Tumor Evolution Research Articles

Inferring replication timing and proliferation dynamics from single-cell DNA sequencing data

Dysregulated DNA replication is a cause and a consequence of aneuploidy in cancer, yet the interplay between copy number alterations (CNAs), replication timing (RT) and cell cycle dynamics remain understudied in aneuploid tumors. We developed a probabilistic method, PERT, for simultaneous inference of cell-specific replication and copy number states from single-cell whole genome sequencing (scWGS) data. We used PERT to investigate clone-specific RT and proliferation dynamics in >50,000 cells obtained from aneuploid and clonally heterogeneous cell lines, xenografts and primary cancers. We observed bidirectional relationships between RT and CNAs, with CNAs affecting X-inactivation producing the largest RT shifts. Additionally, we found that clone-specific S-phase enrichment positively correlated with ground-truth proliferation rates in genomically stable but not unstable cells. Together, these results demonstrate robust computational identification of S-phase cells from scWGS data, and highlight the importance of RT and cell cycle properties in studying the genomic evolution of aneuploid tumors.

Bases biologiques de l’immunothérapie anti-cancéreuse

Malignant tumors can be recognized as different from self identity by the immunological system, and the basis of immunotherapy thus relies on the use of immune system to fight cancer. Modern immunotherapy is actually a targeted therapy, since targeting proteins and biological mechanisms identified as favoring the anergy of immune system towards cancer. Complex cell interactions occur within the cancer microenvironment, between immune cells (T-lymphocytes CD4 and CD8, B-lymphocytes and plasma cells), between immune cells and cancer cells, between immune cells and stromal cells (cancer-associated fibroblasts), or between stromal cells and cancer cells. Such interactions consist of dynamic inter-cell communication networks, varying during the course of tumor evolution, but still sensitive to therapeutic interventions. A family of receptors named «immune checkpoint controls » has the physiological role to avoid a spontaneous unregulated hyper-activation of T-lymphocytes that could lead to self-immune diseases otherwise. However, such receptors are also used by cancer cells for inactivating T-lymphocytes, and thus escape to the anti-cancer immune system response. The aim of immunotherapy is therefore to restore an efficient T-cell response to cancer cells, either by inhibition of negative immune checkpoints, with blocking antibodies (immune checkpoints inhibitors), or to activate positive immune checkpoints using agonist antibodies. 1877-1203/© 2024 SPLF. Published by Elsevier Masson SAS. All rights reserved.

Prostate Cancer Progression Modeling Provides Insight into Dynamic Molecular Changes Associated with Progressive Disease States.

We developed and validated a progression model of prostate cancer using >1,000 tumor and normal tissue samples. The model provided a comprehensive view of prostate tumor evolution and progression.

Reconstructing oral cavity tumor evolution through brush biopsy

Oral potentially malignant disorders (OPMDs) with genomic alterations have a heightened risk of evolving into oral squamous cell carcinoma (OSCC). Currently, genomic data are typically obtained through invasive tissue biopsy. However, brush biopsy is a non-invasive method that has been utilized for identifying dysplastic cells in OPMD but its effectiveness in reflecting the genomic landscape of OPMDs remains uncertain. This pilot study investigates the potential of brush biopsy samples in accurately reconstructing the genomic profile and tumor evolution in a patient with both OPMD and OSCC. We analyzed single nucleotide variants (SNVs), copy number aberrations (CNAs), and subclonal architectures in paired tissue and brush biopsy samples. The results showed that brush biopsy effectively captured 90% of SNVs and had similar CNA profiles as those seen in its paired tissue biopsies in all lesions. It was specific, as normal buccal mucosa did not share these genomic alterations. Interestingly, brush biopsy revealed shared SNVs and CNAs between the distinct OPMD and OSCC lesions from the same patient, indicating a common ancestral origin. Subclonal reconstruction confirmed this shared ancestry, followed by divergent evolution of the lesions. These findings highlight the potential of brush biopsies in accurately representing the genomic profile of OPL and OSCC, proving insight into reconstructing tumor evolution.

Exploring the potential of extrachromosomal DNA as a novel oncogenic driver.

Extrachromosomal DNA (ecDNA) is a form of circular DNA mostly found in tumor cells. Unlike the typical chromosomal DNA, ecDNA is circular, self-replicating, and carries complete or partial gene fragments. Although ecDNA occurrence remains a rare event in cancer, recent studies have shown that oncogene amplification on ecDNA is widespread throughout many types of cancer, implying that ecDNA plays a central role in accelerating tumor evolution. ecDNA has also been associated with increased tumor mutation burden, chromosomal instability, and even tumor microenvironment remodeling. ecDNA may be crucial in influencing tumor heterogeneity, drug sensitivity, oncogenic senescence, and tumor immunogenicity, leading to a worsening prognosis for tumor patients. In this way, several clinical trials have been conducted to investigate the importance of ecDNA in clinical treatment. In this review, we summarize the biogenesis, characteristics, and current research methods of ecDNA, discuss the vital role of ecDNA-caused tumor heterogeneity in cancers, and highlight the potential role of ecDNA in cancer therapy.

Reconstructing tumor clonal heterogeneity and evolutionary relationships based on tumor DNA sequencing data.

The heterogeneity of tumor clones drives the selection and evolution of distinct tumor cell populations, resulting in an intricate and dynamic tumor evolution process. While tumor bulk DNA sequencing helps elucidate intratumor heterogeneity, challenges such as the misidentification of mutation multiplicity due to copy number variations and uncertainties in the reconstruction process hinder the accurate inference of tumor evolution. In this study, we introduce a novel approach, REconstructing Tumor Clonal Heterogeneity and Evolutionary Relationships (RETCHER), which characterizes more realistic cancer cell fractions by accurately identifying mutation multiplicity while considering uncertainty during the reconstruction process and the credibility and reasonableness of subclone clustering. This method comprehensively and accurately infers multiple forms of tumor clonal heterogeneity and phylogenetic relationships. RETCHER outperforms existing methods on simulated data and infers clearer subclone structures and evolutionary relationships in real multisample sequencing data from five tumor types. By precisely analysing the complex clonal heterogeneity within tumors, RETCHER provides a new approach to tumor evolution research and offers scientific evidence for developing precise and personalized treatment strategies. This approach is expected to play a significant role in tumor evolution research, clinical diagnosis, and treatment. RETCHER is available for free at https://github.com/zlsys3/RETCHER.

Robotic and Laparoscopic Cytoreductive Surgery and Hyperthermic Intraperitoneal Chemotherapy, Multicenter Study From Saudi Arabia.

Peritoneal metastasis (PM) is a common evolution of abdominal tumors. Without aggressive multimodal treatment, it is associated with a poor prognosis. The aim of this study is to present a multicenter results from Saudi Arabia on minimally invasive CRS and HIIPEC. A retrospective analysis of a prospective maintained multicenter database was queried for all patients treated with laparoscopic or robotic CRS and HIPEC between 2019 and 2024 in Saudi Arabia. Surgical and oncological outcome was analyzed. Eleven consecutive patients underwent minimally invasive CRS and HIPEC between 2019 and 2024. Eight patients (72.7%) were operated by laparoscopy, one of them by single port access and three patients (27.3%) were operated robotically. Six patients (54.5%) were female. Median age was 42 (29-64). Primary tumor was PMP from the appendix, colon, and MCM in 6 (54.5%), 4 (36.4%), and 1 (9.1%) respectively. The median duration to complete the surgical procedure for all patients was 330 (230-580) min and for robotic CRS the median docking time was 570 (330-580) min. Median PCI was 2 (1-7) and completeness Cytoreduction (CC score 0) was achieved in the all patients (100%). Median hospital stay was 8 days (3-20). Four patients had one night postoperative ICU stay. Major morbidity (CTCAE) 3 and 4 occurred in three patients (27.3%) (Port site hernia, bleeding, and wound infection). No readmission to the hospital and no 90 days mortalities. The minimally invasive approach by laparoscopy or robot is a feasible and promising option for CRS and HIPEC. It reduces the hospital stay, early return to intended oncological treatment (RIOT). Further prospective clinical studies are needed to evaluate this approach.

Recent progress and applications of single-cell sequencing technology in breast cancer.

Single-cell RNA sequencing (scRNA-seq) technology enables the precise analysis of individual cell transcripts with high sensitivity and throughput. When integrated with multiomics technologies, scRNA-seq significantly enhances the understanding of cellular diversity, particularly within the tumor microenvironment. Similarly, single-cell DNA sequencing has emerged as a powerful tool in cancer research, offering unparalleled insights into the genetic heterogeneity and evolution of tumors. In the context of breast cancer, this technology holds substantial promise for decoding the intricate genomic landscape that drives disease progression, treatment resistance, and metastasis. By unraveling the complexities of tumor biology at a granular level, single-cell DNA sequencing provides a pathway to advancing our comprehension of breast cancer and improving patient outcomes through personalized therapeutic interventions. As single-cell sequencing technology continues to evolve and integrate into clinical practice, its application is poised to revolutionize the diagnosis, prognosis, and treatment strategies for breast cancer. This review explores the potential of single-cell sequencing technology to deepen our understanding of breast cancer, highlighting key approaches, recent advancements, and the role of the tumor microenvironment in disease plasticity. Additionally, the review discusses the impact of single-cell sequencing in paving the way for the development of personalized therapies.

Lipids and adipocytes involvement in tumor progression with a focus on obesity and diet.

The adipose tissue is a complex organ that can play endocrine, metabolic, and immune regulatory roles in cancer. In particular, adipocytes provide metabolic substrates for cancer cell proliferation and produce signaling molecules that can stimulate cell adhesion, migration, invasion, angiogenesis, and inflammation. Cancer cells, in turn, can reprogram adipocytes towards a more inflammatory state, resulting in a vicious cycle that fuels tumor growth and evolution. These mechanisms are enhanced in obesity, which is associated with the risk of developing certain tumors. Diet, an exogenous source of lipids with pro- or anti-inflammatory functions, has also been connected to cancer risk. This review analyzes how adipocytes and lipids are involved in tumor development and progression, focusing on the relationship between obesity and cancer. In addition, we discuss how diets with varying lipid intakes can affect the disease outcomes. Finally, we introduce novel metabolism-targeted treatments and adipocyte-based therapies in oncology.

Multiomics Profiling Distinguishes Sebaceous Carcinoma from Benign Sebaceous Neoplasms and Provides Insight into the Genetic Evolution of Sebaceous Carcinogenesis.

Sebaceous carcinoma is the third most common nonkeratinocyte skin cancer in the United States with 1,000 cases per year. The clinicopathologic features of sebaceous carcinoma and benign sebaceous neoplasms (adenomas, sebaceomas) can overlap, highlighting the need for molecular biomarkers to improve classification. This study describes the genomic and transcriptomic landscape of sebaceous neoplasms in order to understand tumor etiology and biomarkers relevant for diagnosis and treatment. We performed whole-genome sequencing (WGS) and whole-transcriptome sequencing (WTS) of sebaceous neoplasms from six academic and two federal healthcare facilities in the United States diagnosed between January 1, 1999, and December 31, 2021. We evaluated 98 sebaceous neoplasms: 64 tumors (32 adenomas, 2 sebaceomas, 5 atypical sebaceous neoplasms, 25 carcinomas) had sufficient material for WGS, 96 tumors (42 adenomas, 11 sebaceomas, 8 atypical sebaceous neoplasms, 35 carcinomas) had sufficient material for WTS, and 62 tumors (31 adenomas, 2 sebaceomas, 5 atypical sebaceous neoplasms, 24 carcinomas) had sufficient material for combined WGS and WTS. Overall, we found decreased cholesterol biosynthesis and increased TP53 mutations, copy number gains (chromosome 6, 8q, and/or 18), and tumor mutation burden-high (>10 mutations/MB) in carcinomas compared to adenomas. Although diminished compared to adenomas, most carcinomas still had higher cholesterol biosynthesis than nonmalignant skin. Multiomics profiling also supported a precancerous model of tumor evolution with sebaceomas and atypical sebaceous neoplasms being likely intermediate lesions. The study findings highlight key diagnostic biomarkers for sebaceous carcinoma and suggest that immunotherapy and modulation of cholesterol biosynthesis could be effective treatment strategies.

Dynamics of tumor evolution after Gammaknife radiosurgery for sporadic vestibular schwannoma: defining volumetric patterns characterizing individual trajectory.

Definition of tumor control and treatment failure after Gammaknife radiosurgery (GKRS) for vestibular schwannoma (VS) is still debated. The lack of knowledge on the dynamics of tumor evolution can lead to misinterpretation and subsequent inappropriate second treatment. The aim of this study was to evaluate the post-GKRS dynamics of evolution of tumor volume, and characterize volumetric patterns. We included patients with sporadic VS treated by GKRS with an MRI follow-up of minimum 3 years. A clustering in 2 steps was performed: definition of the patterns of evolution based on a subset of patients with the most comprehensive follow-up, then assignment of the remaining patients on a best fit basis. The minimum length of follow-up was assessed by measuring the consistency of the clusters over time (Adjusted Rand Index and Normalized Mutual Information). An analysis of the discriminant variables was finally performed. 1,607 patients were included (median follow-up: 67 months). Five patterns were defined with one pattern gathering almost all cases of treatment failure. The clustering at 5 years afforded the highest consistency with long-term follow-up. Discriminant variables for clusters were: sex, initial symptoms, delay of diagnosis, Koos grading, fundus invasion, and number of isocenters. The definition of these robust distinct patterns is likely to help tremendously the physicians to distinguish tumor control from potential failure. We advocate for no retreatment decision before 5 years post-GKRS. Further investigations are required to decide if the dynamics of evolution can be predicted at GKRS on an individual basis.

Abstract C053: Pancreatic cancer patient-derived organoids, preclinical tools for therapeutic profiling, patient response prediction, and tumor evolution

Abstract Pancreatic cancer (PC) is characterized by an aggressive biology and an exceptionally high tumor heterogeneity that causes considerable variations in response to chemotherapies, targeted agents, and immunotherapies. Patient-derived organoids (PDOs) accurately reflect parental tumor biological and molecular features and may represent powerful preclinical avatars to predict drug response and support clinical decision-making. We generated a living organoid biobank of >100 PC PDO lines from treatment-naïve and pretreated primary tumor and metastases with a reliable efficacy (60.8%), and previously developed a pharmacotyping-guided prediction model to prognosticate patient therapy response in an initial feasibility trial (Beutel AK et al, 2021). Real-life chemotherapy responses in 46 patients (for a total of 93 therapy lines) matched to pharmacotyping-informed predictions with overall 73.1% accuracy, 85.4% sensitivity (responsiveness), and 63.5% specificity (non-responsiveness). Overall, our model allowed a successful drug-response prediction in naïve patients with an accuracy of 73.0% and 70.0% for first and second-line regimens. Prediction power was nevertheless lower in pretreated and heavily pretreated patients with a precision of 68.2% and 50.0% for subsequent chemotherapy lines, respectively. Interestingly, PDO-based pharmacotyping also precisely predicted patient clinical outcome in the neoadjuvant and adjuvant settings, with respective accuracies of 83.3% and 71.4%. Retrospective analysis of patient clinical data in palliative setting finally showed that the administration of a regimen predicted to be efficient ultimately translated into a significantly longer progression-free survival. Implementing automation and drug screening miniaturization to our workflow also significantly enhanced our process capacity, reduced time before pharmacotyping, and improved compliance to internal quality controls. Tracking clonal evolution in longitudinal biopsies (a set of seven PDO pairs derived from the same patients at two distinct timepoints) revealed lower mutational burden and therapy-driven genetic alterations upon progression. Notably, this approach revealed a CHEK2-mutated patient responded over time to PARP inhibitor maintenance therapy, aligning with our predictions and underscoring the robustness of our method. Single nucleus-resolved RNA and ATAC-seq analysis of a unique longitudinally-collected case uncovered transcriptomic and epigenetic dynamics associated with an oncogenic FGFR2 fusion and with a subsequent resistance-mediating mutation upon targeted treatment with FGFR2 inhibitors. Particularly, FGFR2 constitutive activation correlated with aberrant epigenetic trace and transcription programs of downstream targets as PI3K-AKT and RAS family members and of RNA polymerase II transcription machinery. Here, we report a robust and clinically-relevant preclinical tool for drug-response prediction, one more step towards a PDO therapeutic profiling-guided personalized medicine in clinical routine. Citation Format: Johann Gout, Yazid J Resheq, Jessica Lindenmayer, Julian D Schwab, Elodie Roger, Johann M Kraus, Thomas Ettrich, Alica K Beutel, Lukas Perkhofer, Hans A Kestler, Thomas Seufferlein, Alexander Kleger. Pancreatic cancer patient-derived organoids, preclinical tools for therapeutic profiling, patient response prediction, and tumor evolution [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr C053.

Abstract IA-01: Targeting autophagy in pancreatic cancer

Abstract Pancreatic ductal adenocarcinoma (PDAC) is one of the most vexing problems in cancer with 5-year overall survival rates of 13%, thus there is a need for new therapeutic targets. PDAC have a distinct dependence on autophagy, a conserved eukaryotic catabolic pathway that serves to degrade proteins, other macromolecules, and organelles via the lysosome as part of a recycling process to maintain cellular homeostasis during basal and stress conditions. The unique importance of autophagy in PDAC suggests that there may be a subset of proteins that are specifically targeted by autophagy for degradation, which would promote proliferation and survival, and that these may represent new targets for therapy. Using a quantitative PDAC cellular autophagosomal proteomics approach, we identified NCOA4 as the autophagy receptor for ferritin, the cellular iron storage complex, and demonstrated that ferritin autophagy (ferritinophagy) is a highly regulated process and plays a central role in the larger context of cellular and organismal iron homeostasis. Given the reliance of PDAC, on both high levels of autophagy as well as iron, we studied the role of NCOA4 and ferritinophagy in PDAC thereby identifying NCOA4-mediated ferritinophagy and more broadly lysosomal iron metabolism as a PDAC dependency and therapeutic target. We recently determined the cryo-EM structure of the NCOA4-Ferritin complex for future drug design. To identify the role of autophagy and the lysosome in PDAC metastatic progression, we co-developed an in vivo capable lysosomal enrichment that enables capture and proteomic profiling of lysosomes at different stages of tumor evolution, including early stage, late stage, and metastatic disease. Employing this strategy, we successfully captured lysosomal proteins from primary tumors (pancreas), as well as lung and liver metastases. Our preliminary analysis revealed an enrichment of resident lysosomal membrane and luminal proteins in the datasets, confirming successful isolation of intact lysosomes from these complex tissues. Additionally, we identified non-resident lysosomal proteins (termed cargo) that are enriched and co-evolve with advancing tumor stages. Notably, our results reveal distinct differences in the lysosomal proteome of tumor cells across different tissues. These findings emphasize the critical role of lysosomal function in tumor progression and suggest that targeting lysosomal components could be a promising therapeutic strategy for treating metastatic PDAC. Finally, given the challenging pharmacokinetic and pharmacodynamic properties and limited clinical efficacy of hydroxychloroquine as an autophagy/lysosomal inhibition strategy, we are now exploring novel autophagy inhibition strategies in PDAC to effectively target this pathway for clinical benefit. Citation Format: Joseph D. Mancias. Targeting autophagy in pancreatic cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr IA-01.

ERK1/2 mitogen-activated protein kinase dimerization is essential for the regulation of cell motility.

ERK1/2 mitogen-activated protein kinases (ERK) are key regulators of basic cellular processes, including proliferation, survival, and migration. Upon phosphorylation, ERK becomes activated and a portion of it dimerizes. The importance of ERK activation in specific cellular events is generally well documented, but the role played by dimerization is largely unknown. Here, we demonstrate that impeding ERK dimerization precludes cellular movement by interfering with the molecular machinery that executes the rearrangements of the actin cytoskeleton. We also show that a constitutively dimeric ERK mutant can drive cell motility per se, demonstrating that ERK dimerization is both necessary and sufficient for inducing cellular migration. Importantly, we unveil that the scaffold protein kinase suppressor of Ras 1 (KSR1) is a critical element for endowing external agonists, acting through tyrosine kinase receptors, with the capacity to induce ERK dimerization and, subsequently, to unleash cellular motion. In agreement, clinical data disclose that high KSR1 expression levels correlate with greater metastatic potential and adverse evolution of mammary tumors. Overall, our results portray both ERK dimerization and KSR1 as essential factors for the regulation of cell motility and mammary tumor dissemination.

Single cell genome and epigenome co-profiling reveals hardwiring and plasticity in breast cancer.

Understanding the impact of genetic alterations on epigenomic phenotypes during breast cancer progression is challenging with unimodal measurements. Here, we report wellDA-seq, the first high-genomic resolution, high-throughput method that can simultaneously measure the whole genome and chromatin accessibility profiles of thousands of single cells. Using wellDA-seq, we profiled 22,123 single cells from 2 normal and 9 tumors breast tissues. By directly mapping the epigenomic phenotypes to genetic lineages across cancer subclones, we found evidence of both genetic hardwiring and epigenetic plasticity. In 6 estrogen-receptor positive breast cancers, we directly identified the ancestral cancer cells, and found that their epithelial cell-of-origin was Luminal Hormone Responsive cells. We also identified cell types with copy number aberrations (CNA) in normal breast tissues and discovered non-epithelial cell types in the microenvironment with CNAs in breast cancers. These data provide insights into the complex relationship between genetic alterations and epigenomic phenotypes during breast tumor evolution.

Targeting DNA Damage Response Deficiency in Thoracic Cancers.

Thoracic cancers comprise non-small cell lung cancers (NSCLCs), small cell lung cancers (SCLCs) and malignant pleural mesotheliomas (MPM). Collectively, they account for the highest rate of death from malignancy worldwide. Genomic instability is a universal feature of cancer, which fuels mutations and tumour evolution. Deficiencies in DNA damage response (DDR) genes amplify genomic instability. Homologous recombination deficiency (HRD), resulting from BRCA1/BRCA2 inactivation, is exploited for therapeutic synthetic lethality with poly-ADP ribose polymerase (PARP) inhibitors in breast and ovarian cancers, as well as in prostate and pancreatic cancers. However, DDR deficiency and its therapeutic implications are less well established in thoracic cancers. Emerging evidence suggests that a subset of thoracic cancers may harbour DDR deficiency and may, thus, be effectively targeted with DDR agents. Here, we review the current evidence surrounding DDR in thoracic cancers and discuss the challenges and promise for achieving clinical benefit with such therapeutics.

Ecological and evolutionary dynamics to design and improve ovarian cancer treatment.

Ovarian cancer ecosystems are exceedingly complex, consisting of a high heterogeneity of cancer cells. Development of drugs such as poly ADP-ribose polymerase (PARP) inhibitors, targeted therapies and immunotherapies offer more options for sequential or combined treatments. Nevertheless, mortality in metastatic ovarian cancer patients remains high because cancer cells consistently develop resistance to single and combination therapies, urging a need for treatment designs that target the evolvability of cancer cells. The evolutionary dynamics that lead to resistance emerge from the complex tumour microenvironment, the heterogeneous populations, and the individual cancer cell's plasticity. We propose that successful management of ovarian cancer requires consideration of the ecological and evolutionary dynamics of the disease. Here, we review current options and challenges in ovarian cancer treatment and discuss principles of tumour evolution. We conclude by proposing evolutionarily designed strategies for ovarian cancer, with the goal of integrating such principles with longitudinal, quantitative data to improve the treatment design and management of drug resistance. KEY POINTS/HIGHLIGHTS: Tumours are ecosystems in which cancer and non-cancer cells interact and evolve in complex and dynamic ways. Conventional therapies for ovarian cancer inevitably lead to the development of resistance because they fail to consider tumours' heterogeneity and cellular plasticity. Eco-evolutionarily designed therapies should consider cancer cell plasticity and patient-specific characteristics to improve clinical outcome and prevent relapse.

1957: Proton Therapy for Glioblastoma: Insights into Tumor Evolution and Microenvironment Remodeling

1957: Proton Therapy for Glioblastoma: Insights into Tumor Evolution and Microenvironment Remodeling

Medullary thyroid cancer: single-cell transcriptome and tumor evolution

BackgroundMedullary thyroid cancer (MTC) is a rare neuroendocrine tumor that originates from the parafollicular C cells of thyroid gland. Understanding the fundamental pathophysiology of MTC is essential for clinical management. Single-cell RNA sequencing (scRNA-seq) technology is a powerful tool for identifying distinct cell types, offering a new biological foundation for comprehending the MTC ecosystem and developing precise treatment.MethodsFormalin fixed and paraffin-embedded (FFPE) samples of primary and adjacent non-cancerous tissues of three MTC cases were collected, and single-cell transcriptome data of MTC were obtained by using scRNA-seq technology. Annotated cell subpopulations were categorized and functionally enriched by principal component analysis, differential gene expression, and cell clustering analysis, to explore the biological process of tumor evolution that may be involved in each cell subpopulation. The copy number variation (CNV) profile was used to distinguish the malignancy of parafollicular thyroid cells, and the evolutionary trajectories of normal cells and tumor cells were revealed by the proposed time series analysis. The highly expressed genes in each cell subpopulation were analyzed by the FindAllMarker function of Seurat software, and verified by immunohistochemistry and fluorescence in situ hybridization. The prognostic value of specific cell subtypes was validated using large-scale public datasets.ResultsA total of 32,544 cells were obtained from the MTC tissue samples and 11,751 cells from the adjacent non-cancerous samples, which were classified into 7 heterogenous subpopulations by using R package of Seurat module. Copy number variations (CNVs) were significantly higher in tumor tissues than in adjacent non-tumor samples, predominantly enriched in subtypes C2 and C4. In addition, the pseudo-time for trajectory analysis suggested that the evolution of MTC tumor cells might begin with the C2 subtype, then transition to the early cancer subgroup C3, and further differentiate into four major malignant cell subpopulations C0, C1, C5 and C6. Survival analysis of a thyroid cancer cohort using the TCGA dataset revealed that high expression of genes linked to the C0 subcluster was correlated with poorer overall survival compared to low expression. Immunohistochemical staining showed that MAP3K4 was highly expressed in MTC tissues compared to adjacent non-cancerous tissues. Fluorescence in situ hybridization also confirmed the amplification of these two genes in MTC samples.ConclusionsBy conducting scRNA-seq on FFPE samples, we mapped the single-cell transcriptome of MTC, uncovering the tumor heterogeneity and unique biological features of each cellular subpopulation. The biological roles of identified tumor cell subpopulations such as C0 and C3 subtypes of parafollicular cells suggested the potential to discover new therapeutic targets and biomarkers for MTC, providing valuable insights for future translational and clinical research.

Break-induced replication drives large-scale genomic amplifications in cancer cells.

DNA double-strand breaks (DSBs) are highly toxic lesions that underly the efficacy of ionizing radiation (IR) and a large number of cytotoxic chemotherapies 1-3 . Yet, abnormal repair of DSBs is associated with genomic instability and may contribute to cancer heterogeneity and tumour evolution. Here, we show that DSBs induced by IR, by DSB-inducing chemotherapeutics, or by the expression of a rare-cutting restriction endonuclease induce large-scale genomic amplification in human cancer cells. Importantly, the extent of DSB-induced genomic amplification (DIGA) in a panel of melanoma cell lines correlated with the degree of cytotoxicity elicited by IR, suggesting that DIGA contributes significantly to DSB-induced cancer cell lethality. DIGA, which is mediated through conservative DNA synthesis, does not require origin re-licensing, and is enhanced by the depletion or deletion of the methyltransferases SET8 and SUV4-20H1, which function sequentially to mono- and di-methylate histone H4 lysine 20 (H4K20) at DSBs to facilitate the recruitment of 53BP1-RIF1 and its downstream effector shieldin complex to DSBs to prevent hyper-resection 4-11 . Consistently, DIGA was enhanced in cells lacking 53BP1 or RIF1, or in cells that lacked components of the shieldin complex or of other factors that help recruit 53BP1 to DSBs. Mechanistically, DIGA requires MRE11/CtIP and EXO1, factors that promote resection and hyper-resection at DSBs, and is dependent on the catalytic activity of the RAD51 recombinase. Furthermore, deletion or depletion of POLD3, POLD4, or RAD52, proteins involved in break-induced replication (BIR), significantly inhibited DIGA, suggesting that DIGA is mediated through a RAD51-dependent BIR-like process. DIGA induction was maximal if the cells encountered DSBs in early and mid S-phase, whereas cells competent for homologous recombination (in late S and G2) exhibited less DIGA induction. We propose that unshielded, hyper-resected ends of DSBs may nucleate a replication-like intermediate that enables cytotoxic long-range genomic DNA amplification mediated through BIR.