Tumour heterogeneity and the evolution of polyclonal drug resistance

Subcellular progression of mesenchymal transition identified by two discrete synchronous cell lines derived from the same glioblastoma

Glioblastomas (GBM) exhibit intratumoral heterogeneity of various oncogenic evolutional processes. We have successfully isolated and established two distinct cancer cell lines with different morphological and biological characteristics that were derived from the same tissue sample of a GBM. When we compared their genomic and transcriptomic characteristics, each cell line harbored distinct mutation clusters while sharing core driver mutations. Transcriptomic analysis revealed that one cell line was undergoing a mesenchymal transition process, unlike the other cell line. Furthermore, we could identify four tumor samples containing our cell line-like clusters from the publicly available single-cell RNA-seq data, and in a set of paired longitudinal GBM samples, we could confirm three pairs where the recurrent sample was enriched in the genes specific to our cell line undergoing mesenchymal transition. The present study provides direct evidence and a valuable source for investigating the ongoing process of subcellular mesenchymal transition in GBM, which has prognostic and therapeutic implications.

Dynamics of RAS/BRAF Mutations in cfDNA from Metastatic Colorectal Carcinoma Patients Treated with Polychemotherapy and Anti-EGFR Monoclonal Antibodies

Analysis of plasma-derived cell-free DNA (cfDNA) might allow for the early identification of resistance in metastatic colorectal carcinoma (mCRC) patients receiving anti-EGFR monoclonal antibodies. We tested plasma samples from the Erbitux Metastatic Colorectal Cancer Strategy (ERMES) phase III trial of FOLFIRI+Cetuximab in first-line treatment of RAS/BRAF wild-type mCRC. Samples were collected at baseline (n = 37), at 8 weeks of treatment (n = 32), progressive disease (PD; n = 36) and 3 months after PD (n = 21). cfDNA testing was performed using the Idylla™ ctKRAS and ctNRAS-BRAF tests and the Oncomine Pan-Cancer Cell-Free Assay. Analysis of basal samples revealed RAS/BRAF mutations in 6/37 cases. A transient RAS positivity not associated with PD was observed at 8 weeks in five cases that showed no mutations at baseline and PD. The frequency of mutant cases increased at PD (33.3%) and decreased again at 3 months after PD (9.5%). The median progression-free survival (mPFS) of patients RAS/BRAF mutant at PD was 7.13 months versus 7.71 months in wild-type patients (p = 0.3892). These data confirm that the occurrence of RAS/BRAF mutations in mCRC patients receiving anti-EGFR agents is relatively frequent. However, the cfDNA dynamics of RAS mutations in patients treated with anti-EGFR agents plus polychemotherapy are complex and might not be directly associated with resistance to treatment.

Options to Improve the Action of PROTACs in Cancer: Development of Controlled Delivery Nanoparticles

Classical targeting in cancer focuses on the development of chemical structures able to bind to protein pockets with enzymatic activity. Some of these molecules are designed to bind the ATP side of the kinase domain avoiding protein activation and the subsequent oncogenic activity. A further improvement of these agents relies on the generation of non-allosteric inhibitors that once bound are able to limit the kinase function by producing a conformational change at the protein and, therefore, augmenting the antitumoural potency. Unfortunately, not all oncogenic proteins have enzymatic activity and cannot be chemically targeted with these types of molecular entities. Very recently, exploiting the protein degradation pathway through the ubiquitination and subsequent proteasomal degradation of key target proteins has gained momentum. With this approach, non-enzymatic proteins such as Transcription Factors can be degraded. In this regard, we provide an overview of current applications of the PROteolysis TArgeting Chimeras (PROTACs) compounds for the treatment of solid tumours and ways to overcome their limitations for clinical development. Among the different constraints for their development, improvements in bioavailability and safety, due to an optimized delivery, seem to be relevant. In this context, it is anticipated that those targeting pan-essential genes will have a narrow therapeutic index. In this article, we review the advantages and disadvantages of the potential use of drug delivery systems to improve the activity and safety of PROTACs.

Stability of scRNA-Seq Analysis Workflows is Susceptible to Preprocessing and is Mitigated by Regularized or Supervised Approaches

Background:

Statistical methods developed to address various questions in single-cell datasets show increased variability to different parameter regimes. In order to delineate further the robustness of commonly utilized methods for single-cell RNA-Seq, we aimed to comprehensively review scRNA-Seq analysis workflows in the setting of dimension reduction, clustering, and trajectory inference.

Methods:

We utilized datasets with temporal single-cell transcriptomics profiles from public repositories. Combining multiple methods at each level of the workflow, we have performed over 6 k analysis and evaluated the results of clustering and pseudotime estimation using adjusted rand index and rank correlation metrics. We have further integrated neural network methods to assess whether models with increased complexity can show increased bias/variance trade-off.

Results:

Combinatorial workflows showed that utilizing non-linear dimension reduction techniques such as t-SNE and UMAP are sensitive to initial preprocessing steps hence clustering results on dimension reduced space of single-cell datasets should be utilized carefully. Similarly, pseudotime estimation methods that depend on previous non-linear dimension reduction steps can result in highly variable trajectories. In contrast, methods that avoid non-linearity such as WOT can result in repeatable inferences of temporal gene expression dynamics. Furthermore, imputation methods do not improve clustering or trajectory inference results substantially in terms of repeatability. In contrast, the selection of the normalization method shows an increased effect on downstream analysis where ScTransform reduces variability overall.

Identification of Pan-Cancer Biomarkers Based on the Gene Expression Profiles of Cancer Cell Lines

There are many types of cancers. Although they share some hallmarks, such as proliferation and metastasis, they are still very different from many perspectives. They grow on different organ or tissues. Does each cancer have a unique gene expression pattern that makes it different from other cancer types? After the Cancer Genome Atlas (TCGA) project, there are more and more pan-cancer studies. Researchers want to get robust gene expression signature from pan-cancer patients. But there is large variance in cancer patients due to heterogeneity. To get robust results, the sample size will be too large to recruit. In this study, we tried another approach to get robust pan-cancer biomarkers by using the cell line data to reduce the variance. We applied several advanced computational methods to analyze the Cancer Cell Line Encyclopedia (CCLE) gene expression profiles which included 988 cell lines from 20 cancer types. Two feature selection methods, including Boruta, and max-relevance and min-redundancy methods, were applied to the cell line gene expression data one by one, generating a feature list. Such list was fed into incremental feature selection method, incorporating one classification algorithm, to extract biomarkers, construct optimal classifiers and decision rules. The optimal classifiers provided good performance, which can be useful tools to identify cell lines from different cancer types, whereas the biomarkers (e.g. NCKAP1, TNFRSF12A, LAMB2, FKBP9, PFN2, TOM1L1) and rules identified in this work may provide a meaningful and precise reference for differentiating multiple types of cancer and contribute to the personalized treatment of tumors.

NTRK point mutations and their functional consequences

The neurotrophic receptor tyrosine kinase (NTRK) family of genes, including NTRK1, NTRK2, and NTRK3, encodes membrane-bound receptors that normally regulate cell survival and differentiation upon binding of growth factors. Not surprisingly, mutations in these genes are known to contribute to the growth of a diverse number of cancers. With the recent FDA approval of two first-generation tyrosine-kinase inhibitors (TKIs) for adult and pediatric patients with solid tumors harboring NTRK gene fusions, much of the literature has focused on the biology behind these types of NTRK abnormalities; however, point mutations can also contribute to oncogenesis or resistance to TKI therapy, albeit at a lower frequency than fusions. This review focuses on NTRK gene mutations that are associated with resistance to directed therapies, mutations detected in the primary setting that confer increased oncogenic activity, and evidence that suggests that some of these variants may be treated using specific targeted therapies. Finally, this review focuses on the detection of point mutations, including the utility of cell-free DNA (cfDNA) for monitoring the acquisition of resistance mutations.

Intratumor heterogeneity and clonal evolution revealed in castration-resistant prostate cancer by longitudinal genomic analysis

Intratumor heterogeneity is a key driver for local relapse and treatment failure. Thus, using multifocal prostate cancer as a model to investigate tumor inter-clonal relationships and tumor evolution could aid in our understanding of drug resistance. Previous studies discovered genomic alterations by comparing hormone-sensitive prostate cancer (HSPC) with castration-resistant prostate cancer (CRPC) in large cohorts. However, most studies did not sequentially sample tumors from the same patient. In our study, we performed whole-exome sequencing (WES) on 14 specimens from five locally relapsed patients before and after androgen-deprivation therapy. We described the landscape of genomic alterations before and after treatment and identified critical driver events that could have contributed to the evolution of CRPC. In addition to confirming known cancer genes such as TP53 and CDK12, we also identified new candidate genes that may play a role in the progression of prostate cancer, including MYO15A, CHD6 and LZTR1. At copy number alteration (CNA) level, gain of 8q24.13-8q24.3 was observed in 60% of patients and was the most commonly altered locus in both HSPC and CRPC tumors. Finally, utilizing phylogenetic reconstruction, we explored the clonal progression pattern from HSPC to CRPC in each patient. Our findings highlight the complex and heterogeneous mechanisms underlying the development of drug resistance, and underscore the potential value of monitoring tumor clonal architectures during disease progression in a clinical setting.

Drug combination screening as a translational approach toward an improved drug therapy for chordoma

PURPOSE

Drug screening programmes have revealed epidermal growth factor receptor inhibitors (EGFRis) as promising therapeutics for chordoma, an orphan malignant bone tumour, in the absence of a known genetic driver. Concurrently, the irreversible EGFRi afatinib (Giotrif®) is being evaluated in a multicentric Phase II trial. As tyrosine kinase inhibitor (TKI) monotherapies are invariably followed by resistance, we aimed to evaluate potential therapeutic combinations with EGFRis.

METHODS

We screened 133 clinically approved anticancer drugs as single agents and in combination with two EGFRis (afatinib and erlotinib) in the clival chordoma cell line UM-Chor1. Synergistic combinations were analysed in a 7 × 7 matrix format. The most promising combination was further explored in clival (UM-Chor1, MUG-CC1) and sacral (MUG-Chor1, U-CH1) chordoma cell lines. Secretomes were analysed for receptor tyrosine kinase ligands (EGF, TGF-α, FGF-2 and VEGF-A) upon drug treatment.

RESULTS

Drugs that were active as single agents (n = 45) included TKIs, HDAC and proteasome inhibitors, and cytostatic drugs. Six combinations were analysed in a matrix format: n = 4 resulted in a significantly increased cell killing (crizotinib, dabrafenib, panobinostat and doxorubicin), and n = 2 exhibited no or negligible effects (regorafenib, venetoclax). Clival chordoma cell lines were more responsive to combined EGFR-MET inhibition. EGFR-MET cross-talk (e.g. via TGF-α secretion) likely accounts for the synergistic effects of EGFR-MET inhibition.

CONCLUSION

Our screen revealed promising combinations with EGFRis, such as the ALK/MET-inhibitor crizotinib, the HDAC-inhibitor panobinostat or the topoisomerase-II-inhibitor doxorubicin, which are part of standard chemotherapy regimens for various bone and soft-tissue sarcomas.

Identification and Validation of a Malignant Cell Subset Marker-Based Polygenic Risk Score in Stomach Adenocarcinoma Through Integrated Analysis of Bulk and Single-Cell RNA Sequencing Data

Objectives: The aim of the present study was to construct a polygenic risk score (PRS) for poor survival among patients with stomach adenocarcinoma (STAD) based on expression of malignant cell markers. Methods: Integrated analyses of bulk and single-cell RNA sequencing (scRNA-seq) of STAD and normal stomach tissues were conducted to identify malignant and non-malignant markers. Analyses of the scRNA-seq profile from early STAD were used to explore intratumoral heterogeneity (ITH) of the malignant cell subpopulations. Dimension reduction, cell clustering, pseudotime, and gene set enrichment analyses were performed. The marker genes of each malignant tissue and cell clusters were screened to create a PRS using Cox regression analyses. Combined with the PRS and routine clinicopathological characteristics, a nomogram tool was generated to predict prognosis of patients with STAD. The prognostic power of the PRS was validated in two independent external datasets. Results: The malignant and non-malignant cells were identified according to 50 malignant and non-malignant cell markers. The malignant cells were divided into nine clusters with different marker genes and biological characteristics. Pseudotime analysis showed the potential differentiation trajectory of these nine malignant cell clusters and identified genes that affect cell differentiation. Ten malignant cell markers were selected to generate a PRS: RGS1, AADAC, NPC2, COL10A1, PRKCSH, RAMP1, PRR15L, TUBA1A, CXCR6, and UPP1. The PRS was associated with both overall and progression-free survival (PFS) and proved to be a prognostic factor independent of routine clinicopathological characteristics. PRS could successfully divide patients with STAD in three datasets into high- or low-risk groups. In addition, we combined PRS and the tumor clinicopathological characteristics into a nomogram tool to help predict the survival of patients with STAD. Conclusion: We revealed limited but significant intratumoral heterogeneity in STAD and proposed a malignant cell subset marker-based PRS through integrated analysis of bulk sequencing and scRNA-seq data.

Microfluidic Single-Cell Proteomics Assay Chip: Lung Cancer Cell Line Case Study

Cancer is a dynamic disease involving constant changes. With these changes, cancer cells become heterogeneous, resulting in varying sensitivity to chemotherapy. The heterogeneity of cancer cells plays a key role in chemotherapy resistance and cancer recurrence. Therefore, for effective treatment, cancer cells need to be analyzed at the single-cell level by monitoring various proteins and investigating their heterogeneity. We propose a microfluidic chip for a single-cell proteomics assay that is capable of analyzing complex cellular signaling systems to reveal the heterogeneity of cancer cells. The single-cell assay chip comprises (i) microchambers (n = 1376) for manipulating single cancer cells, (ii) micropumps for rapid single-cell lysis, and (iii) barcode immunosensors for detecting nine different secretory and intracellular proteins to reveal the correlation among cancer-related proteins. Using this chip, the single-cell proteomics of a lung cancer cell line, which may be easily masked in bulk analysis, were evaluated. By comparing changes in the level of protein secretion and heterogeneity in response to combinations of four anti-cancer drugs, this study suggests a new method for selecting the best combination of anti-cancer drugs. Subsequent preclinical and clinical trials should enable this platform to become applicable for patient-customized therapies.

Cancer evolution: Darwin and beyond

Clinical and laboratory studies over recent decades have established branched evolution as a feature of cancer. However, while grounded in somatic selection, several lines of evidence suggest a Darwinian model alone is insufficient to fully explain cancer evolution. First, the role of macroevolutionary events in tumour initiation and progression contradicts Darwin's central thesis of gradualism. Whole-genome doubling, chromosomal chromoplexy and chromothripsis represent examples of single catastrophic events which can drive tumour evolution. Second, neutral evolution can play a role in some tumours, indicating that selection is not always driving evolution. Third, increasing appreciation of the role of the ageing soma has led to recent generalised theories of age-dependent carcinogenesis. Here, we review these concepts and others, which collectively argue for a model of cancer evolution which extends beyond Darwin. We also highlight clinical opportunities which can be grasped through targeting cancer vulnerabilities arising from non-Darwinian patterns of evolution.

Conifer: clonal tree inference for tumor heterogeneity with single-cell and bulk sequencing data

BACKGROUND

Genetic heterogeneity of a cancer tumor that develops during clonal evolution is one of the reasons for cancer treatment failure, by increasing the chance of drug resistance. Clones are cell populations with different genotypes, resulting from differences in somatic mutations that occur and accumulate during cancer development. An appropriate approach for identifying clones is determining the variant allele frequency of mutations that occurred in the tumor. Although bulk sequencing data can be used to provide that information, the frequencies are not informative enough for identifying different clones with the same prevalence and their evolutionary relationships. On the other hand, single-cell sequencing data provides valuable information about branching events in the evolution of a cancerous tumor. However, the temporal order of mutations may be determined with ambiguities using only single-cell data, while variant allele frequencies from bulk sequencing data can provide beneficial information for inferring the temporal order of mutations with fewer ambiguities.

RESULT

In this study, a new method called Conifer (ClONal tree Inference For hEterogeneity of tumoR) is proposed which combines aggregated variant allele frequency from bulk sequencing data with branching event information from single-cell sequencing data to more accurately identify clones and their evolutionary relationships. It is proven that the accuracy of clone identification and clonal tree inference is increased by using Conifer compared to other existing methods on various sets of simulated data. In addition, it is discussed that the evolutionary tree provided by Conifer on real cancer data sets is highly consistent with information in both bulk and single-cell data.

CONCLUSIONS

In this study, we have provided an accurate and robust method to identify clones of tumor heterogeneity and their evolutionary history by combining single-cell and bulk sequencing data.

Clonal Evolution of Multiple Myeloma-Clinical and Diagnostic Implications

Plasma cell dyscrasias are a heterogeneous group of diseases characterized by the expansion of bone marrow plasma cells. Malignant transformation of plasma cells depends on the continuity of events resulting in a sequence of well-defined disease stages, from monoclonal gammopathy of undetermined significance (MGUS) through smoldering myeloma (SMM) to symptomatic multiple myeloma (MM). Evolution of a pre-malignant cell into a malignant cell, as well as further tumor progression, dissemination, and relapse, require development of multiple driver lesions conferring selective advantage of the dominant clone and allowing subsequent evolution under selective pressure of microenvironment and treatment. This process of natural selection facilitates tumor plasticity leading to the formation of genetically complex and heterogenous tumors that are notoriously difficult to treat. Better understanding of the mechanisms underlying tumor evolution in MM and identification of lesions driving the evolution from the premalignant clone is therefore a key to development of effective treatment and long-term disease control. Here, we review recent advances in clonal evolution patterns and genomic landscape dynamics of MM, focusing on their clinical implications.

Effect of high variation in transcript expression on identifying differentially expressed genes in RNA-seq analysis

Great efforts have been made on the algorithms that deal with RNA-seq data to enhance the accuracy and efficiency of differential expression (DE) analysis. However, no consensus has been reached on the proper threshold values of fold change and adjusted p-value for filtering differentially expressed genes (DEGs). It is generally believed that the more stringent the filtering threshold, the more reliable the result of a DE analysis. Nevertheless, by analyzing the impact of both adjusted p-value and fold change thresholds on DE analyses, with RNA-seq data obtained for three different cancer types from the Cancer Genome Atlas (TCGA) database, we found that, for a given sample size, the reproducibility of DE results became poorer when more stringent thresholds were applied. No matter which threshold level was applied, the overlap rates of DEGs were generally lower for small sample sizes than for large sample sizes. The raw read count analysis demonstrated that the transcript expression of the same gene in different samples, whether in tumor groups or in normal groups, showed high variations, which resulted in a drastic fluctuation in fold change values and adjustedp-values when different sets of samples were used. Overall, more stringent thresholds did not yield more reliable DEGs due to high variations in transcript expression; the reliability of DEGs obtained with small sample sizes was more susceptible to these variations. Therefore, less stringent thresholds are recommended for screening DEGs. Moreover, large sample sizes should be considered in RNA-seq experimental designs to reduce the interfering effect of variations in transcript expression on DEG identification.

Cancer recurrence and lethality are enabled by enhanced survival and reversible cell cycle arrest of polyaneuploid cells

We present a unifying theory to explain cancer recurrence, therapeutic resistance, and lethality. The basis of this theory is the formation of simultaneously polyploid and aneuploid cancer cells, polyaneuploid cancer cells (PACCs), that avoid the toxic effects of systemic therapy by entering a state of cell cycle arrest. The theory is independent of which of the classically associated oncogenic mutations have already occurred. PACCs have been generally disregarded as senescent or dying cells. Our theory states that therapeutic resistance is driven by PACC formation that is enabled by accessing a polyploid program that allows an aneuploid cancer cell to double its genomic content, followed by entry into a nondividing cell state to protect DNA integrity and ensure cell survival. Upon removal of stress, e.g., chemotherapy, PACCs undergo depolyploidization and generate resistant progeny that make up the bulk of cancer cells within a tumor.

HDAC Inhibitors: Dissecting Mechanisms of Action to Counter Tumor Heterogeneity

Intra-tumoral heterogeneity presents a major obstacle to cancer therapeutics, including conventional chemotherapy, immunotherapy, and targeted therapies. Stochastic events such as mutations, chromosomal aberrations, and epigenetic dysregulation, as well as micro-environmental selection pressures related to nutrient and oxygen availability, immune infiltration, and immunoediting processes can drive immense phenotypic variability in tumor cells. Here, we discuss how histone deacetylase inhibitors, a prominent class of epigenetic drugs, can be leveraged to counter tumor heterogeneity. We examine their effects on cellular processes that contribute to heterogeneity and provide insights on their mechanisms of action that could assist in the development of future therapeutic approaches.

PhyliCS: a Python library to explore scCNA data and quantify spatial tumor heterogeneity

BACKGROUND

Tumors are composed by a number of cancer cell subpopulations (subclones), characterized by a distinguishable set of mutations. This phenomenon, known as intra-tumor heterogeneity (ITH), may be studied using Copy Number Aberrations (CNAs). Nowadays ITH can be assessed at the highest possible resolution using single-cell DNA (scDNA) sequencing technology. Additionally, single-cell CNA (scCNA) profiles from multiple samples of the same tumor can in principle be exploited to study the spatial distribution of subclones within a tumor mass. However, since the technology required to generate large scDNA sequencing datasets is relatively recent, dedicated analytical approaches are still lacking.

RESULTS

We present PhyliCS, the first tool which exploits scCNA data from multiple samples from the same tumor to estimate whether the different clones of a tumor are well mixed or spatially separated. Starting from the CNA data produced with third party instruments, it computes a score, the Spatial Heterogeneity score, aimed at distinguishing spatially intermixed cell populations from spatially segregated ones. Additionally, it provides functionalities to facilitate scDNA analysis, such as feature selection and dimensionality reduction methods, visualization tools and a flexible clustering module.

CONCLUSIONS

PhyliCS represents a valuable instrument to explore the extent of spatial heterogeneity in multi-regional tumour sampling, exploiting the potential of scCNA data.

Targeting HSF1 as a Therapeutic Strategy for Multiple Mechanisms of EGFR Inhibitor Resistance in EGFR Mutant Non-Small-Cell Lung Cancer

Simple Summary

We attempted to identify target proteins and compounds that can be used to overcome EGFR-TKI resistance in NSCLC. To accomplish this, we generated EGFR inhibitor erlotinib-resistant HCC827-ErlR cells and obtained a list of differentially expressed genes. Then, we performed connectivity map analysis and identified heat shock factor 1 (HSF1) as a potential target protein to overcome erlotinib resistance. Using specific HSF1 shRNAs and KRIBB11 (N²-(1H-Indazol-5-yl)-N⁶-methyl-3-nitropyridine-2,6-diamine), we proved the effectiveness of HSF1 inhibition for overcoming erlotinib resistance in vitro. In addition, we proved the efficacy of emetine in inhibiting HSF1 activity and the tumor growth of erlotinib-resistant PC9-ErlR cells in a mouse model.

Abstract

Although EGFR-TKI treatment of NSCLC (non-small-cell lung cancer) patients often achieves profound initial responses, the efficacy is transient due to acquired resistance. Multiple receptor tyrosine kinase (RTK) pathways contribute to the resistance of NSCLC to first- and third-generation EGFR-TKIs, such as erlotinib and osimertinib. To identify potential targets for overcoming EGFR-TKI resistance, we performed a gene expression signature-based strategy using connectivity map (CMap) analysis. We generated erlotinib-resistant HCC827-ErlR cells, which showed resistance to erlotinib, gefitinib, osimertinib, and doxorubicin. A list of differentially expressed genes (DEGs) in HCC827-ErlR cells was generated and queried using CMap analysis. Analysis of the top 4 compounds from the CMap list suggested HSF1 as a potential target to overcome EGFR-TKI resistance. HSF1 inhibition by using HSF1 shRNAs or KRIBB11 decreased the expression of HSF1 downstream proteins, such as HSP70 and HSP27, and also decreased the expression of HSP90/HSP70/BAG3 client proteins, such as BCL2, MCL1, EGFR, MET, and AXL, causing apoptosis of EGFR-TKI-resistant cancer cells. Finally, we demonstrated the efficacy of the HSF1 inhibitor on PC9-ErlR cells expressing mutant EGFR (T790M) in vivo. Collectively, these findings support a targetable HSF1-(HSP90/HSP70/BAG3)-(BCL2/MCL1/EGFR/MET/AXL) pathway to overcome multiple mechanisms of EGFR-TKI resistance.

The role of local therapy in the treatment of solitary melanoma progression on immune checkpoint inhibition: A multicentre retrospective analysis

INTRODUCTION

In patients with metastatic melanoma, progression of a single tumour lesion (solitary progression) after response to immune checkpoint inhibition (ICI) is increasingly treated with local therapy. We evaluated the role of local therapy for solitary progression in melanoma.

PATIENTS AND METHODS

Patients with metastatic melanoma treated with ICI between 2010 and 2019 with solitary progression as first progressive event were included from 17 centres in 9 countries. Follow-up and survival are reported from ICI initiation.

RESULTS

We identified 294 patients with solitary progression after stable disease in 15%, partial response in 55% and complete response in 30%. The median follow-up was 43 months; the median time to solitary progression was 13 months, and the median time to subsequent progression after treatment of solitary progression (TTSP) was 33 months. The estimated 3-year overall survival (OS) was 79%; median OS was not reached. Treatment consisted of systemic therapy (18%), local therapy (36%), both combined (42%) or active surveillance (4%). In 44% of patients treated for solitary progression, no subsequent progression occurred. For solitary progression during ICI (n = 143), the median TTSP was 29 months. Both TTSP and OS were similar for local therapy, ICI continuation and both combined. For solitary progression post ICI (n = 151), the median TTSP was 35 months. TTSP was higher for ICI recommencement plus local therapy than local therapy or ICI recommencement alone (p = 0.006), without OS differences.

CONCLUSION

Almost half of patients with melanoma treated for solitary progression after initial response to ICI had no subsequent progression. This study suggests that local therapy can benefit patients and is associated with favourable long-term outcomes.

Next-Generation Sequencing with Liquid Biopsies from Treatment-Naïve Non-Small Cell Lung Carcinoma Patients

Recently, the liquid biopsy (LB), a non-invasive and easy to repeat approach, has started to compete with the tissue biopsy (TB) for detection of targets for administration of therapeutic strategies for patients with advanced stages of lung cancer at tumor progression. A LB at diagnosis of late stage non-small cell lung carcinoma (NSCLC) is also being performed. It may be asked if a LB can be complementary (according to the clinical presentation or systematics) or even an alternative to a TB for treatment-naïve advanced NSCLC patients. Nucleic acid analysis with a TB by next-generation sequencing (NGS) is gradually replacing targeted sequencing methods for assessment of genomic alterations in lung cancer patients with tumor progression, but also at baseline. However, LB is still not often used in daily practice for NGS. This review addresses different aspects relating to the use of LB for NGS at diagnosis in advanced NSCLC, including its advantages and limitations.

In-vitro tumor microenvironment models containing physical and biological barriers for modelling multidrug resistance mechanisms and multidrug delivery strategies

The complexity and heterogeneity of the three-dimensional (3D) tumor microenvironment have brought challenges to tumor studies and cancer treatment. The complex functions and interactions of cells involved in tumor microenvironment have led to various multidrug resistance (MDR) and raised challenges for cancer treatment. Traditional tumor models are limited in their ability to simulate the resistance mechanisms and not conducive to the discovery of multidrug resistance and delivery processes. New technologies for making 3D tissue models have shown the potential to simulate the 3D tumor microenvironment and identify mechanisms underlying the MDR. This review overviews the main barriers against multidrug delivery in the tumor microenvironment and highlights the advances in microfluidic-based tumor models with the success in simulating several drug delivery barriers. It also presents the progress in modeling various genetic and epigenetic factors involved in regulating the tumor microenvironment as a noticeable insight in 3D microfluidic tumor models for recognizing multidrug resistance and delivery mechanisms. Further correlation between the results obtained from microfluidic drug resistance tumor models and the clinical MDR data would open up avenues to gain insight into the performance of different multidrug delivery treatment strategies.

Chromosome instability is prevalent and dynamic in high-grade serous ovarian cancer patient samples

OBJECTIVE

High-grade serous ovarian cancer (HGSOC) is the most lethal gynaecological malignancy in women with a high level of mortality, metastatic disease, disease recurrence and multi-drug resistance. Many previous studies have focused on characterising genome instability in recurrent resistant HGSOC and while this has advanced our understanding of HGSOC, our fundamental knowledge of the mechanisms driving genome instability remains limited. Chromosome instability (CIN; an increased rate of chromosome gains and losses) is a form of genome instability that is commonly associated with recurrence and multi-drug resistance in many cancer types but has just begun to be characterised in HGSOC.

METHOD

To examine the relationship between CIN and HGSOC, we employed single-cell quantitative imaging microscopy approaches capable of capturing the cell-to-cell heterogeneity associated with CIN, to assess the prevalence and dynamics of CIN within individual and patient-matched HGSOC ascites and solid tumour samples.

RESULTS

CIN occurs in 90.9% of ascites samples and 100% of solid tumours, while in-depth analyses identified statistically significant temporal dynamics within the serial ascites samples. In general, aneuploidy and CIN increase with disease progression and frequently decrease following chemotherapy treatments in responsive disease. Finally, our work identified higher levels of CIN in solid tumours relative to ascites samples isolated from the same individual, which identifies a novel difference existing between solid tumours and ascites samples.

CONCLUSIONS

Our findings provide novel insight into the relationship between CIN and HGSOC, and uncover a previously unknown relationship existing between CIN in solid tumours and metastatic disease (ascites).

Epigenetic regulation of p62/SQSTM1 overcomes the radioresistance of head and neck cancer cells via autophagy-dependent senescence induction

Tumors are composed of subpopulations of cancer cells with functionally distinct features. Intratumoral heterogeneity limits the therapeutic effectiveness of cancer drugs. To address this issue, it is important to understand the regulatory mechanisms driving a subclonal variety within a therapy-resistant tumor. We identified tumor subclones of HN9 head and neck cancer cells showing distinct responses to radiation with different levels of p62 expression. Genetically identical grounds but epigenetic heterogeneity of the p62 promoter regions revealed that radioresistant HN9-R clones displayed low p62 expression via the creation of repressive chromatin architecture, in which cooperation between DNMT1 (DNA methyltransferases 1) and HDAC1 (histone deacetylases 1) resulted in DNA methylation and repressive H3K9me3 and H3K27me3 marks in the p62 promoter. Combined inhibition of DNMT1 and HDAC1 by genetic depletion or inhibitors enhanced the suppressive effects on proliferative capacity and in vivo tumorigenesis following irradiation. Importantly, ectopically p62-overexpressed HN9-R clones increased the induction of senescence along with p62-dependent autophagy activation. These results demonstrate the heterogeneous expression of p62 as the key component of clonal variation within a tumor against irradiation. Understanding the epigenetic diversity of p62 heterogeneity among subclones allows for improved identification of the functional state of subclones and provides a novel treatment option to resolve resistance to current therapies.

High heterogeneity undermines generalization of differential expression results in RNA-Seq analysis

BACKGROUND

RNA sequencing (RNA-Seq) has been widely applied in oncology for monitoring transcriptome changes. However, the emerging problem that high variation of gene expression levels caused by tumor heterogeneity may affect the reproducibility of differential expression (DE) results has rarely been studied. Here, we investigated the reproducibility of DE results for any given number of biological replicates between 3 and 24 and explored why a great many differentially expressed genes (DEGs) were not reproducible.

RESULTS

Our findings demonstrate that poor reproducibility of DE results exists not only for small sample sizes, but also for relatively large sample sizes. Quite a few of the DEGs detected are specific to the samples in use, rather than genuinely differentially expressed under different conditions. Poor reproducibility of DE results is mainly caused by high variation of gene expression levels for the same gene in different samples. Even though biological variation may account for much of the high variation of gene expression levels, the effect of outlier count data also needs to be treated seriously, as outlier data severely interfere with DE analysis.

CONCLUSIONS

High heterogeneity exists not only in tumor tissue samples of each cancer type studied, but also in normal samples. High heterogeneity leads to poor reproducibility of DEGs, undermining generalization of differential expression results. Therefore, it is necessary to use large sample sizes (at least 10 if possible) in RNA-Seq experimental designs to reduce the impact of biological variability and DE results should be interpreted cautiously unless soundly validated.

Morphological intratumor heterogeneity in ductal carcinoma in situ of the breast

Ductal carcinoma in situ (DCIS) of the breast is a heterogeneous disease in terms of morphological characteristics, protein expression profiles, genetic abnormalities, and potential for progression. Molecular heterogeneity has been extensively studied in DCIS. Yet morphological heterogeneity remains relatively undefined. This study investigated morphological intratumor heterogeneity in a series of 51 large DCIS. Nuclear atypia, DCIS architecture, necrosis, calcifications, stromal architecture, and stromal inflammation were assessed in one biopsy slide and three representative slides from each corresponding resection. For each histopathological feature, a histo-score was determined per slide and compared between the biopsy and the resection, as well as within a single resection. Statistical analysis comprised of Friedman tests, post hoc Wilcoxon tests with Bonferroni corrections, Mann-Whitney U tests, and chi-square tests. Despite substantial morphological heterogeneity in around 50% of DCIS, the histopathological assessment of the biopsy did not statistically significantly differ from the resection. Morphological heterogeneity was not significantly associated with patient age, DCIS size, or type of surgery, except for a weak association between heterogeneous stromal inflammation and smaller DCIS size. At the group level, the degree of heterogeneity did not significantly affect the representativity of a biopsy. At the individual patient level, however, the presence of necrosis, intraductal calcifications, myxoid stromal changes, and high-grade nuclear atypia was underestimated in a minority of DCIS patients. This study confirms the presence of morphological heterogeneity in DCIS for all six evaluated histopathological features. This should be kept in mind when taking biopsy-based treatment decisions for DCIS patients.

In Silico Inference of Synthetic Cytotoxic Interactions from Paclitaxel Responses

To exploit negatively interacting pairs of cancer somatic mutations in chemotherapy responses or synthetic cytotoxicity (SC), we systematically determined mutational pairs that had significantly lower paclitaxel half maximal inhibitory concentration (IC₅₀) values. We evaluated 407 cell lines with somatic mutation profiles and estimated their copy number and drug-inhibitory concentrations in Genomics of Drug Sensitivity in Cancer (GDSC) database. The SC effect of 142 mutated gene pairs on response to paclitaxel was successfully cross-validated using human cancer datasets for urogenital cancers available in The Cancer Genome Atlas (TCGA) database. We further analyzed the cumulative effect of increasing SC pair numbers on the TP53 tumor suppressor gene. Patients with TCGA bladder and urogenital cancer exhibited improved cancer survival rates as the number of disrupted SC partners (i.e., SYNE2, SON, and/or PRY) of TP53 increased. The prognostic effect of SC burden on response to paclitaxel treatment could be differentiated from response to other cytotoxic drugs. Thus, the concept of pairwise SC may aid the identification of novel therapeutic and prognostic targets.

Lymph node response to chemoradiotherapy in oesophageal cancer patients: relationship with radiotherapy fields

BACKGROUND

The presence of lymph node metastasis (LNmets) is a poor prognostic factor in oesophageal cancer (OeC) patients treated with neoadjuvant chemoradiotherapy (nCRT) followed by surgery. Tumour regression grade (TRG) in LNmets has been suggested as a predictor for survival. The aim of this study was to investigate whether TRG in LNmets is related to their location within the radiotherapy (RT) field.

METHODS

Histopathological TRG was retrospectively classified in 2565 lymph nodes (LNs) from 117 OeC patients treated with nCRT and surgery as: (A) no tumour, no signs of regression; (B) tumour without regression; (C) viable tumour and regression; and (D) complete response. Multivariate survival analysis was used to investigate the relationship between LN location within the RT field, pathological TRG of the LN and TRG of the primary tumour.

RESULTS

In 63 (54%) patients, viable tumour cells or signs of regression were seen in 264 (10.2%) LNs which were classified as TRG-B (n = 56), C (n = 104) or D (n = 104) LNs. 73% of B, C and D LNs were located within the RT field. There was a trend towards a relationship between LN response and anatomical LN location with respect to the RT field (p = 0.052). Multivariate analysis showed that only the presence of LNmets within the RT field with TRG-B is related to poor overall survival.

CONCLUSION

Patients have the best survival if all LNmets show tumour regression, even if LNmets are located outside the RT field. Response in LNmets to nCRT is heterogeneous which warrants further studies to better understand underlying mechanisms.

Intrahepatic Cholangiocarcinoma: State of the Art of FGFR Inhibitors

OBJECTIVE

Intrahepatic cholangiocarcinoma (iCCA), the second most common type of primary liver tumor, has an increasing incidence in the past few decades. iCCA is highly malignant, with a 5-year survival rate of approximately 5-10%. Surgical resection is usually the prescribed treatment for patients with early stage iCCA; however, patients are usually in an advanced stage iCCA upon diagnosis. Currently, targeted therapy combined with chemotherapy and other comprehensive treatment measures have been mainly adopted as palliative treatment measures. As a common candidate of targeted therapy, FGFR inhibitors have demonstrated their unique advantages in clinical trials. At present, the prospect of FGFR targeted therapy is encouraging. The landscape of FGFR inhibitors in iCCA is needed to be showed urgently.

METHODS

We searched relative reports of clinical trials on FGFR inhibitors in PubMed as well as Web of Science. We also concluded other available clinical trials of FGFR inhibitors (Data were collected from clinicaltrials.gov).

RESULTS

Several relatively effective targeted drugs are being used in clinical trials. Some preliminary results indicate the outlook of targeted therapy such as BGJ398, TAS120, and HSP90 inhibitors.

CONCLUSIONS

In summary, FGFR targeted therapy has broad prospects for the treatment of iCCA.

Drug Sensitivity and Drug Repurposing Platform for Cancer Precision Medicine

One of the critical Global challenges in achieving the UN Sustainable Development Goals 3 Good Health and Well Being is optimizing drug discovery and translational research for unmet medical need in both communicable and non-communicable diseases. Recently, the WHO reports there has been a shift from communicable diseases to non-communicable diseases with respect to being the leading cause of death globally and particularly in low- and middle-income countries such as South Africa. Hence, there is current drive to establish functional precision medicine program that addresses the unmet medical need using high throughput drug sensitivity and drug repurposing platform. Here, this paper serves as a perspective to showcase the recent development in high throughput drug sensitivity screening platform for the cancer precision medicine. We also elaborate on the benefit and applications of high-throughput drug screening platform for Precision Medicine. From a future perspective, this paper aims to showcase the possibility to integrate existing high-throughput drug sensitivity screening platform with the newly developed platform technologies such as microfluidics based single cell drug screening.

Organotypic Models in Drug Development "Tumor Models and Cancer Systems Biology for the Investigation of Anticancer Drugs and Resistance Development"

The landscape of cancer treatment has improved over the past decades, aiming to reduce systemic toxicity and enhance compatibility with the quality of life of the patient. However, at the therapeutic level, metastatic cancer remains hugely challenging, based on the almost inevitable emergence of therapy resistance. A small subpopulation of cells able to survive drug treatment termed the minimal residual disease may either harbor resistance-associated mutations or be phenotypically resistant, allowing them to regrow and become the dominant population in the therapy-resistant tumor. Characterization of the profile of minimal residual disease represents the key to the identification of resistance drivers that underpin cancer evolution. Therapeutic regimens must, therefore, be dynamic and tailored to take into account the emergence of resistance as tumors evolve within a complex microenvironment in vivo. This requires the adoption of new technologies based on the culture of cancer cells in ways that more accurately reflect the intratumor microenvironment, and their analysis using omics and system-based technologies to enable a new era in the diagnostics, classification, and treatment of many cancer types by applying the concept "from the cell plate to the patient." In this chapter, we will present and discuss 3D model building and use, and provide comprehensive information on new genomic techniques that are increasing our understanding of drug action and the emergence of resistance.

Differences of the tumour cell glycocalyx affect binding of capsaicin-loaded chitosan nanocapsules

The glycocalyx regulates the interaction of mammalian cells with extracellular molecules, such as cytokines. However, it is unknown to which extend the glycocalyx of distinct cancer cells control the binding and uptake of nanoparticles. In the present study, exome sequencing data of cancer patients and analysis of distinct melanoma and bladder cancer cell lines suggested differences in cancer cell-exposed glycocalyx components such as heparan sulphate. Our data indicate that glycocalyx differences affected the binding of cationic chitosan nanocapsules (Chi-NCs). The pronounced glycocalyx of bladder cancer cells enhanced the internalisation of nanoencapsulated capsaicin. Consequently, capsaicin induced apoptosis in the cancer cells, but not in the less glycosylated benign urothelial cells. Moreover, we measured counterion condensation on highly negatively charged heparan sulphate chains. Counterion condensation triggered a cooperative binding of Chi-NCs, characterised by a weak binding rate at low Chi-NC doses and a strongly increased binding rate at high Chi-NC concentrations. Our results indicate that the glycocalyx of tumour cells controls the binding and biological activity of nanoparticles. This has to be considered for the design of tumour cell directed nanocarriers to improve the delivery of cytotoxic drugs. Differential nanoparticle binding may also be useful to discriminate tumour cells from healthy cells.

Circulating tumor DNA profile recognizes transformation to castration-resistant neuroendocrine prostate cancer

Loss of androgen receptor (AR) signaling dependence occurs in approximately 15%-20% of advanced treatment-resistant prostate cancers, and this may manifest clinically as transformation from a prostate adenocarcinoma histology to a castration-resistant neuroendocrine prostate cancer (CRPC-NE). The diagnosis of CRPC-NE currently relies on a metastatic tumor biopsy, which is invasive for patients and sometimes challenging to diagnose due to morphologic heterogeneity. By studying whole-exome sequencing and whole-genome bisulfite sequencing of cell free DNA (cfDNA) and of matched metastatic tumor biopsies from patients with metastatic prostate adenocarcinoma and CRPC-NE, we identified CRPC-NE features detectable in the circulation. Overall, there was markedly higher concordance between cfDNA and biopsy tissue genomic alterations in patients with CRPC-NE compared with castration-resistant adenocarcinoma, supporting greater intraindividual genomic consistency across metastases. Allele-specific copy number and serial sampling analyses allowed for the detection and tracking of clonal and subclonal tumor cell populations. cfDNA methylation was indicative of circulating tumor content fraction, reflective of methylation patterns observed in biopsy tissues, and was capable of detecting CRPC-NE-associated epigenetic changes (e.g., hypermethylation of ASXL3 and SPDEF; hypomethylation of INSM1 and CDH2). A targeted set combining genomic (TP53, RB1, CYLD, AR) and epigenomic (hypo- and hypermethylation of 20 differential sites) alterations applied to ctDNA was capable of identifying patients with CRPC-NE.

Integrating Genomics Into Clinical Practice in Hepatocellular Carcinoma: The Challenges Ahead

The incidence and mortality related to hepatocellular carcinoma (HCC) continue to increase in the United States, with most patients presenting at advanced stages where curative therapy and long-term survival is unlikely. Fortunately, significant progress has been made in identifying the landscape of HCC mutations due to advances in whole genome expression profiling. Drug development has also evolved in recent years with multiple first- and second-line systemic chemotherapy agents approved for HCC for the first time in over a decade. However, despite advances in molecular profiling, mutations that were identified at the highest frequency were not amenable to drug development, and curative therapy for advanced HCC remains elusive. This review focuses on the current understanding of HCC genomics and the limitations of translating the current HCC molecular profiling into clinical practice and examines the effectiveness and benefits of approved systemic therapies for advanced HCC.

Cancer cells employ an evolutionarily conserved polyploidization program to resist therapy

Unusually large cancer cells with abnormal nuclei have been documented in the cancer literature since 1858. For more than 100 years, they have been generally disregarded as irreversibly senescent or dying cells, too morphologically misshapen and chromatin too disorganized to be functional. Cell enlargement, accompanied by whole genome doubling or more, is observed across organisms, often associated with mitigation strategies against environmental change, severe stress, or the lack of nutrients. Our comparison of the mechanisms for polyploidization in other organisms and non-transformed tissues suggest that cancer cells draw from a conserved program for their survival, utilizing whole genome doubling and pausing proliferation to survive stress. These polyaneuploid cancer cells (PACCs) are the source of therapeutic resistance, responsible for cancer recurrence and, ultimately, cancer lethality.

The emerging roles of exosomes in anti-cancer drug resistance and tumor progression: An insight towards tumor-microenvironment interaction

The tumor microenvironment (TME) is a complex network of cellular organization consisting of fibroblasts, adipocytes, pericytes, immune cells endothelial cells, and extracellular matrix proteins. Besides communicating with each other, tumor cells are also involved in the tumor stroma interaction. Presently, most of the studies have focused on the contribution of TME in supporting tumor growth through intercellular communication by physical contact between the cells or through paracrine signaling cascades of growth factors and cytokines. The crosstalk between the tumor and TME has a pivotal role in the development of anti-cancer drug resistance. Drug resistance, be it against targeted or non-targeted drugs, has emerged as a major hurdle in the successful therapeutic intervention of cancer. Among the several mechanisms involved in the development of the resistance to anti-cancer therapies, exosomes have recently come into the limelight. Exosomes are the nano-sized vesicles, originated from the endolysosomal compartments and have the inherent potential to shuttle diverse biomolecules like proteins, lipids, and nucleic acids to the recipient cells. There are also instances where the pharmacological compounds are transferred between the cells via exosomes. For instance, the transfer of the cargoes from the drug-resistant tumor cells immensely affects the recipient drug-sensitive cells in terms of their proliferation, survival, migration, and drug resistance. In this review, we have discussed multiple aspects of the exosome-mediated bidirectional interplay between tumor and TME. Furthermore, we have also emphasized the contribution of exosomes promoting drug resistance and therapeutic strategies to mitigate the exosome induced drug resistance as well.

Exploring the Eco-Evolutionary Dynamics of Tumor Subclones

Mutational processes constantly shape the cancer genome and defects in DNA repair pathways of tumor cells facilitate the accumulation of genomic alterations [...].

Engineering in Medicine To Address the Challenge of Cancer Drug Resistance: From Micro- and Nanotechnologies to Computational and Mathematical Modeling

Drug resistance has profoundly limited the success of cancer treatment, driving relapse, metastasis, and mortality. Nearly all anticancer drugs and even novel immunotherapies, which recalibrate the immune system for tumor recognition and destruction, have succumbed to resistance development. Engineers have emerged across mechanical, physical, chemical, mathematical, and biological disciplines to address the challenge of drug resistance using a combination of interdisciplinary tools and skill sets. This review explores the developing, complex, and under-recognized role of engineering in medicine to address the multitude of challenges in cancer drug resistance. Looking through the "lens" of intrinsic, extrinsic, and drug-induced resistance (also referred to as "tolerance"), we will discuss three specific areas where active innovation is driving novel treatment paradigms: (1) nanotechnology, which has revolutionized drug delivery in desmoplastic tissues, harnessing physiochemical characteristics to destroy tumors through photothermal therapy and rationally designed nanostructures to circumvent cancer immunotherapy failures, (2) bioengineered tumor models, which have benefitted from microfluidics and mechanical engineering, creating a paradigm shift in physiologically relevant environments to predict clinical refractoriness and enabling platforms for screening drug combinations to thwart resistance at the individual patient level, and (3) computational and mathematical modeling, which blends in silico simulations with molecular and evolutionary principles to map mutational patterns and model interactions between cells that promote resistance. On the basis that engineering in medicine has resulted in discoveries in resistance biology and successfully translated to clinical strategies that improve outcomes, we suggest the proliferation of multidisciplinary science that embraces engineering.

Breast Cancer Heterogeneity and Response to Novel Therapeutics

Targeted cancer therapies against oncogenic drivers are actively being developed and tested in clinical trials. Targeting an oncogenic driver may only prove effective if the mutation is present in most tumoral cells. Therefore, highly heterogeneous tumors may be refractory to these therapies. This makes tumor heterogeneity a major challenge in cancer therapy. Although heterogeneity has traditionally been attributed to genetic diversity within cancer cell populations, it is now widely recognized that human cancers are heterogeneous in almost all distinguishable phenotypic characteristics. Understanding the genetic variability and also the non-genetic influences of tumor heterogeneity will provide novel insights into how to reverse therapeutic resistance and improve cancer therapy.

Tumour neoantigen heterogeneity thresholds provide a time window for combination immunotherapy

Following the advent of cancer immunotherapy, increasing insight has been gained on the role of mutational load and neoantigens as key ingredients in T cell recognition of malignancies. However, not all highly mutational tumours react to immune therapies, and initial success is often followed by eventual relapse. Heterogeneity in the neoantigen landscape of a tumour might be key in the failure of immune surveillance. In this work, we present a mathematical framework to describe how neoantigen distributions shape the immune response. The model predicts the existence of an antigen diversity threshold level beyond which T cells fail at controlling heterogeneous tumours. Incorporating this diversity marker adds predictive value to antigen load for two cohorts of anti-CTLA-4 treated melanoma patients. Furthermore, our analytical approach indicates rapid increases in epitope heterogeneity in early malignancy growth following immune escape. We propose a combination therapy scheme that takes advantage of preexisting resistance to a targeted agent. The model indicates that the selective sweep for a resistant subclone reduces neoantigen heterogeneity, and we postulate the existence of a time window before tumour relapse where checkpoint blockade immunotherapy can become more effective.

An engineered pancreatic cancer model with intra-tumoral heterogeneity of driver mutations

Pancreatic ductal adenocarcinoma (PDAC) is a complex disease with significant intra-tumoral heterogeneity (ITH). Currently, no reliable PDAC tumor model is available that can present ITH profiles in a controlled manner. We develop an in vitro microfluidic tumor model mimicking the heterogeneous accumulation of key driver mutations of human PDAC using cancer cells derived from genetically engineered mouse models. These murine pancreatic cancer cell lines have KPC (Kras and Trp53 mutations) and KIC genotypes (Kras mutation and Cdkn2a deletion). Also, the KIC genotypes have two distinct phenotypes - mesenchymal or epithelial. The tumor model mimics the ITH of human PDAC to study the effects of ITH on the gemcitabine response. The results show gemcitabine resistance induced by ITH. Remarkably, it shows that cancer cell-cell interactions induce the gemcitabine resistance potentially through epithelial-mesenchymal-transition. The tumor model can provide a useful testbed to study interaction mechanisms between heterogeneous cancer cell subpopulations.

Andrographis-mediated chemosensitization through activation of ferroptosis and suppression of β-catenin/Wnt-signaling pathways in colorectal cancer

Colorectal cancer (CRC) remains one of the leading causes of cancer-related mortality in the USA. As much as 50-60% of CRC patients develop resistance to 5-fluorouracil (5FU)-based chemotherapeutic regimens, attributing the increased overall morbidity and mortality. In view of the growing evidence that active principles in various naturally occurring botanicals can facilitate chemosensitization in cancer cells, herein, we undertook a comprehensive effort in interrogating the activity of one such botanical-andrographis-by analyzing its activity in CRC cell lines [both sensitive and 5FU resistant (5FUR)], a xenograft animal model and patient-derived tumor organoids. We observed that combined treatment with andrographis was synergistic and resulted in a significant and dose-dependent increase in the efficacy of 5FU in HCT116 and SW480 5FUR cells (P < 0.05), reduced clonogenic formation (P < 0.01) and increased rates of caspase-9-mediated apoptosis (P < 0.05). The genomewide expression analysis in cell lines led us to uncover that activation of ferroptosis and suppression of β-catenin/Wnt-signaling pathways were the key mediators for the anti-cancer and chemosensitizing effects of andrographis. Subsequently, we validated our findings in a xenograft animal model, as well as two independent CRC patient-derived organoids-which confirmed that combined treatment with andrographis was significantly more effective than 5FU and andrographis alone and that these effects were in part orchestrated through dysregulated expression of key genes (including HMOX1, GCLC, GCLM and TCF7L2) within the ferroptosis and Wnt-signaling pathways. Collectively, our data highlight that andrographis might offer a safe and inexpensive adjunctive therapeutic option in the management of CRC patients.

Genomic, transcriptomic, and viral integration profiles associated with recurrent/metastatic progression in high-risk human papillomavirus cervical carcinomas

Acquisition of recurrent/metastatic potential by a tumor cell defines a critical step in malignant progression. However, understanding of metastatic progression at the molecular level is scarce for cervical carcinomas (CES). In this study, we performed genomic, transcriptomic, and viral profiling of five pairs of primary (CES‐P) and matched recurrent/metastatic tumors (CES‐R/M) with high risk human papillomavirus. Whole exome sequencing revealed mutation features of CES‐R/M including elevated mutation burdens and prevalent copy number alterations compared to their matched CES‐P. A relative deficit of APOBEC‐related mutation signatures accompanying the transcriptional downregulation of APOBEC3A was observed for CES‐R/M. Mutations in genes encoding epigenetic regulators were commonly observed as CES‐R/M‐specific alterations. Immunoprofiling and gene set analysis revealed CES‐Ps were enriched with transcripts representing activated anticancer immunity such as interferon‐gamma pathway, while CES‐R/M exhibited upregulation of genes involved in epithelial‐mesenchymal transition and angiogenesis. Viral capture sequencing revealed that integration sites remained enriched in viral E1 protein domain during malignant progression. Moreover, we found transcriptional upregulation of POSTN and downregulation of APOBEC3A were associated with unfavorable clinical outcomes in CES. Comprehensive genomic and transcriptomic profiling of a rare cohort including CES‐R/M identified metastases‐specific features to advance the molecular understanding into CES metastatic progression with potential clinical implications.

FoxM1 insufficiency hyperactivates Ect2-RhoA-mDia1 signaling to drive cancer

FoxM1 activates genes that regulate S-G2-M cell-cycle progression and, when overexpressed, is associated with poor clinical outcome in multiple cancers. Here we identify FoxM1 as a tumor suppressor in mice that, through its N-terminal domain, binds to and inhibits Ect2 to limit the activity of RhoA GTPase and its effector mDia1, a catalyst of cortical actin nucleation. FoxM1 insufficiency impedes centrosome movement through excessive cortical actin polymerization, thereby causing the formation of non-perpendicular mitotic spindles that missegregate chromosomes and drive tumorigenesis in mice. Importantly, low FOXM1 expression correlates with RhoA GTPase hyperactivity in multiple human cancer types, indicating that suppression of the newly discovered Ect2-RhoAmDia1 oncogenic axis by FoxM1 is clinically relevant. Furthermore, by dissecting the domain requirements through which FoxM1 inhibits Ect2 GEF activity, we provide mechanistic insight for the development of pharmacological approaches that target protumorigenic RhoA activity.

Prognostic impact of combined progression index based on peritoneal grading regression score and peritoneal cytology in peritoneal metastasis

AIMS

The peritoneal regression grading score (PRGS) and peritoneal cytology (PC) assess response to chemotherapy in peritoneal metastasis (PM) in a setting of palliative treatment by pressurized intraperitoneal aerosol chemotherapy (PIPAC). Progression has been defined as an increase of PRGS between first and third PIPAC procedures (iPRGS). iPRGSand positive peritoneal cytology were not associated with prognostic impact. These results may be explained by a lack of statistical power. Also, it is not known whether the mean or the highest PRGS among taken peritoneal biopsies bears the highest clinical value. We therefore conducted the largest prospective study to investigate the prognostic impact of PGRS, PC, and their combination, designated as combined progression index (CPI).

METHODS AND RESULTS

Patients with PM who underwent >3 PIPAC (n = 112) between December 2016 and February 2019 were prospectively included. A significant difference in OS and PFS according to CPI (used highest value of PRGS) was found (OS: CPI-, 83.3, 95% CI [49.8; NA] vs. CPI+, 48.1, 95% CI [38.5; 66.4] months; and PFS (respectively, 59.7, 95% CI [43.0; 96.0] vs. 33.7, 95% CI [30.4; 44.2] months). PRGS or PC had no independent prognostic impact. CPI+ was an independent predictor of worse prognosis, in OS (HR = 5.24, 95% CI [2.07; 13.26]), and PFS (HR = 4.41, 95% CI [1.40; 13.88]).

CONCLUSIONS

The CPI based on highest PRGS and PC was found to be independently associated with a worse prognosis for OS and for PFS in the setting of peritoneal metastasis. These results indicate that it should be of interest to systematically take peritoneal fluid for cytological examination and to implement the CPI in the therapeutic decision-making process in the context of PIPAC.

FastClone is a probabilistic tool for deconvoluting tumor heterogeneity in bulk-sequencing samples

Dissecting tumor heterogeneity is a key to understanding the complex mechanisms underlying drug resistance in cancers. The rich literature of pioneering studies on tumor heterogeneity analysis spurred a recent community-wide benchmark study that compares diverse modeling algorithms. Here we present FastClone, a top-performing algorithm in accuracy in this benchmark. FastClone improves over existing methods by allowing the deconvolution of subclones that have independent copy number variation events within the same chromosome regions. We characterize the behavior of FastClone in identifying subclones using stage III colon cancer primary tumor samples as well as simulated data. It achieves approximately 100-fold acceleration in computation for both simulated and patient data. The efficacy of FastClone will allow its application to large-scale data and clinical data, and facilitate personalized medicine in cancers.

Flavin dependency undermines proteome stability, lipid metabolism and cellular proliferation during vitamin B2 deficiency

Tumor cells adapt their metabolism to meet the energetic and anabolic requirements of high proliferation and invasiveness. The metabolic addiction has motivated the development of therapies directed at individual biochemical nodes. However, currently there are few possibilities to target multiple enzymes in tumors simultaneously. Flavin-containing enzymes, ca. 100 proteins in humans, execute key biotransformations in mammalian cells. To expose metabolic addiction, we inactivated a substantial fraction of the flavoproteome in melanoma cells by restricting the supply of the FMN and FAD precursor riboflavin, the vitamin B2. Vitamin B2 deficiency affected stability of many polypeptides and thus resembled the chaperone HSP90 inhibition, the paradigmatic multiple-target approach. In support of this analogy, flavin-depleted proteins increasingly associated with a number of proteostasis network components, as identified by the mass spectrometry analysis of the FAD-free NQO1 aggregates. Proteome-wide analysis of the riboflavin-starved cells revealed a profound inactivation of the mevalonate pathway of cholesterol synthesis, which underlines the manifold cellular vulnerability created by the flavoproteome inactivation. Cell cycle-arrested tumor cells became highly sensitive to alkylating chemotherapy. Our data suggest that the flavoproteome is well suited to design synthetic lethality protocols combining proteostasis manipulation and metabolic reprogramming.