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We aimed to identify common mCRC profiles associated with a discordant mutational status of RAS between the standard of care (SoC) tumour tissue tests and ctDNA tests to understand ctDNA detection and improve treatment responses. This was a multicentre, retrospective and prospective study. A total of 366 Spanish mCRC patients were independently recruited. BEAMing ddPCR technology was employed to detect ctDNA RAS mutations, and logistic regression analyses were performed to investigate clinicopathological factors associated with discordance. The highest concordance ratios were observed in profiles with multiple metastatic sites when the liver was present (89.7%; 95% CI 84.8-93.2), profiles with synchronous disease without primary tumour resection (90.2%; 95% CI 83.6-94.3) and profiles with mCRC originating in the left colon (91.3%; 95% CI 85.0-95.0). Metachronous disease originating in the right colon (OR = 6.1; 95% CI 1.7-26.5; p -value = 0.006) or rectum (OR = 5.0; 95% CI 1.5-17.8; p -value = 0.009) showed the highest probability of discrepancies. Primary tumour resection and a higher frequency of single metastases in the peritoneum or lungs in these patients were associated with reduced plasmatic mutation allele fractions (MAFs) and an increased probability of showing false-negative genotypes. Additional testing of patients with mCRC originating in the right colon or rectum with a single non-mutated ctDNA test is advised before the choice of therapy.

Competing Interests: The authors declare that there are no competing interests.

Molecular profiling of circulating cell-free DNA (cfDNA) has shown utility for the management of colorectal cancer (CRC). TruSight Tumor 170 (TST170) is a next-generation sequencing (NGS) panel that covers 170 cancer-related genes, including KRAS , which is a key driver gene in CRC. We evaluated the capacity of TST170 to detect gene variants in cfDNA from a retrospective cohort of 20 metastatic CRC patients with known KRAS variants in tumor tissue and in cfDNA previously analyzed by pyrosequencing and BEAMing, respectively. The cfDNA of most of the patients (95%) was successfully sequenced. We frequently detected variants with clinical significance in KRAS (79%, 15/19) and PIK3CA (26%, 5/19) genes. Variants with potential clinical significance were also identified in another 27 cancer genes, such as APC . The type of KRAS variant detected in cfDNA by TST170 showed high concordance with those detected in tumor tissue (77%), and very high concordance with cfDNA analyzed by BEAMing (94%). The variant allele fractions for KRAS obtained in cfDNA by TST170 and BEAMing correlated strongly. This proof-of-principle study indicates that targeted NGS analysis of cfDNA with TST170 could be useful for non-invasive detection of gene variants in metastatic CRC patients, providing an assay that could be easily implemented for detecting somatic alterations in the clinic.

Multi-omics approaches use a diversity of high-throughput technologies to profile the different molecular layers of living cells. Ideally, the integration of this information should result in comprehensive systems models of cellular physiology and regulation. However, most multi-omics projects still include a limited number of molecular assays and there have been very few multi-omic studies that evaluate dynamic processes such as cellular growth, development and adaptation. Hence, we lack formal analysis methods and comprehensive multi-omics datasets that can be leveraged to develop true multi-layered models for dynamic cellular systems. Here we present the STATegra multi-omics dataset that combines measurements from up to 10 different omics technologies applied to the same biological system, namely the well-studied mouse pre-B-cell differentiation. STATegra includes high-throughput measurements of chromatin structure, gene expression, proteomics and metabolomics, and it is complemented with single-cell data. To our knowledge, the STATegra collection is the most diverse multi-omics dataset describing a dynamic biological system.

The differentiation of self-renewing progenitor cells requires not only the regulation of lineage- and developmental stage-specific genes but also the coordinated adaptation of housekeeping functions from a metabolically active, proliferative state toward quiescence. How metabolic and cell-cycle states are coordinated with the regulation of cell type-specific genes is an important question, because dissociation between differentiation, cell cycle, and metabolic states is a hallmark of cancer. Here, we use a model system to systematically identify key transcriptional regulators of Ikaros-dependent B cell-progenitor differentiation. We find that the coordinated regulation of housekeeping functions and tissue-specific gene expression requires a feedforward circuit whereby Ikaros down-regulates the expression of Myc. Our findings show how coordination between differentiation and housekeeping states can be achieved by interconnected regulators. Similar principles likely coordinate differentiation and housekeeping functions during progenitor cell differentiation in other cell lineages., Competing Interests: The authors have declared that no competing interests exist.

Ikaros family DNA-binding proteins are critical regulators of B-cell development. Because the current knowledge of Ikaros targets in B-cell progenitors is limited, we have identified genes that are bound and regulated by Ikaros in pre-B cells. To elucidate the role of Ikaros in B-cell lineage specification and differentiation, we analyzed the differential expression of Ikaros targets during the progression of multipotent to lymphoid-restricted progenitors, B- and T-cell lineage specification, and progression along the B-cell lineage. Ikaros targets accounted for one-half of all genes up-regulated during B-cell lineage specification in vivo, explaining the essential role of Ikaros in this process. Expression of the Ikaros paralogs Ikzf1 and Ikzf3 increases incrementally during B-cell progenitor differentiation, and, remarkably, inducible Ikaros expression in cycling pre-B cells was sufficient to drive transcriptional changes resembling the differentiation of cycling to resting pre-Bcells in vivo. The data suggest that Ikaros transcription factor dosage drives the progression of progenitors along a predetermined lineage by regulating multiple targets in key pathways, including pre-B–cell receptor signaling, cell cycle progression, and lymphocyte receptor rearrangement.Our approachmay be of general use to map the contribution of transcription factors to cell lineage commitment and differentiation.