Programmed death ligand-1 expression in adrenocortical carcinoma: an exploratory biomarker study

Background: Adrenocortical carcinoma (ACC) is a rare tumor in which prognostic factors are still not well established. Programmed Death Ligand-1 (PD-L1) expression in ACC and its association with clinico-pathological features and survival outcomes are unknown. Methods: Formalin-fixed paraffin-embedded (FFPE) specimens were obtained from 28 patients with ACC. PD-L1 expression was evaluated by immunohistochemistry (IHC) in both tumor cell membrane and tumor infiltrating mononuclear cells (TIMC). PD-L1 positivity on tumor cells was defined as ≥5% tumor cell membrane staining. TIMC were evaluated by IHC using a CD45 monoclonal antibody. For PD-L1 expression in TIMC, a combined score based on the extent of infiltrates and percentage of positive cells was developed. Any score greater that zero was considered PD-L1 positive. Baseline clinico-pathological characteristics and follow up data were retrospectively collected. Comparisons between PD-L1 expression and clinico-pathological features were evaluated using unpaired t-test and Fisher’s exact test. Kaplan-Meier method and log-rank test were used to assess association between PD-L1 expression and 5-year overall survival (OS). Results: Among 28 patients with surgically treated ACC, 3 (10.7%) were considered PD-L1 positive on tumor cell membrane. On the other hand, PD-L1 expression in TIMC was performed in 27 specimens and PD-L1 positive staining was observed in 19 (70.4%) patients. PD-L1 positivity in either tumor cell membrane or TIMC was not significantly associated with higher stage at diagnosis, higher tumor grade, excessive hormone secretion, or OS. Conclusions: PD-L1 expression can exist in ACC in both tumor cell membrane and TIMC with no relationship to clinico-pathologic parameters or survival. Electronic supplementary material The online version of this article (doi:10.1186/s40425-015-0047-3) contains supplementary material, which is available to authorized users

Overall Survival with Adjuvant Pembrolizumab in Renal-Cell Carcinoma

BackgroundAdjuvant pembrolizumab therapy after surgery for renal-cell carcinoma was approved on the basis of a significant improvement in disease-free survival in the KEYNOTE-564 trial. Whether the results regarding overall survival from the third prespecified interim analysis of the trial would also favor pembrolizumab was uncertain.MethodsIn this phase 3, double-blind, placebo-controlled trial, we randomly assigned (in a 1:1 ratio) participants with clear-cell renal-cell carcinoma who had an increased risk of recurrence after surgery to receive pembrolizumab (at a dose of 200 mg) or placebo every 3 weeks for up to 17 cycles (approximately 1 year) or until recurrence, the occurrence of unacceptable toxic effects, or withdrawal of consent. A significant improvement in disease-free survival according to investigator assessment (the primary end point) was shown previously. Overall survival was the key secondary end point. Safety was a secondary end point.Download a PDF of the Research Summary.ResultsA total of 496 participants were assigned to receive pembrolizumab and 498 to receive placebo. As of September 15, 2023, the median follow-up was 57.2 months. The disease-free survival benefit was consistent with that in previous analyses (hazard ratio for recurrence or death, 0.72; 95% confidence interval [CI], 0.59 to 0.87). A significant improvement in overall survival was observed with pembrolizumab as compared with placebo (hazard ratio for death, 0.62; 95% CI, 0.44 to 0.87; P=0.005). The estimated overall survival at 48 months was 91.2% in the pembrolizumab group, as compared with 86.0% in the placebo group; the benefit was consistent across key subgroups. Pembrolizumab was associated with a higher incidence of serious adverse events of any cause (20.7%, vs. 11.5% with placebo) and of grade 3 or 4 adverse events related to pembrolizumab or placebo (18.6% vs. 1.2%). No deaths were attributed to pembrolizumab therapy.ConclusionsAdjuvant pembrolizumab was associated with a significant and clinically meaningful improvement in overall survival, as compared with placebo, among participants with clear-cell renal-cell carcinoma at increased risk for recurrence after surgery. (Funded by Merck Sharp and Dohme, a subsidiary of Merck; KEYNOTE-564 ClinicalTrials.gov number, NCT03142334.

Cabozantinib in Chemotherapy-Pretreated Metastatic Castration-Resistant Prostate Cancer: Results of a Phase II Nonrandomized Expansion Study

Cabozantinib (XL184), an oral inhibitor of multiple receptor tyrosine kinases such as MET and VEGFR2, was evaluated in a phase II nonrandomized expansion study in castration-resistant prostate cancer (CRPC)

Short-Term Mortality Prediction in Advanced Cancer Patients Eligible for End-of-Life (EOL) Care Processes Using Electronic Health Records

Purpose: For terminally ill cancer patients, accurate and consistent prediction of mortality can have far reaching implications for care delivery and resource utilization. The objective of this study was to apply machine learning and informatics methodologies to construct, test, and compare the performance of short-term mortality prediction models in patients with advanced stage, non-curative cancer using EHR and registry. Methods: EHR and registry data were collected on 22,700 and 7,300 adult, Stage IV prostate and bladder cancer patients. The patients received care between 2004-2014. The ‘traditional’ feature set included standard demographics, 20-variable co-morbidity count. The ‘cumulative impact’ feature set was compiled using a time-segmented tally of encounters in the 1-3 and 3-12 months prior to t0. Lastly, the ‘novel’ features used to augment the above data included cancer stage at initial diagnosis, cancer grade, number of standard treatment lines, durable medical equipment, non-elective hospital admissions, ER visits, inpatient consults. Classifiers tested included Naïve Bayes, support vector machine (SVM), K nearest neighbor (k-NN), artificial neural nets (ANN), random forest (RF), and logistic regression. Each disease cohort was analyzed using the same training and validation samples to compare the different classifiers. Area under receiver operating curve (AUC) was used as the performance measure for all classifiers. Results: Each of the classifiers trained using the augmented features i.e. ‘cumulative impact’ and ‘novel’ features performed better than their ‘traditional’ model counterparts. For the prostate cancer cohort, the best performing model was the RF which had an AUC of 0.895 (SD 0.011) using the augmented features and AUC 0.782 (SD 0.011) using the traditional features. For the bladder cohort, the best performing model was also the RF which had an AUC of 0.934 (SD 0.011) using the augmented features and AUC 0.817 (SD 0.010) using the traditional features. Conclusion: The incorporation of patient’s augmented and time-stratified feature sets from the EHR provided for better performing classification models. Next steps include further integration of data based on palliative care expertise, such as changes in pain meds over time, interventional procedures, etc. Larger implications for this work include guiding end-of-life process improvements, policy, and resource utilization

The role of Src in colon cancer and its therapeutic implications

Src is a member of a superfamily of membrane-associated nonreceptor protein tyrosine kinases. It is stimulated by receptors of growth hormone, cytokines, and adipokines, and it regulates multiple signaling pathways, including phosphatidylinositide 3 kinase-Akt, mitogen-activated protein kinase, signal transducer and activator of transcription 3, interleukin 8, and vascular endothelial growth factor pathways, and cytoskeletal pathways to cause a cascade of cellular responses. Eighty percent of patients with colon cancer overexpress Src in tumor tissue. Evidence has shown that the overexpression of Src in colon cancer accelerates metastasis and causes chemotherapeutic drug resistance via multiple downstream signaling pathways. Therefore, the inhibition of Src may be useful for the treatment of colon cancer. However, the inhibition of Src may also weaken immune responses that are essential for the eradication of cancer cells. Overcoming the problem of inhibiting Src in cancer cells while retaining immune system efficacy is the key to the successful application of Src-inhibition therapy. Different Src family members are used by the immune system and colon cancer. This differential use may provide a good opportunity to develop Src family member-specific inhibitors to avoid immune inhibition