Browsing by Subject "Carcinoma, Renal Cell"

Now showing 1 - 3 of 3
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    An active learning approach for rapid characterization of endothelial cells in human tumors.
    (PLoS One, 2014) Padmanabhan, Raghav K; Somasundar, Vinay H; Griffith, Sandra D; Zhu, Jianliang; Samoyedny, Drew; Tan, Kay See; Hu, Jiahao; Liao, Xuejun; Carin, Lawrence; Yoon, Sam S; Flaherty, Keith T; Dipaola, Robert S; Heitjan, Daniel F; Lal, Priti; Feldman, Michael D; Roysam, Badrinath; Lee, William MF
    Currently, no available pathological or molecular measures of tumor angiogenesis predict response to antiangiogenic therapies used in clinical practice. Recognizing that tumor endothelial cells (EC) and EC activation and survival signaling are the direct targets of these therapies, we sought to develop an automated platform for quantifying activity of critical signaling pathways and other biological events in EC of patient tumors by histopathology. Computer image analysis of EC in highly heterogeneous human tumors by a statistical classifier trained using examples selected by human experts performed poorly due to subjectivity and selection bias. We hypothesized that the analysis can be optimized by a more active process to aid experts in identifying informative training examples. To test this hypothesis, we incorporated a novel active learning (AL) algorithm into FARSIGHT image analysis software that aids the expert by seeking out informative examples for the operator to label. The resulting FARSIGHT-AL system identified EC with specificity and sensitivity consistently greater than 0.9 and outperformed traditional supervised classification algorithms. The system modeled individual operator preferences and generated reproducible results. Using the results of EC classification, we also quantified proliferation (Ki67) and activity in important signal transduction pathways (MAP kinase, STAT3) in immunostained human clear cell renal cell carcinoma and other tumors. FARSIGHT-AL enables characterization of EC in conventionally preserved human tumors in a more automated process suitable for testing and validating in clinical trials. The results of our study support a unique opportunity for quantifying angiogenesis in a manner that can now be tested for its ability to identify novel predictive and response biomarkers.
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    Evaluation of tumor microenvironment and biomarkers of immune checkpoint inhibitor response in metastatic renal cell carcinoma.
    (Journal for immunotherapy of cancer, 2022-10) Brown, Landon C; Zhu, Jason; Desai, Kunal; Kinsey, Emily; Kao, Chester; Lee, Yong Hee; Pabla, Sarabjot; Labriola, Matthew K; Tran, Jennifer; Dragnev, Konstantin H; Tafe, Laura J; Dayyani, Farshid; Gupta, Rajan T; McCall, Shannon; George, Daniel J; Glenn, Sean T; Nesline, Mary K; George, Saby; Zibelman, Matthew; Morrison, Carl; Ornstein, Moshe C; Zhang, Tian

    Background

    Immunotherapy combinations including ipilimumab and nivolumab are now the standard of care for untreated metastatic renal cell carcinoma (mRCC). Biomarkers of response are lacking to predict patients who will have a favorable or unfavorable response to immunotherapy. This study aimed to use the OmniSeq transcriptome-based platform to develop biomarkers of response to immunotherapy.

    Methods

    Two cohorts of patients were retrospectively collected. These included an investigational cohort of patients with mRCC treated with immune checkpoint inhibitor therapy from five institutions, and a subsequent validation cohort of patients with mRCC treated with combination ipilimumab and nivolumab from two institutions (Duke Cancer Institute and Cleveland Clinic Taussig Cancer Center). Tissue-based RNA sequencing was performed using the OmniSeq Immune Report Card on banked specimens to identify gene signatures and immune checkpoints associated with differential clinical outcomes. A 5-gene expression panel was developed based on the investigational cohort and was subsequently evaluated in the validation cohort. Clinical outcomes including progression-free survival (PFS) and overall survival (OS) were extracted by retrospective chart review. Objective response rate (ORR) was assessed by Response Evaluation Criteria in Solid Tumors (RECIST) V.1.1.

    Results

    The initial investigation cohort identified 86 patients with mRCC who received nivolumab (80%, 69/86), ipilimumab/nivolumab (14%, 12/86), or pembrolizumab (6%, 5/86). A gene expression score was created using the top five genes found in responders versus non-responders (FOXP3, CCR4, KLRK1, ITK, TIGIT). The ORR in patients with high gene expression (GEhigh) on the 5-gene panel was 29% (14/48), compared with low gene expression (GElow) 3% (1/38, χ2 p=0.001). The validation cohort was comprised of 62 patients who received ipilimumab/nivolumab. There was no difference between GEhigh and GElow in terms of ORR (44% vs 38.5%), PFS (HR 1.5, 95% CI 0.58 to 3.89), or OS (HR 0.96, 95% CI 0.51 to 1.83). Similarly, no differences in ORR, PFS or OS were observed when patients were stratified by tumor mutational burden (high=top 20%), PD-L1 (programmed death-ligand 1) expression by immunohistochemistry or RNA expression, or CTLA-4 (cytotoxic T-lymphocytes-associated protein 4) RNA expression. The International Metastatic RCC Database Consortium (IMDC) risk score was prognostic for OS but not PFS.

    Conclusion

    A 5-gene panel that was associated with improved ORR in a predominantly nivolumab monotherapy population of patients with mRCC was not predictive for radiographic response, PFS, or OS among patients with mRCC treated with ipilimumab and nivolumab.
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    ItemOpen Access
    Inactivation of the von Hippel-Lindau tumor suppressor leads to selective expression of a human endogenous retrovirus in kidney cancer.
    (Oncogene, 2011-11-24) Cherkasova, E; Malinzak, E; Rao, S; Takahashi, Y; Senchenko, VN; Kudryavtseva, AV; Nickerson, ML; Merino, M; Hong, JA; Schrump, DS; Srinivasan, R; Linehan, WM; Tian, X; Lerman, MI; Childs, RW
    A human endogenous retrovirus type E (HERV-E) was recently found to be selectively expressed in most renal cell carcinomas (RCCs). Importantly, antigens derived from this provirus are immunogenic, stimulating cytotoxic T cells that kill RCC cells in vitro and in vivo. Here, we show HERV-E expression is restricted to the clear cell subtype of RCC (ccRCC) characterized by an inactivation of the von Hippel-Lindau (VHL) tumor-suppressor gene with subsequent stabilization of hypoxia-inducible transcription factors (HIFs)-1α and -2α. HERV-E expression in ccRCC linearly correlated with HIF-2α levels and could be silenced in tumor cells by either transfection of normal VHL or small interfering RNA inhibition of HIF-2α. Using chromatin immunoprecipitation, we demonstrated that HIF-2α can serve as transcriptional factor for HERV-E by binding with HIF response element (HRE) localized in the proviral 5' long terminal repeat (LTR). Remarkably, the LTR was found to be hypomethylated only in HERV-E-expressing ccRCC while other tumors and normal tissues possessed a hypermethylated LTR preventing proviral expression. Taken altogether, these findings provide the first evidence that inactivation of a tumor suppressor gene can result in aberrant proviral expression in a human tumor and give insights needed for translational research aimed at boosting human immunity against antigenic components of this HERV-E.