Genome wide single cell analysis of chemotherapy resistant metastatic cells in a case of gastroesophageal adenocarcinoma

Single-cell sequencing: a promising approach for uncovering the mechanisms of tumor metastasis

Single-cell sequencing (SCS) is an emerging high-throughput technology that can be used to study the genomics, transcriptomics, and epigenetics at a single cell level. SCS is widely used in the diagnosis and treatment of various diseases, including cancer. Over the years, SCS has gradually become an effective clinical tool for the exploration of tumor metastasis mechanisms and the development of treatment strategies. Currently, SCS can be used not only to analyze metastasis-related malignant biological characteristics, such as tumor heterogeneity, drug resistance, and microenvironment, but also to construct metastasis-related cell maps for predicting and monitoring the dynamics of metastasis. SCS is also used to identify therapeutic targets related to metastasis as it provides insights into the distribution of tumor cell subsets and gene expression differences between primary and metastatic tumors. Additionally, SCS techniques in combination with artificial intelligence (AI) are used in liquid biopsy to identify circulating tumor cells (CTCs), thereby providing a novel strategy for treating tumor metastasis. In this review, we summarize the potential applications of SCS in the field of tumor metastasis and discuss the prospects and limitations of SCS to provide a theoretical basis for finding therapeutic targets and mechanisms of metastasis.

KRAS: A Promising Therapeutic Target for Cancer Treatment

Kirsten rat sarcoma 2 viral oncogene homolog (KRAS) is the most commonly mutated oncogene in human cancer. The developments of many cancers depend on sustained expression and signaling of KRAS, which makes KRAS a high-priority therapeutic target. Scientists have not successfully developed drugs that target KRAS, although efforts have been made last three decades. In this review, we highlight the emerging experimental strategies of impairing KRAS membrane localization and the direct targeting of KRAS. We also conclude the combinatorial therapies and RNA interference technology for the treatment of KRAS mutant cancers. Moreover, the virtual screening approach to discover novel KRAS inhibitors and synthetic lethality interactors of KRAS are discussed in detail.

Somatic DNA Copy-Number Alterations Detection for Esophageal Adenocarcinoma Using Digital Polymerase Chain Reaction

Somatic copy-number alterations are commonly found in cancer and play key roles in activating oncogenes and deactivating tumor suppressor genes. Digital polymerase chain reaction is an effective way to detect the changes in copy number. In esophageal adenocarcinoma, detection of somatic copy-number alterations could predict the prognosis of patients as well as the response to therapy. This chapter will review the methods involved in digital polymerase chain reaction for the research or potential clinical applications in esophageal adenocarcinoma.

Molecular genetics and cellular events of K-Ras-driven tumorigenesis

Cellular transformation and the accumulation of genomic instability are the two key events required for tumorigenesis. K-Ras (Kirsten-rat sarcoma viral oncogene homolog) is a prominent oncogene that has been proven to drive tumorigenesis. K-Ras also modulates numerous genetic regulatory mechanisms and forms a large tumorigenesis network. In this review, we track the genetic aspects of K-Ras signaling networks and assemble the sequence of cellular events that constitute the tumorigenesis process, such as regulation of K-Ras expression (which is influenced by miRNA, small nucleolar RNA and lncRNA), activation of K-Ras (mutations), generation of reactive oxygen species (ROS), induction of DNA damage and apoptosis, induction of DNA damage repair pathways and ROS detoxification systems, cellular transformation after apoptosis by the blebbishield emergency program and the accumulation of genomic/chromosomal instability that leads to tumorigenesis.

Proteomic identification of potential cancer markers in human urine using subtractive analysis

Urine is an ideal medium in which to focus diagnostic cancer research due to the non-invasive nature and ease of sampling. Many large-scale proteomic studies have shown that urine is unexpectedly complex. We hypothesised that novel diagnostic cancer biomarkers could be discovered using a comparative proteomic analysis of pre-existing data. We assembled a database of 100 published datasets of 5,620 urinary proteins, as well as 46 datasets of 8,620 non-redundant proteins derived from kidney and blood proteome analyses. The data were then used to either subtract or compare molecules from a novel urinary proteome profiling dataset that we generated. We identified 1,161 unique proteins in samples from either cancer-bearing or healthy subjects. Subtractive analysis yielded a subset of 44 proteins that were found uniquely in urine from cancer patients, 30 of which were linked previously to cancer. In conclusion, this approach is useful in discovering novel biomarkers in tissues where unrelated profiling data is available. Only a limited disease-specific novel dataset is required to define new targets or substantiate previous findings. We have shared this discovery platform in the form of our Large Scale Screening Resource database, accessible through the Proteomic Analysis DataBase portal (www.PADB.org).

Analysis of Copy-Number Alterations in Single Cells Using Microarray-Based Comparative Genomic Hybridization (aCGH)

In this unit, we describe a workflow that enables array comparative genomic hybridization (aCGH) of single cells. The unit first describes the isolation and preparation of single peripheral mononuclear cells from blood (PBMC) to prepare a suitable reference DNA for aCGH experiments. An alternative procedure is described for the preparation of single cells of GM14667 and GM05423 cell lines to use as reference DNA and for sex-mismatched control experiments. A guide is also provided for micromanipulation of single cells. Next, the unit describes whole-genome amplification using adapter-linker PCR (Ampli1 WGA Kit) and an alternative nonlinear WGA method (PicoPLEX WGA Kit) for single-cell amplification. A protocol is also included for reamplification of Ampli1 WGA products, which can be used for aCGH as well. Finally, the use of 4 × 180k oligonucleotide microarrays to perform aCGH with single-cell WGA products is described.

A robust method to analyze copy number alterations of less than 100 kb in single cells using oligonucleotide array CGH

Comprehensive genome wide analyses of single cells became increasingly important in cancer research, but remain to be a technically challenging task. Here, we provide a protocol for array comparative genomic hybridization (aCGH) of single cells. The protocol is based on an established adapter-linker PCR (WGAM) and allowed us to detect copy number alterations as small as 56 kb in single cells. In addition we report on factors influencing the success of single cell aCGH downstream of the amplification method, including the characteristics of the reference DNA, the labeling technique, the amount of input DNA, reamplification, the aCGH resolution, and data analysis. In comparison with two other commercially available non-linear single cell amplification methods, WGAM showed a very good performance in aCGH experiments. Finally, we demonstrate that cancer cells that were processed and identified by the CellSearch® System and that were subsequently isolated from the CellSearch® cartridge as single cells by fluorescence activated cell sorting (FACS) could be successfully analyzed using our WGAM-aCGH protocol. We believe that even in the era of next-generation sequencing, our single cell aCGH protocol will be a useful and (cost-) effective approach to study copy number alterations in single cells at resolution comparable to those reported currently for single cell digital karyotyping based on next generation sequencing data.