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Sökning: WFRF:(Talve L.)

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1.
  • Edqvist, Per-Henrik D., et al. (författare)
  • Loss of ASRGL1 expression is an independent biomarker for disease-specific survival in endometrioid endometrial carcinoma
  • 2015
  • Ingår i: Gynecologic Oncology. - : Elsevier BV. - 0090-8258 .- 1095-6859. ; 137:3, s. 529-537
  • Tidskriftsartikel (refereegranskat)abstract
    • Objective For endometrial carcinoma, prognostic stratification methods do not satisfactorily identify patients with adverse outcome. Currently, histology, tumor grade and stage are used to tailoring surgical treatment and to determine the need for adjuvant treatment. Low-risk patients are not considered to require adjuvant therapy or staging lymphadenectomy. For patients with intermediate or high risk, some guidelines recommend tailoring adjuvant treatment according to additional negative prognostic factors. Our objective was to evaluate the biomarker potential of the ASRGL1 protein in endometrial carcinoma. Methods Using The Human Protein Atlas (www.proteinatlas.org), the l-asparaginase (ASRGL1) protein was identified as an endometrial carcinoma biomarker candidate. ASRGL1 expression was immunohistochemically evaluated with an extensively validated antibody on two independent endometrial carcinoma cohorts (n = 229 and n = 286) arranged as tissue microarrays. Staining results were correlated with clinical features. Results Reduced expression of ASRGL1, defined as < 75% positively stained tumor cells, was significantly associated with poor prognosis and reduced disease-specific survival in endometrioid endometrial adenocarcinoma (EEA). In multivariate analysis the hazard ratios for disease-specific survival were 3.55 (95% CI = 1.10-11.43; p = 0.003) and 3.23 (95% CI = 1.53-6.81; p = 0.002) in the two cohorts, respectively. Of the 48 cases with Grade 3 Stage I tumor all disease-related deaths were associated with low ASRGL1 expression. Conclusions Loss of ASRGL1 in EEA is a powerful biomarker for poor prognosis and retained ASRGL1 has a positive impact on survival. ASRGL1 immunohistochemistry has potential to become an additional tool for prognostication in cases where tailoring adjuvant treatment according to additional prognostic factors besides grade and stage is recommended.
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2.
  • Huvila, J., et al. (författare)
  • Combined ASRGL1 and p53 immunohistochemistry as an independent predictor of survival in endometrioid endometrial carcinoma
  • 2018
  • Ingår i: Gynecologic Oncology. - : Academic Press Inc.. - 0090-8258 .- 1095-6859. ; 149:1, s. 173-180
  • Tidskriftsartikel (refereegranskat)abstract
    • Objective: In clinical practise, prognostication of endometrial cancer is based on clinicopathological risk factors. The use of immunohistochemistry-based markers as prognostic tools is generally not recommended and a systematic analysis of their utility as a panel is lacking. We evaluated whether an immunohistochemical marker panel could reliably assess endometrioid endometrial cancer (EEC) outcome independent of clinicopathological information. Methods: A cohort of 306 EEC specimens was profiled using tissue microarray (TMA). Cost- and time-efficient immunohistochemical analysis of well-established tissue biomarkers (ER, PR, HER2, Ki-67, MLH1 and p53) and two new biomarkers (L1CAM and ASRGL1) was carried out. Statistical modelling with embedded variable selection was applied on the staining results to identify minimal prognostic panels with maximal prognostic accuracy without compromising generalizability. Results: A panel including p53 and ASRGL1 immunohistochemistry was identified as the most accurate predictor of relapse-free and disease-specific survival. Within this panel, patients were allocated into high- (5.9%), intermediate- (29.5%) and low- (64.6%) risk groups where high-risk patients had a 30-fold risk (P < 0.001) of dying of EEC compared to the low-risk group. Conclusions: P53 and ASRGL1 immunoprofiling stratifies EEC patients into three risk groups with significantly different outcomes. This simple and easily applicable panel could provide a useful tool in EEC risk stratification and guiding the allocation of treatment modalities. 
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