonal tumors has implications for drug sensitivity, restoration, and re-treatment strategies.

Low coverage whole genome sequencing of low-grade dysplasia strongly predicts colorectal cancer risk in ulcerative colitis

Patients with inflammatory bowel disease (IBD) are at increased risk of colorectal cancer (CRC), and this risk increases dramatically in those who develop low-grade dysplasia (LGD). However, there is currently no accurate way to risk-stratify patients with LGD, leading to both over- and under-treatment of cancer risk. Here we show that the burden of somatic copy number alterations (CNAs) within resected LGD lesions strongly predicts future cancer development. We performed a retrospective multi-centre validated case-control study of n=122 patients (40 progressors, 82 non-progressors, 270 LGD regions). Low coverage whole genome sequencing revealed CNA burden was significantly higher in progressors than non-progressors (p=2×10-6 in discovery cohort) and was a very significant predictor of CRC risk in univariate analysis (odds ratio = 36; p=9×10-7), outperforming existing clinical risk factors such as lesion size, shape and focality. Optimal risk prediction was achieved with a multivariate model combining CNA burden with the known clinical risk factor of incomplete LGD resection. The measurement of CNAs in LGD lesions is a robust, low-cost and rapidly translatable predictor of CRC risk in IBD that can be used to direct management and so prevent CRC in high-risk individuals whilst sparing those at low-risk from unnecessary intervention.

Leveraging Cancer Phenotypic Plasticity for Novel Treatment Strategies

Cancer cells, like all other organisms, are adept at switching their phenotype to adjust to the changes in their environment. Thus, phenotypic plasticity is a quantitative trait that confers a fitness advantage to the cancer cell by altering its phenotype to suit environmental circumstances. Until recently, new traits, especially in cancer, were thought to arise due to genetic factors; however, it is now amply evident that such traits could also emerge non-genetically due to phenotypic plasticity. Furthermore, phenotypic plasticity of cancer cells contributes to phenotypic heterogeneity in the population, which is a major impediment in treating the disease. Finally, plasticity also impacts the group behavior of cancer cells, since competition and cooperation among multiple clonal groups within the population and the interactions they have with the tumor microenvironment also contribute to the evolution of drug resistance. Thus, understanding the mechanisms that cancer cells exploit to tailor their phenotypes at a systems level can aid the development of novel cancer therapeutics and treatment strategies. Here, we present our perspective on a team medicine-based approach to gain a deeper understanding of the phenomenon to develop new therapeutic strategies.

Phenotypic noise and plasticity in cancer evolution

Non-genetic alterations can produce changes in a cell's phenotype. In cancer, these phenomena can influence a cell's fitness by conferring access to heritable, beneficial phenotypes. Herein, we argue that current discussions of 'phenotypic plasticity' in cancer evolution ignore a salient feature of the original definition: namely, that it occurs in response to an environmental change. We suggest 'phenotypic noise' be used to distinguish non-genetic changes in phenotype that occur independently from the environment. We discuss the conceptual and methodological techniques used to identify these phenomena during cancer evolution. We propose that the distinction will guide efforts to define mechanisms of phenotype change, accelerate translational work to manipulate phenotypes through treatment, and, ultimately, improve patient outcomes.

Multiregional transcriptomics identifies congruent consensus subtypes with prognostic value beyond tumor heterogeneity of colorectal cancer

Intra-tumor heterogeneity compromises the clinical value of transcriptomic classifications of colorectal cancer. We investigated the prognostic effect of transcriptomic heterogeneity and the potential for classifications less vulnerable to heterogeneity in a single-hospital series of 1093 tumor samples from 692 patients, including multiregional samples from 98 primary tumors and 35 primary-metastasis sets. We show that intra-tumor heterogeneity of the consensus molecular subtypes (CMS) is frequent and has poor-prognostic associations independently of tumor microenvironment markers. Multiregional transcriptomics uncover cancer cell-intrinsic and low-heterogeneity signals that recapitulate the intrinsic CMSs proposed by single-cell sequencing. Further subclassification identifies congruent CMSs that explain a larger proportion of variation in patient survival than intra-tumor heterogeneity. Plasticity is indicated by discordant intrinsic phenotypes of matched primary and metastatic tumors. We conclude that multiregional sampling reconciles the prognostic power of tumor classifications from single-cell and bulk transcriptomics in the context of intra-tumor heterogeneity, and phenotypic plasticity challenges the reconciliation of primary and metastatic subtypes.

FUME-TCRseq Enables Sensitive and Accurate Sequencing of the T-cell Receptor from Limited Input of Degraded RNA

Genomic analysis of the T-cell receptor (TCR) reveals the strength, breadth, and clonal dynamics of the adaptive immune response to pathogens or cancer. The diversity of the TCR repertoire, however, means that sequencing is technically challenging, particularly for samples with low-quality, degraded nucleic acids. Here, we developed and validated FUME-TCRseq, a robust and sensitive RNA-based TCR sequencing methodology that is suitable for formalin-fixed paraffin-embedded samples and low amounts of input material. FUME-TCRseq incorporates unique molecular identifiers into each molecule of cDNA, allowing correction for sequencing errors and PCR bias. Using RNA extracted from colorectal and head and neck cancers to benchmark the accuracy and sensitivity of FUME-TCRseq against existing methods demonstrated excellent concordance between the datasets. Furthermore, FUME-TCRseq detected more clonotypes than a commercial RNA-based alternative, with shorter library preparation time and significantly lower cost. The high sensitivity and the ability to sequence RNA of poor quality and limited amount enabled quantitative analysis of small numbers of cells from archival tissue sections, which is not possible with other methods. Spatially resolved FUME-TCRseq analysis of colorectal cancers using macrodissected archival samples revealed the shifting T-cell landscapes at the transition to an invasive phenotype and between tumor subclones containing distinct driver alterations. In summary, FUME-TCRseq represents an accurate, sensitive, and low-cost tool for the characterization of T-cell repertoires, particularly in samples with low-quality RNA that have not been accessible using existing methodology.

SIGNIFICANCE

FUME-TCRseq is a TCR sequencing methodology that supports sensitive and spatially resolved detection of TCR clones in archival clinical specimens, which can facilitate longitudinal tracking of immune responses through disease course and treatment.

Decoding the interplay between genetic and non-genetic drivers of metastasis

Metastasis is a multistep process by which cancer cells break away from their original location and spread to distant organs, and is responsible for the vast majority of cancer-related deaths. Preventing early metastatic dissemination would revolutionize the ability to fight cancer. Unfortunately, the relatively poor understanding of the molecular underpinnings of metastasis has hampered the development of effective anti-metastatic drugs. Although it is now accepted that disseminating tumour cells need to acquire multiple competencies to face the many obstacles they encounter before reaching their metastatic site(s), whether these competencies are acquired through an accumulation of metastasis-specific genetic alterations and/or non-genetic events is often debated. Here we review a growing body of literature highlighting the importance of both genetic and non-genetic reprogramming events during the metastatic cascade, and discuss how genetic and non-genetic processes act in concert to confer metastatic competencies. We also describe how recent technological advances, and in particular the advent of single-cell multi-omics and barcoding approaches, will help to better elucidate the cross-talk between genetic and non-genetic mechanisms of metastasis and ultimately inform innovative paths for the early detection and interception of this lethal process.

Long-term Multimodal Recording Reveals Epigenetic Adaptation Routes in Dormant Breast Cancer Cells

Patients with estrogen receptor-positive breast cancer receive adjuvant endocrine therapies (ET) that delay relapse by targeting clinically undetectable micrometastatic deposits. Yet, up to 50% of patients relapse even decades after surgery through unknown mechanisms likely involving dormancy. To investigate genetic and transcriptional changes underlying tumor awakening, we analyzed late relapse patients and longitudinally profiled a rare cohort treated with long-term neoadjuvant ETs until progression. Next, we developed an in vitro evolutionary study to record the adaptive strategies of individual lineages in unperturbed parallel experiments. Our data demonstrate that ETs induce nongenetic cell state transitions into dormancy in a stochastic subset of cells via epigenetic reprogramming. Single lineages with divergent phenotypes awaken unpredictably in the absence of recurrent genetic alterations. Targeting the dormant epigenome shows promising activity against adapting cancer cells. Overall, this study uncovers the contribution of epigenetic adaptation to the evolution of resistance to ETs.

SIGNIFICANCE

This study advances the understanding of therapy-induced dormancy with potential clinical implications for breast cancer. Estrogen receptor-positive breast cancer cells adapt to endocrine treatment by entering a dormant state characterized by strong heterochromatinization with no recurrent genetic changes. Targeting the epigenetic rewiring impairs the adaptation of cancer cells to ETs. See related commentary by Llinas-Bertran et al., p. 704. This article is featured in Selected Articles from This Issue, p. 695.

Modeling tumors as species-rich ecological communities

Many advanced cancers resist therapeutic intervention. This process is fundamentally related to intra-tumor heterogeneity: multiple cell populations, each with different mutational and phenotypic signatures, coexist within a tumor and its metastatic nodes. Like species in an ecosystem, many cancer cell populations are intertwined in a complex network of ecological interactions. Most mathematical models of tumor ecology, however, cannot account for such phenotypic diversity nor are able to predict its consequences. Here we propose that the Generalized Lotka-Volterra model (GLV), a standard tool to describe complex, species-rich ecological communities, provides a suitable framework to describe the ecology of heterogeneous tumors. We develop a GLV model of tumor growth and discuss how its emerging properties, such as outgrowth and multistability, provide a new understanding of the disease. Additionally, we discuss potential extensions of the model and their application to three active areas of cancer research, namely phenotypic plasticity, the cancer-immune interplay and the resistance of metastatic tumors to treatment. Our work outlines a set of questions and a tentative road map for further research in cancer ecology.

Punctuational evolution is pervasive in distal site metastatic colonization

The evolution of metastasis represents a lethal stage of cancer progression. Yet, the evolutionary kinetics of metastatic disease remain unresolved. Here, using single cell CRISPR-Cas9 lineage tracing data, we show that in metastatic disease, gradual molecular evolution is punctuated by episodes of rapid evolutionary change associated with lineage divergence. By measuring punctuational effects across the metastatic cascade, we show that punctuational effects contribute more to the molecular diversity at distal site metastases compared to the paired primary tumor, suggesting qualitatively different modes of evolution may drive primary and metastatic tumor progression. This is the first empirical evidence for distinct patterns of molecular evolution at early and late stages of metastasis and demonstrates the complex interplay of cell intrinsic and extrinsic factors that shape lethal cancer.

Mapping single-cell developmental potential in health and disease with interpretable deep learning

Single-cell RNA sequencing (scRNA-seq) has transformed our understanding of cell fate in developmental systems. However, identifying the molecular hallmarks of potency - the capacity of a cell to differentiate into other cell types - has remained challenging. Here, we introduce CytoTRACE 2, an interpretable deep learning framework for characterizing potency and differentiation states on an absolute scale from scRNA-seq data. Across 31 human and mouse scRNA-seq datasets encompassing 28 tissue types, CytoTRACE 2 outperformed existing methods for recovering experimentally determined potency levels and differentiation states covering the entire range of cellular ontogeny. Moreover, it reconstructed the temporal hierarchy of mouse embryogenesis across 62 timepoints; identified pan-tissue expression programs that discriminate major potency levels; and facilitated discovery of cellular phenotypes in cancer linked to survival and immunotherapy resistance. Our results illuminate a fundamental feature of cell biology and provide a broadly applicable platform for delineating single-cell differentiation landscapes in health and disease.

Joint analysis of mutational and transcriptional landscapes in human cancer reveals key perturbations during cancer evolution

BACKGROUND

Tumors are able to acquire new capabilities, including traits such as drug resistance and metastasis that are associated with unfavorable clinical outcomes. Single-cell technologies have made it possible to study both mutational and transcriptomic profiles, but as most studies have been conducted on model systems, little is known about cancer evolution in human patients. Hence, a better understanding of cancer evolution could have important implications for treatment strategies.

RESULTS

Here, we analyze cancer evolution and clonal selection by jointly considering mutational and transcriptomic profiles of single cells acquired from tumor biopsies from 49 lung cancer samples and 51 samples with chronic myeloid leukemia. Comparing the two profiles, we find that each clone is associated with a preferred transcriptional state. For metastasis and drug resistance, we find that the number of mutations affecting related genes increases as the clone evolves, while changes in gene expression profiles are limited. Surprisingly, we find that mutations affecting ligand-receptor interactions with the tumor microenvironment frequently emerge as clones acquire drug resistance.

CONCLUSIONS

Our results show that lung cancer and chronic myeloid leukemia maintain a high clonal and transcriptional diversity, and we find little evidence in favor of clonal sweeps. This suggests that for these cancers selection based solely on growth rate is unlikely to be the dominating driving force during cancer evolution.

Increased heterogeneity in expression of genes associated with cancer progression and drug resistance

Fluctuations in the number of regulatory molecules and differences in timings of molecular events can generate variation in gene expression among genetically identical cells in the same environmental condition. This variation, termed as expression noise, can create differences in metabolic state and cellular functions, leading to phenotypic heterogeneity. Expression noise and phenotypic heterogeneity have been recognized as important contributors to intra-tumor heterogeneity, and have been associated with cancer growth, progression, and therapy resistance. However, how expression noise changes with cancer progression in actual cancer patients has remained poorly explored. Such an analysis, through identification of genes with increasing expression noise, can provide valuable insights into generation of intra-tumor heterogeneity, and could have important implications for understanding immune-suppression, drug tolerance and therapy resistance. In this work, we performed a genome-wide identification of changes in gene expression noise with cancer progression using single-cell RNA-seq data of lung adenocarcinoma patients at different stages of cancer. We identified 37 genes in epithelial cells that showed an increasing noise trend with cancer progression, many of which were also associated with cancer growth, EMT and therapy resistance. We found that expression of several of these genes was positively associated with expression of mitochondrial genes, suggesting an important role of mitochondria in generation of heterogeneity. In addition, we uncovered substantial differences in sample-specific noise profiles which could have implications for personalized prognosis and treatment.

Plastic persisters: revival stem cells in colorectal cancer

Colorectal cancer (CRC) is traditionally considered to be a genetically driven disease. However, nongenetic plasticity has recently emerged as a major driver of tumour initiation, metastasis, and therapy response in CRC. Central to these processes is a recently discovered cell type, the revival colonic stem cell (revCSC). In contrast to traditional proliferative CSCs (proCSCs), revCSCs prioritise survival over propagation. revCSCs play an essential role in primary tumour formation, metastatic dissemination, and nongenetic chemoresistance. Current evidence suggests that CRC tumours leverage intestinal stem cell plasticity to both proliferate (via proCSCs) when unchallenged and survive (via revCSCs) in response to cell-extrinsic pressures. Although revCSCs likely represent a major source of therapeutic failure in CRC, our increasing knowledge of this important stem cell fate provides novel opportunities for therapeutic intervention.

Epigenome and early selection determine the tumour-immune evolutionary trajectory of colorectal cancer

Immune system control is a major hurdle that cancer evolution must circumvent. The relative timing and evolutionary dynamics of subclones that have escaped immune control remain incompletely characterized, and how immune-mediated selection shapes the epigenome has received little attention. Here, we infer the genome- and epigenome-driven evolutionary dynamics of tumour-immune coevolution within primary colorectal cancers (CRCs). We utilise our existing CRC multi-region multi-omic dataset that we supplement with high-resolution spatially-resolved neoantigen sequencing data and highly multiplexed imaging of the tumour microenvironment (TME). Analysis of somatic chromatin accessibility alterations (SCAAs) reveals frequent somatic loss of accessibility at antigen presenting genes, and that SCAAs contribute to silencing of neoantigens. We observe that strong immune escape and exclusion occur at the outset of CRC formation, and that within tumours, including at the microscopic level of individual tumour glands, additional immune escape alterations have negligible consequences for the immunophenotype of cancer cells. Further minor immuno-editing occurs during local invasion and is associated with TME reorganisation, but that evolutionary bottleneck is relatively weak. Collectively, we show that immune evasion in CRC follows a "Big Bang" evolutionary pattern, whereby genetic, epigenetic and TME-driven immune evasion acquired by the time of transformation defines subsequent cancer-immune evolution.

Lineage Plasticity: The New Cancer Hallmark on the Block

Plasticity refers to the ability of cells to adopt a spectrum of states or phenotypes. In cancer, it is a critical contributor to tumor initiation, progression, invasiveness, and therapy resistance, and it has recently been recognized as an emerging cancer hallmark. Plasticity can occur as a result of cell-intrinsic factors (e.g., genetic, transcriptional, or epigenetic fluctuations), or through cell-extrinsic cues (e.g., signaling from components of the tumor microenvironment or selective pressure from therapy). Over the past decade, technological advances, analysis of patient samples, and studies in mouse model systems have led to a deeper understanding of how such plastic states come about. In this review, we discuss: (i) the definition of plasticity; (ii) methods to measure and quantify plasticity; (iii) the clinical relevance of plasticity; and (iv) therapeutic hypotheses to modulate plasticity in the clinic.

Peroxisome proliferator-activated receptorα/γ agonist pioglitazone for rescuing relapsed or refractory neoplasias by unlocking phenotypic plasticity

A series of seven clinical trials on relapsed or refractory (r/r) metastatic neoplasias followed the question: Are networks of ligand-receptor cross-talks that support tumor-specific cancer hallmarks, druggable with tumor tissue editing approaches therapeutically exploiting tumor plasticity? Differential recombinations of pioglitazone, a dual peroxisome-proliferator activated receptorα/γ (PPARα/γ) agonist, with transcriptional modulators, i.e., all-trans retinoic acid, interferon-α, or dexamethasone plus metronomic low-dose chemotherapy (MCT) or epigenetic modeling with azacitidine plus/minus cyclooxygenase-2 inhibition initiated tumor-specific reprogramming of cancer hallmarks, as exemplified by inflammation control in r/r melanoma, renal clear cell carcinoma (RCCC), Hodgkin's lymphoma (HL) and multisystem Langerhans cell histiocytosis (mLCH) or differentiation induction in non-promyelocytic acute myeloid leukemia (non-PML AML). Pioglitazone, integrated in differentially designed editing schedules, facilitated induction of tumor cell death as indicated by complete remission (CR) in r/r non-PML AML, continuous CR in r/r RCCC, mLCH, and in HL by addition of everolimus, or long-term disease control in melanoma by efficaciously controlling metastasis, post-therapy cancer repopulation and acquired cell-resistance and genetic/molecular-genetic tumor cell heterogeneity (M-CRAC). PPARα/γ agonists provided tumor-type agnostic biomodulatory efficacy across different histologic neoplasias. Tissue editing techniques disclose that wide-ranging functions of PPARα/γ agonists may be on-topic focused for differentially unlocking tumor phenotypes. Low-dose MCT facilitates targeted reprogramming of cancer hallmarks with transcriptional modulators, induction of tumor cell death, M-CRAC control and editing of non-oncogene addiction. Thus, pioglitazone, integrated in tumor tissue editing protocols, is an important biomodulatory drug for addressing urgent therapeutic problems, such as M-CRAC in relapsed or refractory tumor disease.

Transcriptional state dynamics lead to heterogeneity and adaptive tumor evolution in urothelial bladder carcinoma

Intra-tumor heterogeneity contributes to treatment failure and poor survival in urothelial bladder carcinoma (UBC). Analyzing transcriptome from a UBC cohort, we report that intra-tumor transcriptomic heterogeneity indicates co-existence of tumor cells in epithelial and mesenchymal-like transcriptional states and bi-directional transition between them occurs within and between tumor subclones. We model spontaneous and reversible transition between these partially heritable states in cell lines and characterize their population dynamics. SMAD3, KLF4 and PPARG emerge as key regulatory markers of the transcriptional dynamics. Nutrient limitation, as in the core of large tumors, and radiation treatment perturb the dynamics, initially selecting for a transiently resistant phenotype and then reconstituting heterogeneity and growth potential, driving adaptive evolution. Dominance of transcriptional states with low PPARG expression indicates an aggressive phenotype in UBC patients. We propose that phenotypic plasticity and dynamic, non-genetic intra-tumor heterogeneity modulate both the trajectory of disease progression and adaptive treatment response in UBC.

Molecular cartography uncovers evolutionary and microenvironmental dynamics in sporadic colorectal tumors

Colorectal cancer exhibits dynamic cellular and genetic heterogeneity during progression from precursor lesions toward malignancy. Analysis of spatial multi-omic data from 31 human colorectal specimens enabled phylogeographic mapping of tumor evolution that revealed individualized progression trajectories and accompanying microenvironmental and clonal alterations. Phylogeographic mapping ordered genetic events, classified tumors by their evolutionary dynamics, and placed clonal regions along global pseudotemporal progression trajectories encompassing the chromosomal instability (CIN+) and hypermutated (HM) pathways. Integrated single-cell and spatial transcriptomic data revealed recurring epithelial programs and infiltrating immune states along progression pseudotime. We discovered an immune exclusion signature (IEX), consisting of extracellular matrix regulators DDR1, TGFBI, PAK4, and DPEP1, that charts with CIN+ tumor progression, is associated with reduced cytotoxic cell infiltration, and shows prognostic value in independent cohorts. This spatial multi-omic atlas provides insights into colorectal tumor-microenvironment co-evolution, serving as a resource for stratification and targeted treatments.

Trellis tree-based analysis reveals stromal regulation of patient-derived organoid drug responses

Patient-derived organoids (PDOs) can model personalized therapy responses; however, current screening technologies cannot reveal drug response mechanisms or how tumor microenvironment cells alter therapeutic performance. To address this, we developed a highly multiplexed mass cytometry platform to measure post-translational modification (PTM) signaling, DNA damage, cell-cycle activity, and apoptosis in >2,500 colorectal cancer (CRC) PDOs and cancer-associated fibroblasts (CAFs) in response to clinical therapies at single-cell resolution. To compare patient- and microenvironment-specific drug responses in thousands of single-cell datasets, we developed "Trellis"-a highly scalable, tree-based treatment effect analysis method. Trellis single-cell screening revealed that on-target cell-cycle blockage and DNA-damage drug effects are common, even in chemorefractory PDOs. However, drug-induced apoptosis is rarer, patient-specific, and aligns with cancer cell PTM signaling. We find that CAFs can regulate PDO plasticity-shifting proliferative colonic stem cells (proCSCs) to slow-cycling revival colonic stem cells (revCSCs) to protect cancer cells from chemotherapy.

Contribution of pks+ E. coli mutations to colorectal carcinogenesis

The dominant mutational signature in colorectal cancer genomes is C > T deamination (COSMIC Signature 1) and, in a small subgroup, mismatch repair signature (COSMIC signatures 6 and 44). Mutations in common colorectal cancer driver genes are often not consistent with those signatures. Here we perform whole-genome sequencing of normal colon crypts from cancer patients, matched to a previous multi-omic tumour dataset. We analyse normal crypts that were distant vs adjacent to the cancer. In contrast to healthy individuals, normal crypts of colon cancer patients have a high incidence of pks + (polyketide synthases) E.coli (Escherichia coli) mutational and indel signatures, and this is confirmed by metagenomics. These signatures are compatible with many clonal driver mutations detected in the corresponding cancer samples, including in chromatin modifier genes, supporting their role in early tumourigenesis. These results provide evidence that pks + E.coli is a potential driver of carcinogenesis in the human gut.

AEP-cleaved DDX3X induces alternative RNA splicing events to mediate cancer cell adaptation in harsh microenvironments

Oxygen and nutrient deprivation are common features of solid tumors. Although abnormal alternative splicing (AS) has been found to be an important driving force in tumor pathogenesis and progression, the regulatory mechanisms of AS that underly the adaptation of cancer cells to harsh microenvironments remain unclear. Here, we found that hypoxia- and nutrient deprivation-induced asparagine endopeptidase (AEP) specifically cleaved DDX3X in a HIF1A-dependent manner. This cleavage yields truncated carboxyl-terminal DDX3X (tDDX3X-C), which translocates and aggregates in the nucleus. Unlike intact DDX3X, nuclear tDDX3X-C complexes with an array of splicing factors and induces AS events of many pre-mRNAs; for example, enhanced exon skipping (ES) in exon 2 of the classic tumor suppressor PRDM2 leads to a frameshift mutation of PRDM2. Intriguingly, the isoform ARRB1-Δexon 13 binds to glycolytic enzymes and regulates glycolysis. By utilizing in vitro assays, glioblastoma organoids, and animal models, we revealed that AEP/tDDX3X-C promoted tumor malignancy via these isoforms. More importantly, high AEP/tDDX3X-C/ARRB1-Δexon 13 in cancerous tissues was tightly associated with poor patient prognosis. Overall, our discovery of the effect of AEP-cleaved DDX3X switching on alternative RNA splicing events identifies a mechanism in which cancer cells adapt to oxygen and nutrient shortages and provides potential diagnostic and/or therapeutic targets.

Reactivation of embryonic genetic programs in tissue regeneration and disease

Embryonic genetic programs are reactivated in response to various types of tissue damage, providing cell plasticity for tissue regeneration or disease progression. In acute conditions, these programs remedy the damage and then halt to allow a return to homeostasis. In chronic situations, including inflammatory diseases, fibrosis and cancer, prolonged activation of embryonic programs leads to disease progression and tissue deterioration. Induction of progenitor identity and cell plasticity, for example, epithelial-mesenchymal plasticity, are critical outcomes of reactivated embryonic programs. In this Review, we describe molecular players governing reactivated embryonic genetic programs, their role during disease progression, their similarities and differences and lineage reversion in pathology and discuss associated therapeutics and drug-resistance mechanisms across many organs. We also discuss the diversity of reactivated programs in different disease contexts. A comprehensive overview of commonalities between development and disease will provide better understanding of the biology and therapeutic strategies.

Subclonal accumulation of immune escape mechanisms in microsatellite instability-high colorectal cancers

BACKGROUND

Intratumor heterogeneity (ITH) in microsatellite instability-high (MSI-H) colorectal cancer (CRC) has been poorly studied. We aimed to clarify how the ITH of MSI-H CRCs is generated in cancer evolution and how immune selective pressure affects ITH.

METHODS

We reanalyzed public whole-exome sequencing data on 246 MSI-H CRCs. In addition, we performed a multi-region analysis from 6 MSI-H CRCs. To verify the process of subclonal immune escape accumulation, a novel computational model of cancer evolution under immune pressure was developed.

RESULTS

Our analysis presented the enrichment of functional genomic alterations in antigen-presentation machinery (APM). Associative analysis of neoantigens indicated the generation of immune escape mechanisms via HLA alterations. Multiregion analysis revealed the clonal acquisition of driver mutations and subclonal accumulation of APM defects in MSI-H CRCs. Examination of variant allele frequencies demonstrated that subclonal mutations tend to be subjected to selective sweep. Computational simulations of tumour progression with the interaction of immune cells successfully verified the subclonal accumulation of immune escape mutations and suggested the efficacy of early initiation of an immune checkpoint inhibitor (ICI) -based treatment.

CONCLUSIONS

Our results demonstrate the heterogeneous acquisition of immune escape mechanisms in MSI-H CRCs by Darwinian selection, providing novel insights into ICI-based treatment strategies.

Evolutionary fingerprints of EMT in pancreatic cancers

Mesenchymal plasticity has been extensively described in advanced and metastatic epithelial cancers; however, its functional role in malignant progression, metastatic dissemination and therapy response is controversial. More importantly, the role of epithelial mesenchymal transition (EMT) and cell plasticity in tumor heterogeneity, clonal selection and clonal evolution is poorly understood. Functionally, our work clarifies the contribution of EMT to malignant progression and metastasis in pancreatic cancer. We leveraged ad hoc somatic mosaic genome engineering, lineage tracing and ablation technologies and dynamic genetic reporters to trace and ablate tumor-specific lineages along the phenotypic spectrum of epithelial to mesenchymal plasticity. The experimental evidences clarify the essential contribution of mesenchymal lineages to pancreatic cancer evolution and metastatic dissemination. Spatial genomic analysis combined with single cell transcriptomic and epigenomic profiling of epithelial and mesenchymal lineages reveals that EMT promotes with the emergence of chromosomal instability (CIN). Specifically tumor lineages with mesenchymal features display highly conserved patterns of genomic evolution including complex structural genomic rearrangements and chromotriptic events. Genetic ablation of mesenchymal lineages robustly abolished these mutational processes and evolutionary patterns, as confirmed by cross species analysis of pancreatic and other human epithelial cancers. Mechanistically, we discovered that malignant cells with mesenchymal features display increased chromatin accessibility, particularly in the pericentromeric and centromeric regions, which in turn results in delayed mitosis and catastrophic cell division. Therefore, EMT favors the emergence of high-fitness tumor cells, strongly supporting the concept of a cell-state, lineage-restricted patterns of evolution, where cancer cell sub-clonal speciation is propagated to progenies only through restricted functional compartments. Restraining those evolutionary routes through genetic ablation of clones capable of mesenchymal plasticity and extinction of the derived lineages completely abrogates the malignant potential of one of the most aggressive form of human cancer.

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.

CEA-delta could be a biomarker of tumor phenotype, clinical stage, and chemotherapeutic response in rectal cancer with OCT4-positive cancer stem cells

Background

There is very limited evidence on biomarkers for evaluating the clinical behavior and therapeutic response in rectal cancer (RC) with positive expression of cancer stem cells (CSCs).

Methods

An exploratory prospective study was conducted, which included fresh samples of tumor tissue from 109 patients diagnosed with primary RC. Sociodemographic, pathological and clinical characteristics were collected from medical records and survey. The OCT4 protein was isolated using the Western Blot technique. It was calculated the ΔCEA, ΔOCT4, and ΔOCT4/GUSB values by assessing the changes before and after chemotherapy, aiming to evaluate the therapeutic response.

Results

Patients had an average age of 69.9 years, with 55% (n=60) being male. Approximately 63.3% of the tumors were undifferentiated, and the most frequent staging classification was pathological stage III (n=64; 58.7%). Initial positive expression was observed in 77.1% of the patients (n=84), and the median ΔCEA was -1.03 (-3.82 - 0.84) ng/ml, with elevated levels (< -0.94 ng/ml) found in 51.4% of the subjects (n=56). Being OCT4 positive and having an elevated ΔCEA value were significantly associated with undifferentiated tumor phenotype (p=0.002), advanced tumor progression stage (p <0.001), and negative values of ΔOCT4 (p <0.001) (suggestive of poor therapeutic response) compared to those without this status.

Conclusion

This study identified a significant and directly proportional association among the values of ΔCEA, ΔOCT4, and ΔOCT4/GUSB. These findings suggest that ΔCEA holds potential as a clinical biomarker for determining the undifferentiated tumor phenotype, advanced clinical stage, and poor therapeutic response in RC with CSCs positive expression.

cloneRate: fast estimation of single-cell clonal dynamics using coalescent theory

MOTIVATION

While evolutionary approaches to medicine show promise, measuring evolution itself is difficult due to experimental constraints and the dynamic nature of body systems. In cancer evolution, continuous observation of clonal architecture is impossible, and longitudinal samples from multiple timepoints are rare. Increasingly available DNA sequencing datasets at single-cell resolution enable the reconstruction of past evolution using mutational history, allowing for a better understanding of dynamics prior to detectable disease. There is an unmet need for an accurate, fast, and easy-to-use method to quantify clone growth dynamics from these datasets.

RESULTS

We derived methods based on coalescent theory for estimating the net growth rate of clones using either reconstructed phylogenies or the number of shared mutations. We applied and validated our analytical methods for estimating the net growth rate of clones, eliminating the need for complex simulations used in previous methods. When applied to hematopoietic data, we show that our estimates may have broad applications to improve mechanistic understanding and prognostic ability. Compared to clones with a single or unknown driver mutation, clones with multiple drivers have significantly increased growth rates (median 0.94 versus 0.25 per year; P = 1.6×10-6). Further, stratifying patients with a myeloproliferative neoplasm (MPN) by the growth rate of their fittest clone shows that higher growth rates are associated with shorter time to MPN diagnosis (median 13.9 versus 26.4 months; P = 0.0026).

AVAILABILITY AND IMPLEMENTATION

We developed a publicly available R package, cloneRate, to implement our methods (Package website: https://bdj34.github.io/cloneRate/). Source code: https://github.com/bdj34/cloneRate/.

Spatial transcriptomics: Technologies, applications and experimental considerations

The diverse cell types of an organ have a highly structured organization to enable their efficient and correct function. To fully appreciate gene functions in a given cell type, one needs to understand how much, when and where the gene is expressed. Classic bulk RNA sequencing and popular single cell sequencing destroy cell structural organization and fail to provide spatial information. However, the spatial location of gene expression or of the cell in a complex tissue provides key clues to comprehend how the neighboring genes or cells cross talk, transduce signals and work together as a team to complete the job. The functional requirement for the spatial content has been a driving force for rapid development of the spatial transcriptomics technologies in the past few years. Here, we present an overview of current spatial technologies with a special focus on the commercially available or currently being commercialized technologies, highlight their applications by category and discuss experimental considerations for a first spatial experiment.

Progressive plasticity during colorectal cancer metastasis

Metastasis is the principal cause of cancer death, yet we lack an understanding of metastatic cell states, their relationship to primary tumor states, and the mechanisms by which they transition. In a cohort of biospecimen trios from same-patient normal colon, primary and metastatic colorectal cancer, we show that while primary tumors largely adopt LGR5 + intestinal stem-like states, metastases display progressive plasticity. Loss of intestinal cell states is accompanied by reprogramming into a highly conserved fetal progenitor state, followed by non-canonical differentiation into divergent squamous and neuroendocrine-like states, which is exacerbated by chemotherapy and associated with poor patient survival. Using matched patient-derived organoids, we demonstrate that metastatic cancer cells exhibit greater cell-autonomous multilineage differentiation potential in response to microenvironment cues than their intestinal lineage-restricted primary tumor counterparts. We identify PROX1 as a stabilizer of intestinal lineage in the fetal progenitor state, whose downregulation licenses non-canonical reprogramming.

Unravelling the Complexity of Colorectal Cancer: Heterogeneity, Clonal Evolution, and Clinical Implications

Colorectal cancer (CRC) is a global health concern and a leading cause of death worldwide. The disease's course and response to treatment are significantly influenced by its heterogeneity, both within a single lesion and between primary and metastatic sites. Biomarkers, such as mutations in KRAS, NRAS, and BRAF, provide valuable guidance for treatment decisions in patients with metastatic CRC. While high concordance exists between mutational status in primary and metastatic lesions, some heterogeneity may be present. Circulating tumor DNA (ctDNA) analysis has proven invaluable in identifying genetic heterogeneity and predicting prognosis in RAS-mutated metastatic CRC patients. Tumor heterogeneity can arise from genetic and non-genetic factors, affecting tumor development and response to therapy. To comprehend and address clonal evolution and intratumoral heterogeneity, comprehensive genomic studies employing techniques such as next-generation sequencing and computational analysis are essential. Liquid biopsy, notably through analysis of ctDNA, enables real-time clonal evolution and treatment response monitoring. However, challenges remain in standardizing procedures and accurately characterizing tumor subpopulations. Various models elucidate the origin of CRC heterogeneity, highlighting the intricate molecular pathways involved. This review focuses on intrapatient cancer heterogeneity and genetic clonal evolution in metastatic CRC, with an emphasis on clinical applications.

Cannabis- and Substance-Related Carcinogenesis in Europe: A Lagged Causal Inferential Panel Regression Study

Recent European data facilitate an epidemiological investigation of the controversial cannabis-cancer relationship. Of particular concern were prior findings associating high-dose cannabis use with reproductive problems and potential genetic impacts. Cancer incidence data age-standardised to the world population was obtained from the European Cancer Information System 2000-2020 and many European national cancer registries. Drug use data were obtained from the European Monitoring Centre for Drugs and Drug Addiction. Alcohol and tobacco consumption was sourced from the WHO. Median household income was taken from the World bank. Cancer rates in high-cannabis-use countries were significantly higher than elsewhere (β-estimate = 0.4165, p = 3.54 × 10^-115). Eighteen of forty-one cancers (42,675 individual rates) were significantly associated with cannabis exposure at bivariate analysis. Twenty-five cancers were linked in inverse-probability-weighted multivariate models. Temporal lagging in panel models intensified these effects. In multivariable models, cannabis was a more powerful correlate of cancer incidence than tobacco or alcohol. Reproductive toxicity was evidenced by the involvement of testis, ovary, prostate and breast cancers and because some of the myeloid and lymphoid leukaemias implicated occur in childhood, indicating inherited intergenerational genotoxicity. Cannabis is a more important carcinogen than tobacco and alcohol and fulfills epidemiological qualitative and quantitative criteria for causality for 25/41 cancers. Reproductive and transgenerational effects are prominent. These findings confirm the clinical and epidemiological salience of cannabis as a major multigenerational community carcinogen.

Colorectal cancer liver metastasis: genomic evolution and crosstalk with the liver microenvironment

Colorectal cancer (CRC) patients frequently develop liver metastases, which are the major cause of cancer-related mortality. The molecular basis and management of colorectal liver metastases (CRLMs) remain a challenging clinical issue. Recent genomic evidence has demonstrated the liver tropism of CRC and the presence of a stricter evolutionary bottleneck in the liver as a target organ compared to lymph nodes. This bottleneck challenging CRC cells in the liver is organ-specific and requires adaptation not only at the genetic level, but also at the phenotypic level to crosstalk with the hepatic microenvironment. Here, we highlight the emerging evidence on the clonal evolution of CRLM and review recent insights into the molecular mechanisms orchestrating the bidirectional interactions between metastatic CRC cells and the unique liver microenvironment.

Toward a systems-level probing of tumor clonality

Cancer has been described as a genetic disease that clonally evolves in the face of selective pressures imposed by cell-intrinsic and extrinsic factors. Although classical models based on genetic data predominantly propose Darwinian mechanisms of cancer evolution, recent single-cell profiling of cancers has described unprecedented heterogeneity in tumors providing support for alternative models of branched and neutral evolution through both genetic and non-genetic mechanisms. Emerging evidence points to a complex interplay between genetic, non-genetic, and extrinsic environmental factors in shaping the evolution of tumors. In this perspective, we briefly discuss the role of cell-intrinsic and extrinsic factors that shape clonal behaviors during tumor progression, metastasis, and drug resistance. Taking examples of pre-malignant states associated with hematological malignancies and esophageal cancer, we discuss recent paradigms of tumor evolution and prospective approaches to further enhance our understanding of this spatiotemporally regulated process.

In vitro cancer models as an approach to identify targetable developmental phenotypes in cancer stem cells

Cancer therapeutics are often highly toxic to the patient, and they often elicit rapid resistance in the tumour. Recent advances have suggested a potential new way in which we may improve on this, through two important concepts: (1) that multitudinous pathway alterations converge on a limited number of cancer cellular phenotypes, and (2) that these cancer cellular phenotypes depend on reactivation of developmental processes that are only minimally active in adult tissues. This provides a rationale for pursuing an approach of 'drugging the phenotype' focussed on targeting reactivated cellular processes from embryonic development. In this concepts paper, we cover these recent developments and their implications for the development of new cancer therapeutics that can avoid patient toxicity and acquired resistance. We then propose that in vitro tumour and developmental models can provide an experimental approach to identify and target the specific developmental processes at play, with a focus on the reactivation of developmental processes in the cancer stem cells that drive tumour progression and spread. Ultimately, the aim is to identify cellular processes that are specific to developmental phenotypes, are reactivated in cancer stem cells, and are essential to tumour progression. Therapeutically targeting these cellular processes could represent a new approach of 'drugging the phenotype' that treats the tumour whilst avoiding patient toxicity or the acquisition of therapeutic resistance.

N6-methyladenosine (m6A) in cancer stem cell: From molecular mechanisms to therapeutic implications

The emergence of drug resistance and metastasis has long been a difficult problem for cancer treatment. Recent studies have shown that cancer stem cell populations are key factors in the regulation of cancer aggressiveness, relapse and drug resistance. Cancer stem cell (CSC) populations are highly plastic and self-renewing, giving them unique metabolic, metastatic, and chemotherapy resistance properties. N6-methyladenosine (m6A) is the most abundant internal modification of mRNA and is involved in a variety of cell growth and development processes, including RNA transcription, alternative splicing, degradation, and translation. It has also been linked to the development of various cancers. At present, the important role of m6A in tumour progression is gradually attracting attention, especially in the tumour stemness regulation process. Abnormal m6A modifications regulate tumour metastasis, recurrence and drug resistance. This paper aims to explore the regulatory mechanism of m6A in CSCs and clinical therapy, clarify its regulatory network, and provide theoretical guidance for the development of clinical targets and improvement of therapeutic effects.

The Evolutionary Landscape of Colorectal Tumorigenesis: Recent Paradigms, Models, and Hypotheses

Using colorectal cancer as a model, we review some of the insights into cancer evolution afforded by cancer sequencing. These include nonlinear and neutral evolution; polyclonality of driver mutations and parallel evolution in adenomas, although these are rare in carcinomas; the ability of mutational processes to shape evolution against the force of selection; the presence of rare driver genes that function in the same signaling pathways as the longstanding canonical drivers; and the existence of selective windows that constrain the functional effects of cancer driver mutations within limits. Many of these nascent evolutionary paradigms are potentially important for treating colorectal cancers as well as understanding their development.

State-dependent evolutionary models reveal modes of solid tumour growth

Spatial properties of tumour growth have profound implications for cancer progression, therapeutic resistance and metastasis. Yet, how spatial position governs tumour cell division remains difficult to evaluate in clinical tumours. Here, we demonstrate that faster division on the tumour periphery leaves characteristic genetic patterns, which become evident when a phylogenetic tree is reconstructed from spatially sampled cells. Namely, rapidly dividing peripheral lineages branch more extensively and acquire more mutations than slower-dividing centre lineages. We develop a Bayesian state-dependent evolutionary phylodynamic model (SDevo) that quantifies these patterns to infer the differential division rates between peripheral and central cells. We demonstrate that this approach accurately infers spatially varying birth rates of simulated tumours across a range of growth conditions and sampling strategies. We then show that SDevo outperforms state-of-the-art, non-cancer multi-state phylodynamic methods that ignore differential sequence evolution. Finally, we apply SDevo to single-time-point, multi-region sequencing data from clinical hepatocellular carcinomas and find evidence of a three- to six-times-higher division rate on the tumour edge. With the increasing availability of high-resolution, multi-region sequencing, we anticipate that SDevo will be useful in interrogating spatial growth restrictions and could be extended to model non-spatial factors that influence tumour progression.

Addressing the genetic/nongenetic duality in cancer with systems biology

The dogma that cancer is a genetic disease is being questioned. Recent findings suggest that genetic/nongenetic duality is necessary for cancer progression. A think tank organized by the Shraman Foundation's Institute for Theoretical Biology compiled key challenges and opportunities that theoreticians, experimentalists, and clinicians can explore from a systems biology perspective to provide a better understanding of the disease as well as help discover new treatment options and therapeutic strategies.

Lineage tracing of mutant granulosa cells reveals in vivo protective mechanisms that prevent granulosa cell tumorigenesis

Ovarian granulosa cell tumors (GCTs) originate from granulosa cells (GCs) and represent the most common sex cord-stromal tumor in humans. However, the developmental regulations and molecular mechanisms underlying their etiology are largely unknown. In the current study, we combined a multi-fluorescent reporter mouse model with a conditional knockout mouse model, in which the tumor suppressor genes Pten and p27 were deleted in GCs, to perform cell lineage tracing of mutant GCs. We found that only 30% of ovaries with substantial mutant GCs developed into GCTs that derived from a single mutant GC. In-depth molecular analysis of the process of tumorigenesis demonstrated that up-regulation of immune evasion genes Cd24a and Cd47 led, in part, to the transition of mutant GCs to GCTs. Therefore, treatment with the Cd47 inhibitor RRX-001 was tested and found to efficiently suppress the growth of GCTs in vivo. Together, our study has revealed an immune evasion mechanism via CD24/CD47 upregulation to GCT formation, shedding light on the future potential clinical therapies for GCTs.

From Retrograde Menstruation to Endometrial Determinism and a Brave New World of "Root Treatment" of Endometriosis: Destiny or a Fanciful Utopia?

Practically unknown outside of China, the "endometrial determinism" theory was proposed to account for the apparent gap between the relatively low prevalence of endometriosis and nearly universal retrograde menstruation. Attracting uncritical advocacy, the theory culminates in a recent consensus by elite Chinese gynecologists in favor of "root treatment", intended to nip endometriosis in the bud. Correcting endometrial "defects" can gain further momentum by the presence of cancer-driver mutations such as KRAS mutations in the endometrium of women with endometriosis and the recent introduction of therapeutics aiming to rectify the effect of these mutations for cancer treatment. We provide a critical appraisal of evidence for endometrial aberrations in endometriosis and relevant experimental evidence. All available evidence of endometrial "defect" is invariably post hoc and may well be secondary to induced endometriosis. We propose that the theory of "endometrial determinism" needs to demonstrate a clear causal and a phylogenetic relationship between endometrial aberrations and endometriosis. We argue that while it is highly likely that endometriosis is a consequence of retrograde menstruation, the case that molecular aberrations as a sole or a necessary determinant remains to be proven. "Root treatment" is a worthy ambition but as of now it is close to a fanciful Utopia.

Spatial biology of cancer evolution

The natural history of cancers can be understood through the lens of evolution given that the driving forces of cancer development are mutation and selection of fitter clones. Cancer growth and progression are spatial processes that involve the breakdown of normal tissue organization, invasion and metastasis. For these reasons, spatial patterns are an integral part of histological tumour grading and staging as they measure the progression from normal to malignant disease. Furthermore, tumour cells are part of an ecosystem of tumour cells and their surrounding tumour microenvironment. A range of new spatial genomic, transcriptomic and proteomic technologies offers new avenues for the study of cancer evolution with great molecular and spatial detail. These methods enable precise characterizations of the tumour microenvironment, cellular interactions therein and micro-anatomical structures. In conjunction with spatial genomics, it emerges that tumours and microenvironments co-evolve, which helps explain observable patterns of heterogeneity and offers new routes for therapeutic interventions.

Nectins and Nectin-like Molecules in Colorectal Cancer: Role in Diagnostics, Prognostic Values, and Emerging Treatment Options: A Literature Review

In 2020, colorectal cancer was the third most common type of cancer worldwide with a clearly visible increase in the number of cases each year. With relatively high mortality rates and an uncertain prognosis, colorectal cancer is a serious health problem. There is an urgent need to investigate its specific mechanism of carcinogenesis and progression in order to develop new strategies of action against this cancer. Nectins and Nectin-like molecules are cell adhesion molecules that take part in a plethora of essential processes in healthy tissues as well as mediating substantial actions for tumor initiation and evolution. Our understanding of their role and a viable application of this in anti-cancer therapy has rapidly improved in recent years. This review summarizes the current data on the role nectins and Nectin-like molecules play in colorectal cancer.

An Epigenetic LINE-1-Based Mechanism in Cancer

In the last fifty years, large efforts have been deployed in basic research, clinical oncology, and clinical trials, yielding an enormous amount of information regarding the molecular mechanisms of cancer and the design of effective therapies. The knowledge that has accumulated underpins the complexity, multifactoriality, and heterogeneity of cancer, disclosing novel landscapes in cancer biology with a key role of genome plasticity. Here, we propose that cancer onset and progression are determined by a stress-responsive epigenetic mechanism, resulting from the convergence of upregulation of LINE-1 (long interspersed nuclear element 1), the largest family of human retrotransposons, genome damage, nuclear lamina fragmentation, chromatin remodeling, genome reprogramming, and autophagy activation. The upregulated expression of LINE-1 retrotransposons and their protein products plays a key role in these processes, yielding an increased plasticity of the nuclear architecture with the ensuing reprogramming of global gene expression, including the reactivation of embryonic transcription profiles. Cancer phenotypes would thus emerge as a consequence of the unscheduled reactivation of embryonic gene expression patterns in an inappropriate context, triggering de-differentiation and aberrant proliferation in differentiated cells. Depending on the intensity of the stressing stimuli and the level of LINE-1 response, diverse degrees of malignity would be generated.