Hard wiring of normal tissue-specific chromosome-wide gene expression levels is an additional factor driving cancer type-specific aneuploidies

Patterns of Aneuploidy and Signaling Consequences in Cancer

Aneuploidy, or a change in the number of whole chromosomes or chromosome arms, is a near-universal feature of cancer. Chromosomes affected by aneuploidy are not random, with observed cancer-specific and tissue-specific patterns. Recent advances in genome engineering methods have allowed the creation of models with targeted aneuploidy events. These models can be used to uncover the downstream effects of individual aneuploidies on cancer phenotypes including proliferation, apoptosis, metabolism, and immune signaling. Here, we review the current state of research into the patterns of aneuploidy in cancer and their impact on signaling pathways and biological processes.

Machine-learning analysis reveals an important role for negative selection in shaping cancer aneuploidy landscapes

BACKGROUND

Aneuploidy, an abnormal number of chromosomes within a cell, is a hallmark of cancer. Patterns of aneuploidy differ across cancers, yet are similar in cancers affecting closely related tissues. The selection pressures underlying aneuploidy patterns are not fully understood, hindering our understanding of cancer development and progression.

RESULTS

Here, we apply interpretable machine learning methods to study tissue-selective aneuploidy patterns. We define 20 types of features corresponding to genomic attributes of chromosome-arms, normal tissues, primary tumors, and cancer cell lines (CCLs), and use them to model gains and losses of chromosome arms in 24 cancer types. To reveal the factors that shape the tissue-specific cancer aneuploidy landscapes, we interpret the machine learning models by estimating the relative contribution of each feature to the models. While confirming known drivers of positive selection, our quantitative analysis highlights the importance of negative selection for shaping aneuploidy landscapes. This is exemplified by tumor suppressor gene density being a better predictor of gain patterns than oncogene density, and vice versa for loss patterns. We also identify the importance of tissue-selective features and demonstrate them experimentally, revealing KLF5 as an important driver for chr13q gain in colon cancer. Further supporting an important role for negative selection in shaping the aneuploidy landscapes, we find compensation by paralogs to be among the top predictors of chromosome arm loss prevalence and demonstrate this relationship for one paralog interaction. Similar factors shape aneuploidy patterns in human CCLs, demonstrating their relevance for aneuploidy research.

CONCLUSIONS

Our quantitative, interpretable machine learning models improve the understanding of the genomic properties that shape cancer aneuploidy landscapes.

Minimally invasive biopsy-based diagnostics in support of precision cancer medicine

Precision cancer medicine (PCM) to support the treatment of solid tumors requires minimally invasive diagnostics. Here, we describe the development of fine-needle aspiration biopsy-based (FNA) molecular cytology which will be increasingly important in diagnostics and adaptive treatment. We provide support for FNA-based molecular cytology having a significant potential to replace core needle biopsy (CNB) as a patient-friendly potent technique for tumor sampling for various tumor types. This is not only because CNB is a more traumatic procedure and may be associated with more complications compared to FNA-based sampling, but also due to the recently developed molecular methods used with FNA. Recent studies show that image-guided FNA in combination with ultrasensitive molecular methods also offers opportunities for characterization of the tumor microenvironment which can aid therapeutic decisions. Here we provide arguments for an increased implementation of molecular FNA-based sampling as a patient-friendly diagnostic method, which may, due to its repeatability, facilitate regular sampling that is needed during different treatment lines, to provide tumor information, supporting treatment decisions, shortening lead times in healthcare, and benefit healthcare economics.

Targeting chromosomal instability and aneuploidy in cancer

Cancer development and therapy resistance are driven by chromosomal instability (CIN), which causes chromosome gains and losses (i.e., aneuploidy) and structural chromosomal alterations. Technical limitations and knowledge gaps have delayed therapeutic targeting of CIN and aneuploidy in cancers. However, our toolbox for creating and studying aneuploidy in cell models has greatly expanded recently. Moreover, accumulating evidence suggests that seven conventional antimitotic chemotherapeutic drugs achieve clinical response by inducing CIN instead of mitotic arrest, although additional anticancer activities may also contribute in vivo. In this review, we discuss these recent developments. We also highlight new discoveries, which together show that 25 chromosome arm aneuploidies (CAAs) may be targetable by 36 drugs across 14 types of cancer. Collectively, these advances offer many new opportunities to improve cancer treatment.

Modeling specific aneuploidies: from karyotype manipulations to biological insights

An abnormal chromosome number, or aneuploidy, underlies developmental disorders and is a common feature of cancer, with different cancer types exhibiting distinct patterns of chromosomal gains and losses. To understand how specific aneuploidies emerge in certain tissues and how they contribute to disease development, various methods have been developed to alter the karyotype of mammalian cells and mice. In this review, we provide an overview of both classic and novel strategies for inducing or selecting specific chromosomal gains and losses in human and murine cell systems. We highlight how these customized aneuploidy models helped expanding our knowledge of the consequences of specific aneuploidies to (cancer) cell physiology.

Impact of somatic mutations and transcriptomic alterations on cancer aneuploidy

Aneuploidy has been recognized as one of hallmark of tumorigenesis since the early 20th century. Recent developments in structural variation analysis in the human genome have revealed the diversity of aneuploidy in cancer. However, the effects of gene mutation and expression in tumors on aneuploidy remain poorly understood. Here, we performed whole exome analysis of over 5,000 Japanese cancer cases and investigated the impact of somatic mutations and gene expression alterations on aneuploidy. First, we evaluated tumor content and genomic alterations that could influence aneuploidy. Next, we compared the aneuploidy frequency in 18 cancer types and observed that TP53 mutations were associated with the aneuploidy on specific chromosomes in colorectal and gastric cancers. Finally, we used expression analysis to isolate pathways involved in aneuploidy accumulation from tumors without TP53 mutations. Chromosomal instability and cell cycle aberration were associated with aneuploidy in TP53 wild-type tumors, and 26 commonly upregulated genes were identified in aneuploidy-high solid tumors without TP53 mutations. Among them, two cancer-related genes (CENPA and PBK) were involved in aneuploidy. Our integrated analysis revealed that both TP53 mutations and transcriptomic alterations independent of somatic mutations affect aneuploidy accumulation. Our findings will facilitate further understanding of diverse aneuploidies in the tumorigenesis.

Chromosomal Instability, Selection and Competition: Factors That Shape the Level of Karyotype Intra-Tumor Heterogeneity

Simple Summary

Each cancer consists of billions of cells. These cells are far from identical; hence, the population of cells that constitute a tumor is heterogeneous. A salient property that varies between cells in a tumor is their karyotype, the number and configuration of the chromosomes. The level of karyotype heterogeneity can be used to predict the survival of a patient. In this review, we describe the processes that shape the level of karyotype heterogeneity in a cancer.

Abstract

Intra-tumor heterogeneity (ITH) is a pan-cancer predictor of survival, with high ITH being correlated to a dismal prognosis. The level of ITH is, hence, a clinically relevant characteristic of a malignancy. ITH of karyotypes is driven by chromosomal instability (CIN). However, not all new karyotypes generated by CIN are viable or competitive, which limits the amount of ITH. Here, we review the cellular processes and ecological properties that determine karyotype ITH. We propose a framework to understand karyotype ITH, in which cells with new karyotypes emerge through CIN, are selected by cell intrinsic and cell extrinsic selective pressures, and propagate through a cancer in competition with other malignant cells. We further discuss how CIN modulates the cell phenotype and immune microenvironment, and the implications this has for the subsequent selection of karyotypes. Together, we aim to provide a comprehensive overview of the biological processes that shape the level of karyotype heterogeneity.

Chromatin Mechanisms Driving Cancer

The change in cell state from normal to malignant is driven fundamentally by oncogenic mutations in cooperation with epigenetic alterations of chromatin. These alterations in chromatin can be a consequence of environmental stressors or germline and/or somatic mutations that directly alter the structure of chromatin machinery proteins, their levels, or their regulatory function. These changes can result in an inability of the cell to differentiate along a predefined lineage path, or drive a hyperactive, highly proliferative state with addiction to high levels of transcriptional output. We discuss how these genetic alterations hijack the chromatin machinery for the oncogenic process to reveal unique vulnerabilities and novel targets for cancer therapy.

Anti-miR-135/SPOCK1 axis antagonizes the influence of metabolism on drug response in intestinal/colon tumour organoids

Little is known about the role of microRNAs (miRNAs) in rewiring the metabolism within tumours and adjacent non-tumour bearing normal tissue and their potential in cancer therapy. This study aimed to investigate the relationship between deregulated miRNAs and metabolic components in murine duodenal polyps and non-polyp-derived organoids (mPOs and mNPOs) from a double-mutant Apc^MinFbxw7^∆G mouse model of intestinal/colorectal cancer (CRC). We analysed the expression of 373 miRNAs and 12 deregulated metabolic genes in mPOs and mNPOs. Our findings revealed miR-135b might target Spock1. Upregulation of SPOCK1 correlated with advanced stages of CRCs. Knockdown of miR-135b decreased the expression level of SPOCK1, glucose consumption and lactic secretion in CRC patient-derived tumours organoids (CRC tPDOs). Increased SPOCK1 induced by miR-135b overexpression promoted the Warburg effect and consequently antitumour effect of 5-fluorouracil. Thus, combination with miR-135b antisense nucleotides may represent a novel strategy to sensitise CRC to the chemo-reagent based treatment.