Adaptation and selection shape clonal evolution of tumors during residual disease and recurrence

Splicing inhibition mediated by reduced splicing factors and helicases is associated with the cellular response of lung cancer cells to cisplatin

Lung cancer's mortality is predominantly linked to post-chemotherapy recurrence, driven by the reactivation of dormant cancer cells. Despite the critical role of these reactivated cells in cancer recurrence and metastasis, the molecular mechanisms governing their therapeutic selection remain poorly understood. In this study, we conducted an integrative analysis by combining PacBio single molecule real-time (SMRT) sequencing with short reads Illumina RNA-seq. Our study revealed that cisplatin-induced dormant and reactivated cancer cells exhibited a noteworthy reduction in gene transcripts and alternative splicing events. Particularly, the differential alternative splicing events were found to be overlapping with the differentially expression genes and enriched in genes related to cell cycle and cell division. Utilizing ENCORI database and correlation analysis, we identified key splicing factors, including SRSF7, SRSF3, PRPF8, and HNRNPC, as well as RNA helicase such as EIF4A3, DDX39A, DDX11, and BRIP1, which were associated with the observed reduction in alternative splicing and subsequent decrease in gene expression. Our study demonstrated that lung cancer cells reduce gene transcripts through diminished alternative splicing events mediated by specific splicing factors and RNA helicase in response to the chemotherapeutic stress. These findings provide insights into the molecular mechanisms underlying the therapeutic selection and reactivation of dormant cancer cells. This discovery opens a potential avenue for the development of therapeutic strategies aimed at preventing cancer recurrence following chemotherapy.

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

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

Principles of digital sequencing using unique molecular identifiers

Massively parallel sequencing technologies have long been used in both basic research and clinical routine. The recent introduction of digital sequencing has made previously challenging applications possible by significantly improving sensitivity and specificity to now allow detection of rare sequence variants, even at single molecule level. Digital sequencing utilizes unique molecular identifiers (UMIs) to minimize sequencing-induced errors and quantification biases. Here, we discuss the principles of UMIs and how they are used in digital sequencing. We outline the properties of different UMI types and the consequences of various UMI approaches in relation to experimental protocols and bioinformatics. Finally, we describe how digital sequencing can be applied in specific research fields, focusing on cancer management where it can be used in screening of asymptomatic individuals, diagnosis, treatment prediction, prognostication, monitoring treatment efficacy and early detection of treatment resistance as well as relapse.

Stochastic epithelial-mesenchymal transitions diversify non-cancerous lung cell behaviours

Epithelial-mesenchymal plasticity (EMP) is a hallmark of cancer. By enabling cells to shift between different morphological and functional states, EMP promotes invasion, metastasis and therapy resistance. We report that near-diploid non-cancerous human epithelial lung cells spontaneously shift along the EMP spectrum without genetic changes. Strikingly, more than half of single cell-derived clones adopt a mesenchymal morphology. We independently characterise epithelial-like and mesenchymal-like clones. Mesenchymal clones lose epithelial markers, display larger cell aspect ratios and lower motility, with mostly unaltered proliferation rates. Stemness marker expression and metabolic rewiring diverge independently of phenotypes. In 3D culture, more epithelial clones become mesenchymal-like. Thus, non-cancerous epithelial cells may acquire cancer metastasis-associated features prior to genetic alterations and cancerous transformation.

Dormancy in Breast Cancer

The pattern of delayed recurrence in a subset of breast cancer patients has long been explained by a model that incorporates a variable period of cellular or tumor mass dormancy prior to disease relapse. In this review, we critically evaluate existing data to develop a framework for inferring the existence of dormancy in clinical contexts of breast cancer. We integrate these clinical data with rapidly evolving mechanistic insights into breast cancer dormancy derived from a broad array of genetically engineered mouse models as well as experimental models of metastasis. Finally, we propose actionable interventions and discuss ongoing clinical trials that translate the wealth of knowledge gained in the laboratory to the long-term clinical management of patients at a high risk of developing recurrence.

Proposing a novel molecular subtyping scheme for predicting distant recurrence-free survival in breast cancer post-neoadjuvant chemotherapy with close correlation to metabolism and senescence

Background

High relapse rates remain a clinical challenge in the management of breast cancer (BC), with distant recurrence being a major driver of patient deterioration. To optimize the surveillance regimen for distant recurrence after neoadjuvant chemotherapy (NAC), we conducted a comprehensive analysis using bioinformatics and machine learning approaches.

Materials and methods

Microarray data were retrieved from the GEO database, and differential expression analysis was performed with the R package 'Limma'. We used the Metascape tool for enrichment analyses, and 'WGCNA' was utilized to establish co-expression networks, selecting the soft threshold power with the 'pickSoftThreshold' algorithm. We integrated ten machine learning algorithms and 101 algorithm combinations to identify key genes associated with distant recurrence in BC. Unsupervised clustering was performed with the R package 'ConsensusCluster Plus'. To further screen the key gene signature of residual cancer burden (RCB), multiple knockdown studies were analyzed with the Genetic Perturbation Similarity Analysis (GPSA) database. Single-cell RNA sequencing (scRNA-seq) analysis was conducted through the Tumour Immune Single-cell Hub (TISCH) database, and the XSum algorithm was used to screen candidate small molecule drugs based on the Connectivity Map (CMAP) database. Molecular docking processes were conducted using Schrodinger software. GMT files containing gene sets associated with metabolism and senescence were obtained from GSEA MutSigDB database. The GSVA score for each gene set across diverse samples was computed using the ssGSEA function implemented in the GSVA package.

Results

Our analysis, which combined Limma, WGCNA, and machine learning approaches, identified 16 RCB-relevant gene signatures influencing distant recurrence-free survival (DRFS) in BC patients following NAC. We then screened GATA3 as the key gene signature of high RCB index using GPSA analysis. A novel molecular subtyping scheme was developed to divide patients into two clusters (C1 and C2) with different distant recurrence risks. This molecular subtyping scheme was found to be closely associated with tumor metabolism and cellular senescence. Patients in cluster C2 had a poorer DRFS than those in cluster C1 (HR: 4.04; 95% CI: 2.60-6.29; log-rank test p < 0.0001). High GATA3 expression, high levels of resting mast cell infiltration, and a high proportion of estrogen receptor (ER)-positive patients contributed to better DRFS in cluster C1. We established a nomogram based on the N stage, RCB class, and molecular subtyping. The ROC curve for 5-year DRFS showed excellent predictive value (AUC=0.91, 95% CI: 0.95-0.86), with a C-index of 0.85 (95% CI: 0.81-0.90). Entinostat was identified as a potential small molecule compound to reverse high RCB after NAC. We also provided a comprehensive review of the EDCs exposures that potentially impact the effectiveness of NAC among BC patients.

Conclusion

This study established a molecular classification scheme associated with tumor metabolism and cancer cell senescence to predict RCB and DRFS in BC patients after NAC. Furthermore, GATA3 was identified and validated as a key gene associated with BC recurrence.

Beyond Neoantigens: Antigens Derived from Tumor Drivers as Cancer Vaccine Targets

A vaccine targeting HER2, a nonmutated but overexpressed tumor antigen, readily primed T cells for ex vivo expansion and adoptive transfer with minimal toxicity. This regimen led to intramolecular epitope spreading in a majority of patients and offers a treatment modality that may improve outcomes for patients with metastatic breast cancer expressing HER2. See related article by Disis et al., p. 3362.

Experimental and spontaneous metastasis assays can result in divergence in clonal architecture

Intratumoural heterogeneity is associated with poor outcomes in breast cancer. To understand how malignant clones survive and grow in metastatic niches, in vivo models using cell lines and patient-derived xenografts (PDX) have become the gold standard. Injections of cancer cells in orthotopic sites (spontaneous metastasis assays) or into the vasculature (experimental metastasis assays) have been used interchangeably to study the metastatic cascade from early events or post-intravasation, respectively. However, less is known about how these different routes of injection impact heterogeneity. Herein we directly compared the clonality of spontaneous and experimental metastatic assays using the human cell line MDA-MB-231 and a PDX model. Genetic barcoding was used to study the fitness of the subclones in primary and metastatic sites. Using spontaneous assays, we found that intraductal injections resulted in less diverse tumours compared to other routes of injections. Using experimental metastasis assays via tail vein injection of barcoded MDA-MB-231 cells, we also observed an asymmetry in metastatic heterogeneity between lung and liver that was not observed using spontaneous metastasis assays. These results demonstrate that these assays can result in divergent clonal outputs in terms of metastatic heterogeneity and provide a better understanding of the biases inherent to each technique.

Implications of tumour heterogeneity on cancer evolution and therapy resistance: lessons from breast cancer

Tumour heterogeneity is pervasive amongst many cancers and leads to disease progression, and therapy resistance. In this review, using breast cancer as an exemplar, we focus on the recent advances in understanding the interplay between tumour cells and their microenvironment using single cell sequencing and digital spatial profiling technologies. Further, we discuss the utility of lineage tracing methodologies in pre-clinical models of breast cancer, and how these are being used to unravel new therapeutic vulnerabilities and reveal biomarkers of breast cancer progression. © 2023 The Pathological Society of Great Britain and Ireland.

Establishment and Molecular Characterization of an In Vitro Model for PARPi-Resistant Ovarian Cancer

Overcoming PARPi resistance is a high clinical priority. We established and characterized comparative in vitro models of acquired PARPi resistance, derived from either a BRCA1-proficient or BRCA1-deficient isogenic background by long-term exposure to olaparib. While parental cell lines already exhibited a certain level of intrinsic activity of multidrug resistance (MDR) proteins, resulting PARPi-resistant cells from both models further converted toward MDR. In both models, the PARPi-resistant phenotype was shaped by (i) cross-resistance to other PARPis (ii) impaired susceptibility toward the formation of DNA-platinum adducts upon exposure to cisplatin, which could be reverted by the drug efflux inhibitors verapamil or diphenhydramine, and (iii) reduced PARP-trapping activity. However, the signature and activity of ABC-transporter expression and the cross-resistance spectra to other chemotherapeutic drugs considerably diverged between the BRCA1-proficient vs. BRCA1-deficient models. Using dual-fluorescence co-culture experiments, we observed that PARPi-resistant cells had a competitive disadvantage over PARPi-sensitive cells in a drug-free medium. However, they rapidly gained clonal dominance under olaparib selection pressure, which could be mitigated by the MRP1 inhibitor MK-751. Conclusively, we present a well-characterized in vitro model, which could be instrumental in dissecting mechanisms of PARPi resistance from HR-proficient vs. HR-deficient background and in studying clonal dynamics of PARPi-resistant cells in response to experimental drugs, such as novel olaparib-sensitizers.

Cellular barcoding tracks heterogeneous clones through selective pressures and phenotypic transitions

Genomic DNA barcoding has emerged as a sensitive and flexible tool to measure the fates of clonal subpopulations within a heterogeneous cancer cell population. Coupling cellular barcoding with single-cell transcriptomics permits the longitudinal analysis of molecular mechanisms with detailed clone-level resolution. Numerous recent studies have employed these tools to track clonal cell states in cancer progression and treatment response. With these new technologies comes the opportunity to examine longstanding questions about the origins and contributions of tumor cell heterogeneity and the roles of selection and phenotypic plasticity in disease progression and treatment.

Primary refractory plasmablastic lymphoma: A precision oncology approach

Introduction

Hematologic malignancies are currently underrepresented in multidisciplinary molecular-tumor-boards (MTB). This study assesses the potential of precision-oncology in primary-refractory plasmablastic-lymphoma (prPBL), a highly lethal blood cancer.

Methods

We evaluated clinicopathological and molecular-genetic data of 14 clinically annotated prPBL-patients from initial diagnosis. For this proof-of-concept study, we employed our certified institutional MTB-pipeline (University-Cancer-Center-Schleswig-Holstein, UCCSH) to annotate a comprehensive dataset within the scope of a virtual MTB-setting, ultimately recommending molecularly stratified therapies. Evidence-levels for MTB-recommendations were defined in accordance with the NCT/DKTK and ESCAT criteria.

Results

Median age in the cohort was 76.5 years (range 56-91), 78.6% of patients were male, 50% were HIV-positive and clinical outcome was dismal. Comprehensive genomic/transcriptomic analysis revealed potential recommendations of a molecularly stratified treatment option with evidence-levels according to NCT/DKTK of at least m2B/ESCAT of at least IIIA were detected for all 14 prPBL-cases. In addition, immunohistochemical-assessment (CD19/CD30/CD38/CD79B) revealed targeted treatment-recommendations in all 14 cases. Genetic alterations were classified by treatment-baskets proposed by Horak et al. Hereby, we identified tyrosine-kinases (TK; n=4), PI3K-MTOR-AKT-pathway (PAM; n=3), cell-cycle-alterations (CC; n=2), RAF-MEK-ERK-cascade (RME; n=2), immune-evasion (IE; n=2), B-cell-targets (BCT; n=25) and others (OTH; n=4) for targeted treatment-recommendations. The minimum requirement for consideration of a drug within the scope of the study was FDA-fast-track development.

Discussion

The presented proof-of-concept study demonstrates the clinical potential of precision-oncology, even in prPBL-patients. Due to the aggressive course of the disease, there is an urgent medical-need for personalized treatment approaches, and this population should be considered for MTB inclusion at the earliest time.

Alterations of Cytoskeleton Networks in Cell Fate Determination and Cancer Development

Cytoskeleton proteins have been long recognized as structural proteins that provide the necessary mechanical architecture for cell development and tissue homeostasis. With the completion of the cancer genome project, scientists were surprised to learn that huge numbers of mutated genes are annotated as cytoskeletal or associated proteins. Although most of these mutations are considered as passenger mutations during cancer development and evolution, some genes show high mutation rates that can even determine clinical outcomes. In addition, (phospho)proteomics study confirms that many cytoskeleton-associated proteins, e.g., β-catenin, PIK3CA, and MB21D2, are important signaling mediators, further suggesting their biofunctional roles in cancer development. With emerging evidence to indicate the involvement of mechanotransduction in stemness formation and cell differentiation, mutations in these key cytoskeleton components may change the physical/mechanical properties of the cells and determine the cell fate during cancer development. In particular, tumor microenvironment remodeling triggered by such alterations has been known to play important roles in autophagy, metabolism, cancer dormancy, and immune evasion. In this review paper, we will highlight the current understanding of how aberrant cytoskeleton networks affect cancer behaviors and cellular functions through mechanotransduction.

Cell-cell interactions that drive tumorigenesis in Drosophila

Cell-cell interactions within tumour microenvironment play crucial roles in tumorigenesis. Genetic mosaic techniques available in Drosophila have provided a powerful platform to study the basic principles of tumour growth and progression via cell-cell communications. This led to the identification of oncogenic cell-cell interactions triggered by endocytic dysregulation, mitochondrial dysfunction, cell polarity defects, or Src activation in Drosophila imaginal epithelia. Such oncogenic cooperations can be caused by interactions among epithelial cells, mesenchymal cells, and immune cells. Moreover, microenvironmental factors such as nutrients, local tissue structures, and endogenous growth signalling activities critically affect tumorigenesis. Dissecting various types of oncogenic cell-cell interactions at the single-cell level in Drosophila will greatly increase our understanding of how tumours progress in living animals.

Learning to distinguish progressive and non-progressive ductal carcinoma in situ

Ductal carcinoma in situ (DCIS) is a non-invasive breast neoplasia that accounts for 25% of all screen-detected breast cancers diagnosed annually. Neoplastic cells in DCIS are confined to the ductal system of the breast, although they can escape and progress to invasive breast cancer in a subset of patients. A key concern of DCIS is overtreatment, as most patients screened for DCIS and in whom DCIS is diagnosed will not go on to exhibit symptoms or die of breast cancer, even if left untreated. However, differentiating low-risk, indolent DCIS from potentially progressive DCIS remains challenging. In this Review, we summarize our current knowledge of DCIS and explore open questions about the basic biology of DCIS, including those regarding how genomic events in neoplastic cells and the surrounding microenvironment contribute to the progression of DCIS to invasive breast cancer. Further, we discuss what information will be needed to prevent overtreatment of indolent DCIS lesions without compromising adequate treatment for high-risk patients.

Mastering the use of cellular barcoding to explore cancer heterogeneity

Tumours are often composed of a multitude of malignant clones that are genomically unique, and only a few of them may have the ability to escape cancer therapy and grow as symptomatic lesions. As a result, tumours with a large degree of genomic diversity have a higher chance of leading to patient death. However, clonal fate can be driven by non-genomic features. In this context, new technologies are emerging not only to track the spatiotemporal fate of individual cells and their progeny but also to study their molecular features using various omics analysis. In particular, the recent development of cellular barcoding facilitates the labelling of tens to millions of cancer clones and enables the identification of the complex mechanisms associated with clonal fate in different microenvironments and in response to therapy. In this Review, we highlight the recent discoveries made using lentiviral-based cellular barcoding techniques, namely genetic and optical barcoding. We also emphasize the strengths and limitations of each of these technologies and discuss some of the key concepts that must be taken into consideration when one is designing barcoding experiments. Finally, we suggest new directions to further improve the use of these technologies in cancer research.

Single-cell spatial architectures associated with clinical outcome in head and neck squamous cell carcinoma

There is increasing evidence that the spatial organization of cells within the tumor-immune microenvironment (TiME) of solid tumors influences survival and response to therapy in numerous cancer types. Here, we report results and demonstrate the applicability of quantitative single-cell spatial proteomics analyses in the TiME of primary and recurrent human papillomavirus (HPV)-negative head and neck squamous cell carcinoma (HNSCC) tumors. Single-cell compositions of a nine patient, primary and recurrent (n = 18), HNSCC cohort is presented, followed by deeper investigation into the spatial architecture of the TiME and its relationship with clinical variables and progression free survival (PFS). Multiple spatial algorithms were used to quantify the spatial landscapes of immune cells within TiMEs and demonstrate that neoplastic tumor-immune cell spatial compartmentalization, rather than mixing, is associated with longer PFS. Mesenchymal (αSMA⁺) cellular neighborhoods describe distinct immune landscapes associated with neoplastic tumor-immune compartmentalization and improved patient outcomes. Results from this investigation are concordant with studies in other tumor types, suggesting that trends in TiME cellular heterogeneity and spatial organization may be shared across cancers and may provide prognostic value in multiple cancer types.

Genetic Determinants of Somatic Selection of Mutational Processes in 3,566 Human Cancers

The somatic landscape of the cancer genome results from different mutational processes represented by distinct "mutational signatures." Although several mutagenic mechanisms are known to cause specific mutational signatures in cell lines, the variation of somatic mutational activities in patients, which is mostly attributed to somatic selection, is still poorly explained. Here, we introduce a quantitative trait, mutational propensity (MP), and describe an integrated method to infer genetic determinants of variations in the mutational processes in 3,566 cancers with specific underlying mechanisms. As a result, we report 2,314 candidate determinants with both significant germline and somatic effects on somatic selection of mutational processes, of which, 485 act via cancer gene expression and 1,427 act through the tumor-immune microenvironment. These data demonstrate that the genetic determinants of MPs provide complementary information to known cancer driver genes, clonal evolution, and clinical biomarkers. SIGNIFICANCE: The genetic determinants of the somatic mutational processes in cancer elucidate the biology underlying somatic selection and evolution of cancers and demonstrate complementary predictive power across cancer types.

Context-dependent effects of whole-genome duplication during mammary tumor recurrence

Whole-genome duplication (WGD) generates polyploid cells possessing more than two copies of the genome and is among the most common genetic abnormalities in cancer. The frequency of WGD increases in advanced and metastatic tumors, and WGD is associated with poor prognosis in diverse tumor types, suggesting a functional role for polyploidy in tumor progression. Experimental evidence suggests that polyploidy has both tumor-promoting and suppressing effects, but how polyploidy regulates tumor progression remains unclear. Using a genetically engineered mouse model of Her2-driven breast cancer, we explored the prevalence and consequences of whole-genome duplication during tumor growth and recurrence. While primary tumors in this model are invariably diploid, nearly 40% of recurrent tumors undergo WGD. WGD in recurrent tumors was associated with increased chromosomal instability, decreased proliferation and increased survival in stress conditions. The effects of WGD on tumor growth were dependent on tumor stage. Surprisingly, in recurrent tumor cells WGD slowed tumor formation, growth rate and opposed the process of recurrence, while WGD promoted the growth of primary tumors. These findings highlight the importance of identifying conditions that promote the growth of polyploid tumors, including the cooperating genetic mutations that allow cells to overcome the barriers to WGD tumor cell growth and proliferation.

Slow-cycling (dormant) cancer cells in therapy resistance, cancer relapse and metastasis

It is increasingly appreciated that cancer cell heterogeneity and plasticity constitute major barriers to effective clinical treatments and long-term therapeutic efficacy. Research in the past two decades suggest that virtually all treatment-naive human cancers harbor subsets of cancer cells that possess many of the cardinal features of normal stem cells. Such stem-like cancer cells, operationally defined as cancer stem cells (CSCs), are frequently quiescent and dynamically change and evolve during tumor progression and therapeutic interventions. Intrinsic tumor cell heterogeneity is reflected in a different aspect in that tumors also harbor a population of slow-cycling cells (SCCs) that are not in the proliferative cell cycle and thus are intrinsically refractory to anti-mitotic drugs. In this Perspective, we focus our discussions on SCCs in cancer and on various methodologies that can be employed to enrich and purify SCCs, compare the similarities and differences between SCCs, CSCs and cancer cells undergoing EMT, and present evidence for the involvement of SCCs in surviving anti-neoplastic treatments, mediating tumor relapse, maintaining tumor dormancy and mediating metastatic dissemination. Our discussions make it clear that an in-depth understanding of the biological properties of SCCs in cancer will be instrumental to developing new therapeutic strategies to prevent tumor relapse and distant metastasis.

Patient-Derived Tumor Organoids for Drug Repositioning in Cancer Care: A Promising Approach in the Era of Tailored Treatment

Simple Summary

Currently, organoid research is having a growing impact in oncology. Tumor organoids, directly derived from patients’ specimens, can easily be expanded and cryopreserved. For that reason, they are becoming an indispensable ally in clinics for quicker diagnosis and prognosis of malignancies. Patient-derived cancer organoids are used as a platform to predict the efficacy of standard-of-care, as well as novel drugs. Therefore, this approach might be further utilized for validating off-label molecules, in order to widen the cancer care offer.

Abstract

Malignancies heterogeneity represents a critical issue in cancer care, as it often causes therapy resistance and tumor relapse. Organoids are three-dimensional (3D) miniaturized representations of selected tissues within a dish. Lately, organoid technology has been applied to oncology with growing success and Patients Derived Tumor Organoids (PDTOs) constitute a novel available tool which fastens cancer research. PDTOs are in vitro models of cancer, and importantly, they can be used as a platform to validate the efficacy of anti-cancer drugs. For that reason, they are currently utilized in clinics as emerging in vitro screening technology to tailor the therapy around the patient, with the final goal of beating cancer resistance and recurrence. In this sense, PDTOs biobanking is widely used and PDTO-libraries are helping the discovery of novel anticancer molecules. Moreover, they represent a good model to screen and validate compounds employed for other pathologies as off-label drugs potentially repurposed for the treatment of tumors. This will open up novel avenues of care thus ameliorating the life expectancy of cancer patients. This review discusses the present advancements in organoids research applied to oncology, with special attention to PDTOs and their translational potential, especially for anti-cancer drug testing, including off-label molecules.