Profiling non-small cell lung cancer reveals that PD-L1 is associated with wild type EGFR and vascular invasion, and immunohistochemistry quantification of PD-L1 correlates weakly with RT-qPCR.

Most lung cancer patients are diagnosed at an advanced stage, limiting their treatment options with very low response rate. Lung cancer is the most common cause of cancer death worldwide. Therapies that target driver gene mutations (e.g. EGFR, ALK, ROS1) and checkpoint inhibitors such anti-PD-1 and PD-L1 immunotherapies are being used to treat lung cancer patients. Identification of correlations between driver mutations and PD-L1 expression will allow for the best management of patient treatment. 851 cases of non-small cell lung cancer cases were profiled for the presence of biomarkers EGFR, KRAS, BRAF, and PIK3CA mutations by SNaPshot/sizing genotyping. Immunohistochemistry was used to identify the protein expression of ALK and PD-L1. Total PD-L1 mRNA expression (from unsorted tumor samples) was quantified by RT-qPCR in a sub-group of the cohort to assess its correlation with PD-L1 protein level in tumor cells. Statistical analysis revealed correlations between the presence of the mutations, PD-L1 expression, and the pathological data. Specifically, increased PD-L1 expression was associated with wildtype EGFR and vascular invasion, and total PD-L1 mRNA levels correlated weakly with protein expression on tumor cells. These data provide insights into driver gene mutations and immune checkpoint status in relation to lung cancer subtypes and suggest that RT-qPCR is useful for assessing PD-L1 levels.

Molecular profiling of non-small cell lung cancer.

Lung cancer is generally treated with conventional therapies, including chemotherapy and radiation. These methods, however, are not specific to cancer cells and instead attack every cell present, including normal cells. Personalized therapies provide more efficient treatment options as they target the individual's genetic makeup. The goal of this study was to identify the frequency of causal genetic mutations across a variety of lung cancer subtypes in the earlier stages. 833 samples of non-small cell lung cancer from 799 patients who received resection of their lung cancer, were selected for molecular analysis of six known mutations, including EGFR, KRAS, BRAF, PIK3CA, HER2 and ALK. A SNaPshot assay was used for point mutations and fragment analysis searched for insertions and deletions. ALK was evaluated by IHC +/- FISH. Statistical analysis was performed to determine correlations between molecular and clinical/pathological patient data. None of the tested variants were identified in most (66.15%) of cases. The observed frequencies among the total samples vs. only the adenocarcinoma cases were notable different, with the highest frequency being the KRAS mutation (24.49% vs. 35.55%), followed by EGFR (6.96% vs. 10.23%), PIK3CA (1.20% vs. 0.9%), BRAF (1.08% vs. 1.62%), ALK (0.12% vs. 0.18%), while the lowest was the HER2 mutation (0% for both). The statistical analysis yielded correlations between presence of a mutation with gender, cancer type, vascular invasion and smoking history. The outcome of this study will provide data that helps stratify patient prognosis and supports development of more precise treatments, resulting in improved outcomes for future lung cancer patients.

Prevention of alopecia in medical and interventional chemotherapy patients.

BACKGROUND: Chemotherapy-induced alopecia is one of the most distressing side effects of cancer treatment. Although there have been a number of investigated strategies to reduce this, there is no standard of care for treatment. OBJECTIVE: This review aims to summarize the relevant evidence for the treatments available for chemotherapy-induced alopecia. METHODS: A literature search using PubMed and the MEDLINE subengine was completed. The terms "chemotherapy," "alopecia," "quality of life," and "strategies" were used, and articles from the last 10 years were considered. The pediatric population was not investigated. RESULTS: Physical therapies for alopecia prevention have shown some promise but range from insufficient to detrimental depending on the type of cancer. Cold caps may be more effective than tourniquets and may be associated with fewer metastatic events. Pharmacologic therapies, both immunomodulators and growth factors, have stood the test of several trials to date. In particular, cyclosporine has been shown either to prevent alopecia or promote hair growth during a chemotherapy regimen. CONCLUSION: Although the evidence is not yet overwhelming, it is becoming clear that a combination of mechanical and chemical interventions may help compensate for the downfalls of either therapy alone.

Brief report: a phase II study of sunitinib in malignant pleural mesothelioma. the NCIC Clinical Trials Group.

INTRODUCTION: Malignant pleural mesothelioma (MPM) is an aggressive malignancy that most often presents at an advanced, incurable stage. After the failure of standard first-line cisplatin/antifolate chemotherapy, there is no accepted treatment. The vascular endothelial growth factor pathway may be a relevant therapeutic target in MPM. METHODS: This open-labeled phase II trial evaluated single-agent sunitinib, an inhibitor of multiple receptor tyrosine kinases including the vascular endothelial growth factor receptors, given at 50 mg daily orally for 4 weeks followed by a 2-week rest, in patients with advanced MPM. Two cohorts were studied: cohort 1, in which patients had previously received cisplatin-based chemotherapy, and cohort 2, consisting of previously untreated patients. A two-stage design was used for both cohorts; the primary outcome was objective response rate as determined by the RECIST criteria modified for MPM. Secondary outcomes included rates and duration of disease control, progression-free survival and overall survival, and safety and tolerability. RESULTS: A total of 35 eligible patients were enrolled (17 to cohort 1 and 18 to cohort 2). Neither cohort met the criteria for continuing to the second stage of accrual; only one objective response, confirmed by independent review, was observed in a previously untreated patient. Median progression-free and overall survivals were 2.8 and 8.3 months in cohort 1, and 2.7 and 6.7 months in cohort 2, respectively. Observed toxicity was within that expected for sunitinib. CONCLUSIONS: Sunitinib, similar to other angiogenesis inhibitors, has limited activity in MPM. Future trials of angiogenesis inhibitors given as single agents in unselected patients with MPM are not warranted.

Adjuvant chemotherapy uptake in non-small cell lung cancer.

INTRODUCTION: Adjuvant chemotherapy in non-small cell lung cancer (NSCLC) has become a new standard of care. This study examines the uptake patterns for adjuvant chemotherapy outside of clinical trials. METHODS: A retrospective study of all patients diagnosed with NSCLC in the year 2005 who underwent curative-intent surgery in Nova Scotia, Canada was conducted. Logistic regression models and discriminant function analyses were employed to identify cofactors associated with referral to medical oncology and/or utilization of adjuvant chemotherapy. RESULTS: Of 540 patients with NSCLC, 108 underwent curative-intent surgery (67% lobectomy; 15% pneumonectomy; 19% wedge resection) for NSCLC (39% IA; 24% IB; 25% II; 14% III). Referral to medical oncology was observed in 44% (47 of 108) of all patients including 73% (30 of 41) of those with stage II-III. Adjuvant chemotherapy utilization was observed in 62% (29 of 47) of those referred including 73% (22 of 30) of those with stage II-III. Overall, 27% (29 of 108) of all patients received adjuvant chemotherapy, including 54% (22 of 41) of those with stage II-III. Higher uptake was significantly associated with age (younger versus older), stage (II/III versus I), and surgery type (pneumonectomy versus wedge). Weaker associations were observed with other cofactors including surgeon, health center, mean household income, and surgery-medical oncologist consult timeline. CONCLUSIONS: The uptake of adjuvant chemotherapy in patients with resected NSCLC outside of clinical trials is low overall, but is higher among younger patients and those with more advanced stages. These uptake patterns may allow future planning of health resource utilization and/or improvement of chemotherapy utilization rates.

Waiting times in early-stage non-small cell lung cancer (NSCLC).

INTRODUCTION: Wait times in cancer care continue to be an important clinical, social, and political issue. This study examines wait times along the care path from suspicious imaging study (Detection) to adjuvant chemotherapy initiation (Chemotherapy) for patients with early-stage non-small cell lung cancer (NSCLC) who undergo surgical resection. METHODS: A retrospective chart review of patients diagnosed in 2005 with NSCLC who underwent curative-intent surgery in Nova Scotia, Canada was conducted to abstract dates of care events (Detection, Surgery Consultation, Surgery, Medical Oncology [MO] Referral, MO Consultation and Chemotherapy) and patient characteristics. Multifactorial regression methods were used to identify statistically-significant cofactors associated with wait times at various resolutions of care intervals (low, intermediate, high). RESULTS: A median wait time of 141 days elapsed between Detection-Chemotherapy; and a median 107 and 52 days elapsed between Detection-Surgery and Surgery-Chemotherapy, respectively. A number of demographic, clinical, epidemiological, and system resource dependant factors influenced wait times at different resolutions, and were best detailed utilizing high resolution analysis. Wait time between MO referral-MO Consultation was inversely related to that experienced in the preceding interval of Surgery-MO Referral. CONCLUSIONS: This study provides a first detailed examination of wait times experienced by NSCLC patients undergoing curative-intent surgery according to care interval definitions; demonstrates the value of high care interval resolution analysis to detect bottlenecks in access to care; and reports on the interdependence of elapsed times between care events along the care path for cancer patients.