We performed a systematic review with meta-analyses to summarize current knowledge on prognostic factors for invasive disease after a diagnosis of ductal carcinoma in situ (DCIS). Eligible studies assessed risk of invasive recurrence in women primarily diagnosed and treated for DCIS and included at least 10 ipsilateral-invasive breast cancer events and 1 year of follow-up. Quality in Prognosis Studies tool was used for risk of bias assessment. Meta-analyses were performed to estimate the average effect size of the prognostic factors. Of 1,781 articles reviewed, 40 articles met the inclusion criteria. Highest risk of bias was attributable to insufficient handling of confounders and poorly described study groups. Six prognostic factors were statistically significant in the meta-analyses: African-American race [pooled estimate (ES), 1.43; 95% confidence interval (CI), 1.15-1.79], premenopausal status (ES, 1.59; 95% CI, 1.20-2.11), detection by palpation (ES, 1.84; 95% CI, 1.47-2.29), involved margins (ES, 1.63; 95% CI, 1.14-2.32), high histologic grade (ES, 1.36; 95% CI, 1.04-1.77), and high p16 expression (ES, 1.51; 95% CI, 1.04-2.19). Six prognostic factors associated with invasive recurrence were identified, whereas many other factors need confirmation in well-designed studies on large patient numbers. Furthermore, we identified frequently occurring biases in studies on invasive recurrence after DCIS. Avoiding these common methodological pitfalls can improve future study designs.
KRAS is the most frequently mutated oncogene. The incidence of specific KRAS alleles varies between cancers from different sites, but it is unclear whether allelic selection results from biological selection for specific mutant KRAS proteins. We used a cross-disciplinary approach to compare KRAS^G12D, a common mutant form, and KRAS^A146T, a mutant that occurs only in selected cancers. Biochemical and structural studies demonstrated that KRAS^A146T exhibits a marked extension of switch 1 away from the protein body and nucleotide binding site, which activates KRAS by promoting a high rate of intrinsic and guanine nucleotide exchange factor–induced nucleotide exchange. Using mice genetically engineered to express either allele, we found that KRAS^G12D and KRAS^A146T exhibit distinct tissue-specific effects on homeostasis that mirror mutational frequencies in human cancers. These tissue-specific phenotypes result from allele-specific signaling properties, demonstrating that context-dependent variations in signaling downstream of different KRAS mutants drive the KRAS mutational pattern seen in cancer.
Significance: Although epidemiologic and clinical studies have suggested allele-specific behaviors for KRAS, experimental evidence for allele-specific biological properties is limited. We combined structural biology, mass spectrometry, and mouse modeling to demonstrate that the selection for specific KRAS mutants in human cancers from different tissues is due to their distinct signaling properties.
We are in the midst of a renaissance in cancer genetics. Over the past several decades, candidate-based targeted sequencing efforts provided a steady stream of information on the genetic drivers for certain cancer types. However, with recent technological advances in DNA sequencing, this stream has become a torrent of unbiased genetic information revealing the frequencies and patterns of point mutations and copy number variations (CNVs) across the entire spectrum of cancers. One of the most important observations from this work is that genetic alterations in bona fide cancer drivers (those genes that, when mutated, promote tumorigenesis) show a remarkable spectrum of tissue specificity: Alterations in certain driver genes appear only in cancers derived from one or a few tissue types (1). Only a handful of cancer drivers [such as telomerase reverse transcriptase (TERT), TP53, the cyclin-dependent kinase inhibitor 2A (CDKN2A) locus, and MYC] show broad tissue spectrums. Here, we discuss the concept of tissue specificity of genetic alterations in cancer and provide general hypotheses to help explain this biological phenomenon.
Measuring gene expression of tumor clones at single-cell resolution links functional consequences to somatic alterations. Without scalable methods to simultaneously assay DNA and RNA from the same single cell, parallel single-cell DNA and RNA measurements from independent cell populations must be mapped for genome-transcriptome association. We present clonealign, which assigns gene expression states to cancer clones using single-cell RNA and DNA sequencing independently sampled from a heterogeneous population. We apply clonealign to triple-negative breast cancer patient-derived xenografts and high-grade serous ovarian cancer cell lines and discover clone-specific dysregulated biological pathways not visible using either sequencing method alone.
Multiple signatures of somatic mutations have been identified in cancer genomes. Exome sequences of 1,001 human cancer cell lines and 577 xenografts revealed most common mutational signatures, indicating past activity of the underlying processes, usually in appropriate cancer types. To investigate ongoing patterns of mutational-signature generation, cell lines were cultured for extended periods and subsequently DNA sequenced. Signatures of discontinued exposures, including tobacco smoke and ultraviolet light, were not generated in vitro. Signatures of normal and defective DNA repair and replication continued to be generated at roughly stable mutation rates. Signatures of APOBEC cytidine deaminase DNA-editing exhibited substantial fluctuations in mutation rate over time with episodic bursts of mutations. The initiating factors for the bursts are unclear, although retrotransposon mobilization may contribute. The examined cell lines constitute a resource of live experimental models of mutational processes, which potentially retain patterns of activity and regulation operative in primary human cancers.