Project description:Expression levels of proteins and phosphoproteins, covering major cancer signaling pathways with a special focus on breast cancer biology, were obtained for a series of 109 breast cancer tumor specimens with positive estrogen receptor status.
Project description:Expression levels of proteins and phosphoproteins, covering major cancer signaling pathways with a special focus on breast cancer biology, were obtained for a series of 164 breast cancer tumor specimens with positive estrogen receptor status.
Project description:This SuperSeries is composed of the following subset Series: GSE36324: Targeted inhibition of human breast cancer cell lines selected as model systems of ERBB2-positive/EGFR high breast cancer [RPPA-HCC1954] GSE36325: Targeted inhibition of human breast cancer cell lines selected as model systems of ERBB2-positive/EGFR high breast cancer [RPPA-Longterm] GSE36326: Targeted inhibition of human breast cancer cell lines selected as model systems of ERBB2-positive/EGFR high breast cancer [RPPA-SKBR3] Refer to individual Series
Project description:Although an increased level of the prostate-specific antigen can be an indication for prostate cancer, other reasons often lead to a high rate of false positive results. Therefore, an additional serological screening of autoantibodies in patients’ sera could improve the detection of prostate cancer. We performed protein macroarray screening with sera from 49 prostate cancer patients, 70 patients with benign prostatic hyperplasia and 28 healthy controls and compared the autoimmune response in those groups. We were able to distinguish prostate cancer patients from normal controls with an accuracy of 83.2%, patients with benign prostatic hyperplasia from normal controls with an accuracy of 86.0% and prostate cancer patients from patients with benign prostatic hyperplasia with an accuracy of 70.3%. Combining seroreactivity pattern with a PSA level of higher than 4.0 ng/ml this classification could be improved to an accuracy of 84.1%. For selected proteins we were able to confirm the differential expression by using Lluminex on 84 samples. We provide a minimally invasive serological method to reduce false positive results in detection of prostate cancer and according to PSA screening to distinguish men with prostate cancer from men with benign prostatic hyperplasia.
Project description:Mitogen-activated protein kinases (MEK 1/2) are central components of the RAS signaling pathway and attractive targets for cancer therapy. However, PIK3CA mutation, which commonly co-occurs with KRAS mutation, offered resistance to MEK inhibitor through activation of PI3K-AKT signaling. We identified a gene that cooperates with MEK inhibitors to forcefully treat PIK3CA mutant colon cancer cells. -catenin, a key molecule of the WNT pathway, emerged as a candidate by protein/Ab Chip array. MEK inhibitor treatment led to a decrease in -catenin in PIK3CA wild-type colon cancer cells but not in PIK3CA mutant colon cancer cells. Tumor regression was promoted by a combination of MEK inhibitor and NVP-TNS656, which targets the WNT pathway. Furthermore, combined inhibition of MEK and -catenin by NVP-TNS656 promoted tumor regression in colon cancer patient-derived xenograft (PDX) models expressing mutant PIK3CA. Taken together, we propose that inhibition of the WNT pathway, particularly -catenin, may bypass resistance to MEK inhibitor in human PIK3CA mutant colon cancer. Additionally, -catenin is a potential PD marker of MEK inhibitor resistance.
Project description:Introduction: Serous ovarian cancer is the leading cause of gynecological cancers, with a 5-year survival rate below 45% due in part to the nonspecific symptoms and lack of accurate screening for early detection. In comparison, patients diagnosed at an early stage have a five-year survival rate of 92%, demonstrating the urgent need for biomarkers for the early detection of disease. Serum from patients with serous ovarian cancer contain antibodies to tumor antigens that are potential biomarkers for early detection. The purpose of this study is to identify a panel of novel serum autoantibody (AAb) biomarkers for the early diagnosis of serous ovarian cancer. Methods: To detect AAb we probed high-density programmable protein microarrays (NAPPA) containing 10,247 antigens with sera from patients with serous ovarian cancer (n = 30 cases/ 30 healthy controls) and measured bound IgG. We identified 735 promising tumor antigens using cutoff values of 10% sensitivity at 95% specificity and K-value>0.8, as well as visual analysis and evaluated these with an independent set of serous ovarian cancer sera (n = 30 cases/ 30 benign disease controls/ 30 heathy controls). Thirty-nine potential tumor autoantigens were identified with sensitivities ranging from 3 to 39.7% sensitivity at 95% specificity and were retested using an orthogonal programmable ELISA assay. A total of 13 potential tumor antigens were identified for further validation using an independent ovarian cancer sera set (n = 44 cases/ 34 healthy controls). Sensitivities at 95% specificity were calculated and a serous ovarian cancer classifier was constructed. In addition, we evaluated a longitudinal study using blinded serous pre-diagnostic ovarian cancer sera (n = 9 cases/ 90 controls) to examine the value of three (CTAG1, CTAG2, and p53) of these AAb in comparison to CA 125. Results: We identified 11-AAbs (ICAM3, CTAG2, p53, STYXL1, PVR, POMC, NUDT11, TRIM39, UHMK1, KSR1, and NXF3) that distinguished serous ovarian cancer cases from healthy controls with a combined 45% sensitivity at 100% specificity. In our longitudinal analysis, p53- and CTAG-AAb were detected up to 9 months prior to ovarian cancer diagnosis and increased with CA 125 levels. Conclusion: These are potential circulating biomarkers for the early detection of serous ovarian cancer, and warrant confirmation in larger clinical cohorts. In addition, p53- and CTAG1/2-AAb are detected in a subset of women with ovarian cancer up to 9 months prior to clinical diagnosis. Their utility as a biomarker for early detection, beyond CA 125, warrant further investigation.
Project description:Introduction: Serous ovarian cancer is the leading cause of gynecological cancers, with a 5-year survival rate below 45% due in part to the nonspecific symptoms and lack of accurate screening for early detection. In comparison, patients diagnosed at an early stage have a five-year survival rate of 92%, demonstrating the urgent need for biomarkers for the early detection of disease. Serum from patients with serous ovarian cancer contain antibodies to tumor antigens that are potential biomarkers for early detection. The purpose of this study is to identify a panel of novel serum autoantibody (AAb) biomarkers for the early diagnosis of serous ovarian cancer. Methods: To detect AAb we probed high-density programmable protein microarrays (NAPPA) containing 10,247 antigens with sera from patients with serous ovarian cancer (n = 30 cases/ 30 healthy controls) and measured bound IgG. We identified 735 promising tumor antigens using cutoff values of 10% sensitivity at 95% specificity and K-value>0.8, as well as visual analysis and evaluated these with an independent set of serous ovarian cancer sera (n = 30 cases/ 30 benign disease controls/ 30 heathy controls). Thirty-nine potential tumor autoantigens were identified with sensitivities ranging from 3 to 39.7% sensitivity at 95% specificity and were retested using an orthogonal programmable ELISA assay. A total of 13 potential tumor antigens were identified for further validation using an independent ovarian cancer sera set (n = 44 cases/ 34 healthy controls). Sensitivities at 95% specificity were calculated and a serous ovarian cancer classifier was constructed. In addition, we evaluated a longitudinal study using blinded serous pre-diagnostic ovarian cancer sera (n = 9 cases/ 90 controls) to examine the value of three (CTAG1, CTAG2, and p53) of these AAb in comparison to CA 125. Results: We identified 11-AAbs (ICAM3, CTAG2, p53, STYXL1, PVR, POMC, NUDT11, TRIM39, UHMK1, KSR1, and NXF3) that distinguished serous ovarian cancer cases from healthy controls with a combined 45% sensitivity at 100% specificity. In our longitudinal analysis, p53- and CTAG-AAb were detected up to 9 months prior to ovarian cancer diagnosis and increased with CA 125 levels. Conclusion: These are potential circulating biomarkers for the early detection of serous ovarian cancer, and warrant confirmation in larger clinical cohorts. In addition, p53- and CTAG1/2-AAb are detected in a subset of women with ovarian cancer up to 9 months prior to clinical diagnosis. Their utility as a biomarker for early detection, beyond CA 125, warrant further investigation.
Project description:Introduction: Serous ovarian cancer is the leading cause of gynecological cancers, with a 5-year survival rate below 45% due in part to the nonspecific symptoms and lack of accurate screening for early detection. In comparison, patients diagnosed at an early stage have a five-year survival rate of 92%, demonstrating the urgent need for biomarkers for the early detection of disease. Serum from patients with serous ovarian cancer contain antibodies to tumor antigens that are potential biomarkers for early detection. The purpose of this study is to identify a panel of novel serum autoantibody (AAb) biomarkers for the early diagnosis of serous ovarian cancer. Methods: To detect AAb we probed high-density programmable protein microarrays (NAPPA) containing 10,247 antigens with sera from patients with serous ovarian cancer (n = 30 cases/ 30 healthy controls) and measured bound IgG. We identified 735 promising tumor antigens using cutoff values of 10% sensitivity at 95% specificity and K-value>0.8, as well as visual analysis and evaluated these with an independent set of serous ovarian cancer sera (n = 30 cases/ 30 benign disease controls/ 30 heathy controls). Thirty-nine potential tumor autoantigens were identified with sensitivities ranging from 3 to 39.7% sensitivity at 95% specificity and were retested using an orthogonal programmable ELISA assay. A total of 13 potential tumor antigens were identified for further validation using an independent ovarian cancer sera set (n = 44 cases/ 34 healthy controls). Sensitivities at 95% specificity were calculated and a serous ovarian cancer classifier was constructed. In addition, we evaluated a longitudinal study using blinded serous pre-diagnostic ovarian cancer sera (n = 9 cases/ 90 controls) to examine the value of three (CTAG1, CTAG2, and p53) of these AAb in comparison to CA 125. Results: We identified 11-AAbs (ICAM3, CTAG2, p53, STYXL1, PVR, POMC, NUDT11, TRIM39, UHMK1, KSR1, and NXF3) that distinguished serous ovarian cancer cases from healthy controls with a combined 45% sensitivity at 100% specificity. In our longitudinal analysis, p53- and CTAG-AAb were detected up to 9 months prior to ovarian cancer diagnosis and increased with CA 125 levels. Conclusion: These are potential circulating biomarkers for the early detection of serous ovarian cancer, and warrant confirmation in larger clinical cohorts. In addition, p53- and CTAG1/2-AAb are detected in a subset of women with ovarian cancer up to 9 months prior to clinical diagnosis. Their utility as a biomarker for early detection, beyond CA 125, warrant further investigation.
Project description:Small-molecule inhibitors of AKT signaling are being in evaluated in patients with various cancer types, but have so far proven therapeutically disappointing for reasons that remain unclear. Here, we treat cancer cells with sub-therapeutic doses of Akti-1/2, an allosteric small molecule AKT inhibitor, in order to experimentally model pharmacologic inhibition of AKT signaling in vitro. We then apply a combined RNA, protein, and metabolite profiling approach to develop an integrated, multi-scale, molecular snapshot of this “AKTlow” cancer cell state. We find that AKT-inhibited cancer cells suppress thousands of mRNA transcripts, and proteins related to the cell cycle, ribosome, and protein translation. Surprisingly, however, these AKT-inhibited cells simultaneously up-regulate a host of other proteins and metabolites post-transcriptionally, reflecting activation of their endo-vesiculo-membrane system, secretion of inflammatory proteins, and elaboration of extracellular microvesicles. Importantly, these microvesicles enable rapidly proliferating cancer cells of various types to better withstand different stress conditions, including serum deprivation, hypoxia, or cytotoxic chemotherapy in vitro and xenografting in vivo. These findings suggest a model whereby cancer cells experiencing a partial inhibition of AKT signaling may actually promote the survival of neighbors through non-cell autonomous communication.
Project description:Small-molecule inhibitors of AKT signaling are being in evaluated in patients with various cancer types, but have so far proven therapeutically disappointing for reasons that remain unclear. Here, we treat cancer cells with sub-therapeutic doses of Akti-1/2, an allosteric small molecule AKT inhibitor, in order to experimentally model pharmacologic inhibition of AKT signaling in vitro. We then apply a combined RNA, protein, and metabolite profiling approach to develop an integrated, multi-scale, molecular snapshot of this “AKTlow” cancer cell state. We find that AKT-inhibited cancer cells suppress thousands of mRNA transcripts, and proteins related to the cell cycle, ribosome, and protein translation. Surprisingly, however, these AKT-inhibited cells simultaneously up-regulate a host of other proteins and metabolites post-transcriptionally, reflecting activation of their endo-vesiculo-membrane system, secretion of inflammatory proteins, and elaboration of extracellular microvesicles. Importantly, these microvesicles enable rapidly proliferating cancer cells of various types to better withstand different stress conditions, including serum deprivation, hypoxia, or cytotoxic chemotherapy in vitro and xenografting in vivo. These findings suggest a model whereby cancer cells experiencing a partial inhibition of AKT signaling may actually promote the survival of neighbors through non-cell autonomous communication.