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Summary: Oncoproteins such as the BRAFV600E kinase endow cancer cells with malignant properties, but they also create unique vulnerabilities. Targeting of BRAFV600E-driven cytoplasmic signaling networks has proved ineffective, as patients regularly relapse with reactivation of the targeted pathways. We identify the nuclear protein SFPQ to be synthetically lethal with BRAFV600E in a loss-of-function shRNA screen. SFPQ depletion decreases proliferation and specifically induces S-phase arrest and apoptosis in BRAFV600E-driven colorectal and melanoma cells. Mechanistically, SFPQ loss in BRAF-mutant cancer cells triggers the Chk1-dependent replication checkpoint, results in decreased numbers and reduced activities of replication factories, and increases collision between replication and transcription. We find that BRAFV600E-mutant cancer cells and organoids are sensitive to combinations of Chk1 inhibitors and chemically induced replication stress, pointing toward future therapeutic approaches exploiting nuclear vulnerabilities induced by BRAFV600E.

The most fascinating aspect of transcriptomics is that the entire set of RNA molecules or transcripts (messenger RNAs, microRNAs, long noncoding RNAs) produced in a population of cells or in tissues can be analyzed simultaneously. While capturing transcript abundance on genome-wide level has become a routine task thanks to high-throughput technologies, analyzing the transcriptome continues to be a challenging task, since the RNA content of a biological entity is heterogeneous and can vary substantially. The abundance of individual transcripts varies from a few copies to hundreds or thousands of copies per cell. The kind and copy numbers of individual transcripts expressed at a given time depend on the developmental stage, external conditions, and environmental stimuli. Quantitative and qualitative alterations of RNAs can be directly linked to the molecular mechanism of disease, reflect the downstream consequences of these disease processes, or even possess prognostic and predictive value.

The hallmarks of cancer capture the most essential phenotypic characteristics of malignant transformation and progression. Although numerous factors involved in this multi-step process are still unknown to date, an ever-increasing number of mutated/altered candidate genes are being identified within large-scale cancer genomic projects. Therefore, investigators need to be aware of available and appropriate techniques capable of determining characteristic features of each hallmark. We review the methods tailored to experimental cancer researchers to evaluate cell proliferation, programmed cell death, replicative immortality, induction of angiogenesis, invasion and metastasis, genome instability, and reprogramming of energy metabolism. Selecting the ideal method is based on the investigator's goals, available equipment and also on financial constraints. Multiplexing strategies enable a more in-depth data collection from a single experiment — obtaining several results from a single procedure reduces variability and saves time and relative cost, leading to more robust conclusions compared to a single end point measurement. Each hallmark possesses characteristics that can be analyzed by immunoblot, RT-PCR, immunocytochemistry, immunoprecipitation, RNA microarray or RNA-seq. In general, flow cytometry, fluorescence microscopy, and multiwell readers are extremely versatile tools and, with proper sample preparation, allow the detection of a vast number of hallmark features. Finally, we also provide a list of hallmark-specific genes to be measured in transcriptome-level studies. Although our list is not exhaustive, we provide a snapshot of the most widely used methods, with an emphasis on methods enabling the simultaneous evaluation of multiple hallmark features.

Publisher Summary The most fascinating aspect of transcriptomics is that the entire set of messenger RNA (mRNA) molecules or transcripts produced in a population of cells or in tissues can be analyzed simultaneously. The present microarray technology produces devices equivalent to the size of a stamp for gene expression profiling. Analyzing the transcriptome is a challenging task, since the mRNA content of a biological entity is heterogeneous and can vary substantially. The abundance of individual transcripts varies from a few copies to hundreds or thousands of copies per cell. The kinds and copy numbers of individual transcripts expressed at a given time depend on the developmental stage, on external conditions, and environmental stimuli. Quantitative and qualitative alterations of mRNAs can be directly linked to the molecular mechanism of disease or reflect the downstream consequences of these disease processes. This chapter outlines the methodological prerequisites for transcriptome analysis and describes typical applications in molecular cell biology and pathology.

Many signal transduction processes converge on Ras proteins that serve as molecular switches to couple external stimuli with cytoplasmic and nuclear targets. Oncogenic mutations lock Ras proteins in their activated state. Cellular responses to permanent Ras activation such as the induction of neoplastic phenotypes are mediated by distinct transcriptional alterations. A number of studies have reported alterations of the genetic program because of short‐term or long‐term activation of Ras signaling pathways. However, a consistent pattern of Ras‐related transcriptional alterations has not yet emerged, because currently available investigations were based on different methods for assessing mRNA expression profiles, on different types of cells, and on heterogeneous experimental conditions. Here we describe the “Ras signaling target array” (RASTA) representing approximately 300 Ras‐responsive target genes. This customized oligonucleotide array is a universal tool for assessing transcriptional patterns of cells or tissues expressing oncogenic Ras genes, as well as upstream and downstream effectors. To validate the results obtained by array‐based expression profiling, we have compared the data with those obtained by suppression subtractive hybridization and conventional expression analysis by Northern blotting. Target RNAs were prepared from preneoplastic rat ovarian surface epithelial cells (ROSE) and the KRAS‐transformed derivative A2/5. By interrogating Ras signaling target arrays with mRNAs prepared from the same types of cells as hybridization target, we correctly recognized 85% of genes differentially expressed on conversion of normal ovarian epithelial cells to the Ras‐transformed state.