How Do Elderly Poor Prognosis Patients Tolerate Palliative Concurrent Chemoradiotherapy for Locally Advanced Non–Small-Cell Lung Cancer Stage III? A Subset Analysis From a Clinical Phase III Trial

AbstractBackgroundIn a phase III trial of patients with unresectable, locally advanced, stage III non–small-cell lung cancer (NSCLC) with a poor prognosis, palliative concurrent chemoradiotherapy (CRT) provided a significantly better outcome than chemotherapy alone, except among performance status (PS) 2 patients. In the present subgroup analysis, we evaluated the effect on patients aged ≥ 70 years (42% of all included) compared with patients aged < 70 years enrolled in the trial.Patients and MethodsAll patients received 4 courses of intravenous carboplatin and oral vinorelbine. The experimental arm also received radiotherapy (42 Gy in 15 fractions). The included patients were required to have large tumors (> 8 cm), weight loss (> 10% within the previous 6 months) and/or PS 2.ResultsThe overall survival was increased among the CRT patients in both age groups, but the difference was significant only in patients aged < 70 years (median survival, 14.8 vs. 9.7 months; P = .001; age ≥ 70 years, median survival, 10.2 vs. 9.1 months; P = .09). Patients aged ≥ 70 years experienced better preserved health-related quality of life (QOL) and significantly less hematologic toxicity. The 2- and 3-year survival was significantly increased in both age groups receiving CRT.ConclusionElderly patients aged ≥ 70 years with unresectable, stage III, locally advanced, NSLCL and a poor prognosis can tolerate CRT with the doses adjusted to age and palliative intent. These results indicate that CRT can provide both survival and QOL benefits in elderly patients, except for those with PS 2 or worse. The male predominance in the ≥ 70-year-age group and the reduced chemotherapy intensity for the patients aged > 75 years might explain the lack of significant survival improvement among those patients aged ≥ 70 years

miRNA detection methods and clinical implications in lung cancer

[EN] Lung cancer is the leading cause of cancer death worldwide. Therefore, advances in the diagnosis and treatment of the disease are urgently needed. miRNAs are a family of small, noncoding RNAs that regulate gene expression at the transcriptional level. miRNAs have been reported to be deregulated and to play a critical role in different types of cancer, including lung cancer. Thus, miRNA profiling in lung cancer patients has become the core of several investigations. To this end, the development of a multitude of platforms for miRNA profiling analysis has been essential. This article focuses on the different technologies available for assessing miRNAs and the most important results obtained to date in lung cancer.This study was partially supported by a grant from the Ministerio de Ciencia e Inovacion de Espana (TRA09-0132), Beca Roche en Onco-Hematologia 2009 and Red Tematica de Investigacion Cooperativa en Cancer (RD12/0036/0025). The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.Usó, M.; Jantus Lewintre, E.; Sirera Pérez, R.; Bremnes, RM.; Camps, C. (2014). miRNA detection methods and clinical implications in lung cancer. Future Oncology. 10(14):2279-2292. https://doi.org/10.2217/FON.14.93S227922921014Jemal, A., Bray, F., Center, M. M., Ferlay, J., Ward, E., & Forman, D. (2011). Global cancer statistics. CA: A Cancer Journal for Clinicians, 61(2), 69-90. doi:10.3322/caac.20107Herbst, R. S., Heymach, J. V., & Lippman, S. M. (2008). Lung Cancer. New England Journal of Medicine, 359(13), 1367-1380. doi:10.1056/nejmra0802714Ferlay, J., Parkin, D. M., & Steliarova-Foucher, E. (2010). Estimates of cancer incidence and mortality in Europe in 2008. European Journal of Cancer, 46(4), 765-781. doi:10.1016/j.ejca.2009.12.014Goldstraw, P., Crowley, J., Chansky, K., Giroux, D. J., Groome, P. A., Rami-Porta, R., … Sobin, L. (2007). The IASLC Lung Cancer Staging Project: Proposals for the Revision of the TNM Stage Groupings in the Forthcoming (Seventh) Edition of the TNM Classification of Malignant Tumours. Journal of Thoracic Oncology, 2(8), 706-714. doi:10.1097/jto.0b013e31812f3c1aLee, R. C., Feinbaum, R. L., & Ambros, V. (1993). The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14. Cell, 75(5), 843-854. doi:10.1016/0092-8674(93)90529-yWinter, J., Jung, S., Keller, S., Gregory, R. I., & Diederichs, S. (2009). Many roads to maturity: microRNA biogenesis pathways and their regulation. Nature Cell Biology, 11(3), 228-234. doi:10.1038/ncb0309-228Lai, E. C. (2002). Micro RNAs are complementary to 3′ UTR sequence motifs that mediate negative post-transcriptional regulation. Nature Genetics, 30(4), 363-364. doi:10.1038/ng865Stark, A., Brennecke, J., Bushati, N., Russell, R. B., & Cohen, S. M. (2005). Animal MicroRNAs Confer Robustness to Gene Expression and Have a Significant Impact on 3′UTR Evolution. Cell, 123(6), 1133-1146. doi:10.1016/j.cell.2005.11.023Zhang, B., Pan, X., Cobb, G. P., & Anderson, T. A. (2007). microRNAs as oncogenes and tumor suppressors. Developmental Biology, 302(1), 1-12. doi:10.1016/j.ydbio.2006.08.028Calin, G. A., Dumitru, C. D., Shimizu, M., Bichi, R., Zupo, S., Noch, E., … Croce, C. M. (2002). Nonlinear partial differential equations and applications: Frequent deletions and down-regulation of micro- RNA genes miR15 and miR16 at 13q14 in chronic lymphocytic leukemia. Proceedings of the National Academy of Sciences, 99(24), 15524-15529. doi:10.1073/pnas.242606799Landi, M. T., Zhao, Y., Rotunno, M., Koshiol, J., Liu, H., Bergen, A. W., … Wang, E. (2010). MicroRNA Expression Differentiates Histology and Predicts Survival of Lung Cancer. Clinical Cancer Research, 16(2), 430-441. doi:10.1158/1078-0432.ccr-09-1736Takamizawa, J., Konishi, H., Yanagisawa, K., Tomida, S., Osada, H., Endoh, H., … Takahashi, T. (2004). Reduced Expression of thelet-7MicroRNAs in Human Lung Cancers in Association with Shortened Postoperative Survival. Cancer Research, 64(11), 3753-3756. doi:10.1158/0008-5472.can-04-0637Garofalo, M., Di Leva, G., Romano, G., Nuovo, G., Suh, S.-S., Ngankeu, A., … Croce, C. M. (2009). miR-221&222 Regulate TRAIL Resistance and Enhance Tumorigenicity through PTEN and TIMP3 Downregulation. Cancer Cell, 16(6), 498-509. doi:10.1016/j.ccr.2009.10.014Gallardo, E., Navarro, A., Viñolas, N., Marrades, R. M., Diaz, T., Gel, B., … Monzo, M. (2009). miR-34a as a prognostic marker of relapse in surgically resected non-small-cell lung cancer. Carcinogenesis, 30(11), 1903-1909. doi:10.1093/carcin/bgp219Lu, J., Getz, G., Miska, E. A., Alvarez-Saavedra, E., Lamb, J., Peck, D., … Golub, T. R. (2005). MicroRNA expression profiles classify human cancers. Nature, 435(7043), 834-838. doi:10.1038/nature03702Xi, Y., Nakajima, G., Gavin, E., Morris, C. G., Kudo, K., Hayashi, K., & Ju, J. (2007). Systematic analysis of microRNA expression of RNA extracted from fresh frozen and formalin-fixed paraffin-embedded samples. RNA, 13(10), 1668-1674. doi:10.1261/rna.642907Shen, J., & Jiang, F. (2012). Applications of microRNAs in the diagnosis and prognosis of lung cancer. Expert Opinion on Medical Diagnostics, 6(3), 197-207. doi:10.1517/17530059.2012.672970Doleshal, M., Magotra, A. A., Choudhury, B., Cannon, B. D., Labourier, E., & Szafranska, A. E. (2008). Evaluation and Validation of Total RNA Extraction Methods for MicroRNA Expression Analyses in Formalin-Fixed, Paraffin-Embedded Tissues. The Journal of Molecular Diagnostics, 10(3), 203-211. doi:10.2353/jmoldx.2008.070153Taylor, D. D., & Gercel-Taylor, C. (2008). MicroRNA signatures of tumor-derived exosomes as diagnostic biomarkers of ovarian cancer. Gynecologic Oncology, 110(1), 13-21. doi:10.1016/j.ygyno.2008.04.033Ibberson, D., Benes, V., Muckenthaler, M. U., & Castoldi, M. (2009). RNA degradation compromises the reliability of microRNA expression profiling. BMC Biotechnology, 9(1), 102. doi:10.1186/1472-6750-9-102Yin, J. Q., Zhao, R. C., & Morris, K. V. (2008). Profiling microRNA expression with microarrays. Trends in Biotechnology, 26(2), 70-76. doi:10.1016/j.tibtech.2007.11.007Beuvink, I., Kolb, F. A., Budach, W., Garnier, A., Lange, J., Natt, F., … Weiler, J. (2007). A novel microarray approach reveals new tissue-specific signatures of known and predicted mammalian microRNAs. Nucleic Acids Research, 35(7), e52. doi:10.1093/nar/gkl1118Raponi, M., Dossey, L., Jatkoe, T., Wu, X., Chen, G., Fan, H., & Beer, D. G. (2009). MicroRNA Classifiers for Predicting Prognosis of Squamous Cell Lung Cancer. Cancer Research, 69(14), 5776-5783. doi:10.1158/0008-5472.can-09-0587Benes, V., & Castoldi, M. (2010). Expression profiling of microRNA using real-time quantitative PCR, how to use it and what is available. Methods, 50(4), 244-249. doi:10.1016/j.ymeth.2010.01.026Dijkstra, J. R., Mekenkamp, L. J. M., Teerenstra, S., De Krijger, I., & Nagtegaal, I. D. (2012). MicroRNA expression in formalin-fixed paraffin embedded tissue using real time quantitative PCR: the strengths and pitfalls. Journal of Cellular and Molecular Medicine, 16(4), 683-690. doi:10.1111/j.1582-4934.2011.01467.xChen, C. (2005). Real-time quantification of microRNAs by stem-loop RT-PCR. Nucleic Acids Research, 33(20), e179-e179. doi:10.1093/nar/gni178Lao, K., Xu, N. L., Yeung, V., Chen, C., Livak, K. J., & Straus, N. A. (2006). Multiplexing RT-PCR for the detection of multiple miRNA species in small samples. Biochemical and Biophysical Research Communications, 343(1), 85-89. doi:10.1016/j.bbrc.2006.02.106Mestdagh, P., Feys, T., Bernard, N., Guenther, S., Chen, C., Speleman, F., & Vandesompele, J. (2008). High-throughput stem-loop RT-qPCR miRNA expression profiling using minute amounts of input RNA. Nucleic Acids Research, 36(21), e143-e143. doi:10.1093/nar/gkn725Nolan, T., Hands, R. E., & Bustin, S. A. (2006). Quantification of mRNA using real-time RT-PCR. Nature Protocols, 1(3), 1559-1582. doi:10.1038/nprot.2006.236Zipper, H. (2004). Investigations on DNA intercalation and surface binding by SYBR Green I, its structure determination and methodological implications. Nucleic Acids Research, 32(12), e103-e103. doi:10.1093/nar/gnh101Mohammadian, A., Mowla, S. J., Elahi, E., Tavallaei, M., Nourani, M. R., & Liang, Y. (2013). Normalization of miRNA qPCR high-throughput data: a comparison of methods. Biotechnology Letters, 35(6), 843-851. doi:10.1007/s10529-013-1150-5Xie, Y., Todd, N. W., Liu, Z., Zhan, M., Fang, H., Peng, H., … Jiang, F. (2010). Altered miRNA expression in sputum for diagnosis of non-small cell lung cancer. Lung Cancer, 67(2), 170-176. doi:10.1016/j.lungcan.2009.04.004Yu, S.-L., Chen, H.-Y., Chang, G.-C., Chen, C.-Y., Chen, H.-W., Singh, S., … Yang, P.-C. (2008). MicroRNA Signature Predicts Survival and Relapse in Lung Cancer. Cancer Cell, 13(1), 48-57. doi:10.1016/j.ccr.2007.12.008Mascaux, C., Laes, J. F., Anthoine, G., Haller, A., Ninane, V., Burny, A., & Sculier, J. P. (2008). Evolution of microRNA expression during human bronchial squamous carcinogenesis. European Respiratory Journal, 33(2), 352-359. doi:10.1183/09031936.00084108Silva, J., Garcia, V., Zaballos, A., Provencio, M., Lombardia, L., Almonacid, L., … Bonilla, F. (2010). Vesicle-related microRNAs in plasma of nonsmall cell lung cancer patients and correlation with survival. European Respiratory Journal, 37(3), 617-623. doi:10.1183/09031936.00029610Berghmans, T., Ameye, L., Willems, L., Paesmans, M., Mascaux, C., Lafitte, J. J., … Sculier, J. P. (2013). Identification of microRNA-based signatures for response and survival for non-small cell lung cancer treated with cisplatin-vinorelbine A ELCWP prospective study. Lung Cancer, 82(2), 340-345. doi:10.1016/j.lungcan.2013.07.020Hennessey, P. T., Sanford, T., Choudhary, A., Mydlarz, W. W., Brown, D., Adai, A. T., … Califano, J. A. (2012). Serum microRNA Biomarkers for Detection of Non-Small Cell Lung Cancer. PLoS ONE, 7(2), e32307. doi:10.1371/journal.pone.0032307Skrzypski, M., Czapiewski, P., Goryca, K., Jassem, E., Wyrwicz, L., Pawłowski, R., … Jassem, J. (2014). Prognostic value of microRNA expression in operable non-small cell lung cancer patients. British Journal of Cancer, 110(4), 991-1000. doi:10.1038/bjc.2013.786Cazzoli, R., Buttitta, F., Di Nicola, M., Malatesta, S., Marchetti, A., Rom, W. N., & Pass, H. I. (2013). microRNAs Derived from Circulating Exosomes as Noninvasive Biomarkers for Screening and Diagnosing Lung Cancer. Journal of Thoracic Oncology, 8(9), 1156-1162. doi:10.1097/jto.0b013e318299ac32Rosenfeld, N., Aharonov, R., Meiri, E., Rosenwald, S., Spector, Y., Zepeniuk, M., … Barshack, I. (2008). MicroRNAs accurately identify cancer tissue origin. Nature Biotechnology, 26(4), 462-469. doi:10.1038/nbt1392Boeri, M., Verri, C., Conte, D., Roz, L., Modena, P., Facchinetti, F., … Sozzi, G. (2011). MicroRNA signatures in tissues and plasma predict development and prognosis of computed tomography detected lung cancer. Proceedings of the National Academy of Sciences, 108(9), 3713-3718. doi:10.1073/pnas.1100048108Yu, L., Todd, N. W., Xing, L., Xie, Y., Zhang, H., Liu, Z., … Jiang, F. (2010). Early detection of lung adenocarcinoma in sputum by a panel of microRNA markers. International Journal of Cancer, 127(12), 2870-2878. doi:10.1002/ijc.25289Xing, L., Todd, N. W., Yu, L., Fang, H., & Jiang, F. (2010). Early detection of squamous cell lung cancer in sputum by a panel of microRNA markers. Modern Pathology, 23(8), 1157-1164. doi:10.1038/modpathol.2010.111Shen, J., Todd, N. W., Zhang, H., Yu, L., Lingxiao, X., Mei, Y., … Jiang, F. (2010). Plasma microRNAs as potential biomarkers for non-small-cell lung cancer. Laboratory Investigation, 91(4), 579-587. doi:10.1038/labinvest.2010.194Campayo, M., Navarro, A., Viñolas, N., Diaz, T., Tejero, R., Gimferrer, J. M., … Marrades, R. (2012). Low miR-145 and high miR-367 are associated with unfavourable prognosis in resected nonsmall cell lung cancer. European Respiratory Journal, 41(5), 1172-1178. doi:10.1183/09031936.00048712Zhu, W., Liu, X., He, J., Chen, D., Hunag, Y., & Zhang, Y. K. (2011). Overexpression of members of the microRNA-183 family is a risk factor for lung cancer: A case control study. BMC Cancer, 11(1). doi:10.1186/1471-2407-11-393Duncavage, E., Goodgame, B., Sezhiyan, A., Govindan, R., & Pfeifer, J. (2010). Use of MicroRNA Expression Levels to Predict Outcomes in Resected Stage I Non-small Cell Lung Cancer. Journal of Thoracic Oncology, 5(11), 1755-1763. doi:10.1097/jto.0b013e3181f3909dChen, Q., Si, Q., Xiao, S., Xie, Q., Lin, J., Wang, C., … Wang, L. (2012). Prognostic significance of serum miR-17-5p in lung cancer. Medical Oncology, 30(1). doi:10.1007/s12032-012-0353-2Zhang, H., Su, Y., Xu, F., Kong, J., Yu, H., & Qian, B. (2013). Circulating MicroRNAs in Relation to EGFR Status and Survival of Lung Adenocarcinoma in Female Non-Smokers. PLoS ONE, 8(11), e81408. doi:10.1371/journal.pone.0081408Garofalo, M., Romano, G., Di Leva, G., Nuovo, G., Jeon, Y.-J., Ngankeu, A., … Croce, C. M. (2011). EGFR and MET receptor tyrosine kinase–altered microRNA expression induces tumorigenesis and gefitinib resistance in lung cancers. Nature Medicine, 18(1), 74-82. doi:10.1038/nm.2577Romano, G., Acunzo, M., Garofalo, M., Di Leva, G., Cascione, L., Zanca, C., … Croce, C. M. (2012). MiR-494 is regulated by ERK1/2 and modulates TRAIL-induced apoptosis in non-small-cell lung cancer through BIM down-regulation. Proceedings of the National Academy of Sciences, 109(41), 16570-16575. doi:10.1073/pnas.1207917109Kreil, D. P., Russell, R. R., & Russell, S. (2006). [4] Microarray Oligonucleotide Probes. DNA Microarrays, Part A: Array Platforms and Wet-Bench Protocols, 73-98. doi:10.1016/s0076-6879(06)10004-xKRICHEVSKY, A. M. (2003). A microRNA array reveals extensive regulation of microRNAs during brain development. RNA, 9(10), 1274-1281. doi:10.1261/rna.5980303SHINGARA, J. (2005). An optimized isolation and labeling platform for accurate microRNA expression profiling. RNA, 11(9), 1461-1470. doi:10.1261/rna.2610405Castoldi, M. (2006). A sensitive array for microRNA expression profiling (miChip) based on locked nucleic acids (LNA). RNA, 12(5), 913-920. doi:10.1261/rna.2332406Wang, H., Ach, R. A., & Curry, B. (2006). Direct and sensitive miRNA profiling from low-input total RNA. RNA, 13(1), 151-159. doi:10.1261/rna.234507Davison, T. S., Johnson, C. D., & Andruss, B. F. (2006). [2] Analyzing Micro‐RNA Expression Using Microarrays. DNA Microarrays, Part B: Databases and Statistics, 14-34. doi:10.1016/s0076-6879(06)11002-2Volinia, S., Calin, G. A., Liu, C.-G., Ambs, S., Cimmino, A., Petrocca, F., … Croce, C. M. (2006). A microRNA expression signature of human solid tumors defines cancer gene targets. Proceedings of the National Academy of Sciences, 103(7), 2257-2261. doi:10.1073/pnas.0510565103Yanaihara, N., Caplen, N., Bowman, E., Seike, M., Kumamoto, K., Yi, M., … Harris, C. C. (2006). Unique microRNA molecular profiles in lung cancer diagnosis and prognosis. Cancer Cell, 9(3), 189-198. doi:10.1016/j.ccr.2006.01.025Patnaik, S. K., Kannisto, E., Knudsen, S., & Yendamuri, S. (2009). Evaluation of MicroRNA Expression Profiles That May Predict Recurrence of Localized Stage I Non-Small Cell Lung Cancer after Surgical Resection. Cancer Research, 70(1), 36-45. doi:10.1158/0008-5472.can-09-3153Patnaik, S. K., Yendamuri, S., Kannisto, E., Kucharczuk, J. C., Singhal, S., & Vachani, A. (2012). MicroRNA Expression Profiles of Whole Blood in Lung Adenocarcinoma. PLoS ONE, 7(9), e46045. doi:10.1371/journal.pone.0046045Roth, C., Stückrath, I., Pantel, K., Izbicki, J. R., Tachezy, M., & Schwarzenbach, H. (2012). Low Levels of Cell-Free Circulating miR-361-3p and miR-625* as Blood-Based Markers for Discriminating Malignant from Benign Lung Tumors. PLoS ONE, 7(6), e38248. doi:10.1371/journal.pone.0038248Metzker, M. L. (2009). Sequencing technologies — the next generation. Nature Reviews Genetics, 11(1), 31-46. doi:10.1038/nrg2626Margulies, M., Egholm, M., Altman, W. E., Attiya, S., Bader, J. S., Bemben, L. A., … Chen, Z. (2005). Genome sequencing in microfabricated high-density picolitre reactors. Nature, 437(7057), 376-380. doi:10.1038/nature03959Pritchard, C. C., Cheng, H. H., & Tewari, M. (2012). MicroRNA profiling: approaches and considerations. Nature Reviews Genetics, 13(5), 358-369. doi:10.1038/nrg3198Beane, J., Vick, J., Schembri, F., Anderlind, C., Gower, A., Campbell, J., … Spira, A. (2011). Characterizing the Impact of Smoking and Lung Cancer on the Airway Transcriptome Using RNA-Seq. Cancer Prevention Research, 4(6), 803-817. doi:10.1158/1940-6207.capr-11-0212Kalari, K. R., Rossell, D., Necela, B. M., Asmann, Y. W., Nair, A., Baheti, S., … Thompson, E. A. (2012). Deep Sequence Analysis of Non-Small Cell Lung Cancer: Integrated Analysis of Gene Expression, Alternative Splicing, and Single Nucleotide Variations in Lung Adenocarcinomas with and without Oncogenic KRAS Mutations. Frontiers in Oncology, 2. doi:10.3389/fonc.2012.00012Ju, Y. S., Lee, W.-C., Shin, J.-Y., Lee, S., Bleazard, T., Won, J.-K., … Seo, J.-S. (2011). A transforming KIF5B and RET gene fusion in lung adenocarcinoma revealed from whole-genome and transcriptome sequencing. Genome Research, 22(3), 436-445. doi:10.1101/gr.133645.111Chen, X., Ba, Y., Ma, L., Cai, X., Yin, Y., Wang, K., … Zhang, C.-Y. (2008). Characterization of microRNAs in serum: a novel class of biomarkers for diagnosis of cancer and other diseases. Cell Research, 18(10), 997-1006. doi:10.1038/cr.2008.282Hu, Z., Chen, X., Zhao, Y., Tian, T., Jin, G., Shu, Y., … Shen, H. (2010). Serum MicroRNA Signatures Identified in a Genome-Wide Serum MicroRNA Expression Profiling Predict Survival of Non–Small-Cell Lung Cancer. Journal of Clinical Oncology, 28(10), 1721-1726. doi:10.1200/jco.2009.24.9342Keller, A., Backes, C., Leidinger, P., Kefer, N., Boisguerin, V., Barbacioru, C., … Meese, E. (2011). Next-generation sequencing identifies novel microRNAs in peripheral blood of lung cancer patients. Molecular BioSystems, 7(12), 3187. doi:10.1039/c1mb05353aMeng, W., Ye, Z., Cui, R., Perry, J., Dedousi-Huebner, V., Huebner, A., … Lautenschlaeger, T. (2013). MicroRNA-31 Predicts the Presence of Lymph Node Metastases and Survival in Patients with Lung Adenocarcinoma. Clinical Cancer Research, 19(19), 5423-5433. doi:10.1158/1078-0432.ccr-13-0320Nuovo, G. J. (2010). In situ detection of microRNAs in paraffin embedded, formalin fixed tissues and the co-localization of their putative targets. Methods, 52(4), 307-315. doi:10.1016/j.ymeth.2010.08.009Jørgensen, S., Baker, A., Møller, S., & Nielsen, B. S. (2010). Robust one-day in situ hybridization protocol for detection of microRNAs in paraffin samples using LNA probes. Methods, 52(4), 375-381. doi:10.1016/j.ymeth.2010.07.002Wang, S., Aurora, A. B., Johnson, B. A., Qi, X., McAnally, J., Hill, J. A., … Olson, E. N. (2008). The Endothelial-Specific MicroRNA miR-126 Governs Vascular Integrity and Angiogenesis. Developmental Cell, 15(2), 261-271. doi:10.1016/j.devcel.2008.07.002Voortman, J., Goto, A., Mendiboure, J., Sohn, J. J., Schetter, A. J., Saito, M., … Giaccone, G. (2010). MicroRNA Expression and Clinical Outcomes in Patients Treated with Adjuvant Chemotherapy after Complete Resection of Non-Small Cell Lung Carcinoma. Cancer Research, 70(21), 8288-8298. doi:10.1158/0008-5472.can-10-1348Nuovo, G. J. (2008). In situ detection of precursor and mature microRNAs in paraffin embedded, formalin fixed tissues and cell preparations. Methods, 44(1), 39-46. doi:10.1016/j.ymeth.2007.10.008Donnem, T., Lonvik, K., Eklo, K., Berg, T., Sorbye, S. W., Al-Shibli, K., … Busund, L.-T. (2011). Independent and tissue-specific prognostic impact of miR-126 in nonsmall cell lung cancer. Cancer, 117(14), 3193-3200. doi:10.1002/cncr.25907Donnem, T., Eklo, K., Berg, T., Sorbye, S. W., Lonvik, K., Al-Saad, S., … Busund, L.-T. (2011). Prognostic Impact of MiR-155 in Non-Small Cell Lung Cancer Evaluated by in Situ Hybridization. Journal of Translational Medicine, 9(1). doi:10.1186/1479-5876-9-6Donnem, T., Fenton, C. G., Lonvik, K., Berg, T., Eklo, K., Andersen, S., … Busund, L.-T. (2012). MicroRNA Signatures in Tumor Tissue Related to Angiogenesis in Non-Small Cell Lung Cancer. PLoS ONE, 7(1), e29671. doi:10.1371/journal.pone.0029671Eilertsen, M., Andersen, S., Al-Saad, S., Richardsen, E., Stenvold, H., Hald, S. M., … Bremnes, R. M. (2014). Positive prognostic impact of miR-210 in non-small cell lung cancer. Lung Cancer, 83(2), 272-278. doi:10.1016/j.lungcan.2013.11.005He, L., & Hannon, G. J. (2004). MicroRNAs: small RNAs with a big role in gene regulation. Nature Reviews Genetics, 5(7), 522-531. doi:10.1038/nrg137

Concurrent palliative chemoradiation leads to survival and quality of life benefits in poor prognosis stage III non-small-cell lung cancer: a randomised trial by the Norwegian Lung Cancer Study Group

Background: The palliative role of chemoradiation in the treatment of patients with locally advanced, inoperable non-small-cell lung cancer stage III and negative prognostic factors remains unresolved. Methods: Patients not eligible for curative radiotherapy were randomised to receive either chemoradiation or chemotherapy alone. Four courses of intravenous carboplatin on day 1 and oral vinorelbin on days 1 and 8 were given with 3-week intervals. Patients in the chemoradiation arm also received radiotherapy with fractionation 42 Gy/15, starting at the second chemotherapy course. The primary end point was overall survival; secondary end points were health-related quality of life (HRQOL) and toxicity. Results: Enrolment was terminated due to slow accrual after 191 patients from 25 Norwegian hospitals were randomised. Median age was 67 years and 21% had PS 2. In the chemotherapy versus the chemoradiation arm, the median overall survival was 9.7 and 12.6 months, respectively (Po0.01). One-year survival was 34.0% and 53.2% (Po0.01). Following a minor decline during treatment, HRQOL remained unchanged in the chemoradiation arm. The patients in the chemotherapy arm reported gradual deterioration during the subsequent months. In the chemoradiation arm, there were more hospital admissions related to side effects (Po0.05). Conclusion: Chemoradiation was superior to chemotherapy alone with respect to survival and HRQoL at the expense of more hospital admissions due to toxicity

Profiling of VEGFs and VEGFRs as Prognostic Factors in Soft Tissue Sarcoma: VEGFR-3 Is an Independent Predictor of Poor Prognosis

BACKGROUND: In non-gastrointestinal stromal tumor soft tissue sarcoma (non-GIST STS) optimal treatment is surgery with wide resection margins. Vascular endothelial growth factors (VEGFs) and receptors (VEGFRs) are known to be key players in the initiation of angiogenesis and lymphangiogenesis. This study investigates the prognostic impact of VEGFs and VEGFRs in non-GIST STS with wide and non-wide resection margins. METHODS: Tumor samples from 249 patients with non-GIST STS were obtained and tissue microarrays were constructed for each specimen. Immunohistochemistry was used to evaluate the expressions of VEGF-A, -C and -D and VEGFR-1, -2 and -3. RESULTS: In the univariate analyses, VEGF-A (P=0.040) in the total material, and VEGF-A (P=0.018), VEGF-C (P=0.025) and VEGFR-3 (P=0.027) in the subgroup with wide resection margins, were significant negative prognostic indicators of disease-specific survival (DSS). In the multivariate analysis, high expression of VEGFR-3 (P=0.042, HR=1.907, 95% CI 1.024-3.549) was an independent significant negative prognostic marker for DSS among patients with wide resection margins. CONCLUSION: VEGFR-3 is a strong and independent negative prognostic marker for non-GIST STSs with wide resection margins

Fibroblast growth factor 2 orchestrates angiogenic networking in non-GIST STS patients

<p>Abstract</p> <p>Background</p> <p>Non-gastrointestinal stromal tumor soft-tissue sarcomas (non-GIST STSs) constitute a heterogeneous group of tumors with poor prognosis. Fibroblast growth factor 2 (FGF2) and fibroblast growth factor receptor-1 (FGFR-1), in close interplay with platelet-derived growth factor-B (PDGF-B) and vascular endothelial growth factor receptor-3 (VEGFR-3), are strongly involved in angiogenesis. This study investigates the prognostic impact of FGF2 and FGFR-1 and explores the impact of their co-expression with PDGF-B and VEGFR-3 in widely resected tumors from non-GIST STS patients.</p> <p>Methods</p> <p>Tumor samples from 108 non-GIST STS patients were obtained and tissue microarrays were constructed for each specimen. Immunohistochemistry was used to evaluate the expressions of FGF-2, FGFR-1, PDGF-B and VEGFR-3.</p> <p>Results</p> <p>In the multivariate analysis, high expression of FGF2 (P = 0.024, HR = 2.2, 95% CI 1.1-4.4) and the co-expressions of FGF2 & PDGF-B (overall; P = 0.007, intermediate; P = 0.013, HR = 3.6, 95% CI = 1.3-9.7, high; P = 0.002, HR = 6.0, 95% CI = 2.0-18.1) and FGF2 & VEGFR-3 (overall; P = 0.050, intermediate; P = 0.058, HR = 2.0, 95% CI = 0.98-4.1, high; P = 0.028, HR = 2.6, 95% CI = 1.1-6.0) were significant independent prognostic indicators of poor disease-specific survival.</p> <p>Conclusion</p> <p>FGF2, alone or in co-expression with PDGF-B and VEGFR-3, is a significant independent negative prognosticator in widely resected non-GIST STS patients.</p

Prognostic Impacts of Hypoxic Markers in Soft Tissue Sarcoma

Background. We aimed to explore the prognostic impact of the hypoxia-induced factors (HIFαs) 1 and 2, the metabolic HIF-regulated glucose transporter GLUT-1, and carbonic anhydrase IX (CAIX) in non-gastrointestinal stromal tumor soft tissue sarcomas (non-GIST STS). Methods. Duplicate cores with viable tumor tissue from 206 patients with non-GIST STS were obtained and tissue microarrays were constructed. Immunohistochemistry (IHC) was used to evaluate expression of hypoxic markers. Results. In univariate analyses, GLUT-1 (P < 0.001) and HIF-2α (P = 0.032) expression correlated significantly with a poor disease-specific survival (DSS). In the multivariate analysis, however, only high expression of GLUT-1 (HR 1.7, CI 95% 1.1–2.7, P = 0.021) was a significant independent prognostic indicator of poor DSS. Conclusion. GLUT-1 is a significant independent negative prognostic factor in non-GIST STS

Prognostic Impact of Lymphocytes in Soft Tissue Sarcomas

PURPOSE: The purpose of this study was to clarify the prognostic significance of lymphocyte infiltration in soft tissue sarcomas (STS). Prognostic markers in potentially curable STS should guide therapy after surgical resection. The immune status at the time of resection may be important, but the prognostic significance of tumor infiltrating lymphocytes is controversial as the immune system has conflicting roles during cancer development. EXPERIMENTAL DESIGN: Tissue microarrays from 249 patients with STS were constructed from duplicate cores of viable and representative neoplastic tumor areas. Immunohistochemistry was used to evaluate the CD3+, CD4+, CD8+, CD20+ and CD45+ lymphocytes in tumors. RESULTS: In univariate analyses, increased numbers of CD4+ (P = 0.008) and CD20+ (P = 0.006) lymphocytes in tumor correlated significantly with an improved disease-specific survival (DSS) in patients with wide resection margins (n = 108). In patients with non-wide resection margins (n = 141) increased numbers of CD3+ (P = 0.028) lymphocytes in tumor correlated significantly with shorter DSS. In multivariate analyses, a high number of CD20+ lymphocytes (HR = 5.5, CI 95%  = 1.6-18.6, P = 0.006) in the tumor was an independent positive prognostic factor for DSS in patients with wide resections margins. CONCLUSIONS: High density of CD20+ lymphocytes in STS with wide resection margins is an independent positive prognostic indicator for these patients. Further research is needed to define if CD20+ cells can modify tumors in a way that reduces disease progression and metastatic potential

Disease-specific outcomes of Radical Prostatectomies in Northern Norway; A case for the impact of perineural infiltration and postoperative PSA-doubling time

Background Prostate cancer is the most common male malignancy and a mayor cause of mortality in the western world. The impact of clinicopathological variables on disease related outcomes have mainly been reported from a few large US series, most of them not reporting on perineural infiltration. We therefore wanted to investigate relevant cancer outcomes in patients undergoing radical prostatectomy in two Norwegian health regions with an emphasis on the impact of perineural infiltration (PNI) and prostate specific antigen- doubling time (PSA-DT). Methods We conducted a retrospective analysis of 535 prostatectomy patients at three hospitals between 1995 and 2005 estimating biochemical failure- (BFFS), clinical failure- (CFFS) and prostate cancer death-free survival (PCDFS) with the Kaplan-Meier method. We investigated clinicopathological factors influencing risk of events using cox proportional hazard regression. Results After a median follow-up of 89 months, 170 patients (32%) experienced biochemical failure (BF), 36 (7%) experienced clinical failure and 15 (3%) had died of prostate cancer. pT-Stage (p = 0.001), preoperative PSA (p = 0.047), Gleason Score (p = 0.032), non-apical positive surgical margins (PSM) (p = 0.003) and apical PSM (p = 0.031) were all independently associated to BFFS. Gleason score (p = 0.019), PNI (p = 0.012) and non-apical PSM (p = 0.002) were all independently associated to CFFS while only PNI (P = 0.047) and subgroups of Gleason score were independently associated to PCDFS. After BF, patients with a shorter PSA-DT had independent and significant worse event-free survivals than patients with PSA-DT > 15 months (PSA-DT = 3-9 months, CFFS HR = 6.44, p < 0.001, PCDFS HR = 13.7, p = 0.020; PSA-DT < 3 months, CFFS HR = 11.2, p < 0.001, PCDFS HR = 27.5, p = 0.006). Conclusions After prostatectomy, CFFS and PCDFS are variable, but both are strongly associated to Gleason score and PNI. In patients with BF, PSA-DT was most strongly associated to CF and PCD. Our study adds weight to the importance of PSA-DT and re-launches PNI as a strong prognosticator for clinically relevant endpoints

Prognostic Impact of MiR-155 in Non-Small Cell Lung Cancer Evaluated by in Situ Hybridization

<p>Abstract</p> <p>Background</p> <p>In recent years, microRNAs (miRNAs) have been found to play an essential role in tumor development. In lung tumorigenesis, targets and pathways of miRNAs are being revealed, and further translational research in this field is warranted. MiR-155 is one of the miRNAs most consistently involved in various neoplastic diseases. We aimed to investigate the prognostic impact of the multifunctional miR-155 in non-small cell lung cancer (NSCLC) patients.</p> <p>Methods</p> <p>Tumor tissue samples from 335 resected stage I to IIIA NSCLC patients were obtained and tissue microarrays (TMAs) were constructed with four cores from each tumor specimen. <it>In situ </it>hybridization (ISH) was used to evaluate the expression of miR-155.</p> <p>Results</p> <p>There were 191 squamous cell carcinomas (SCCs), 95 adenocarcinomas (ACs), 31 large cell carcinomas and 18 bronchioalveolar carcinomas. MiR-155 expression did not have a significant prognostic impact in the total cohort (P = 0.43). In ACs, high miR-155 expression tended to a significant negative prognostic effect on survival in univariate analysis (P = 0.086) and was an independent prognostic factor in multivariate analysis (HR 1.87, CI 95% 1.01 - 3.48, P = 0.047). In SCC patients with lymph node metastasis, however, miR-155 had a positive prognostic impact on survival in univariate (P = 0.034) as well as in multivariate (HR 0.45, CI 95% 0.21-0.96, P = 0.039) analysis.</p> <p>Conclusions</p> <p>The prognostic impact of miR-155 depends on histological subtype and nodal status in NSCLC.</p

Transcription factor PAX6 as a novel prognostic factor and putative tumour suppressor in non-small cell lung cancer

Source at https://doi.org/10.1038/s41598-018-23417-z. Licensed CC BY-NC-ND 4.0.Lung cancer is the leading cause of cancer deaths. Novel predictive biomarkers are needed to improve treatment selection and more accurate prognostication. PAX6 is a transcription factor with a proposed tumour suppressor function. Immunohistochemical staining was performed on tissue microarrays from 335 non-small cell lung cancer (NSCLC) patients for PAX6. Multivariate analyses of clinico-pathological variables and disease-specific survival (DSS) was carried out, and phenotypic changes of two NSCLC cell lines with knockdown of PAX6 were characterized. While PAX6 expression was only associated with a trend of better disease-specific survival (DSS) (p = 0.10), the pN+ subgroup (N = 103) showed significant correlation between high PAX6 expression and longer DSS (p = 0.022). Median survival for pN + patients with high PAX6 expression was 127.4 months, versus 22.9 months for patients with low PAX6 expression. In NCI-H661 cells, knockdown of PAX6 strongly activated serum-stimulated migration. In NCI-H460 cells, PAX6 knockdown activated anchorage-independent growth. We did not observe any significant effect of PAX6 on proliferation in either of cell lines. Our findings strongly support the proposition of PAX6 as a valid and positive prognostic marker in NSCLC in node-positive patients. There is a need for further studies, which should provide mechanistical explanation for the role of PAX6 in NSCLC