A transcriptomics approach to expand therapeutic options and optimize clinical trials in oncology.

Background: The current model of clinical drug development in oncology displays major limitations due to a high attrition rate in patient enrollment in early phase trials and a high failure rate of drugs in phase III studies. Objective: Integrating transcriptomics for selection of patients has the potential to achieve enhanced speed and efficacy of precision oncology trials for any targeted therapies or immunotherapies. Methods: Relative gene expression level in the metastasis and normal organ-matched tissues from the WINTHER database was used to estimate in silico the potential clinical benefit of specific treatments in a variety of metastatic solid tumors. Results: As example, high mRNA expression in tumor tissue compared to analogous normal tissue of c-MET and its ligand HGF correlated in silico with shorter overall survival (OS; p < 0.0001) and may constitute an independent prognostic marker for outcome of patients with metastatic solid tumors, suggesting a strategy to identify patients most likely to benefit from MET-targeted treatments. The prognostic value of gene expression of several immune therapy targets (PD-L1, CTLA4, TIM3, TIGIT, LAG3, TLR4) was investigated in non-small-cell lung cancers and colorectal cancers (CRCs) and may be useful to optimize the development of their inhibitors, and opening new avenues such as use of anti-TLR4 in treatment of patients with metastatic CRC. Conclusion: This in silico approach is expected to dramatically decrease the attrition of patient enrollment and to simultaneously increase the speed and detection of early signs of efficacy. The model may significantly contribute to lower toxicities. Altogether, our model aims to overcome the limits of current approaches.

Comorbidity between lung cancer and COVID-19 pneumonia: role of immunoregulatory gene transcripts in high ACE2-expressing normal lung.

Background: SARS-CoV-2 (COVID-19) elicits a T-cell antigen-mediated immune response of variable efficacy. To understand this variability, we explored transcriptomic expression of angiotensin-converting enzyme 2 (ACE2, the SARS-CoV-2 receptor) and of immunoregulatory genes in normal lung tissues from patients with non-small cell lung cancer (NSCLC). Methods: This study used the transcriptomic and the clinical data for NSCLC patients generated during the CHEMORES study [n = 123 primary resected (early-stage) NSCLC] and the WINTHER clinical trial (n = 32 metastatic NSCLC). Results: We identified patient subgroups with high and low ACE2 expression (p = 1.55 × 10-19) in normal lung tissue, presumed to be at higher and lower risk, respectively, of developing severe COVID-19 should they become infected. ACE2 transcript expression in normal lung tissues (but not in tumor tissue) of patients with NSCLC was higher in individuals with more advanced disease. High-ACE2 expressors had significantly higher levels of CD8+ cytotoxic T lymphocytes and natural killer cells but with presumably impaired function by high Thymocyte Selection-Associated High Mobility Group Box Protein TOX (TOX) expression. In addition, immune checkpoint-related molecules - PD-L1, CTLA-4, PD-1, and TIGIT - are more highly expressed in normal (but not tumor) lung tissues; these molecules might dampen immune response to either viruses or cancer. Importantly, however, high inducible T-cell co-stimulator (ICOS), which can amplify immune and cytokine reactivity, significantly correlated with high ACE2 expression in univariable analysis of normal lung (but not lung tumor tissue). Conclusions: We report a normal lung immune-tolerant state that may explain a potential comorbidity risk between two diseases - NSCLC and susceptibility to COVID-19 pneumonia. Further, a NSCLC patient subgroup has normal lung tissue expressing high ACE2 and high ICOS transcripts, the latter potentially promoting a hyperimmune response, and possibly leading to severe COVID-19 pulmonary compromise.

Transcriptomics in Tumor and Normal Lung Tissues Identify Patients With Early-Stage Non-Small-Cell Lung Cancer With High Risk of Postsurgery Recurrence Who May Benefit From Adjuvant Therapies.

PURPOSE: The prognosis of patients with non-small-cell lung cancer (NSCLC), traditionally determined by anatomic histology and TNM staging, neglects the biological features of the tumor that may be important in determining patient outcome and guiding therapeutic interventions. Identifying patients with NSCLC at increased risk of recurrence after curative-intent surgery remains an important unmet need so that known effective adjuvant treatments can be offered to those at highest risk of recurrence. METHODS: Relative gene expression level in the primary tumor and normal bronchial tissues was used to retrospectively assess their association with disease-free survival (DFS) in a cohort of 120 patients with NSCLC who underwent curative-intent surgery. RESULTS: Low versus high Digital Display Precision Predictor (DDPP) score (a measure of relative gene expression) was significantly associated with shorter DFS (highest recurrence risk; P = .006) in all patients and in patients with TNM stages 1-2 (P = .00051; n = 83). For patients with stages 1-2 and low DDPP score (n = 29), adjuvant chemotherapy was associated with improved DFS (P = .0041). High co-overexpression of CTLA-4, PD-L1, and ICOS in normal lung (28 of 120 patients) was also significantly associated with decreased DFS (P = .0013), suggesting an immune tolerance to tumor neoantigens in some patients. Patients with DDPP low and immunotolerant normal tissue had the shortest DFS (P = 2.12E-11). CONCLUSION: TNM stage, DDPP score, and immune competence status of normal lung are independent prognostic factors in multivariate analysis. Our findings open new avenues for prospective prognostic assessment and treatment assignment on the basis of transcriptomic profiling of tumor and normal lung tissue in patients with NSCLC.

A WIN Consortium phase I study exploring avelumab, palbociclib, and axitinib in advanced non-small cell lung cancer.

BACKGROUND: The Worldwide Innovative Network (WIN) Consortium has developed the Simplified Interventional Mapping System (SIMS) to better define the cancer molecular milieu based on genomics/transcriptomics from tumor and analogous normal tissue biopsies. SPRING is the first trial to assess a SIMS-based tri-therapy regimen in advanced non-small cell lung cancer (NSCLC). METHODS: Patients with advanced NSCLC (no EGFR, ALK, or ROS1 alterations; PD-L1 unrestricted; ≤2 prior therapy lines) received avelumab, axitinib, and palbociclib (3 + 3 dose escalation design). RESULTS: Fifteen patients were treated (five centers, four countries): six at each of dose levels 1 (DL1) and DL2; three at DL3. The most common ≥Grade 3 adverse events were neutropenia, hypertension, and fatigue. The recommended Phase II dose (RP2D) was DL1: avelumab 10 mg/kg IV q2weeks, axitinib 3 mg po bid, and palbociclib 75 mg po daily (7 days off/21 days on). Four patients (27%) achieved a partial response (PR) (progression-free survival [PFS]: 14, 24, 25 and 144+ weeks), including two after progression on pembrolizumab. Four patients attained stable disease (SD) that lasted ≥24 weeks: 24, 27, 29, and 64 weeks. At DL1 (RP2D), four of six patients (66%) achieved stable disease (SD) ≥6 months/PR (2 each). Responders included patients with no detectable PD-L1 expression and low tumor mutational burden. CONCLUSIONS: Overall, eight of 15 patients (53%) achieved clinical benefit (SD ≥ 24 weeks/PR) on the avelumab, axitinib, and palbociclib combination. This triplet showed antitumor activity in NSCLC, including in tumors post-pembrolizumab progression, and was active at the RP2D, which was well tolerated. NCT03386929 clinicaltrial.gov.

Synthetic lethality-mediated precision oncology via the tumor transcriptome.

Precision oncology has made significant advances, mainly by targeting actionable mutations in cancer driver genes. Aiming to expand treatment opportunities, recent studies have begun to explore the utility of tumor transcriptome to guide patient treatment. Here, we introduce SELECT (synthetic lethality and rescue-mediated precision oncology via the transcriptome), a precision oncology framework harnessing genetic interactions to predict patient response to cancer therapy from the tumor transcriptome. SELECT is tested on a broad collection of 35 published targeted and immunotherapy clinical trials from 10 different cancer types. It is predictive of patients' response in 80% of these clinical trials and in the recent multi-arm WINTHER trial. The predictive signatures and the code are made publicly available for academic use, laying a basis for future prospective clinical studies.

Digital Display Precision Predictor: the prototype of a global biomarker model to guide treatments with targeted therapy and predict progression-free survival.

The expanding targeted therapy landscape requires combinatorial biomarkers for patient stratification and treatment selection. This requires simultaneous exploration of multiple genes of relevant networks to account for the complexity of mechanisms that govern drug sensitivity and predict clinical outcomes. We present the algorithm, Digital Display Precision Predictor (DDPP), aiming to identify transcriptomic predictors of treatment outcome. For example, 17 and 13 key genes were derived from the literature by their association with MTOR and angiogenesis pathways, respectively, and their expression in tumor versus normal tissues was associated with the progression-free survival (PFS) of patients treated with everolimus or axitinib (respectively) using DDPP. A specific eight-gene set best correlated with PFS in six patients treated with everolimus: AKT2, TSC1, FKB-12, TSC2, RPTOR, RHEB, PIK3CA, and PIK3CB (r = 0.99, p = 5.67E-05). A two-gene set best correlated with PFS in five patients treated with axitinib: KIT and KITLG (r = 0.99, p = 4.68E-04). Leave-one-out experiments demonstrated significant concordance between observed and DDPP-predicted PFS (r = 0.9, p = 0.015) for patients treated with everolimus. Notwithstanding the small cohort and pending further prospective validation, the prototype of DDPP offers the potential to transform patients' treatment selection with a tumor- and treatment-agnostic predictor of outcomes (duration of PFS).

DNA FISH Diagnostic Assay on Cytological Samples of Thyroid Follicular Neoplasms.

Although fine-needle aspiration cytology (FNAC) is helpful in determining whether thyroid nodules are benign or malignant, this distinction remains a cytological challenge in follicular neoplasms. Identification of genomic alterations in cytological specimens with direct and routine techniques would therefore have great clinical value. A series of 153 cases consisting of 72 and 81 histopathologically confirmed classic follicular adenomas (cFAs) and classic follicular thyroid carcinomas (cFTCs), respectively, was studied by means of different molecular techniques in three different cohorts of patients (pts). In the first cohort (training set) of 66 pts, three specific alterations characterized by array comparative genomic hybridization (aCGH) were exclusively found in half of cFTCs. These structural abnormalities corresponded to losses of 1p36.33-35.1 and 22q13.2-13.31, and gain of whole chromosome X. The second independent cohort (validation set) of 60 pts confirmed these data on touch preparations of frozen follicular neoplasms by triple DNA fluorescent in situ hybridization using selected commercially available probes. The third cohort, consisting of 27 archived cytological samples from an equal number of pts that had been obtained for preoperative FNAC and morphologically classified as and histologically verified to be follicular neoplasms, confirmed our previous findings and showed the feasibility of the DNA FISH (DNA fluorescent in situ hybridization) assay. All together, these data suggest that our triple DNA FISH diagnostic assay may detect 50% of cFTCs with a specificity higher than 98% and be useful as a low-cost adjunct to cytomorphology to help further classify follicular neoplasms on already routinely stained cytological specimens.

Adipocyte-Based Cell Therapy in Oncology: The Role of Cancer-Associated Adipocytes and Their Reinterpretation as Delivery Platforms.

Cancer-associated adipocytes have functional roles in tumor development through secreted adipocyte-derived factors and exosomes and also through metabolic symbiosis, where the malignant cells take up the lactate, fatty acids and glutamine produced by the neighboring adipocytes. Recent research has demonstrated the value of adipocytes as cell-based delivery platforms for drugs (or prodrugs), nucleic acids or loaded nanoparticles for cancer therapy. This strategy takes advantage of the biocompatibility of the delivery system, its ability to locate the tumor site and also the predisposition of cancer cells to come in functional contact with the adipocytes from the tumor microenvironment for metabolic sustenance. Also, their exosomal content can be used in the context of cancer stem cell reprogramming or as a delivery vehicle for different cargos, like non-coding nucleic acids. Moreover, the process of adipocytes isolation, processing and charging is quite straightforward, with minimal economical expenses. The present review comprehensively presents the role of adipocytes in cancer (in the context of obese and non-obese individuals), the main methods for isolation and characterization and also the current therapeutic applications of these cells as delivery platforms in the oncology sector.

A Comprehensive Picture of Extracellular Vesicles and Their Contents. Molecular Transfer to Cancer Cells.

Critical processes such as growth, invasion, and metastasis of cancer cells are sustained via bidirectional cell-to-cell communication in tissue complex environments. Such communication involves the secretion of soluble factors by stromal cells and/or cancer cells within the tumor microenvironment (TME). Both stromal and cancer cells have been shown to export bilayer nanoparticles: encapsulated regulatory molecules that contribute to cell-to-cell communication. These nanoparticles are known as extracellular vesicles (EVs) being classified into exosomes, microvesicles, and apoptotic bodies. EVs carry a vast repertoire of molecules such as oncoproteins and oncopeptides, DNA fragments from parental to target cells, RNA species (mRNAs, microRNAs, and long non-coding RNA), and lipids, initiating phenotypic changes in TME. According to their specific cargo, EVs have crucial roles in several early and late processes associated with tumor development and metastasis. Emerging evidence suggests that EVs are being investigated for their implication in early cancer detection, monitoring cancer progression and chemotherapeutic response, and more relevant, the development of novel targeted therapeutics. In this study, we provide a comprehensive understanding of the biophysical properties and physiological functions of EVs, their implications in TME, and highlight the applicability of EVs for the development of cancer diagnostics and therapeutics.

SERS-based differential diagnosis between multiple solid malignancies: breast, colorectal, lung, ovarian and oral cancer.

PURPOSE: Surface-enhanced Raman scattering (SERS) spectroscopy on serum and other biofluids for cancer diagnosis represents an emerging field, which has shown promising preliminary results in several types of malignancies. The purpose of this study was to demonstrate that SERS spectroscopy on serum can be employed for the differential diagnosis between five of the leading malignancies, ie, breast, colorectal, lung, ovarian and oral cancer. PATIENTS AND METHODS: Serum samples were acquired from healthy volunteers (n=39) and from patients diagnosed with breast (n=42), colorectal (n=109), lung (n=33), oral (n=17), and ovarian cancer (n=13), comprising n=253 samples in total. SERS spectra were acquired using a 532 nm laser line as excitation source, while the SERS substrates were represented by Ag nanoparticles synthesized by reduction with hydroxylamine. The classification accuracy yielded by SERS was assessed by principal component analysis-linear discriminant analysis (PCA-LDA). RESULTS: The sensitivity and specificity in discriminating between cancer patients and controls was 98% and 91%, respectively. Cancer samples were correctly assigned to their corresponding cancer types with an accuracy of 88% for oral cancer, 86% for colorectal cancer, 80% for ovarian cancer, 76% for breast cancer and 59% for lung cancer. CONCLUSION: SERS on serum represents a promising strategy of diagnosing cancer which can discriminate between cancer patients and controls, as well as between cancer types such as breast, colorectal, lung ovarian and oral cancer.

Inhibition of the NKp44-PCNA Immune Checkpoint Using a mAb to PCNA.

mAb-based blocking of the immune checkpoints involving the CTLA4-B7 and PD1-PDL1 inhibitory axes enhance T-cell-based adaptive immune responses in patients with cancer. We show here that antitumor responses by natural killer (NK) cells can be enhanced by a checkpoint-blocking mAb, 14-25-9, which we developed against proliferating cell nuclear antigen (PCNA). PCNA is expressed on the surface of cancer cells and acts as an inhibitory ligand for the NK-cell receptor, NKp44-isoform1. We tested for cytoplasmic- and membrane-associated PCNA by FACS- and ImageStream-based staining of cell lines and IHC of human cancer formalin fixed, paraffin embedded tissues. The mAb, 14-25-9, inhibited binding of chimeric NKp44 receptor to PCNA and mostly stained the cytoplasm and membrane of tumor cells, whereas commercial antibody (clone PC10) stained nuclear PCNA. NK functions were measured using ELISA-based IFNγ secretion assays and FACS-based killing assays. The NK92-NKp44-1 cell line and primary human NK cells showed increased IFNγ release upon coincubation with mAb 14-25-9 and various solid tumor cell lines and leukemias. Treatment with 14-25-9 also increased NK cytotoxic activity. In vivo efficacy was evaluated on patient-derived xenografts (PDX)-bearing NSG mice. In PDX-bearing mice, intravenous administration of mAb 14-25-9 increased degranulation (CD107a expression) of intratumorally injected patient autologous or allogeneic NK cells, as well as inhibited tumor growth when treated long term. Our study describes a mAb against the NKp44-PCNA innate immune checkpoint that can enhance NK-cell antitumor activity both in vitro and in vivo.

Genomic and transcriptomic profiling expands precision cancer medicine: the WINTHER trial.

Precision medicine focuses on DNA abnormalities, but not all tumors have tractable genomic alterations. The WINTHER trial ( NCT01856296 ) navigated patients to therapy on the basis of fresh biopsy-derived DNA sequencing (arm A; 236 gene panel) or RNA expression (arm B; comparing tumor to normal). The clinical management committee (investigators from five countries) recommended therapies, prioritizing genomic matches; physicians determined the therapy given. Matching scores were calculated post-hoc for each patient, according to drugs received: for DNA, the number of alterations matched divided by the total alteration number; for RNA, expression-matched drug ranks. Overall, 303 patients consented; 107 (35%; 69 in arm A and 38 in arm B) were evaluable for therapy. The median number of previous therapies was three. The most common diagnoses were colon, head and neck, and lung cancers. Among the 107 patients, the rate of stable disease ≥6 months and partial or complete response was 26.2% (arm A: 23.2%; arm B: 31.6% (P = 0.37)). The patient proportion with WINTHER versus previous therapy progression-free survival ratio of >1.5 was 22.4%, which did not meet the pre-specified primary end point. Fewer previous therapies, better performance status and higher matching score correlated with longer progression-free survival (all P < 0.05, multivariate). Our study shows that genomic and transcriptomic profiling are both useful for improving therapy recommendations and patient outcome, and expands personalized cancer treatment.

Tumor Tissue Explant Culture of Patient-Derived Xenograft as Potential Prioritization Tool for Targeted Therapy.

Despite of remarkable progress made in the head and neck cancer (HNC) therapy, the survival rate of this metastatic disease remain low. Tailoring the appropriate therapy to patients is a major challenge and highlights the unmet need to have a good preclinical model that will predict clinical response. Hence, we developed an accurate and time efficient drug screening method of tumor ex vivo analysis (TEVA) system, which can predict patient-specific drug responses. In this study, we generated six patient derived xenografts (PDXs) which were utilized for TEVA. Briefly, PDXs were cut into 2 × 2 × 2 mm3 explants and treated with clinically relevant drugs for 24 h. Tumor cell proliferation and death were evaluated by immunohistochemistry and TEVA score was calculated. Ex vivo and in vivo drug efficacy studies were performed on four PDXs and three drugs side-by-side to explore correlation between TEVA and PDX treatment in vivo. Efficacy of drug combinations was also ventured. Optimization of the culture timings dictated 24 h to be the time frame to detect drug responses and drug penetrates 2 × 2 × 2 mm3 explants as signaling pathways were significantly altered. Tumor responses to drugs in TEVA, significantly corresponds with the drug efficacy in mice. Overall, this low cost, robust, relatively simple and efficient 3D tissue-based method, employing material from one PDX, can bypass the necessity of drug validation in immune-incompetent PDX-bearing mice. Our data provides a potential rationale for utilizing TEVA to predict tumor response to targeted and chemo therapies when multiple targets are proposed.

Genetic alterations in sporadic triple negative breast cancer.

BACKGROUND: Recent studies have aimed to identify gene mutation profiles to explain the cause of TNBC therapy limitations. METHODS: The purpose of our study was to use Next Generation Sequencing (NGS) of 46 genes with a well-defined role in cancer in a cohort of TNBC patients in order to identify novel markers that could lead to the development of strategic, adjuvant, gene-targeted therapies. RESULTS: A total of 118 gene mutations in 35 genes, 75 mutations in BRCA1 and 92 mutations in BRCA2 were identified. The clinical assessment of the identified mutations showed 27 to be possibly damaging and 59 to be damaging. TP53, KDR, PIK3CA (rs3729687), ATM, AKT1 and KIT were among the most frequently mutated genes in our TNBC cohort. The SNP AKT1 (rs3730358) was suggested to modify the risk of breast cancer. SNP PIK3CA (rs3729687) is a damaging mutation that we found to be correlated with the prognosis of TNBC. The survival curve analysis showed that the presence of AKT1, TP53, KDR, KIT, BRCA1 and BRCA2 mutations is correlated with a poor prognosis. CONCLUSION: We show a strong association between TNBC and mutations in BRCA1/2 genes and the poor outcome of these patients. Moreover, we identified several other unknown mutations putatively associated with the poor prognosis of TNBC tumors. We also discovered novel mutations never before associated with breast cancer that could putatively account for the poor prognosis of the TNBC tumors.

High-Throughput Genomics and Clinical Outcome in Hard-to-Treat Advanced Cancers: Results of the MOSCATO 01 Trial.

High-throughput genomic analyses may improve outcomes in patients with advanced cancers. MOSCATO 01 is a prospective clinical trial evaluating the clinical benefit of this approach. Nucleic acids were extracted from fresh-frozen tumor biopsies and analyzed by array comparative genomic hybridization, next-generation sequencing, and RNA sequencing. The primary objective was to evaluate clinical benefit as measured by the percentage of patients presenting progression-free survival (PFS) on matched therapy (PFS2) 1.3-fold longer than the PFS on prior therapy (PFS1). A total of 1,035 adult patients were included, and a biopsy was performed in 948. An actionable molecular alteration was identified in 411 of 843 patients with a molecular portrait. A total of 199 patients were treated with a targeted therapy matched to a genomic alteration. The PFS2/PFS1 ratio was >1.3 in 33% of the patients (63/193). Objective responses were observed in 22 of 194 patients (11%; 95% CI, 7%-17%), and median overall survival was 11.9 months (95% CI, 9.5-14.3 months).Significance: This study suggests that high-throughput genomics could improve outcomes in a subset of patients with hard-to-treat cancers. Although these results are encouraging, only 7% of the successfully screened patients benefited from this approach. Randomized trials are needed to validate this hypothesis and to quantify the magnitude of benefit. Expanding drug access could increase the percentage of patients who benefit. Cancer Discov; 7(6); 586-95. ©2017 AACR.See related commentary by Schram and Hyman, p. 552This article is highlighted in the In This Issue feature, p. 539.

MMS19 as a potential predictive marker of adjuvant chemotherapy benefit in resected non-small cell lung cancer.

BACKGROUND: Resectable non-small cell lung cancer (NSCLC) treatment options most often consist of surgical resection along with adjuvant chemotherapy (ACT). The benefit of ACT however is modest and is accompanied by important side effects. OBJECTIVE: One central quest in the field is therefore the identification of a predictive marker of the response to ACT. METHODS: We applied an unbiased approach based on high content analysis of expression data generated from a discovery patient cohort. RESULTS: We identified MMS19, a component of the cytoplasmic Iron-Sulfur Assembly (CIA) machinery important for the Nucleotide Excision Repair (NER) pathway as a pivotal gene for cisplatin toxicity. We then confirmed the association between MMS19 expression and the response to Cisplatin treatment in a panel of NSCLC cell lines. Finally we validated these pre-clinical data in a subgroup of JBR.10 trial patients through a hypothesis-driven analysis, and showed that MMS19 levels associated with ACT benefit. CONCLUSIONS: We therefore propose the expression level of MMS19 as a candidate predictive marker of ACT benefit in resected NSCLC patients.

Novel insight into triple-negative breast cancers, the emerging role of angiogenesis, and antiangiogenic therapy.

Triple-negative breast cancer (TNBC) is a heterogeneous group of tumours characterised by lack of expression of oestrogen-, progesterone- and human epidermal growth factor receptors. TNBC, which represents approximately 15% of all mammary tumours, has a poor prognosis because of an aggressive behaviour and the lack of specific treatment. Accordingly, TNBC has become a major focus of research into breast cancer and is now classified into several molecular subtypes, each with a different prognosis. Pathological angiogenesis occurs at a late stage in the proliferation of TNBC and is associated with invasion and metastasis; there is an association with metabolic syndrome. Semaphorins are a versatile family of proteins with multiple roles in angiogenesis, tumour growth and metastasis and may represent a clinically useful focus for therapeutic targeting in this type of breast cancer. Another important field of investigation into the control of pathological angiogenesis is related to the expression of noncoding RNA (ncRNA) - these molecules can be considered as a therapeutic target or as a biomarker. Several molecular agents for intervening in the activity of different signalling pathways are being explored in TNBC, but none has so far proved effective in clinical trials and the disease continues to pose a defining challenge for clinical management as well as innovative cancer research.

DUX4-induced constitutive DNA damage and oxidative stress contribute to aberrant differentiation of myoblasts from FSHD patients.

Facioscapulohumeral dystrophy (FSHD) is one of the three most common muscular dystrophies in the Western world, however, its etiology remains only partially understood. Here, we provide evidence of constitutive DNA damage in in vitro cultured myoblasts isolated from FSHD patients and demonstrate oxidative DNA damage implication in the differentiation of these cells into phenotypically-aberrant myotubes. Double homeobox 4 (DUX4), the major actor in FSHD pathology induced DNA damage accumulation when overexpressed in normal human myoblasts, and RNAi-mediated DUX4 inhibition reduced the level of DNA damage in FSHD myoblasts. Addition of tempol, a powerful antioxidant, to the culture medium of proliferating DUX4-transfected myoblasts and FSHD myoblasts reduced the level of DNA damage, suggesting that DNA alterations are mainly due to oxidative stress. Antioxidant treatment during the myogenic differentiation of FSHD myoblasts significantly reduced morphological defects in myotube formation. We propose that the induction of DNA damage is a novel function of the DUX4 protein affecting myogenic differentiation of FSHD myoblasts.

Association of Biomarker-Based Treatment Strategies With Response Rates and Progression-Free Survival in Refractory Malignant Neoplasms: A Meta-analysis.

IMPORTANCE: The impact of a biomarker-based (personalized) cancer treatment strategy in the setting of phase 1 clinical trials was analyzed. OBJECTIVE: To compare patient outcomes in phase 1 studies that used a biomarker selection strategy with those that did not. DATA SOURCES: PubMed search of phase 1 cancer drug trials (January 1, 2011, through December 31, 2013). STUDY SELECTION: Studies included trials that evaluated single agents, and reported efficacy end points (at least response rate [RR]). DATA EXTRACTION AND SYNTHESIS: Data were extracted independently by 2 investigators. MAIN OUTCOMES AND MEASURES: Response rate and progression-free survival (PFS) were compared for arms that used a personalized strategy (biomarker selection) vs those that did not. Overall survival was not analyzed owing to insufficient data. RESULTS: A total of 346 studies published in the designated 3-year time period were included in the analysis. Multivariable analysis (meta-regression and weighted multiple regression models) demonstrated that the personalized approach independently correlated with a significantly higher median RR (30.6% [95% CI, 25.0%-36.9%] vs 4.9% [95% CI, 4.2%-5.7%]; P < .001) and a longer median PFS (5.7 [95% CI, 2.6-13.8] vs 2.95 [95% CI, 2.3-3.7] months; P < .001). Targeted therapy arms that used a biomarker-based selection strategy (n = 57 trials) were associated with statistically improved RR compared with targeted therapy arms (n = 177 arms) that did not (31.1% [95% CI, 25.4%-37.4%] vs 5.1% [95% CI, 4.3%-6.0%]; P < .001). Nonpersonalized targeted arms had outcomes comparable with those that tested a cytotoxic agent (median RR, 5.1% [95% CI, 4.3%-6.0%] vs 4.7% [95% CI, 3.6%-6.2%]; P = .63; respectively; median PFS, 3.3 [95% CI, 2.6-4.0] months vs 2.5 [95% CI, 2.0-3.7] months; P = .22). Personalized arms using a "genomic (DNA) biomarker" had higher median RR than those using a "protein biomarker" (42.0% [95% CI, 33.7%-50.9%] vs 22.4% [95% CI, 15.6%-30.9%]; P = .001). The median treatment-related mortality was not statistically different for arms that used a personalized strategy vs not (1.89% [95% CI, 1.36%-2.61%] vs 2.27% [95% CI, 1.97%-2.62%]; P = .31). CONCLUSIONS AND RELEVANCE: In this meta-analysis, most phase 1 trials of targeted agents did not use a biomarker-based selection strategy. However, use of a biomarker-based approach was associated with significantly improved outcomes (RR and PFS). Response rates were significantly higher with genomic vs protein biomarkers. Studies that used targeted agents without a biomarker had negligible response rates.

Impact of a Biomarker-Based Strategy on Oncology Drug Development: A Meta-analysis of Clinical Trials Leading to FDA Approval.

BACKGROUND: In order to ascertain the impact of a biomarker-based (personalized) strategy, we compared outcomes between US Food and Drug Administration (FDA)-approved cancer treatments that were studied with and without such a selection rationale. METHODS: Anticancer agents newly approved (September 1998 to June 2013) were identified at the Drugs@FDA website. Efficacy, treatment-related mortality, and hazard ratios (HRs) for time-to-event endpoints were analyzed and compared in registration trials for these agents. All statistical tests were two-sided. RESULTS: Fifty-eight drugs were included (leading to 57 randomized [32% personalized] and 55 nonrandomized trials [47% personalized], n = 38 104 patients). Trials adopting a personalized strategy more often included targeted (100% vs 65%, P < .001), oral (68% vs 35%, P = .001), and single agents (89% vs 71%, P = .04) and more frequently permitted crossover to experimental treatment (67% vs 28%, P = .009). In randomized registration trials (using a random-effects meta-analysis), personalized therapy arms were associated with higher relative response rate ratios (RRRs, compared with their corresponding control arms) (RRRs = 3.82, 95% confidence interval [CI] = 2.51 to 5.82, vs RRRs = 2.08, 95% CI = 1.76 to 2.47, adjusted P = .03), longer PFS (hazard ratio [HR] = 0.41, 95% CI = 0.33 to 0.51, vs HR = 0.59, 95% CI = 0.53 to 0.65, adjusted P < .001) and a non-statistically significantly longer OS (HR = 0.71, 95% CI = 0.61 to 0.83, vs HR = 0.81, 95% CI = 0.77 to 0.85, adjusted P = .07) compared with nonpersonalized trials. Analysis of experimental arms in all 112 registration trials (randomized and nonrandomized) demonstrated that personalized therapy was associated with higher response rate (48%, 95% CI = 42% to 55%, vs 23%, 95% CI = 20% to 27%, P < .001) and longer PFS (median = 8.3, interquartile range [IQR] = 5 vs 5.5 months, IQR = 5, adjusted P = .002) and OS (median = 19.3, IQR = 17 vs 13.5 months, IQR = 8, Adjusted P = .04). A personalized strategy was an independent predictor of better RR, PFS, and OS, as demonstrated by multilinear regression analysis. Treatment-related mortality rate was similar for personalized and nonpersonalized trials. CONCLUSIONS: A biomarker-based approach was safe and associated with improved efficacy outcomes in FDA-approved anticancer agents.