1 / 25

G. Lahat, B. Wang, D. Tuvin, DA. Anaya, C. Wei, B. Bekele, KD. Smith, AJ. Lazar, PW. Pisters,

Clinical variables, pathological factors, and molecular markers for enhanced soft tissue sarcoma prognostication. G. Lahat, B. Wang, D. Tuvin, DA. Anaya, C. Wei, B. Bekele, KD. Smith, AJ. Lazar, PW. Pisters, RE. Pollock, D. Lev Sarcoma Research Center UT MD Anderson Cancer Center

kisha
Download Presentation

G. Lahat, B. Wang, D. Tuvin, DA. Anaya, C. Wei, B. Bekele, KD. Smith, AJ. Lazar, PW. Pisters,

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Clinical variables, pathological factors, and molecular markers for enhanced soft tissue sarcoma prognostication G. Lahat, B. Wang, D. Tuvin, DA. Anaya, C. Wei, B. Bekele, KD. Smith, AJ. Lazar, PW. Pisters, RE. Pollock, D. Lev Sarcoma Research Center UT MD Anderson Cancer Center Houston, TX U.S.A.

  2. Current STS staging systems have several important shortcomings The TNM and grade criteria do not reflect the heterogeneity of STS Available nomograms are not universally applicable No current STS staging system includes molecular predictors of outcome • Patient I- 6cm high grade extremity UPS • Patient II- 25cm retroperitoneal dedifferentiated LPS Both are AJCC Stage III patients!

  3. Purpose To identify clinical, pathological, and molecular descriptors of STS clinical behavior for inclusion in revised staging systems

  4. Methods • UTMDACC STS prospective database • Univariate and multivariate statistical analyses • Clinically annotated STS tissue microarray

  5. UTMDACC STS Database 1996-2007 6,702 patients Second opinion 2,985 Local recurrence only 474 Primary & Metastatic 435 Metastatic disease only 350 Definitive treatment 3,717 Non- surgical treatment 1,016 Primary disease only 2,458 R2 resection and non-specific histologies 351 Surgical treatment of primary tumor 1,442 Study cohort 1,091

  6. Head and neck 2.5% Intra thoracic 6% Superficial trunk 6% Intra abdominal 26% Extremity 58% Patient and tumor characteristics Male: 52%; Female: 48% Median age (range): 54.5 years (15-91) Median follow-up: 53.3 months

  7. Non-extremity (n= 464; 42%) Extremity (n= 627; 58%) p<0.0001 Non-extremity location is associated with increased STS-specific mortality

  8. Tumor size>15cm (n= 230; 21%) Tumor size 10-15cm (n= 202; 19%) Tumor size 5-10cm (n=336; 31%) Tumor size< 5cm (n= 309; 29%) p<0.0001 A T3 category may be added to the AJCC STS staging system

  9. High grade is associated with increased STS-specific mortality p<0.0001 High grade (n=737; 67.6%) Low/intermediate grade (n=354; 32.2%)

  10. High grade, size>15cm High grade, size 5-15cm High grade, size<5cm Low/intermediate grade p<0.0001 Interaction between variables: tumor size and grade effects on STS-specific mortality

  11. High grade, positive margins High grade, negative margins Low/intermediate grade, positive margins Low /intermediate grade, negative margins Interaction between variables: margin positivity and grade effects on STS-specific mortality p<0.0001

  12. Multivariate Cox Proportional Hazard Models for STS-specific mortality

  13. Multivariate Cox Proportional Hazard Models for STS local recurrence free survival

  14. ConclusionsAnn Surg Oncol 2008; 15:2739-48 • STS size, site, grade, histology, and microscopic margin status should be included in a revised staging system Can we further improve and individualize prognostication?

  15. Distant metastasis followed by death Cure Every STS is “unique” Patient A Patient B 6cm, extremity, HG, UPS, R0 resection 6cm, extremity, HG, UPS, R0 resection Clinical and pathological prognostic factors are not enough!

  16. Molecular markers are important potential prognostic factors High throughput assays Detection of DNA, RNA, and protein targets Simultaneous analysis of large tumor sets Correlation with clinical data

  17. TMA (n=205) Growth and metastasis Ki-67 Apoptosis/survival P53 MDM2 Bcl2 Bcl-x Cytokines/receptors/signaling EGFR VEGF β-Catenin Extracellular matrix MMP2 MMP9

  18. Percent MMP2 pos ≤ 10% Percent MMP2 pos > 10% 72% 46% Disease specific survival time (months) High MMP2 expression correlates with decreased STS-specific survival

  19. Multivariate Cox Proportional Hazard Models for disease specific survival (TMA cohort)

  20. Multivariate Cox Proportional Hazard Models for local recurrence (TMA cohort)

  21. Matrix metalloproteinases(MMP2) and STS Previous series

  22. Conclusions • High MMP2 expression may be an adverse independent predictor of outcome in STS • Inclusion as a molecular prognostic factor in future STS staging systems, pending large scale validation • Individualized therapeutic strategy • Should be further studied as potential targets for therapy

  23. Acknowledgments Vision and direction: Insights and teamwork: Sarcoma Research Center University of Texas MD Anderson Cancer Center

  24. Thank you for your attention!

  25. Extremity 86% UPS 78% Size> 5cm (76%) HG (75%) TMA Tumor characteristics Negative margins (70%)

More Related