Predictive Factors for Second-Line Therapy in Metastatic Renal Cell Carcinoma: A Retrospective Analysis

Currently, about 50% of patients with metastatic renal cell carcinoma (mRCC) receive a second-line therapy. Therefore, the choice at each subsequent treatment line remains an important issue. In this retrospective study, we sought to identify pretreatment clinical parameters that could predict the likelihood of a patient receiving a second-line therapy. One hundred and sixty-one mRCC patients who received targeted therapy were evaluated. Descriptive statistics, Kaplan–Meier overall survival (OS), Cox regression, and binary logistic regression models were used for data analysis. Second-line therapy was given to 105 patients (65%). Patients with grade 1 tumor received second-line therapy more frequently than those with grade 2/3 tumors (P = 0.03). Only tumor grade was significantly different between patients receiving, or not receiving, second-line treatment. Median OS was significantly superior in patients receiving second-line therapy (32 versus 14 months; P = 0.007; hazard ratio [HR], 1.75; P = 0.008), patients with grade 1 tumors (130 versus 29 months in G2/3 tumors; HR, 3.85; P = 0.009), and in patients without early tumor progression (41 versus 11 months; HR, 5.04; 95% confidence interval [CI], 3.06–8.31; P < 0.001). In binary logistic regression, we identified early progression to be significantly associated with a higher probability of not receiving a second-line therapy (HR, 2.50; 95% CI, 1.01–6.21; P = 0.048). This study hypothesizes that pretreatment grade and early progression are predictive parameters for the selection of patients for second-line therapy

Predictive Factors for Second-Line Therapy in Metastatic Renal Cell Carcinoma: A Retrospective Analysis

Currently, about 50% of patients with metastatic renal cell carcinoma (mRCC) receive a second-line therapy. Therefore, the choice at each subsequent treatment line remains an important issue. In this retrospective study, we sought to identify pretreatment clinical parameters that could predict the likelihood of a patient receiving a second-line therapy. One hundred and sixty-one mRCC patients who received targeted therapy were evaluated. Descriptive statistics, Kaplan–Meier overall survival (OS), Cox regression, and binary logistic regression models were used for data analysis. Second-line therapy was given to 105 patients (65%). Patients with grade 1 tumor received second-line therapy more frequently than those with grade 2/3 tumors (P = 0.03). Only tumor grade was significantly different between patients receiving, or not receiving, second-line treatment. Median OS was significantly superior in patients receiving second-line therapy (32 versus 14 months; P = 0.007; hazard ratio [HR], 1.75; P = 0.008), patients with grade 1 tumors (130 versus 29 months in G2/3 tumors; HR, 3.85; P = 0.009), and in patients without early tumor progression (41 versus 11 months; HR, 5.04; 95% confidence interval [CI], 3.06–8.31; P &lt; 0.001). In binary logistic regression, we identified early progression to be significantly associated with a higher probability of not receiving a second-line therapy (HR, 2.50; 95% CI, 1.01–6.21; P = 0.048). This study hypothesizes that pretreatment grade and early progression are predictive parameters for the selection of patients for second-line therapy.</p

Identification of novel regulators in T-cell differentiation of aplastic anemia patients

BACKGROUND: Aplastic anemia (AA) is a bone marrow failure syndrome mostly characterized by an immune-mediated destruction of marrow hematopoietic progenitor/stem cells. The resulting hypocellularity limits a detailed analysis of the cellular immune response. To overcome this technical problem we performed a microarray analysis of CD3(+ )T-cells derived from bone marrow aspirates and peripheral blood samples of newly diagnosed AA patients and healthy volunteers. Two AA patients were additionally analyzed after achieving a partial remission following immunosuppression. The regulation of selected candidate genes was confirmed by real-time RT-PCR. RESULTS: Among more than 22.200 transcripts, 583 genes were differentially expressed in the bone marrow of AA patients compared to healthy controls. Dysregulated genes are involved in T-cell mediated cytotoxicity, immune response of Th1 differentiated T-cells, and major regulators of immune function. In hematological remission the expression levels of several candidate genes tend to normalize, such as immune regulators and genes involved in proinflammatory immune response. CONCLUSION: Our study suggests a pivotal role of Th1/Tc1 differentiated T-cells in immune-mediated marrow destruction of AA patients. Most importantly, immune regulatory genes could be identified, which are likely involved in the recovery of hematopoiesis and may help to design new therapeutic strategies in bone marrow failure syndromes

Valuing vicinity: Memory attention framework for context-based semantic segmentation in histopathology

The segmentation of histopathological whole slide images into tumourous and non-tumourous types of tissue is a challenging task that requires the consideration of both local and global spatial contexts to classify tumourous regions precisely. The identification of subtypes of tumour tissue complicates the issue as the sharpness of separation decreases and the pathologist’s reasoning is even more guided by spatial context. However, the identification of detailed tissue types is crucial for providing personalized cancer therapies. Due to the high resolution of whole slide images, existing semantic segmentation methods, restricted to isolated image sections, are incapable of processing context information beyond. To take a step towards better context comprehension, we propose a patch neighbour attention mechanism to query the neighbouring tissue context from a patch embedding memory bank and infuse context embeddings into bottleneck hidden feature maps. Our memory attention framework (MAF) mimics a pathologist’s annotation procedure — zooming out and considering surrounding tissue context. The framework can be integrated into any encoder–decoder segmentation method. We evaluate the MAF on two public breast cancer and liver cancer data sets and an internal kidney cancer data set using famous segmentation models (U-Net, DeeplabV3) and demonstrate the superiority over other context-integrating algorithms — achieving a substantial improvement of up to 17% on Dice score

Circulating endothelial cells are an early predictor in renal cell carcinoma for tumor response to sunitinib

<p>Abstract</p> <p>Background</p> <p>Tyrosine kinase inhibitors (TKI) have enriched the therapeutic options in patients with renal cell carcinoma (RCC), which frequently induce morphological changes in tumors. However, only little is known about the biological activity of TKI. Circulating endothelial cells (CEC) have been associated with endothelial damage and, hence, may serve as a putative marker for the biological activity of TKI. The main objective of our study was to evaluate the predictive value of CEC, monocytes, and soluble vascular endothelial growth factor receptor (sVEGFR)-2 in RCC patients receiving sunitinib treatment.</p> <p>Methods</p> <p>Analyses of CEC, monocytes, and sVEGFR-2 were accomplished for twenty-six consecutive patients with metastatic RCC who received treatment with sunitinib (50 mg, 4 wks on 2 wks off schedule) at our institution in 2005 and 2006.</p> <p>Results</p> <p>In RCC patients CEC are elevated to 49 ± 44/ml (control 8 ± 8/ml; P = 0.0001). Treatment with sunitinib is associated with an increase in CEC within 28 days of treatment in patients with a Progression free survival (PFS) above the median to 111 ± 61 (P = 0.0109), whereas changes in patients with a PFS below the median remain insignificant 69 ± 61/ml (P = 0.1848). Monocytes and sVEGFR2 are frequently altered upon sunitinib treatment, but fail to correlate with clinical response, defined by PFS above or below the median.</p> <p>Conclusions</p> <p>Sunitinib treatment is associated with an early increase of CEC in responding patients, suggesting superior endothelial cell damage in these patients as a putative predictive biomarker.</p

Battle of the cells: With the help of the body’s immune defense against cancer

Immunonkologische Therapien helfen, die körpereigene Immunantwort gezielt auf Tumorzellen auszurichten und Krebserkrankungen zu behandeln. Eine besondere Rolle kommt den zytotoxischen T-Lymphozyten zu, die strengen Regulationsmechanismen unterliegen. Diese Regulation durch Immun-Checkpoints nutzen immunonkologische Wirkstoffe und aktivieren auf diesem Weg die T-Lymphozyten für den Angriff auf Krebszellen. Ein weiterer immunonkologischer Ansatz ist die Zelltherapie, die patienteneigene T-Lymphozyten genetisch modifiziert und so ein gezieltes Erkennen von Krebszellen und deren Bekämpfung ermöglicht. Darüber hinaus bietet die Immunonkologie weitere Möglichkeiten, wie etwa eine allgemeine Immunstimulation über Zytokine, Impfstoffe gegen Krebs oder onkolytische Viren. Die Immunonkologie ist Gegenstand intensiver Forschungsarbeit und klinischer Entwicklung. Neue Wirkstoffe sowie Kombinationsansätze helfen dabei, die Versorgung von Krebspatienten weiter zu verbessern.Immuno-oncological therapies help to direct the body’s immune response specifically towards tumour cells. Cytotoxic T lymphocytes which play a crucial role for such therapies are subject to strict regulatory mechanisms. This regulation by immune checkpoints is used by immuno-oncological drugs in order to activate T lymphocytes and allow them to attack cancer cells. Another immuno-oncological approach is cell therapy, where the patient’s T lymphocytes are genetically modified to specifically recognize and fight tumour cells. In addition, immuno-oncology offers other options, such as general immune stimulation via cytokines, vaccines against cancer or oncolytic viruses. Immuno-oncology is the subject of intense research and clinical development. New drugs and combination approaches help to further improve the treatment of cancer patients

Systemic treatment of advanced/metastatic renal cell carcinoma in the context of SARS-CoV-2 pandemic: recommendations from the interdisciplinary working group for renal tumors (IAG-N)

Abstract This letter summarizes recommendations from the interdisciplinary working group of renal tumors (IAGN) of the German Cancer Society for the systemic treatment of advanced/metastatic renal cell carcinoma in the context of the current SARS-CoV-2 pandemi