Nivolumab was associated with higher rates of objective response than chemotherapy in a phase 3 study involving patients with ipilimumab-refractory metastatic melanoma. The use of nivolumab in ...previously untreated patients with advanced melanoma has not been tested in a phase 3 controlled study.
We randomly assigned 418 previously untreated patients who had metastatic melanoma without a BRAF mutation to receive nivolumab (at a dose of 3 mg per kilogram of body weight every 2 weeks and dacarbazine-matched placebo every 3 weeks) or dacarbazine (at a dose of 1000 mg per square meter of body-surface area every 3 weeks and nivolumab-matched placebo every 2 weeks). The primary end point was overall survival.
At 1 year, the overall rate of survival was 72.9% (95% confidence interval CI, 65.5 to 78.9) in the nivolumab group, as compared with 42.1% (95% CI, 33.0 to 50.9) in the dacarbazine group (hazard ratio for death, 0.42; 99.79% CI, 0.25 to 0.73; P<0.001). The median progression-free survival was 5.1 months in the nivolumab group versus 2.2 months in the dacarbazine group (hazard ratio for death or progression of disease, 0.43; 95% CI, 0.34 to 0.56; P<0.001). The objective response rate was 40.0% (95% CI, 33.3 to 47.0) in the nivolumab group versus 13.9% (95% CI, 9.5 to 19.4) in the dacarbazine group (odds ratio, 4.06; P<0.001). The survival benefit with nivolumab versus dacarbazine was observed across prespecified subgroups, including subgroups defined by status regarding the programmed death ligand 1 (PD-L1). Common adverse events associated with nivolumab included fatigue, pruritus, and nausea. Drug-related adverse events of grade 3 or 4 occurred in 11.7% of the patients treated with nivolumab and 17.6% of those treated with dacarbazine.
Nivolumab was associated with significant improvements in overall survival and progression-free survival, as compared with dacarbazine, among previously untreated patients who had metastatic melanoma without a BRAF mutation. (Funded by Bristol-Myers Squibb; CheckMate 066 ClinicalTrials.gov number, NCT01721772.).
Circulating tumor cells (CTCs) carry independent prognostic information in patients with metastatic breast cancer (MBC) on different lines of therapy. Moreover, CTC clusters are suggested to add ...prognostic information to CTC enumeration alone but their significance is unknown in patients with newly diagnosed MBC. We aimed to evaluate whether longitudinal enumeration of circulating tumor cells (CTCs) and CTC clusters could improve prognostication and monitoring of patients with metastatic breast cancer (MBC) starting first-line therapy.
This prospective study included 156 women with newly diagnosed MBC. CTCs and CTC clusters were detected using CellSearch technology at baseline (BL) and after 1, 3, and 6 months of systemic therapy. The primary end point was progression-free survival (PFS) and the secondary end point overall survival (OS). Median follow-up time was 25 (7-69) months.
There were 79 (52%) and 30 (20%) patients with ≥ 5 CTCs and ≥ 1 CTC cluster at baseline, respectively; both factors were significantly associated with impaired survival. Landmark analyses based on follow-up measurements revealed increasing prognostic hazard ratios for ≥ 5 CTCs and CTC clusters during treatment, predicting worse PFS and OS. Both factors added value to a prognostic model based on clinicopathological variables at all time points and ≥ 5 CTCs and presence of CTC clusters enhanced the model's C-index to > 0.80 at 1, 3, and 6 months. Importantly, changes in CTCs during treatment were significantly correlated with survival and patients with a decline from ≥ 5 CTCs at BL to < 5 CTCs at 1 month had a similar odds ratio for progression to patients with < 5 CTCs at BL and 1 month. Stratification of patients based on CTC count and CTC clusters into four groups (0 CTCs, 1-4 CTCs, ≥ 5 CTCs, and ≥ 1 CTC + CTC clusters) demonstrated that patients with CTC clusters had significantly worse survival compared to patients without clusters.
Longitudinal evaluation of CTC and CTC clusters improves prognostication and monitoring in patients with MBC starting first-line systemic therapy. The prognostic value increases over time, suggesting that changes in CTC count are clinically relevant. The presence of CTC clusters adds significant prognostic value to CTC enumeration alone.
NCT01322893 . Registered on 25 March 2011.
Melanoma is currently divided on a genetic level according to mutational status. However, this classification does not optimally predict prognosis. In prior studies, we have defined gene expression ...phenotypes (high-immune, pigmentation, proliferative and normal-like), which are predictive of survival outcome as well as informative of biology. Herein, we employed a population-based metastatic melanoma cohort and external cohorts to determine the prognostic and predictive significance of the gene expression phenotypes. We performed expression profiling on 214 cutaneous melanoma tumors and found an increased risk of developing distant metastases in the pigmentation (HR, 1.9; 95% CI, 1.05-3.28; P=0.03) and proliferative (HR, 2.8; 95% CI, 1.43-5.57; P=0.003) groups as compared to the high-immune response group. Further genetic characterization of melanomas using targeted deep-sequencing revealed similar mutational patterns across these phenotypes. We also used publicly available expression profiling data from melanoma patients treated with targeted or vaccine therapy in order to determine if our signatures predicted therapeutic response. In patients receiving targeted therapy, melanomas resistant to targeted therapy were enriched in the MITF-low proliferative subtype as compared to pre-treatment biopsies (P=0.02). In summary, the melanoma gene expression phenotypes are highly predictive of survival outcome and can further help to discriminate patients responding to targeted therapy.
For primary melanomas, tumor thickness, mitotic rate, and ulceration are well-laid cornerstones of prognostication. However, a molecular exposition of melanoma aggressiveness is critically missing. ...We recently uncovered a four-class structure in metastatic melanoma, which predicts outcome and informs biology. This raises the possibility that a molecular structure exists even in the early stages of melanoma and that molecular determinants could underlie histophenotype and eventual patient outcome.
We subjected 223 archival primary melanomas to a horizontally integrated analysis of RNA expression, oncogenic mutations at 238 lesions, histomorphometry, and survival data.
Our previously described four-class structure that was elucidated in metastatic lesions was evident within the expression space of primary melanomas. Because these subclasses converged into two larger prognostic and phenotypic groups, we used the metastatic lesions to develop a binary subtype-based signature capable of distinguishing between "high" and "low" grade forms of the disease. The two-grade signature was subsequently applied to the primary melanomas. Compared with low-grade tumors, high-grade primary melanomas were significantly associated with increased tumor thickness, mitotic rate, ulceration (all P < 0.01), and poorer relapse-free (HR = 4.94; 95% CI, 2.84-8.59), and overall (HR = 3.66; 95% CI, 2.40-5.58) survival. High-grade melanomas exhibited elevated levels of proliferation and BRCA1/DNA damage signaling genes, whereas low-grade lesions harbored higher expression of immune genes. Importantly, the molecular-grade signature was validated in two external gene expression data sets.
We provide evidence for a molecular organization within melanomas, which is preserved across all stages of disease.
Metastatic melanoma is still one of the most prevalent skin cancers, which upon progression has neither a prognostic marker nor a specific and lasting treatment. Proteomic analysis is a versatile ...approach with high throughput data and results that can be used for characterizing tissue samples. However, such analysis is hampered by the complexity of the disease, heterogeneity of patients, tumors, and samples themselves. With the long term aim of quest for better diagnostics biomarkers, as well as predictive and prognostic markers, we focused on relating high resolution proteomics data to careful histopathological evaluation of the tumor samples and patient survival information.
Regional lymph node metastases obtained from ten patients with metastatic melanoma (stage III) were analyzed by histopathology and proteomics using mass spectrometry. Out of the ten patients, six had clinical follow-up data. The protein deep mining mass spectrometry data was related to the histopathology tumor tissue sections adjacent to the area used for deep-mining. Clinical follow-up data provided information on disease progression which could be linked to protein expression aiming to identify tissue-based specific protein markers for metastatic melanoma and prognostic factors for prediction of progression of stage III disease.
In this feasibility study, several proteins were identified that positively correlated to tumor tissue content including IF6, ARF4, MUC18, UBC12, CSPG4, PCNA, PMEL and MAGD2. The study also identified MYC, HNF4A and TGFB1 as top upstream regulators correlating to tumor tissue content. Other proteins were inversely correlated to tumor tissue content, the most significant being; TENX, EHD2, ZA2G, AOC3, FETUA and THRB. A number of proteins were significantly related to clinical outcome, among these, HEXB, PKM and GPNMB stood out, as hallmarks of processes involved in progression from stage III to stage IV disease and poor survival.
In this feasibility study, promising results show the feasibility of relating proteomics to histopathology and clinical outcome, and insight thus can be gained into the molecular processes driving the disease. The combined analysis of histological features including the sample cellular composition with protein expression of each metastasis enabled the identification of novel, differentially expressed proteins. Further studies are necessary to determine whether these putative biomarkers can be utilized in diagnostics and prognostic prediction of metastatic melanoma.
Diversity between metastatic melanoma tumours in individual patients is known; however, the molecular and genetic differences remain unclear. To examine the molecular and genetic differences between ...metastatic tumours, we performed gene‐expression profiling of 63 melanoma tumours obtained from 28 patients (two or three tumours/patient), followed by analysis of their mutational landscape, using targeted deep sequencing of 1697 cancer genes and DNA copy number analysis. Gene‐expression signatures revealed discordant phenotypes between tumour lesions within a patient in 50% of the cases. In 18 of 22 patients (where matched normal tissue was available), we found that the multiple lesions within a patient were genetically divergent, with one or more melanoma tumours harbouring 'private' somatic mutations. In one case, the distant subcutaneous metastasis of one patient occurring 3 months after an earlier regional lymph node metastasis had acquired 37 new coding sequence mutations, including mutations in PTEN and CDH1. However, BRAF and NRAS mutations, when present in the first metastasis, were always preserved in subsequent metastases. The patterns of nucleotide substitutions found in this study indicate an influence of UV radiation but possibly also DNA alkylating agents. Our results clearly demonstrate that metastatic melanoma is a molecularly highly heterogeneous disease that continues to progress throughout its clinical course. The private aberrations observed on a background of shared aberrations within a patient provide evidence of continued evolution of individual tumours following divergence from a common parental clone, and might have implications for personalized medicine strategies in melanoma treatment. Published by John Wiley & Sons, Ltd. www.pathsoc.org.uk
Metastatic melanoma is one of the most common deadly cancers, and robust biomarkers are still needed, e.g. to predict survival and treatment efficiency. Here, protein expression analysis of one ...hundred eleven melanoma lymph node metastases using high resolution mass spectrometry is coupled with in-depth histopathology analysis, clinical data and genomics profiles. This broad view of protein expression allowed to identify novel candidate protein markers that improved prediction of survival in melanoma patients. Some of the prognostic proteins have not been reported in the context of melanoma before, and few of them exhibit unexpected relationship to survival, which likely reflects the limitations of current knowledge on melanoma and shows the potential of proteomics in clinical cancer research.
In the advanced stages, malignant melanoma (MM) has a very poor prognosis. Due to tremendous efforts in cancer research over the last 10 years, and the introduction of novel therapies such as ...targeted therapies and immunomodulators, the rather dark horizon of the median survival has dramatically changed from under 1 year to several years. With the advent of proteomics, deep-mining studies can reach low-abundant expression levels. The complexity of the proteome, however, still surpasses the dynamic range capabilities of current analytical techniques. Consequently, many predicted protein products with potential biological functions have not yet been verified in experimental proteomic data. This category of ‘missing proteins’ (MP) is comprised of all proteins that have been predicted but are currently unverified. As part of the initiative launched in 2016 in the USA, the European Cancer Moonshot Center has performed numerous deep proteomics analyses on samples from MM patients. In this study, nine MPs were clearly identified by mass spectrometry in MM metastases. Some MPs significantly correlated with proteins that possess identical PFAM structural domains; and other MPs were significantly associated with cancer-related proteins. This is the first study to our knowledge, where unknown and novel proteins have been annotated in metastatic melanoma tumour tissue.
Malignant melanoma (MM) patients are being treated with an increasing number of personalized medicine (PM) drugs, several of which are small molecule drugs developed to treat patients with specific ...disease genotypes and phenotypes. In particular, the clinical application of protein kinase inhibitors has been highly effective for certain subsets of MM patients. Vemurafenib, a protein kinase inhibitor targeting BRAF‐mutated protein, has shown significant efficacy in slowing disease progression. In this paper, we provide an overview of this new generation of targeted drugs, and demonstrate the first data on localization of PM drugs within tumor compartments. In this study, we have introduced MALDI‐MS imaging to provide new information on one of the drugs currently used in the PM treatment of MM, vemurafenib. In a proof‐of‐concept in vitro study, MALDI‐MS imaging was used to identify vemurafenib applied to metastatic lymph nodes tumors of subjects attending the regional hospital network of Southern Sweden. The paper provides evidence of BRAF overexpression in tumors isolated from MM patients and localization of the specific drug targeting BRAF, vemurafenib, using MS fragment ion signatures. Our ability to determine drug uptake at the target sites of directed therapy provides important opportunity for increasing our understanding about the mode of action of drug activity within the disease environment.
Malignant melanoma has the highest increase of incidence of malignancies in the western world. In early stages, front line therapy is surgical excision of the primary tumor. Metastatic disease has ...very limited possibilities for cure. Recently, several protein kinase inhibitors and immune modifiers have shown promising clinical results but drug resistance in metastasized melanoma remains a major problem. The need for routine clinical biomarkers to follow disease progression and treatment efficacy is high. The aim of the present study was to build a protein sequence database in metastatic melanoma, searching for novel, relevant biomarkers. Ten lymph node metastases (South-Swedish Malignant Melanoma Biobank) were subjected to global protein expression analysis using two proteomics approaches (with/without orthogonal fractionation). Fractionation produced higher numbers of protein identifications (4284). Combining both methods, 5326 unique proteins were identified (2641 proteins overlapping). Deep mining proteomics may contribute to the discovery of novel biomarkers for metastatic melanoma, for example dividing the samples into two metastatic melanoma "genomic subtypes", ("pigmentation" and "high immune") revealed several proteins showing differential levels of expression. In conclusion, the present study provides an initial version of a metastatic melanoma protein sequence database producing a total of more than 5000 unique protein identifications. The raw data have been deposited to the ProteomeXchange with identifiers PXD001724 and PXD001725.
PDF
