Dataset Information

Temporal dissection of tumorigenesis in primary cancers.

ABSTRACT: Timely intervention for cancer requires knowledge of its earliest genetic aberrations. Sequencing of tumors and their metastases reveals numerous abnormalities occurring late in progression. A means to temporally order aberrations in a single cancer, rather than inferring them from serially acquired samples, would define changes preceding even clinically evident disease. We integrate DNA sequence and copy number information to reconstruct the order of abnormalities as individual tumors evolve for 2 separate cancer types. We detect vast, unreported expansion of simple mutations sharply demarcated by recombinative loss of the second copy of TP53 in cutaneous squamous cell carcinomas (cSCC) and serous ovarian adenocarcinomas, in the former surpassing 50 mutations per megabase. In cSCCs, we also report diverse secondary mutations in known and novel oncogenic pathways, illustrating how such expanded mutagenesis directly promotes malignant progression. These results reframe paradigms in which TP53 mutation is required later, to bypass senescence induced by driver oncogenes.

SUBMITTER: Durinck S

PROVIDER: S-EPMC3187561 | biostudies-literature | 2011 Jul

REPOSITORIES: biostudies-literature

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Temporal dissection of tumorigenesis in primary cancers.

Durinck Steffen S Ho Christine C Wang Nicholas J NJ Liao Wilson W Jakkula Lakshmi R LR Collisson Eric A EA Pons Jennifer J Chan Sai-Wing SW Lam Ernest T ET Chu Catherine C Park Kyunghee K Hong Sung-woo SW Hur Joe S JS Huh Nam N Neuhaus Isaac M IM Yu Siegrid S SS Grekin Roy C RC Mauro Theodora M TM Cleaver James E JE Kwok Pui-Yan PY LeBoit Philip E PE Getz Gad G Cibulskis Kristian K Aster Jon C JC Huang Haiyan H Purdom Elizabeth E Li Jian J Bolund Lars L Arron Sarah T ST Gray Joe W JW Spellman Paul T PT Cho Raymond J RJ

Cancer discovery 20110629 2

Timely intervention for cancer requires knowledge of its earliest genetic aberrations. Sequencing of tumors and their metastases reveals numerous abnormalities occurring late in progression. A means to temporally order aberrations in a single cancer, rather than inferring them from serially acquired samples, would define changes preceding even clinically evident disease. We integrate DNA sequence and copy number information to reconstruct the order of abnormalities as individual tumors evolve fo ...[more]

PMID: 21984974

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Project description:BackgroundSecond primary cancers (SPCs) are increasing due to improving survival in first primary cancers. Previous studies on SPCs in renal cell carcinoma (RCC) have focused on treatment and other risk factors, but data of RCC as an SPC are scarce.ObjectiveIn this study, we want to elucidate the risk for any SPC after RCC, and in reverse order, for RCC as an SPC after any cancer. We additionally consider how family histories influence the risks.Design setting and participantsPatient data were obtained from the Swedish Cancer Registry from years 1990 through 2015, and family data were obtained from the Multigeneration Register.Outcome measurements and statistical analysisWe employed standardized incidence ratios to estimate bidirectional relative risks of subsequent cancer associated with RCC.Results and limitationsWe identified 17 587 RCCs (60% in male patients). The highest increases for SPCs were observed for nervous system hemangioblastoma (HB; 26.8), adrenal (12.09) tumors, and renal pelvic cancer (6.32). In the reverse order, RCC as an SPC, nervous system HB (17.01), and adrenal tumors (15.34) were associated with the highest risks. Risks for many other sites (12 sites and subsites) were increased bidirectionally. For women, a total of seven sites and subsites were increased bidirectionally, and many were shared with men. The only significant sex difference in SPCs was the higher lung cancer risk in women (2.41) than in men (1.28). Patients with a family history of HBs or of prostate, colorectal and lung cancers showed high risks of these cancers as SPCs after RCC. Family history accounted for 30% of prostate cancers after RCC.ConclusionsThe bidirectional study design was able to suggest risk factors for SPCs and offered a clinical take-home message urging to consider strategies for early detection and prevention of SPCs. Readily available information on lifestyle (eg, smoking) and family history (eg, prostate cancer) may reveal targets for risk reduction with prognostic benefits.Patient summaryClose to 10% of kidney cancer patients develop another cancer. The cause for these other cancers may not depend on kidney cancer.

Project description:PurposeWe developed an original, computer-aided diagnosis (CAD) software that subtracts the initial thoracic vertebral three-dimensional computed tomography (3D-CT) image from the follow-up 3D-CT image. The aim of this study was to investigate the efficacy of this CAD software during screening for vertebral metastases on follow-up CT images of primary lung cancer patients.Materials and methodsThe interpretation experiment included 30 sets of follow-up CT scans in primary lung cancer patients and was performed by two readers (readers A and B), who each had 2.5 years' experience reading CT images. In 395 vertebrae from C6 to L3, 46 vertebral metastases were identified as follows: osteolytic metastases (n = 17), osteoblastic metastases (n = 14), combined osteolytic and osteoblastic metastases (n = 6), and pathological fractures (n = 9). Thirty-six lesions were in the anterior component (vertebral body), and 10 lesions were in the posterior component (vertebral arch, transverse process, and spinous process). The area under the curve (AUC) by receiver operating characteristic (ROC) curve analysis and the sensitivity and specificity for detecting vertebral metastases were compared with and without CAD for each observer.ResultsReader A detected 47 abnormalities on CT images without CAD, and 33 of them were true-positive metastatic lesions. Using CAD, reader A detected 57 abnormalities, and 38 were true positives. The sensitivity increased from 0.717 to 0.826, and on ROC curve analysis, AUC with CAD was significantly higher than that without CAD (0.849 vs. 0.902, p = 0.021). Reader B detected 40 abnormalities on CT images without CAD, and 36 of them were true-positive metastatic lesions. Using CAD, reader B detected 44 abnormalities, and 39 were true positives. The sensitivity increased from 0.783 to 0.848, and AUC with CAD was nonsignificantly higher than that without CAD (0.889 vs. 0.910, p = 0.341). Both readers detected more osteolytic and osteoblastic metastases with CAD than without CAD.ConclusionOur temporal 3D-CT subtraction CAD software easily detected vertebral metastases on the follow-up CT images of lung cancer patients regardless of the osteolytic or osteoblastic nature of the lesions.

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Temporal dissection of tumorigenesis in primary cancers.

Publications

Temporal dissection of tumorigenesis in primary cancers.

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