Karyotype Aberrations in Action: The Evolution of Cancer Genomes and the Tumor Microenvironment

Tracking circulating PD-L1-positive cells to monitor the outcome of patients with gastric cancer receiving anti-HER2 plus anti-PD-1 therapy

Dual blockade of HER2 and PD-1/PD-L1 is the most promising regimen for HER2-positive patients with gastric cancer (GC); PD-L1 combined positive score, rather than HER2 status, indicates potential benefit. Circulating tumor cells (CTCs) and circulating endothelial cells (CECs) derived from the tumor microenvironment provide platforms for the dynamic evaluation of PD-L1 expression. Whether PD-L1 positive CTCs/CECs (PD-L1+CTCs/CECs) can serve as biomarkers for evaluating the efficacy of combination therapy remains unknown. Therefore, this study investigated PD-L1 expression and heterogeneous karyotypic features of CTCs/CECs and their involvement in the clinical response to treatment in 72 patients with advanced GC by applying a pre-established surface molecule-independent subtraction enrichment (SE)-iFISH strategy. In the captured PD-L1 positive cells, there were 42.80% and 57.20% of CTCs and CECs, respectively. PD-L1+ CTCs were pre-therapeutically detected in 0% (0/11) of HER2-negative patients and 14.75% (9/61) of HER2-positive patients. The presence of baseline PD-L1+CTCs was relevant to inferior prognosis (mPFS: 14.40 months vs 5.00 months, P = 0.065); post-treatment PD-L1+ CECs were associated with longer irPFS (immunotherapeutic-related PFS) (mPFS: 15.57 months vs 6.73 months, P = 0.053). Further dynamic karyotype-based profiling of PD-L1+ CTCs/CECs indicated that multiploidy and triploidy were the dominant subtypes of baseline PD-L1+ CTCs, and that triploidy was specifically associated with therapeutic resistance. Intratherapeutically detected multiploid PD-L1+ CECs demonstrated a superior clinical response; triploidy and tetraploidy contributed to acquired resistance. The karyotypic features of PD-L1+CTCs/CECs should be dynamically profiled in patients with GC treated with anti-HER2 plus anti-PD-1 therapy. Triploid-PD-L1+ CTCs and multiploid-PD-L1+ CECs are potential indicators of therapeutic response.

Inferring chromosomal instability from copy number aberrations as a measure of chromosomal instability across human cancers

BACKGROUND

Cancer is a complex disease that is the second leading cause of death in the United States. Despite research efforts, the ability to manage cancer and select optimal therapeutic responses for each patient remains elusive. Chromosomal instability (CIN) is primarily a product of segregation errors wherein one or many chromosomes, in part or whole, vary in number. CIN is an enabling characteristic of cancer, contributes to tumor-cell heterogeneity, and plays a crucial role in the multistep tumorigenesis process, especially in tumor growth and initiation and in response to treatment.

AIMS

Multiple studies have reported different metrics for analyzing copy number aberrations as surrogates of CIN from DNA copy number variation data. However, these metrics differ in how they are calculated with respect to the type of variation, the magnitude of change, and the inclusion of breakpoints. Here we compared metrics capturing CIN as either numerical aberrations, structural aberrations, or a combination of the two across 33 cancer data sets from The Cancer Genome Atlas (TCGA).

METHODS AND RESULTS

Using CIN inferred by methods in the CINmetrics R package, we evaluated how six copy number CIN surrogates compared across TCGA cohorts by assessing each across tumor types, as well as how they associate with tumor stage, metastasis, and nodal involvement, and with respect to patient sex.

CONCLUSIONS

We found that the tumor type impacts how well any two given CIN metrics correlate. While we also identified overlap between metrics regarding their association with clinical characteristics and patient sex, there was not complete agreement between metrics. We identified several cases where only one CIN metric was significantly associated with a clinical characteristic or patient sex for a given tumor type. Therefore, caution should be used when describing CIN based on a given metric or comparing it to other studies.

High-Frequency Dielectrophoresis Reveals That Distinct Bio-Electric Signatures of Colorectal Cancer Cells Depend on Ploidy and Nuclear Volume

Aneuploidy, or an incorrect chromosome number, is ubiquitous among cancers. Whole-genome duplication, resulting in tetraploidy, often occurs during the evolution of aneuploid tumors. Cancers that evolve through a tetraploid intermediate tend to be highly aneuploid and are associated with poor patient prognosis. The identification and enrichment of tetraploid cells from mixed populations is necessary to understand the role these cells play in cancer progression. Dielectrophoresis (DEP), a label-free electrokinetic technique, can distinguish cells based on their intracellular properties when stimulated above 10 MHz, but DEP has not been shown to distinguish tetraploid and/or aneuploid cancer cells from mixed tumor cell populations. Here, we used high-frequency DEP to distinguish cell subpopulations that differ in ploidy and nuclear size under flow conditions. We used impedance analysis to quantify the level of voltage decay at high frequencies and its impact on the DEP force acting on the cell. High-frequency DEP distinguished diploid cells from tetraploid clones due to their size and intracellular composition at frequencies above 40 MHz. Our findings demonstrate that high-frequency DEP can be a useful tool for identifying and distinguishing subpopulations with nuclear differences to determine their roles in disease progression.

"Pulsed Hypoxia" Gradually Reprograms Breast Cancer Fibroblasts into Pro-Tumorigenic Cells via Mesenchymal-Epithelial Transition

Hypoxia arises in most growing solid tumors and can lead to pleotropic effects that potentially increase tumor aggressiveness and resistance to therapy through regulation of the expression of genes associated with the epithelial-mesenchymal transition (EMT) and mesenchymal-epithelial transition (MET). The main goal of the current work was to obtain and investigate the intermediate phenotype of tumor cells undergoing the hypoxia-dependent transition from fibroblast to epithelial morphology. Primary breast cancer fibroblasts BrC4f, being cancer-associated fibroblasts, were subjected to one or two rounds of "pulsed hypoxia" (PH). PH induced transformation of fibroblast-shaped cells to semi-epithelial cells. Western blot analysis, fluorescent microscopy and flow cytometry of transformed cells demonstrated the decrease in the mesenchymal markers vimentin and N-cad and an increase in the epithelial marker E-cad. These cells kept mesenchymal markers αSMA and S100A4 and high ALDH activity. Real-time PCR data of the cells after one (BrC4f_Hyp1) and two (BrC4f_Hyp2) rounds of PH showed consistent up-regulation of TWIST1 gene as an early response and ZEB1/2 and SLUG transcriptional activity as a subsequent response. Reversion of BrC4f_Hyp2 cells to normoxia conditions converted them to epithelial-like cells (BrC4e) with decreased expression of EMT genes and up-regulation of MET-related OVOL2 and c-MYC genes. Transplantation of BrC4f and BrC4f_Hyp2 cells into SCID mice showed the acceleration of tumor growth up to 61.6% for BrC4f_Hyp2 cells. To summarize, rounds of PH imitate the MET process of tumorigenesis in which cancer-associated fibroblasts pass through intermediate stages and become more aggressive epithelial-like tumor cells.

Pan-Cancer Analysis and Experimental Validation Identify ACOT7 as a Novel Oncogene and Potential Therapeutic Target in Lung Adenocarcinoma

Background: Acyl-CoA thioesterase 7 (ACOT7) is of great significance in regulating cell cycle, cell proliferation, and glucose metabolism. The function of ACOT7 in pan-cancer and its capacity as a prognostic indicator in lung adenocarcinoma (LUAD) remains unknown. We intended to perform a comprehensive pan-cancer analysis of ACOT7 and to validate its value in LUAD. Methods: The expression levels, prognostic significance, molecular function, signaling pathways, and immune infiltration pattern of ACOT7 in 33 cancers were explored via systematic bioinformatics analysis. Multivariate Cox regression was applied to construct nomograms to predict patients’ prognoses. Moreover, we conducted in vitro experiments including CCK8, scratch, Transwell, and Matrigel assays to further explore the function of ACOT7 in LUAD. Results: Patients with high ACOT7 expression have notably poorer long-term survival in many cancer types, including LUAD. Further enrichment analyses reveal that ACOT7 is involved in immune cells’ infiltration and is substantially related to the cancer−immune microenvironment. ACOT7 could influence drug sensitivities, including afatinib, gefitinib, ibrutinib, lapatinib, osimertinib, sapitinib, taselisib, and PLX-4720 (all p < 0.01). A nomogram demonstrated a fair predictive value of ACOT7 in LUAD (C-index: 0.613, 95% CI: 0.568−0.658). The proliferation and migration of PC9 cells were significantly repressed when ACOT7 expression was downregulated. Conclusion: As an oncogene, ACOT7 is critical in the tumor microenvironment of pan-cancer and might be a novel therapeutic target for LUAD.

Constitutive Activation of the Tumor Suppressor p53 in Hepatocytes Paradoxically Promotes Non-Cell Autonomous Liver Carcinogenesis

In chronic liver diseases (CLD), p53 is constitutively activated in hepatocytes due to various etiologies as viral infection, ethanol exposure, or lipid accumulation. This study was aimed to clarify the significance of p53 activation on the pathophysiology of CLDs. In Kras-mutant liver cancer model, murine double minute 2 (Mdm2), a negative regulator of p53, was specifically deleted in hepatocytes [Alb-Cre KrasLSL-G12D Mdm2fl/fl (LiKM; KrasG12D mutation and Mdm2 loss in the liver)]. Accumulation of p53 and upregulation of its downstream genes were observed in hepatocytes in LiKM mice. LiKM mice showed liver inflammation accompanied by hepatocyte apoptosis, senescence-associated secretory phenotype (SASP), and the emergence of hepatic progenitor cells (HPC). More importantly, Mdm2 deletion promoted non-cell autonomous development of liver tumors. Organoids generated from HPCs harbored tumor-formation ability when subcutaneously inoculated into NOD/Shi-scid/IL2Rγ (null) mice. Treatment with acyclic retinoid suppressed growth of HPCs in vitro and inhibited tumorigenesis in LiKM mice. All of the phenotypes in LiKM mice, including accelerated liver tumorigenesis, were negated by further deletion of p53 in hepatocytes (Alb-Cre KrasLSL-G12D Mdm2fl/fl p53fl/fl). Activation of hepatic p53 was noted in liver biopsy samples obtained from 182 patients with CLD, in comparison with 23 normal liver samples without background liver diseases. In patients with CLD, activity of hepatic p53 was positively correlated with the expression of apoptosis, SASP, HPC-associated genes and tumor incidence in the liver after biopsy. In conclusion, activation of hepatocyte p53 creates a microenvironment prone to tumor formation from HPCs. Optimization of p53 activity in hepatocytes is important to prevent patients with CLD from hepatocarcinogenesis.

SIGNIFICANCE

This study reveals that activation of p53 in hepatocytes promotes liver carcinogenesis derived from HPCs, which elucidates a paradoxical aspect of a tumor suppressor p53 and novel mechanism of liver carcinogenesis. See related commentary by Barton and Lozano, p. 2824.

Whole-Genome Duplication Shapes the Aneuploidy Landscape of Human Cancers

Aneuploidy is a hallmark of cancer with tissue-specific prevalence patterns that suggest it plays a driving role in cancer initiation and progression. However, the contribution of aneuploidy to tumorigenesis depends on both cellular and genomic contexts. Whole-genome duplication (WGD) is a common macroevolutionary event that occurs in more than 30% of human tumors early in tumorigenesis. Although tumors that have undergone WGD are reported to be more permissive to aneuploidy, it remains unknown whether WGD also affects aneuploidy prevalence patterns. Here we analyzed clinical tumor samples from 5,586 WGD- tumors and 3,435 WGD+ tumors across 22 tumor types and found distinct patterns of aneuploidy in WGD- and WGD+ tumors. WGD+ tumors were characterized by more promiscuous aneuploidy patterns, in line with increased aneuploidy tolerance. Moreover, the genetic interactions between chromosome arms differed between WGD- and WGD+ tumors, giving rise to distinct cooccurrence and mutual exclusivity aneuploidy patterns. The proportion of whole-chromosome aneuploidy compared with arm-level aneuploidy was significantly higher in WGD+ tumors, indicating distinct dominant mechanisms for aneuploidy formation. Human cancer cell lines successfully reproduced these WGD/aneuploidy interactions, confirming the relevance of studying this phenomenon in culture. Finally, induction of WGD and assessment of aneuploidy in isogenic WGD-/WGD+ human colon cancer cell lines under standard or selective conditions validated key findings from the clinical tumor analysis, supporting a causal link between WGD and altered aneuploidy landscapes. We conclude that WGD shapes the aneuploidy landscape of human tumors and propose that this interaction contributes to tumor evolution.

SIGNIFICANCE

These findings suggest that the interactions between whole-genome duplication and aneuploidy are important for tumor evolution, highlighting the need to consider genome status in the analysis and modeling of cancer aneuploidy.

Machine Learning: A New Prospect in Multi-Omics Data Analysis of Cancer

Cancer is defined as a large group of diseases that is associated with abnormal cell growth, uncontrollable cell division, and may tend to impinge on other tissues of the body by different mechanisms through metastasis. What makes cancer so important is that the cancer incidence rate is growing worldwide which can have major health, economic, and even social impacts on both patients and the governments. Thereby, the early cancer prognosis, diagnosis, and treatment can play a crucial role at the front line of combating cancer. The onset and progression of cancer can occur under the influence of complicated mechanisms and some alterations in the level of genome, proteome, transcriptome, metabolome etc. Consequently, the advent of omics science and its broad research branches (such as genomics, proteomics, transcriptomics, metabolomics, and so forth) as revolutionary biological approaches have opened new doors to the comprehensive perception of the cancer landscape. Due to the complexities of the formation and development of cancer, the study of mechanisms underlying cancer has gone beyond just one field of the omics arena. Therefore, making a connection between the resultant data from different branches of omics science and examining them in a multi-omics field can pave the way for facilitating the discovery of novel prognostic, diagnostic, and therapeutic approaches. As the volume and complexity of data from the omics studies in cancer are increasing dramatically, the use of leading-edge technologies such as machine learning can have a promising role in the assessments of cancer research resultant data. Machine learning is categorized as a subset of artificial intelligence which aims to data parsing, classification, and data pattern identification by applying statistical methods and algorithms. This acquired knowledge subsequently allows computers to learn and improve accurate predictions through experiences from data processing. In this context, the application of machine learning, as a novel computational technology offers new opportunities for achieving in-depth knowledge of cancer by analysis of resultant data from multi-omics studies. Therefore, it can be concluded that the use of artificial intelligence technologies such as machine learning can have revolutionary roles in the fight against cancer.

Cell fusion as a link between the SARS-CoV-2 spike protein, COVID-19 complications, and vaccine side effects

A distinctive feature of the SARS-CoV-2 spike protein is its ability to efficiently fuse cells, thus producing syncytia found in COVID-19 patients. This commentary proposes how this ability enables spike to cause COVID-19 complications as well as side effects of COVID-19 vaccines, and suggests how these effects can be prevented.