138 research outputs found
Routine computed tomography after recent operative exploration for penetrating trauma
BACKGROUND Patients with penetrating trauma who cannot be stabilized undergo operative intervention without preoperative imaging. In such cases, postoperative imaging may reveal additional injuries not identified during the initial operative exploration. The purpose of this study is to explore the utility of postoperative CT imaging in the setting of penetrating trauma. METHODS This was a retrospective analysis of patients with penetrating trauma treated at an urban Level 1 trauma center between 2010 and 2015. Patients were included if they underwent an emergent laparotomy without preoperative imaging. Patients were excluded if they had prior imaging or concomitant blunt injury. For the purposes of this study, occult injury was defined as a CT scan finding not mentioned in the first operative report. Descriptive statistics were used to compare patient characteristics who had received imaging immediately postoperatively with those who had not. RESULTS During the 5-year study period, 328 patients who had a laparotomy for penetrating trauma over the study period, 225 patients met the inclusion criteria. Seventy-three (32%) patients underwent CT scanning immediately postoperatively with occult injuries identified in 38 (52%) patients. The most frequent occult injuries were orthopedic (20 of 43) and genitourinary (9 of 43). Importantly, 10 (26%) of the 38 patients required an intervention for these occult injuries. Those selected for immediate postoperative imaging were more likely to have sustained gunshot wounds and were significantly more severely injured (higher Injury Severity Score and longer length of hospital stay) when compared to patients who did not receive immediate imaging. CONCLUSION We recommend the use of immediate postoperative CT after emergent laparotomy especially when there is a high index of suspicion for spine or genitourinary injuries and in patients who have sustained ballistic penetrating injuries. LEVEL OF EVIDENCE Therapeutic/care management, level IV diagnostic tests or criteria, level IV
Early Detection of t(8;21) Chromosomal Translocations During Treatment of PML-RARA Positive Acute Promyelocytic Leukemia: A Case Study
Here we describe a female patient who developed acute promyelocytic leukemia (APL) characterized by t(l5;17) translocation at diagnosis. The patient began treatment with all-trans retinoic acid (ATRA) + chemotherapy. During follow up, the patient was found to be negative for the t(15;17) transcript after 3 months of therapy which remained undetectable, thereafter. However, the emergence of a small clone with a t(8;21) abnormality was observed in the bone marrow and peripheral blood (PB) cells between 3 and 18 months following treatment initiation. The abnormal translocation observed in PB cells obtained at 3 months was detected after the second cycle of consolidation therapy and reappeared at 15 months during maintenance treatment, a period without ATRA. Although based on a single case, we conclude that genetic screening of multiple translocations in AML patients should be requested to allow early identification of other emerging clones during therapy that may manifest clinically following treatment
An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics
For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types
Efeitos da escarificação quĂmica e da concentração de nitrogĂŞnio sobre a germinação e o desenvolvimento in vitro de Vanilla planifolia Jack ex Andr. (Orchidaceae: Vanilloideae)
Concentrações de sais do meio Knudson C e de ácido giberĂ©lico no crescimento in vitro de plântulas de orquĂdea
Driver Fusions and Their Implications in the Development and Treatment of Human Cancers.
Gene fusions represent an important class of somatic alterations in cancer. We systematically investigated fusions in 9,624 tumors across 33 cancer types using multiple fusion calling tools. We identified a total of 25,664 fusions, with a 63% validation rate. Integration of gene expression, copy number, and fusion annotation data revealed that fusions involving oncogenes tend to exhibit increased expression, whereas fusions involving tumor suppressors have the opposite effect. For fusions involving kinases, we found 1,275 with an intact kinase domain, the proportion of which varied significantly across cancer types. Our study suggests that fusions drive the development of 16.5% of cancer cases and function as the sole driver in more than 1% of them. Finally, we identified druggable fusions involving genes such as TMPRSS2, RET, FGFR3, ALK, and ESR1 in 6.0% of cases, and we predicted immunogenic peptides, suggesting that fusions may provide leads for targeted drug and immune therapy
The Cancer Genome Atlas Comprehensive Molecular Characterization of Renal Cell Carcinoma
Renal cell carcinoma(RCC) is not a single disease, but several histologically defined cancers with different genetic drivers, clinical courses, and therapeutic responses. The current study evaluated 843 RCC from the three major histologic subtypes, including 488 clear cell RCC, 274 papillary RCC, and 81 chromophobe RCC. Comprehensive genomic and phenotypic analysis of the RCC subtypes reveals distinctive features of each subtype that provide the foundation for the development of subtype-specific therapeutic and management strategies for patients affected with these cancers. Somatic alteration of BAP1, PBRM1, and PTEN and altered metabolic pathways correlated with subtype-specific decreased survival, while CDKN2A alteration, increased DNA hypermethylation, and increases in the immune-related Th2 gene expression signature correlated with decreased survival within all major histologic subtypes. CIMP-RCC demonstrated an increased immune signature, and a uniform and distinct metabolic expression pattern identified a subset of metabolically divergent (MD) ChRCC that associated with extremely poor survival
Cell-of-Origin Patterns Dominate the Molecular Classification of 10,000 Tumors from 33 Types of Cancer
We conducted comprehensive integrative molecular analyses of the complete set of tumors in The Cancer Genome Atlas (TCGA), consisting of approximately 10,000 specimens and representing 33 types of cancer. We performed molecular clustering using data on chromosome-arm-level aneuploidy, DNA hypermethylation, mRNA, and miRNA expression levels and reverse-phase protein arrays, of which all, except for aneuploidy, revealed clustering primarily organized by histology, tissue type, or anatomic origin. The influence of cell type was evident in DNA-methylation-based clustering, even after excluding sites with known preexisting tissue-type-specific methylation. Integrative clustering further emphasized the dominant role of cell-of-origin patterns. Molecular similarities among histologically or anatomically related cancer types provide a basis for focused pan-cancer analyses, such as pan-gastrointestinal, pan-gynecological, pan-kidney, and pan-squamous cancers, and those related by stemness features, which in turn may inform strategies for future therapeutic development. Comprehensive, integrated molecular analysis identifies molecular relationships across a large diverse set of human cancers, suggesting future directions for exploring clinical actionability in cancer treatment
A Comprehensive Pan-Cancer Molecular Study of Gynecologic and Breast Cancers
We analyzed molecular data on 2,579 tumors from The Cancer Genome Atlas (TCGA) of four gynecological types plus breast. Our aims were to identify shared and unique molecular features, clinically significant subtypes, and potential therapeutic targets. We found 61 somatic copy-number alterations (SCNAs) and 46 significantly mutated genes (SMGs). Eleven SCNAs and 11 SMGs had not been identified in previous TCGA studies of the individual tumor types. We found functionally significant estrogen receptor-regulated long non-coding RNAs (lncRNAs) and gene/lncRNA interaction networks. Pathway analysis identified subtypes with high leukocyte infiltration, raising potential implications for immunotherapy. Using 16 key molecular features, we identified five prognostic subtypes and developed a decision tree that classified patients into the subtypes based on just six features that are assessable in clinical laboratories. By performing molecular analyses of 2,579 TCGA gynecological (OV, UCEC, CESC, and UCS) and breast tumors, Berger et al. identify five prognostic subtypes using 16 key molecular features and propose a decision tree based on six clinically assessable features that classifies patients into the subtypes
Somatic Mutational Landscape of Splicing Factor Genes and Their Functional Consequences across 33 Cancer Types
Hotspot mutations in splicing factor genes have been recently reported at high frequency in hematological malignancies, suggesting the importance of RNA splicing in cancer. We analyzed whole-exome sequencing data across 33 tumor types in The Cancer Genome Atlas (TCGA), and we identified 119 splicing factor genes with significant non-silent mutation patterns, including mutation over-representation, recurrent loss of function (tumor suppressor-like), or hotspot mutation profile (oncogene-like). Furthermore, RNA sequencing analysis revealed altered splicing events associated with selected splicing factor mutations. In addition, we were able to identify common gene pathway profiles associated with the presence of these mutations. Our analysis suggests that somatic alteration of genes involved in the RNA-splicing process is common in cancer and may represent an underappreciated hallmark of tumorigenesis
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