Proof-of-Concept Pilot Study on Comprehensive Spatiotemporal Intra-Patient Heterogeneity for Colorectal Cancer With Liver Metastasis.

Introduction: The mechanisms underlying high drug resistance and relapse rates after multi-modal treatment in patients with colorectal cancer (CRC) and liver metastasis (LM) remain poorly understood. Objective: We evaluate the potential translational implications of intra-patient heterogeneity (IPH) comprising primary and matched metastatic intratumor heterogeneity (ITH) coupled with circulating tumor DNA (ctDNA) variability. Methods: A total of 122 multi-regional tumor and perioperative liquid biopsies from 18 patients were analyzed via targeted next-generation sequencing (NGS). Results: The proportion of patients with ITH were 53% and 56% in primary CRC and LM respectively, while 35% of patients harbored de novo mutations in LM indicating spatiotemporal tumor evolution and the necessity of multiregional analysis. Among the 56% of patients with alterations in liquid biopsies, de novo mutations in cfDNA were identified in 25% of patients, which were undetectable in both CRC and LM. All 17 patients with driver alterations harbored mutations targetable by molecularly targeted drugs, either approved or currently under evaluation. Conclusion: Our proof-of-concept prospective study provides initial evidence on potential clinical superiority of IPH and warrants the conduction of precision oncology trials to evaluate the clinical utility of I PH-driven matched therapy.

Bulk and Single-Cell Next-Generation Sequencing: Individualizing Treatment for Colorectal Cancer.

The increasing incidence combined with constant rates of early diagnosis and mortality of colorectal cancer (CRC) over the past decade worldwide, as well as minor overall survival improvements in the industrialized world, suggest the need to shift from conventional research and clinical practice to the innovative development of screening, predictive and therapeutic tools. Explosive integration of next-generation sequencing (NGS) systems into basic, translational and, more recently, basket trials is transforming biomedical and cancer research, aiming for substantial clinical implementation as well. Shifting from inter-patient tumor variability to the precise characterization of intra-tumor genetic, genomic and transcriptional heterogeneity (ITH) via multi-regional bulk tissue NGS and emerging single-cell transcriptomics, coupled with NGS of circulating cell-free DNA (cfDNA), unravels novel strategies for therapeutic response prediction and drug development. Remarkably, underway and future genomic/transcriptomic studies and trials exploring spatiotemporal clonal evolution represent most rational expectations to discover novel prognostic, predictive and therapeutic tools. This review describes latest advancements and future perspectives of integrated sequencing systems for genome and transcriptome exploration to overcome unmet research and clinical challenges towards Precision Oncology.

Comprehensive intra-individual genomic and transcriptional heterogeneity: Evidence-based Colorectal Cancer Precision Medicine.

Despite advances in translating conventional research into multi-modal treatment for colorectal cancer (CRC), therapeutic resistance and relapse remain unresolved in advanced resectable and, particularly, non-resectable disease. Genome and transcriptome sequencing and editing technologies, coupled with interaction mapping and machine learning, are transforming biomedical research, representing the most rational hope to overcome unmet research and clinical challenges. Rapid progress in both bulk and single-cell next-generation sequencing (NGS) analyses in the identification of primary and metastatic intratumor genomic and transcriptional heterogeneity (ITH) and the detection of circulating cell-free DNA (cfDNA) alterations is providing critical insight into the origins and spatiotemporal evolution of genomic clones responsible for early and late therapeutic resistance and relapse. Moreover, DNA and RNA editing pave new avenues towards the discovery of novel drug targets. Breakthrough combinations of sequencing and editing systems with technologies exploring dynamic interaction networks within pioneering studies could delineate how coding and non-coding mutations perturb regulatory networks and gene expression. This review discusses latest data on genomic and transcriptomic landscapes in time and space, as well as early-phase clinical trials on targeted drug combinations, highlighting the transition from research to clinical Colorectal Cancer Precision Medicine, through non-invasive screening, individualized drug response prediction and development of multiple novel drugs. Future studies exploring the potential to target key transcriptional drivers and regulators will contribute to the next-generation pharmaceutical controllability of multi-layered aberrant transcriptional biocircuits.

Drug resistance: origins, evolution and characterization of genomic clones and the tumor ecosystem to optimize precise individualized therapy.

Progress in understanding and overcoming fatal intrinsic and acquired resistance is slow, with only a few exceptions. Despite advances in modern genome and transcriptome analysis, the controversy of the three different theories on drug resistance and tumor progression, namely dynamic intratumor heterogeneity, pre-existing minor genomic clones and tumor ecosystem, is unresolved. Moreover, evidence on transcriptional heterogeneity suggests the necessity of a drug bank for individualized, precise drug-sensitivity prediction. We propose a cancer type- and stage-specific clinicogenomic and tumor ecosystemic concept toward cancer precision medicine, focusing on early therapeutic resistance and relapse.

Dynamic genome and transcriptional network-based biomarkers and drugs: precision in breast cancer therapy.

Despite remarkable progress in medium-term overall survival benefit in the adjuvant, neoadjuvant and metastatic settings, with multiple recent targeted drug approvals, acquired resistance, late relapse, and cancer-related death rates remain challenging. Integrated technological systems have been developed to overcome these unmet needs. The characterization of structural and functional noncoding genome elements through next-generation sequencing (NGS) systems, Hi-C and CRISPR/Cas9, as well as computational models, allows for whole genome and transcriptome analysis. Rapid progress in large-scale single-biopsy genome analysis has identified several novel breast cancer driver genes and oncotargets. The exploration of spatiotemporal tumor evolution has returned exciting while inconclusive data on dynamic intratumor heterogeneity (ITH) through multiregional NGS and single-cell DNA/RNA sequencing and circulating genomic subclones (cGSs) by serial circulating cell-free DNA NGS to predict and overcome intrinsic and acquired therapeutic resistance. This review discusses reliable breast cancer genome analysis data and focuses on two major crucial perspectives. The validation of ITH, cGSs, and intrapatient genetic/genomic heterogeneity as predictive biomarkers, as well as the valid discovery of novel oncotargets within patient-centric genomic trials, encouraging early drug development, could optimize primary and secondary therapeutic decision-making. A longer-term goal is to identify the individualized landscape of both coding and noncoding key mutations. This progress will enable the understanding of molecular mechanisms perturbating regulatory networks, shaping the pharmaceutical controllability of deregulated transcriptional biocircuits.

Discovering novel valid biomarkers and drugs in patient-centric genomic trials: the new epoch of precision surgical oncology.

Despite standardization of multimodal treatment and approval of several targeted drugs for resectable, non-metastatic cancer (M0 patients), intrinsic and acquired resistance and relapse rates remain high, even in early-stage aggressive tumors. Genome analysis could overcome these unmet needs. Our comprehensive review underlines the controversy on stable or spatiotemporally evolving clones as well as promising yet inconclusive data on genome-based biomarkers and drug development. We propose clinicogenomic trials in M0 patients for the validation of intratumor heterogeneity (ITH), circulating genomic subclones (cGSs) and intra-patient genomic heterogeneity (IPGH) as biomarkers and simultaneous discovery of novel oncotargets. This evidence-based strategy highlights the coming of precision surgical oncology with a future perspective of understanding and disrupting deregulated transcriptional networks.

Primary liver cancer genome sequencing: translational implications and challenges.

INTRODUCTION: The prognosis of primary liver cancer (PLC) remains poor and is explained by the slow progress in understanding the molecular pathways driving tumorigenesis, therapeutic resistance and relapse. For early PLCs, complete surgical resection is the only effective treatment, with sorafenib and, more recently, regorafenib prolonging overall survival by a few months. Areas covered: Application of next-generation sequencing (NGS), including targeted NGS (tNGS), whole-exome sequencing (WES), whole-genome sequencing (WGS) and RNA sequencing (RNAseq), on clinical samples from patients with hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) could aid in comprehending tumorigenesis, genetic and genomic heterogeneity, as well as developing molecular classifications for specialized targeted therapy. Expert commentary: Despite the many overenthusiastic original and opinion reports, we have critically reviewed available NGS studies, with focus on the challenges to achieve clinical implications. Based on the recommendations for valid identification of clinically crucial genomic alterations (GAs) by NGS, we propose NGS integration into appropriately designed clinical trials. Furthermore, valid detection of genomic heterogeneity enables the conduction of clinical trials investigating the efficacy both of GAs as prognostic and predictive tools, as well as the discovery of novel oncotargets, on the basis of an early drug development strategy.