Background The identification of high-risk stage II colon cancers is key to the selection of patients who require adjuvant treatment after surgery. Microarray-based multigene-expression signatures derived from stem cells and progenitor cells hold promise, but they are difficult to use in clinical practice. Methods We used a new bioinformatics approach to search for biomarkers of colon epithelial differentiation across gene-expression arrays and then ranked candidate genes according to the availability of clinical-grade diagnostic assays. With the use of subgroup analysis involving independent and retrospective cohorts of patients with stage II or stage III colon cancer, the top candidate gene was tested for its association with disease-free survival and a benefit from adjuvant chemotherapy. Results The transcription factor CDX2 ranked first in our screening test. A group of 87 of 2115 tumor samples (4.1%) lacked CDX2 expression. In the discovery data set, which included 466 patients, the rate of 5-year disease-free survival was lower among the 32 patients (6.9%) with CDX2-negative colon cancers than among the 434 (93.1%) with CDX2-positive colon cancers (hazard ratio for disease recurrence, 3.44; 95% confidence interval [CI], 1.60 to 7.38; P = 0.002). In the validation data set, which included 314 patients, the rate of 5-year disease-free survival was lower among the 38 patients (12.1%) with CDX2 protein–negative colon cancers than among the 276 (87.9%) with CDX2 protein–positive colon cancers (hazard ratio, 2.42; 95% CI, 1.36 to 4.29; P = 0.003). In both these groups, these findings were independent of the patient's age, sex, and tumor stage and grade. Among patients with stage II cancer, the difference in 5-year disease-free survival was significant both in the discovery data set (49% among 15 patients with CDX2-negative tumors vs. 87% among 191 patients with CDX2-positive tumors, P = 0.003) and in the validation data set (51% among 15 patients with CDX2-negative tumors vs. 80% among 106 patients with CDX2-positive tumors, P = 0.004). In a pooled database of all patient cohorts, the rate of 5-year disease-free survival was higher among 23 patients with stage II CDX2-negative tumors who were treated with adjuvant chemotherapy than among 25 who were not treated with adjuvant chemotherapy (91% vs. 56%, P = 0.006). Conclusions Lack of CDX2 expression identified a subgroup of patients with high-risk stage II colon cancer who appeared to benefit from adjuvant chemotherapy. (Funded by the National Comprehensive Cancer Network, the National Institutes of Health, and others.)
Tuberculosis (TB) in humans is characterized by formation of immune-rich granulomas in infected tissues, the architecture and composition of which are thought to affect disease outcome. However, our understanding of the spatial relationships that control human granulomas is limited. Here, we used multiplexed ion beam imaging by time of flight (MIBI-TOF) to image 37 proteins in tissues from patients with active TB. We constructed a comprehensive atlas that maps 19 cell subsets across 8 spatial microenvironments. This atlas shows an IFN-γ-depleted microenvironment enriched for TGF-β, regulatory T cells and IDO1+ PD-L1+ myeloid cells. In a further transcriptomic meta-analysis of peripheral blood from patients with TB, immunoregulatory trends mirror those identified by granuloma imaging. Notably, PD-L1 expression is associated with progression to active TB and treatment response. These data indicate that in TB granulomas, there are local spatially coordinated immunoregulatory programs with systemic manifestations that define active TB.
Molecular characterization of cell types using single-cell transcriptome sequencing is revolutionizing cell biology and enabling new insights into the physiology of human organs. We created a human reference atlas comprising nearly 500,000 cells from 24 different tissues and organs, many from the same donor. This atlas enabled molecular characterization of more than 400 cell types, their distribution across tissues, and tissue-specific variation in gene expression. Using multiple tissues from a single donor enabled identification of the clonal distribution of T cells between tissues, identification of the tissue-specific mutation rate in B cells, and analysis of the cell cycle state and proliferative potential of shared cell types across tissues. Cell type–specific RNA splicing was discovered and analyzed across tissues within an individual.
Purpose Leiomyosarcoma (LMS) is a malignant neoplasm with smooth muscle differentiation. Little is known about its molecular heterogeneity and no targeted therapy currently exists for LMS. Recognition of different molecular subtypes is necessary to evaluate novel therapeutic options. In a previous study on 51 LMS, we identified three molecular subtypes in LMS. The current study was performed to determine whether the existence of these subtypes could be confirmed in independent cohorts. Experimental Design 99 cases of LMS were expression profiled with 3′end RNA-Sequencing (3SEQ). Consensus Clustering was conducted to determine the optimal number of subtypes. Results We identified 3 LMS molecular subtypes and confirmed this finding by analyzing publically available data on 82 LMS from The Cancer Genome Atlas (TCGA). We identified two new FFPE tissue-compatible diagnostic immunohistochemical markers; LMOD1 for subtype I LMS and ARL4C for subtype II LMS. An LMS tissue microarray with known clinical outcome was used to show that subtype I LMS is associated with good outcome in extrauterine LMS while subtype II LMS is associated with poor prognosis in both uterine and extrauterine LMS. The LMS subtypes showed significant differences in expression levels for genes for which novel targeted therapies are being developed, suggesting that LMS subtypes may respond differentially to these targeted therapies. Conclusion We confirm the existence of 3 molecular subtypes in LMS using two independent datasets and show that the different molecular subtypes are associated with distinct clinical outcomes. The findings offer an opportunity for treating LMS in a subtype-specific targeted approach.
The clinical utility of circulating tumor DNA (ctDNA) monitoring has been shown in tumors that harbor highly recurrent mutations. Leiomyosarcoma represents a type of tumor with a wide spectrum of heterogeneous genomic abnormalities; thus, targeting hotspot mutations or a narrow genomic region for ctDNA detection may not be practical. Here, we demonstrate a combinatorial approach that integrates different sequencing protocols for the orthogonal detection of single-nucleotide variants (SNV), small indels, and copy-number alterations (CNA) in ctDNA. We employed Cancer Personalized Profiling by deep Sequencing (CAPP-Seq) for the analysis of SNVs and indels, together with a genome-wide interrogation of CNAs by Genome Representation Profiling (GRP). We profiled 28 longitudinal plasma samples and 25 tumor specimens from 7 patients with leiomyosarcoma. We detected ctDNA in 6 of 7 of these patients with >98% specificity for mutant allele fractions down to a level of 0.01%. We show that results from CAPP-Seq and GRP are highly concordant, and the combination of these methods allows for more comprehensive monitoring of ctDNA by profiling a wide spectrum of tumor-specific markers. By analyzing multiple tumor specimens in individual patients obtained from different sites and at different times during treatment, we observed clonal evolution of these tumors that was reflected by ctDNA profiles. Our strategy allows for the comprehensive monitoring of a broad spectrum of tumor-specific markers in plasma. Our approach may be clinically useful not only in leiomyosarcoma but also in other tumor types that lack recurrent genomic alterations. .
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