No abstract

Urothelial cancer has served as one of the most important sources of information about the mutational events that underlie the development of human solid maligancies. Although "field effects" that affect the entire bladder mucosa appear to initiate disease, tumors develop along two distinct biological "tracks" that present vastly different challenges for clinical management. Recent whole genome methodologies have facilitated even more rapid progress in the identification of the molecular mechanisms involved in bladder cancer initiation and progression. Specifically, whole organ mapping combined with high resolution, high throughput SNP analyses have identified a novel class of candidate tumor suppressors ("forerunner genes") that localize near more familiar tumor suppressors but are disrupted at an earlier stage of cancer development. Furthermore, whole genome comparative genomic hybridization (CGH) and mRNA expression profiling have demonstrated that the two major subtypes of urothelial cancer (papillary/superficial and non-papillary/muscle-invasive) are truly distinct molecular entities, and in recent work our group has discovered that muscle-invasive tumors express molecular markers characteristic of a developmental process known as "epithelialto-mesenchymal transition" (EMT). Emerging evidence indicates that urothelial cancers contain subpopulations of tumor-initiating cells ("cancer stem cells") but the phenotypes of these cells in different tumors are heterogeneous, raising questions about whether or not the two major subtypes of cancer share a common precursor. This review will provide an overview of these new insights and discuss priorities for future investigation.

The search for the genomic sequences involved in human cancers can be greatly facilitated by maps of genomic imbalances identifying the involved chromosomal regions, particularly those that participate in the development of occult preneoplastic conditions that progress to clinically aggressive invasive cancer. The integration of such regions with human genome sequence variation may provide valuable clues about their overall structure and gene content. By extension, such knowledge may help us understand the underlying genetic components involved in the initiation and progression of these cancers. We describe the development of a genome-wide map of human bladder cancer that tracks its progression from in situ precursor conditions to invasive disease. Testing for allelic losses using a genome-wide panel of 787 microsatellite markers was performed on multiple DNA samples, extracted from the entire mucosal surface of the bladder and corresponding to normal urothelium, in situ preneoplastic lesions, and invasive carcinoma. Using this approach, we matched the clonal allelic losses in distinct chromosomal regions to specific NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author Manuscript phases of bladder neoplasia and produced a detailed genetic map of bladder cancer development. These analyses revealed three major waves of genetic changes associated with growth advantages of successive clones and reflecting a stepwise conversion of normal urothelial cells into cancer cells. The genetic changes map to six regions at 3q22-q24, 5q22-q31, 9q21-q22, 10q26, 13q14, and 17p13, which may represent critical hits driving the development of bladder cancer. Finally, we performed high-resolution mapping using single nucleotide polymorphism markers within one region on chromosome 13q14, containing the model tumor suppressor gene RB1, and defined a minimal deleted region associated with clonal expansion of in situ neoplasia. These analyses provided new insights on the involvement of several non-coding sequences mapping to the region and identified novel target genes, termed forerunner (FR) genes, involved in early phases of cancer development. Keywordsforerunner genes; whole-organ histologic and genetic mapping; high-resolution mapping with SNPs; dual-track pathway of bladder cancer development; apoptosisWe have developed a strategy to identify genetic hits across the entire mucosa of an affected organ relative to cancer progression, from in situ precursor conditions to invasive disease, on a total genomic scale. We used the approach, which we refer to as whole-organ histologic and genetic mapping (WOHGM), to identify clonal hits associated with growth advantage, thus tracking the development of human bladder cancer from occult in situ lesions. Human bladder carcinoma was used as a model of a common epithelial malignancy that develops by progression of microscopically recognizable intraurothelial preneoplastic conditions known as dysplasia and carcinoma in situ. 1 Carcinoma of the bladder is the fifth most frequent...

Response to neoadjuvant chemotherapy is a significant prognostic factor for osteosarcoma; however, this information can be determined only after surgical resection. If we could predict histologic response before surgery, it might be helpful for the planning of surgeries and tailoring of treatment. We evaluated the usefulness of 18 F-FDG PET for this purpose. Methods: A total of 70 consecutive patients with a high-grade osteosarcoma treated at our institute were prospectively enrolled. All patients underwent 18 F-FDG PET and MRI before and after neoadjuvant chemotherapy. We analyzed the predictive values of 5 parameters, namely, maximum standardized uptake values (SUVs), before and after (SUV2) chemotherapy, SUV change ratio, tumor volume change ratio, and metabolic volume change ratio (MVCR) in terms of their abilities to discriminate responders from nonresponders. Results: Patients with an SUV2 of less than or equal to 2 showed a good histologic response, and patients with an SUV2 of greater than 5 showed a poor histologic response. The histologic response of a patient with an intermediate SUV2 (2 , SUV2 # 5) was found to be predictable using MVCR. A patient with an MVCR of less than 0.65 is likely to be a good responder, whereas a patient with an MVCR of greater than or equal to 0.65 is likely to be a poor responder. According to our model, the predictive values for good responders and poor responders were 97% (31/32) and 95% (36/38), respectively. Conclusion: We found that combined information on 18 F-FDG PET and MRI scans, acquired before and after chemotherapy, could be used to predict histologic response to neoadjuvant chemotherapy in osteosarcoma.

We evaluated the potential of 18 F-FDG PET/CT and diffusionweighted imaging (DWI) to monitor the histologic response in patients with extremity osteosarcoma receiving neoadjuvant chemotherapy, using sequential PET/CT and MR imaging. Methods: We prospectively registered 28 patients with high-grade osteosarcoma treated with 2 cycles of neoadjuvant chemotherapy and surgery. All patients underwent sequential 18 F-FDG PET/CT and MR imaging before (PET/MR1) and after neoadjuvant chemotherapy (PET/MR2). Maximum standardized uptake value (SUV), tumor volume based on MR imaging (MRV), and the mean apparent diffusion coefficient (ADC) values were measured on PET/MR1 (SUV1, MRV1, and ADC1) and PET/MR2 (SUV2, MRV2, and ADC2). The percentage changes in maximum SUV (ΔSUV), MRV (ΔMRV), and ADC (ΔADC) were calculated, and the correlations among these parameters were evaluated. After surgery, the effects of neoadjuvant chemotherapy were graded histopathologically: grades III and IV (necrosis of $ 90%) indicated a good response, and grades I and II (necrosis of , 90%) indicated a poor response. The optimum cutoff values of ΔSUV, ΔMRV, ΔADC, and their combination for predicting histologic response were assessed by single-and multi-receiver-operating-characteristic curve analysis. Results: Twenty-seven patients were enrolled in the present study after 1 patient with inadequate acquisition of MR imaging was excluded. ΔSUV and ΔADC negatively correlated with each other (r 5 20.593, P 5 0.001), and ΔMRV did not correlate with ΔSUV or ΔADC. The cutoff value, sensitivity, specificity, and accuracy for predicting good histologic response were # 252%, 67%, 87%, and 78%, respectively, for ΔSUV and . 13%, 83%, 73%, and 78%, respectively, for ΔADC. However, ΔMRV did not predict histologic response. Sensitivity, specificity, and accuracy were 83%, 87%, and 85%, respectively, using the combined criterion of ΔSUV # 231% and ΔADC . 13%. Conclusion: In the current preliminary study, both PET/CT and DWI are useful for predicting histologic response after neoadjuvant chemotherapy in osteosarcoma. Combining PET/CT and DWI may be an effective method to predict the histologic response of patients to neoadjuvant chemotherapy.

The RANKL-RANK-OPG axis might be a promising target for the treatment of osteosarcoma, but further studies are needed to verify our data in a larger cohort.

No abstract

The necrosis rate adjusted by the tumor volume change is an independent prognostic factor in osteosarcoma. This adjusted tumor necrosis rate may serve as a basis for risk-adapted therapy in combination with other prognostic factors.