Publications by authors named "Tumkur Sitaram Raviprakash"

4 Publications

  • Page 1 of 1

Significance of PI3K signalling pathway in clear cell renal cell carcinoma in relation to VHL and HIF status.

J Clin Pathol 2021 Apr 28;74(4):216-222. Epub 2020 May 28.

Department of Surgical and Preoperative Sciences, Urology and Andrology, Umeå Universitet, Umea, Västerbotten, Sweden.

Renal cell carcinoma (RCC) includes diverse tumour types characterised by various genetic abnormalities. The genetic changes, like mutations, deletions and epigenetic alterations, play a crucial role in the modification of signalling networks, tumour pathogenesis and prognosis. The most prevalent RCC type, clear cell RCC (ccRCC), is asymptomatic in the early stages and has a poorer prognosis compared with the papillary and the chromophobe types RCCs. Generally, ccRCC is refractory to chemotherapy and radiation therapy. Loss of von Hippel-Lindau (VHL) gene and upregulation of hypoxia-inducible factors (HIF), the signature of most sporadic ccRCC, promote multiple growth factors. Hence, VHL/HIF and a variety of pathways, including phosphatase and TEnsin homolog on chromosome 10/phosphatidylinositol-3-kinase (PI3K)/AKT, are closely connected and contribute to the ontogeny of ccRCC. In the recent decade, multiple targeting agents have been developed based on blocking major signalling pathways directly or indirectly involved in ccRCC tumour progression, metastasis, angiogenesis and survival. However, most of these drugs have limitations; either metastatic ccRCC develops resistance to these agents, or despite blocking receptors, tumour cells use alternate signalling pathways. This review compiles the state of knowledge about the PI3K/AKT signalling pathway confined to ccRCC and its cross-talks with VHL/HIF pathway.
View Article and Find Full Text PDF

Download full-text PDF

Source Listing
April 2021

Interactions between TGF-β type I receptor and hypoxia-inducible factor-α mediates a synergistic crosstalk leading to poor prognosis for patients with clear cell renal cell carcinoma.

Cell Cycle 2019 09 24;18(17):2141-2156. Epub 2019 Jul 24.

a Department of Medical Biosciences, Pathology , Umeå , Sweden.

To investigate the significance of expression of HIF-1α, HIF-2α, and SNAIL1 proteins; and TGF-β signaling pathway proteins in ccRCC, their relation with clinicopathological parameters and patient's survival were examined. We also investigated potential crosstalk between HIF-α and TGF-β signaling pathway, including the TGF-β type 1 receptor (ALK5-FL) and the intracellular domain of ALK5 (ALK5-ICD). Tissue samples from 154 ccRCC patients and comparable adjacent kidney cortex samples from 38 patients were analyzed for HIF-1α/2α, TGF-β signaling components, and SNAIL1 proteins by immunoblot. Protein expression of HIF-1α and HIF-2α were significantly higher, while SNAIL1 had similar expression levels in ccRCC compared with the kidney cortex. HIF-2α associated with poor cancer-specific survival, while HIF-1α and SNAIL1 did not associate with survival. Moreover, HIF-2α positively correlated with ALK5-ICD, pSMAD2/3, and PAI-1; HIF-1α positively correlated with pSMAD2/3; SNAIL1 positively correlated with ALK5-FL, ALK5-ICD, pSMAD2/3, PAI-1, and HIF-2α. Intriguingly, experiments performed under normoxic conditions revealed that ALK5 interacts with HIF-1α and HIF-2α, and promotes their expression and the expression of their target genes GLUT1 and CA9, in a VHL dependent manner. We found that ALK5 induces expression of HIF-1α and HIF-2α, through its kinase activity. Under hypoxic conditions, HIF-α proteins correlated with the activated TGF-β signaling pathway. In conclusion, we reveal that ALK5 plays a pivotal role in synergistic crosstalk between TGF-β signaling and hypoxia pathway, and that the interaction between ALK5 and HIF-α contributes to tumor progression.
View Article and Find Full Text PDF

Download full-text PDF

Source Listing
September 2019

The influence of obesity-related factors in the etiology of renal cell carcinoma-A mendelian randomization study.

PLoS Med 2019 01 3;16(1):e1002724. Epub 2019 Jan 3.

National Institute of Public Health, Bucharest, Romania.

Background: Several obesity-related factors have been associated with renal cell carcinoma (RCC), but it is unclear which individual factors directly influence risk. We addressed this question using genetic markers as proxies for putative risk factors and evaluated their relation to RCC risk in a mendelian randomization (MR) framework. This methodology limits bias due to confounding and is not affected by reverse causation.

Methods And Findings: Genetic markers associated with obesity measures, blood pressure, lipids, type 2 diabetes, insulin, and glucose were initially identified as instrumental variables, and their association with RCC risk was subsequently evaluated in a genome-wide association study (GWAS) of 10,784 RCC patients and 20,406 control participants in a 2-sample MR framework. The effect on RCC risk was estimated by calculating odds ratios (ORSD) for a standard deviation (SD) increment in each risk factor. The MR analysis indicated that higher body mass index increases the risk of RCC (ORSD: 1.56, 95% confidence interval [CI] 1.44-1.70), with comparable results for waist-to-hip ratio (ORSD: 1.63, 95% CI 1.40-1.90) and body fat percentage (ORSD: 1.66, 95% CI 1.44-1.90). This analysis further indicated that higher fasting insulin (ORSD: 1.82, 95% CI 1.30-2.55) and diastolic blood pressure (DBP; ORSD: 1.28, 95% CI 1.11-1.47), but not systolic blood pressure (ORSD: 0.98, 95% CI 0.84-1.14), increase the risk for RCC. No association with RCC risk was seen for lipids, overall type 2 diabetes, or fasting glucose.

Conclusions: This study provides novel evidence for an etiological role of insulin in RCC, as well as confirmatory evidence that obesity and DBP influence RCC risk.
View Article and Find Full Text PDF

Download full-text PDF

Source Listing
January 2019

The Radiogenomic Risk Score: Construction of a Prognostic Quantitative, Noninvasive Image-based Molecular Assay for Renal Cell Carcinoma.

Radiology 2015 Oct 19;277(1):114-23. Epub 2015 Aug 19.

From the Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Box 951721, CHS 17-135, 10833 LeConte Ave, Los Angeles, CA 90095-1721 (N.J., M.Z., S.B., M.D.K.); Department of Genitourinary Medical Oncology, The University of Texas M.D. Anderson Cancer Center, Houston, Tex (E.J.); Department of Radiology, Hospital of Veterans Affairs, University of California-San Diego, San Diego, Calif (M.Z., L.A.); Scottsdale Medical Imaging, Scottsdale, Ariz (R.K.); Department of Urology, Stanford University School of Medicine, Stanford, Calif (H.Z., J.D.B.); Department of Surgical and Perioperative Sciences, Urology and Andrology, Umea Hospital, Umea, Sweden (R.T.S., B.L.); and Department of Statistics, Stanford University, Stanford, Calif (R.J.T.).

Purpose: To evaluate the feasibility of constructing radiogenomic-based surrogates of molecular assays (SOMAs) in patients with clear-cell renal cell carcinoma (CCRCC) by using data extracted from a single computed tomographic (CT) image.

Materials And Methods: In this institutional review board approved study, gene expression profile data and contrast material-enhanced CT images from 70 patients with CCRCC in a training set were independently assessed by two radiologists for a set of predefined imaging features. A SOMA for a previously validated CCRCC-specific supervised principal component (SPC) risk score prognostic gene signature was constructed and termed the radiogenomic risk score (RRS). It uses the microarray data and a 28-trait image array to evaluate each CT image with multiple regression of gene expression analysis. The predictive power of the RRS SOMA was then prospectively validated in an independent dataset to confirm its relationship to the SPC gene signature (n = 70) and determination of patient outcome (n = 77). Data were analyzed by using multivariate linear regression-based methods and Cox regression modeling, and significance was assessed with receiver operator characteristic curves and Kaplan-Meier survival analysis.

Results: Our SOMA faithfully represents the tissue-based molecular assay it models. The RRS scaled with the SPC gene signature (R = 0.57, P < .001, classification accuracy 70.1%, P < .001) and predicted disease-specific survival (log rank P < .001). Independent validation confirmed the relationship between the RRS and the SPC gene signature (R = 0.45, P < .001, classification accuracy 68.6%, P < .001) and disease-specific survival (log-rank P < .001) and that it was independent of stage, grade, and performance status (multivariate Cox model P < .05, log-rank P < .001).

Conclusion: A SOMA for the CCRCC-specific SPC prognostic gene signature that is predictive of disease-specific survival and independent of stage was constructed and validated, confirming that SOMA construction is feasible.
View Article and Find Full Text PDF

Download full-text PDF

Source Listing
October 2015