4.1. Enrichment of IL17C in tumors with low TNM staging IL17C exhibited distinct clinical and pathological patterns among different patients.
In the TCGA database, the average expression levels of IL17C showed significant differences among HNSCC patients with different tumor T staging and TNM staging (Figure1). The average expression levels followed the pattern T1>T2>T3>T4(Figure 1D) and I stage>II stage>III stage>IV stage (Figure 1C) (TNM staging, with statistically significant differences (P<0.05). Additionally, the average expression level of IL17C was lower in HNSCC patients with lymph node metastasis compared to those without metastasis, although this difference was not statistically significant (Figure 1E).
4.2. Tumor cell IL17C regulates immune responses through the classical complement activation pathway
To explore the biological functions associated with IL17C, Pearson correlation analysis was performed to identify the genes most correlated with IL17C (top 200 genes based on descending order of r-values, P<0.05). The results revealed that the most correlated functions with IL17C included adaptive immune response, immune response, bacterial defense response, and cell phagocytosis (Figure 2A). Furthermore, the most correlated cellular component was the extracellular side of the plasma membrane, with the molecular function being immunoglobulin binding (Figure 2B). The most correlated signaling pathway with IL17C was the classical complement activation pathway, involving the binding of receptor complexes on T cells and the assembly of immune globulin complexes (Figure2 C,Figure2D). These findings suggest that IL17C on head and neck squamous cells may play a critical role in regulating immune responses and disease through the classical complement activation pathway in the tumor microenvironment.
4.3. Tumor cell IL17C is positively correlated with T cell-mediated tumor immune response
During immunogenic cancer cell death, activation of lymphocytes such as NK cells, T cells, and B cells, as well as the release of chemokines, can induce apoptosis or necrotic apoptosis of cancer cells(16) . Therefore, the study examined the impact of IL17C activation on immune pathways and cytokine profiles. Gene Set Variation Analysis (GSVA) from the TCGA database was used to determine the enrichment scores of immune processes. The correlation analysis between enrichment scores and IL17C expression revealed a positive correlation between IL17C expression and most immune functions (Figure3).
4.4. Activation of the inhibitory immune checkpoint CTLA-4 is negatively correlated with high IL17C expression
Based on the GSVA analysis that identified the immunological role of IL17C in the tumor microenvironment, the study explored the relationship between IL17C and known inhibitory immune checkpoints in the TCGA database, including PD-2, CD200R1, HVEM, CD47, and CTLA-4. IL17C expression was positively correlated with PD-2, CD200R1, HVEM, and CD47. Notably, a negative correlation was observed between high IL17C expression and CTLA-4(Figure4.1), suggesting that IL17C may inhibit CTLA-4 expression, thereby delaying T cell exhaustion and enhancing immune surveillance against tumor cells. In addition, the relationship between IL17C and 28 immune cells was also examined, and the results showed that the expression level of IL17C was significantly positively correlated with the majority of immune cells (Figure4.2).
4.5. IL17C is an independent prognostic factor for overall survival in HNSCC patients
To investigate the prognostic value of IL17C in HNSCC patients, Kaplan-Meier and Cox proportional hazards models were established based on the TCGA database. The analysis revealed that patients with lower IL17C expression (median survival: 1394 days) had lower overall survival (OS) compared to patients with higher IL17C expression (median survival: 1718 days)(Figure5). Furthermore, in both univariate and multivariate Cox regression analyses, IL17C was identified as an independent prognostic factor, independent of age, T staging, N staging, and TNM staging (Table1).
4.5.1 Univariate Cox regression analysis and multivariate Cox regression analysis.
Table1 As shown in the table, in both univariate and multivariate Cox regression analyses, IL17C was identified as an independent prognostic factor for overall survival (OS) in patients.
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uXD3inNt8djGAX6THuL3WsBJXcQOODwB7BQda1El/4wheqoaXzNQcZmx5RJpjGe68ccyqmgfzQ9SOea7EMLY5oQNfLldW+IhCN3fWUXwN4/vnnlzUK609PrfW5Osl6lENR9jZ1k/Zrva4bs7he8FchAnWrqH+RzvWgKbhesF8//OEPl9XdOD5dX4tiueSX+kcn2R9J0nxYt2AA6q8KxEWVi9G0lSoujPk9x32BC3YOaEzyjW98o8wDtv/GG28sw+HEE0+shsarpxWPEbK8OtaV359fayeffHI1tPTodH0b6l+w58vPs0SAKO5sUcnOgZx6muXHRqkkxdMW7MMsKuj5cX7ulORGateg1ltvvVUNfYwKG+cPOJ/aKmlN+SP78MMPq6GlClwOHEwT8OoiznvwZe54IijOjWlx7KKiSeU8zknSuR44y+nAfATL8tNHXfZ1LZahxRINaPJuNJDJc1FutKn/xZp8fjK82rKmqUyYhGB23K2lYTfufFnrc3WStSiHmgLTn/vc56qh5j+rGCaVk+t13ViL60Vdvgb+zd/8zejY1gMB9TQgT3CXPzfmJ21DfRnkOb6xk80qD0mSprOuwYB8McoXTi5GUcnIPvnJT1ZDS/jTQFTEaPzy7tl63HU+5phjqqElXNTifUE+RJQrS5MwLfOwr0cdddSy1w9o0NX/KkAbKiC58UE6kB5sU3S8a8m6+HLxrPzBH/xBNbT3NrD+fGeD7W06xmst3/WKJ0u4qzGu0k4gg28M0PE38WcRDMhYPu9N0higT5CoTf4QE+lJ3mMezoHwR3/0R9XQ0qsSTMOy2Z+Ytulv/bchgETHMjjfcj5dawTEWA/rW82dv7jrxTkW52TT8jjvSA9e/4k0ygG9LgG5tViGFgvlWYj81eUVAcqdCNaBfMo5yTm60j+v1qVMmCTu9FJux/7kv8jSZK3O1a6mKYdy+c60pEekM7i2xnHgusA1KpbNecx0HONpPrK6XteNaa4X43D9zcHyQFpkpAHfQiAdI43o53m41o/DX2UgPUlX0odl5L/UwLGoB54kSfvGugYDuBjlx81C29eLaXjnaDSVFio/8VQB76Pl32eBR5BzZY4LYrwvyPiu3y0gut+074FHjqdpLPMnevL7naQH2xTdrComGXdtOAYhb0NeP9vJ9q4H8kw+Xmh6BSVXxKkQ85cp6Nj2nK5rhbSKu3Hg0XLexaXP46X5t4wAWt4f8h7z5Ioxd6ZjmzkGTMOy2Z/6tG1yIIpl8K5qvCu81umRl8e2sR7Wx/clxp0j49Sf/EBbcI11EpyKNIqgIuncNSC3FsvQ4mi6djXluSZ/8id/Ug0tXT84JzlHOc9Wkt+7lAmT1F8HQNP+zOJcHWel5VBu0DIf6UEXfx2A48crCJFulPOxbM5j0rDLNXO9rhsrvV5MUq9rsZz89EUgDUnzSCP6jAPfEejSkI+6EukT2x5yAFuStG+tazAA9YYZF2cacG14tIyLbK78cDHiHTSeKJj1B5y440AlIld82Bb+z3gupF0qRUzDo3ZcEPOFnPEEFOqP6nVBAIF5WUa9ckAaUcmZ9m8CT4vt5tFsjlHehkgjggWz3oa6XCljO5oquWw3FZX6seD9yG3bti3Lb2uFvynNOgLrJj+Mex82KrEcz8C21SuepDFpnZcP1sG03OUZh3xOXsrBNYY5z1h2Xv9qkb7kzUjj2J8XX3xx2dMm0yCdcpqw7U1Pg7DeegCR/zOe9XcJyK3FMrR48rWrLX814RHveuCa85Tz7YYbbqjGdNe1TBiHxlzeHpbVtD+zOFfHWWk5xHWYaXJ5znB+PYB9ptHO/uTpwHK5Hkx6lW09rxsruV5MQl2rvu11vNrCMW5Lo0nfVQAfLWbZOT0YZhzHiQC2JGk+bNozVA232rRp06DDZCPr+QV5SQIBD+5mgcbXSgJskrSR8fh+PAVBIL9rUEuS5tVK/kz7PJi2fT0r6/5kgCStNT5GFYEAdH2EW5L6gu8jRCBgmqdbJEkbl08GSFpI/GlOHpfmC+QEAuKdVh4DXq9vVEjSPOPjfS+88EL5yxM5YMrj+uNe0ZSkReGTAatjMEDSQqKSy4epMu528Z0R39uXpEH5CwT5433gmwDr/S0fSZoVgwGr42sCkhbSz/3cz1VDH39cy0CAJH3sE5/4RDW0FCzdFx/1lSTNL58MkCRJkiQtHJ8MWB2fDJAkSZIkqWcMBkiSJEmS1DMGAyRJkiRJ6hmDAZIkSZIk9YzBAEmSJEmSesZggCRJkiRJPWMwQJIkSZKknjEYIEmSJElSzxgMkCRJkiSpZwwGSJIkSZLUMwYDJEmSJEnqGYMBkiRJkiT1jMEASZIkSZJ6xmCAJEmSJEk9YzBAkiRJkqSeMRggSZIkSVLPGAyQJEmSJKlnDAZIkiRJktQzBgMkSZIkSeoZgwGSJEmSJPWMwQBJkiRJknrGYIAkSZIkST1jMECSJEmSpJ4xGCBJkiRJUs8YDJAkSZIkqWcMBkiSJEmS1DMGAyRJkiRJ6hmDAZIkSZIk9YzBAEmSJEmSesZggKR19aMf/Whw4IEHlu7cc8+txkqSFoXluCRtDAYD9rG4mNK1ydNwAc7yb7nj4nzTTTcN3n333WrKbl555ZXRMr797W9XY5c8/fTTZbnx+6/92q8NvvrVrzau46KLLhpN19Tdfvvt1ZRLWDbL47cjjjiibHuTv/u7vxtN8+abb1Zjp0Mast2xPrrYF7Yji9/pIu3ZX9bPuLbtXE+kZd7O6NhGjkN9nyR9LJ8/9XIp5GnqDZ/cKMod5x/T1svRLpgnlkOZHCh76mUX62g6x3NZ3tZlsez47Td+4zeWrTuL9a+m/KMsp3yKsjTWyTLzetvSPqf7RijjLMclSfuCwYAN6plnnhl861vfGmzZsqW1Qtfk937v90r/lFNOGXzxi18sw6CCtnXr1rLc8G//9m+Dv/7rv25cxwcffFANTUaljmWzPLz//vtl2+sVTSqrN998cxn+oz/6o8Hhhx9ehqfBMs8888yy3bE+xL6wHZPSiwraN7/5zTLMdkaQYN6Qjt/97nfLPlHJl7R+OP8oL7/85S+XRm5T0LQJQU7mwZ/+6Z8OPvWpT5VhxlPW1ssu1tF0jv/sZz+rhrq55JJLyrLDP//zPw/OPvvsvYKuBCpY/wEHHDC44oorqrHdkQ406i+++OJSPpFOgXVSprLeST7zmc8Mfv/3f78MX3rppZ3Td9FYjkuSZslgwAZCxZHK0a/+6q9WY5YqEtHAn4Q7E1HJzJUOGrtU0AKBAtb1i7/4i+X/k9bB9jBP7g499NDq18Hgscceq4YGg0ceeWTw+c9/vgzndeI73/nOqBL6hS98oRrbHYGAvEy2P7Yn9oVtjcr3OL/1W781mufKK68s/XnAvkQ+iO0Dlfx5DVpIGwXnHOcfZVg+/2jk3nLLLdX/xouyt17OMT4azvxGwCAaw+Ac5257E6aPsi53gQZ/BHrZdsphsL7vfe97ZRg0uL/xjW+UYQKyBEandd555y0LKufrA9uJvF/jXHXVVaXPdnZN30VAWliOS5LWg8GADeTqq68ud6z/8R//cXD//fdXY5fuetfv7jT5m7/5m9Kn8sFdl5Ab61QU+T/r4rHFqKiwjvwYYwQVwPYwT+5oTIfYNipAp5566uCss84q/0dUfJjmr/7qr8ow+zhtJZT5cyCAStZLL7002h6GH3/88dGTB1384R/+Yemzr/NSQTvppJNG+SAfH7Cf4zB9fjS1SfxOF/tMA4G7hdztqz/yS4Bpmjt2TcsP4x7VBk900GDK28DjtVaetV443zj/HnjggVKm5Ebts88+Ww21o5yKhjJlJHkYeTxooF9//fXlPM/l2p133lkNDQZvv/12NbTUcI+yLnfhP/7jP6qhweAP/uAPSjkcZccPf/jD0sddd91VGt6xn9MiWEFgJHCdyteHN954o4zrGuzl6bAIHrPsjfJ0gOW45bgkrReDARtUbmwjV/aacAGOBnz9Ln801kFFMXCRztP++Mc/roaWBwOmdcghh1RDH7vjjjtGldD6vnXBUwWBZVDJqiMAkoMgk3z2s5+thiZX0PaF+vHJx7EJDYC4M0da1ytfOdhDGkZa/dM//VO5S0ljhfkClX7ubnEncNbYNirQ3DnL28DjtbwW0nbHVJql3NjpUiZyLoU8by6/CZrmp5fy61ycc9Fo+/d///fSX6ncAEUOqF533XWlP60crCBQ0lSWM26aV8AieMx5n9Nvo7ActxyXpFkyGLBB1aP4P/dzP1cNNct3nY477rhqaDq7du2qhpbLEX4quLky0iTf0QKBCioHyJXJaeS7cuNeaZgGFdaoMHe567cIcuX8H/7hH6qhJU8++WQ1tPSESGAe0oFxVBp5woJ+oDI5y0oceZ13hgONDLaBO4xRKeb95EmVaGmtffTRR9XQ0qP6k3z/+9+vhpaCkyvxr//6r9XQx3iqKsrg+FjqpDu99eDFjTfeWPoEI1YSkGV9+amAprvCK/HpT3+6GhoMnn/++Wqo3yzHJUldGQyYI1FZq3fTovH8X/7Lf6n+txT9n/QefH4UdFwl9IUXXqiGluT5Qr2SmSP8BB34EBKPCoa4C8RvBAp27NhR/g+2JSokVEJ/+Zd/uVRkI23GffE6y5XQlQY7mhxzzDGlT8V5UuV6vbE98eoHYlvHyXcZuRuT5Ypg/TFeHonm0WgebeWY0c+PSK/2LuU4PDIdeYw8wlMfbAOV2/wESH46RGpCWZPL3uhyo6gryrJbb721+t/yBlqbCMqSj9v89Kc/XVbWtD0+/eGHH1ZDy8tgyiqCq3yMMJbz8z//86WP//bf/lvZ9ggGcKeWdUR5QPnL7/EXBQj21j/22qQepFhpsKOO60c0FnM5v1FYjluOS9IsGQzYQKLiSuUtKgBUknJFYpKmu1ef+9znqqGlyjIVPxrz3NnJTxRkVCD4MBR95uFuQ1424yLCHx+BAoGC2HYeWaQSGutgHoIc8ZQAqPw1ffF6vRx99NHVUPMdufVGcCaODZX9fHevy3u4BI3iaQfmjUALlf+oqHFcuzzGe9hhh1VDs7Vz585qaKnhkuVXTtqeXJHWCmVVlMOUZdE45ZzZtm1bGe5i//33r4aW0CiK8pPzkEe2Oc8piy+88MIyvu7Xf/3XRx/no+ykPOX/geXER/c4n6PRR/nLtoN1Ur5GY4xynKfM+D3KFpbD6wNdAgKzEk8HbJRggOW45bgkrReDAXOESltTt1Jc7Im2d/k6PnebkB+5DFQGcyWSih+VSyq+efuiYkFFmMojH4aiz90F7jawLTkgEO93Mh9fr451MA0VVz6QFV/qp6JKJTQCBVRK8xevvVuwhGMSxyYqfeBRyzg+VDCjwZK7kF+j+Pu///vSz4+W/u7v/m41tIQ7V/Hhqfz3z9mO9ZD/jCXrzPvEe6ZSVzSgctkbXTSsVoKy6tFHHy35cZz8hFMOMoZ8d5RGL3k93uHP5XPc5efd8fg4H2Uw5Sn/z3d6811ighX8FmV0XD+4NkRA9oYbbijneqj/9Zf8xIJWznLcclyS1ovBgDkSX1Sud11xAaURHbgj0PQxvmlxMaYymyuKVI5ZX37Hb9IdBIISOdiQH2ONiisVEr4oTcWViir7wDp5eiB/ROv8888v80QleNLdglyZ/5d/+ZdqaGNjnzlm3GXq8ohyyH/jO4Iv+ZsI+XeOF3cp48NTcQdrtQ0oaV+gAdVUBnf9zkiUi9FABo0cytDV4hzOQVOwHhrs2aS7vTT2Qm5oso0EHCh/Oa8pjymz4y+scI6z7HgKi+2gDKYsDuOejsqvIqDL612yHJckzZbBgA0k7v5ERZSKXv52wDjRSI8nBOrqFUXeLWR9+U4DFYe1wjp4NxX8Wax6BXe//fYr/c2bN5f+JPk9y/yRro2GhghpF8eIY1Z/MoTHipmu3gXSOhocVArz+8PkrdywoSESj+YStOGDT6x7mgZUV2+99VY11C7uTjZ1bJM0SzScKBf//M//fNSIonGV76a3yefpyy+/XA0tl4OmdDxxxRNTcQ7mIMRa4FH1CMheccUV1dglUfZGWTwJ5UoEk0G6qBnlcRxjy/HlneW4JK0tgwEbEBXRqHRxR2CaLwDnO0WTsNx4f59AQFRWeM+/6R1+7gTlYMMnP/nJamhvPPbPtrAf496RfO+996qh8fKfRKQS2vR+KxWNae9W5YoNHzdcBNxdosFS77J4PQP33ntvNfTxn/EK+ekOlps/CtbWoBkn34XKH6vk2LTl4/xNi3GBHpYhrQcaWvkvn3zjG9+YqmzJj0yPQ57mb7CHXM61nS+5MZWfMqhj2fwVAhCQzY3HLP/FhElYTqDhSgO1jmvHtN+AiUbuuP3ZaCzHJUlrwWDABkSlLV/4ucM+qXKVP9jT9HVq7mxxlyg+WsVX/PkzPyHfkeDiz5MGTENFlXno81hiBBuoLHCXqwnbGpVQ7ohEJTQ3tvniNZXruJsx6QvLVG7ykwvceeC9SB6Zje6oo45ath9d5LspbZXlRfTZz362Gvr4Dh77OO4xVSp5dOQf8lw8mjqNfBzJA+Q18g95pS1QRb6K4BfbyrGM7SDfsgyO9Tx84FH9QZkTr22Rd//zf/7PZXicKKOa7ppT3kUZHGUqH5fLTwXkRhzlM1/653zgHIhyO3+ANTcW6+66666y3fG0Q4hzlG1kmx5++OHyf0wKiBLYjXMVfIiQbYoymGGuHfVXH8ahcRjBgPoTZH1nOS5JmsRgwAbFRTe/LpDvHjXJf26v6Z16IvXxGCIN6dwI5j3W+iOMYBoqEsxDPyoBzDPuLxzccccdo0porrTQ2I7KNcvLAYwuX1i+7777lt05ogJJpSO6aRG0iHQYV7laRKR1/ZHjpn3M751yzGiA8LEnGhz5Q2VdfelLX6qGlpZHXiP/cKzaHoFmW2k85IpkbAf5hWVEY0FaTzxaH3dJKSto0IyTy7T6kwQ/+9nPRmVwvUzl3OCJsDp+53zgHMjlNjg/28otyjamx3XXXVf6ITfo2d5oLLK8SQHR+rkKtinK4Lx9XcWHaFG/4913luOSpEkMBmxg+XUBKllE5ttwRykqrX/7t39b+uNwB4uL84svvrjXHX4qFly8649s8n8qBMzTFDwAFeC4c5Ufsw1Urll27BfL5P3GLneEqGzwvi1fZGb7c4WUfaeSkj+IOEmuhJ5++unV0MaRPwwG7tTUke6kfz7WDBMg4qmO/DRGF+QLlpcrjCyPY8b70ZFH65iPyiN5oz5N5NVFeY1DGwdlTi7HyIdNT16F3CiLL8C3IZ/TUON84dxgXRnnDOdRLucYZhzzcH62ufHGG0ufc6feeOScf/DBB0fnPMvkvOv6pxM5V7kGcC2olw8sk32qjx9nx44d1dDyO+FaYjkuSRpn056harjVpk2bBh0mG+n6HrfmC8ECKmjgQp4fOdXeeGSROxVUWvjIkyStFo01GkQ0smk01xv5+hhPMMTHbwkijAtwSJI2pq4fE58307avZ8UnAzTC458RjbdSNR7vMsYji7feemvpS9JqRUCWx6v5kKra8UoZCJzw52clSdJ0DAZoJD/Syp2pLn8Oq4/4YFX82UPuRrV9CFGSpsWj0hEQoF//doCW8LpFvFJG8NqPB0qSND1fE5AkSZIkLRxfE1gdnwyQJEmSJKlnDAZIkiRJktQzBgMkSZIkSeoZgwGSJEmSJPWMwQBJkiRJknrGYIAkSZIkST1jMECSJEmSpJ4xGCBJkiRJUs8YDJAkSZIkqWcMBkiSJEmS1DMGAyRJkiRJ6hmDAZIkSZIk9YzBAEmSJEmSesZggCRJkiRJPWMwQJIkSZKknjEYIEmSJElSzxgMkCRJkiSpZwwGSJIkSZLUMwYDJEmSJEnqGYMBkiRJkiT1jMEASZIkSZJ6xmCAJEmSJEk9YzBAkiRJkqSeMRggSZIkSVLPGAyQJEmSJKlnDAZIkiRJktQzm/YMVcOtNm3aVA1JkiRJkqTV6NAMn7nOwYB52FhJkiRJkhbZvLSvfU1AkiRJkqSeMRggSZIkSVLPGAyQJEmSJKlnDAZIkiRJktQzBgMkSZIkSeqZmQcD3njjjfK1RLoDDzxw8M4771S/qM3DDz9c0oo0u/fee6ux4912222Do446apTWV1xxxV5p/fjjjw+OPfbY0TRnnHHG4OWXX65+XcJy8jQMd90G1sf8MW992W0mbTt5iHGRJvTr07CNMX/u2MdF1+XYNuky36RpGK5Pc/7553c+tpovcTzjWK7VOYp5LF+Yh23NZQfLaMK0eR8ph7OVpp2mQ7pSxkQ6c0zIW5N0ma9Lfnjuuef2Wk5bnpEkaeHxpwUn6ThZo+3bt5f5N2/eXPr33HNP9Yvqdu3atWfLli0lnaIj/SbZtm3bsnmiY1lhx44djdNwXF5//fUyTRyrpo75x+H3OMbR7dy5s/q1XZdtry83uq1bt1ZTtG/76aefXk2xmLqkT5Mu83WZhjRumubII4+sptCimOU5Oq/lC9uY54mOfaqr72cue1e6fk2HvNJW3o/LI13nm5QfuAY3/U5n3UWStJa4tsyDmT8ZcN9995X+n/3Zn5X+/fffX/ra25NPPjl47733BsNKZjVmMu503HLLLWV4WHktf69yWPkp/3/xxRdHd0a+/vWvl/6wcTfYvXv3YFh5GgwrT2V9DzzwQPntmWeeKf1hxagsh+mGjb4y7pVXXin9NrfffvvguOOOGzz00EPVmMm6bjt3b1hubNOwgV/Gv//++6WfxXKie+KJJ6pfFk/X9KnrMt80yx5Wgku60w0r02Uc+Yc7aFocszxH57F8YdvYRlCmsk7WDfaJfQs8fcQ4tifKl2wl69f0yCvkGY4DeSiX95HHmnSZr0t++Oijj8p88XvkY3zwwQelL0nSRjLTYACP7XExpQFx7rnnlnFcjOuPV/J/HimNx/JyRyUNXMjz46Ub8VHla665ZvDaa68NTjjhhGrMZD/+8Y+roaX5ceaZZy6rZFPJiUrQVVddNTjooIMGRxxxRElDvPTSS6Uf9t9//9JnuqgIHXbYYaXfhkY33aGHHlqNmazLtoM0iW2lQhaVePZhI+uaPnVd5uu6bB6VvvTSS0teoDvvvPPKeC2eWZ2j81q+/J//839Kn8ZdlKkXXXRR6ePVV1+thgbl0XHQ6G+ykvVrek899VTpX3LJJSUPkUe++MUvlnGRx5p0ma9LfmA8xzl+f/vtt0sfk/KoJEmLaKbBgP/5P/9n6V988cXl4sxdI8R4UJE8+eSTBy+88EK580QXFcRAIOCss85aVhl45JFHynwRLOiraLTFXZDAe44hV3pzoOHwww+vhpZE2l977bUlOEPwhTS//PLLRxX7tdRl20HQJ4JANELYJu7o3HjjjdUUH2Pbc8Boke9ed02fui7zrXTZjz76aOlzHHJe0sa0yOVLBCFOOeWU0kdTAJHrC09lsY8EOrTvxDX++OOPL310CcB0ma9rfsjfnznxxBPLEwc8ETKLPCpJ0r4202DA3XffXfqnnnpq6Z9zzjmlT0M+UJHkYssjmNx5omMYu3btKhfreMwvHlPlEUACC8z39NNPl9+0ekcfffTgrrvuKsNUjqlgUXm/8MILyzjEh5ei6/rxr7XGY52PPfZY9b9m5DMqc30PGK0VjnVUutvuoEpt5rF8IRh99dVXl2GuL1ITnhzxtShJ0kY0s2AAd1torPOKQETfIyjAqwP8jk9+8pOlQsiTAXyxl45hxu23335lmmiAxF3fgw8+eBRQeOutt0pfq8cj4RdccEG568udEO7YcQxpUMfx2hdoRBAEoiNAFO+tX3bZZaNXRQgixTR0vOceJgUNNBl5g/QGecM7qJrWPJYvlA1cj9gWyhmJ16LiOsL3MaiLkE/PPvvsagpJkjaOmQUDvv/975c+Dfm4y0MjPsTviPdPb7311tLg5//f+973Gh/hq4v3T/sq3mPkTlsW79XjkEMOqYaW/mxSyB9EYnoq6uD9Sx6J5C5efGAp7gS/++67yxrdVJxWqsu211Fh/6//9b9W/xuUDz41Wc12zYuVpA+6zDfNsqMRBx+X7ZdFLl/i+hEfLkQ9f3/3u98tfZ5ii+tU7CvXIvP6+oq6wPPPP1/6+PDDD6uhdl3m65If6gh6EigCAQFJkjaamQQDuMDGKwJtaGAwHY/5EzDgghsVwZ/85CfL3j2NC328JpC7+KhVX5BuVFjj7+fHKxWIR2qZJp6m4D1YKkGRhnfccUfpc0c9jtHnP//5Ze/9xqsXHB/umq0VHrVk2+NvNnfZdhoX7Gs0Mnjk/7//9/9ehhFPj1Bpz3cX8+PF0aBZNF3SByvJE9Ms20BAf6wkL81r+XLSSSeVPo37eILohhtuKH3u9nKNOeCAA8r/NR9OO+200uevEJE/6PJfqgh8s4JjHdeFLvN1yQ/kHfJRvFrGdPEUItNIkrThDBvUE3WcbGTYaCjzDCuI1ZiPDSt/o7/by3T8reb4f+6GF/DyN3+xfczfp2b+jaItLehIAwwr36NxIY/LHWkY2tKQY7R79+4yDcNN09DF+tt0OUbxf7Y3TNr2cX/3Oe9f23L4u9KLrMuxzdOEaedrm2ZYAW6chi5Pp/nX5RxdaV6ax/KF9bbl33F/Mz72N29Tl/Vr9cZdA6M+kKeJY9Rlvi75gX7T73Tj8owkSdPi2jIPOm3FtBtLJZF52ip4UdliOoIDbZVExgcCBzTs6tPEhX4jGFehibSMQEtUeEEl5/LLLx9VdOhv27ZtVAkPLCOndaR/YDgvh440Z52TdKkss2z+n/NFl23fsWPHsgYJ21TPW7HtMQ37yTT1NFg0XdJnpXmiyzTjGnAGAxZLl3N0o5UvXB/iekTH9k1q1EVZk6frsn6tDcr7fK1nuJ7Gkc/y+C7zdckPHOu8HPIDy5YkaS1xjZkHm/hnuDFj8Theh8lWhMeOeQxvWJEbfWmax1HjY2WzWq8kSZIkSettlu3racz0TwtOI3/AKQIBp1fvLUuSJEmSpLWzz4MBd955Z3kq4MjqA1RgePv27YP/8T/+RzVGkiRJkiStlX3+moAkSZIkSX3hawKSJEmSJGmfMBggSZIkSVLPGAyQJEmSJKlnDAZIkiRJktQzBgMkSZIkSeoZgwGSJEmSJPWMwQBJkiRJknrGYIAkSZIkST1jMECSJEmSpJ4xGCBJkiRJUs8YDJAkSZIkqWcMBkiSJEmS1DMGAyRJkiRJ6hmDAZIkSZIk9YzBAEmSJEmSesZggCRJkiRJPWMwQJIkSZKknjEYIEmSJElSzxgMkCRJkiSpZwwGSJIkSZLUMwYDJEmSJEnqGYMBkiRJkiT1jMEASZIkSZJ6xmCAJEmSJEk9YzBAkiRJkqSeMRggSZIkSVLPGAyQJEmSJKlnDAZIkiRJktQzBgMkSZIkSeqZmQQDzjjjjMGmTZtaO35vc9tttw2OOuqoMt2BBx44uOKKKwZvvPFG9avCc889Nzj22GNLOp1//vnV2G7uvffe0bEgrbN33nmnpDlpH8eAY5J1mabNww8/PNpuOoYff/zx6tdmsZ6mLu/7yy+/XP4fv7Fv9WV3mWYRrXS/1irN1iLfsJ5YR1NHvgXlQX05/J/lazLOwUi7SNNJON75vKUM53hl9Wnq53bOQ/WO7RmHY5uvDXQsr74NdZHn8nxsO+VniLRo6lgHVrp+rY162nc53+PY53KiXiYhjm0su35Mm5ZjeSNJ2jD2dNBxspHTTz+9zNPW8XuTbdu2NU6/ffv2aoo9e7Zu3VrG3XPPPdWYftm9e/coDaJrS88mr7/++p7Nmzcvmz/bsmXLst+i49iELtM04Zg1zUfHdrWpb2/uSAs07Vd0O3bs6DzNIlrpfq1lmq1Fvtm1a1fj79HFOd+2PZdffnn5Xc1I3/oxyGVrG45znic6jgP5Y9w0dDt37izT1Mut3LGscdrmPfLII6spmrVdi/K2t+Unuihf2tY/abu1em31AvLyOF3KJPJt/fhHfg1ty5nmuitJUh3Xknkwk2BAFpWxLhfOuChHBZWGL8O5whrL61KJ3YioqJBONIymSdtAg4l5ok8XcoU+KkS5Isbx6DJNG44Z00YlPG/DNMeTdUReeeihh8q42AYaByyfaSJ9otLYZZpFtNL9Wqs0m2W+YdqYhvWDbWF5oIGbK/NqxzlG2uU07XLecZyZlgYxx4njEGnOMUTkiZiGjnUxblyQJuabFMhhuZR5sezYJrrIT01impxfJs3H8uvlC+snrfgNOe9qdkjvSOfIq7ksieNa17W8If/RcZzr0yOfKzE+B7WjTJIkaVpcR+ZBp61YzcZGZY/+JHGBbasYxu+5iwoC80Tlk47hekWXCkKeJk8bmCemoULIcqPiMG+mSVtExYaKdK7khKgs5eVR2YnpmKfLNF3lbagfq3GYlnnycYvGQV5OruChyzSLaKX7tVZpNst8w/T83qVBSaduIr3ycW2SG2P5GHE8GBfHs2kals048lCTfP5P26iKZdfXWVefJu9P2zpj2bl8yVhG7H/bNFobuVGfxTW6Lf9OW97kvJh/i7yQl4OYti0YIUnSJFxH5sFcfUBweAEv/bvvvru8H8j7rJPey9t///3L+5/MM7zYV2MHZfjaa68t78eCac4666zBsIE/GF7gR+vKrrvuujJPLOe9994ryx33jYNF8qUvfan0//Iv/7L061566aXSP+WUU0ofRxxxRDW0pMs0Xf3gBz+ohgaDc889txoaj/xw6623luFLLrmk9PHiiy+W/vHHH1/6OPTQQ6uhJV2mWUQr3a+1SrNZ5RvO2SeffLIMX3jhhaVfR36IaYYNtNLX2nn11VerocHghBNOqIYGg8MPP7waWjJsnJX+HXfcUfoclzfffLMMRx6qu+mmm0p/2NCaugx59NFHS5/15u2qe+ihh0r/xBNPLO95/9Iv/VL5P+Ob1tlWvuDA6p3xgw8+uFwX2O6nnnqq+lWz8Morr5Q+aZ1RPxhnra5Thx12WOlTxsS3BPI3BWL7JElaVPskGFD/kFR8pOnmm28eNdJpkF922WWl8hYfodqzZ8+oUkCDnv9feumlpTJ4zz33DHbt2lXG0W3ZsqVM99Zbb5X+888/X/rnnXfe4JprrinrAsGB1157rVQCb7nlljJu586dZRlsA5VNKrOL/qEoAivsx9atW8dWntdC/kAhHZXoOtIz0ptj3rWi9sADD5QgDcftoosuqsZqI8qNxbY8e+WVV5Y++eGrX/1qGdb6O+2000r/kUceKed8NJjb5EDP9ddfX/pouzZkUZbh9ttvL/02zB9BIraHsoNrw3HHHVfG1U1TvrD9TUFlbRw5nxxzzDElT9KXJGmjmLs/LUgjnUY4jX0qZFTMvvCFL5TG+jg8IcBd/ahE1u9GxZ1N7ijx5WCeAkDc0cp3wLiLxDL4LZ4S+H//7/+V/qL64z/+49KPBvi+RCDg5JNPLsNU1CMw00XctWO+gw46qAxr4yGPRGPx6quvLv067vTS+KScePbZZ1d0509r48YbbyznJMcClJ0EHhGB2SyeIOC3aYKTPOlFkBjc3T/zzDPLcBvySNzFZ3r6XBtYb9NfqRlXvrz77rujIHEEGMh/Xf8igxYPZcqOHTuW5WHyddQbPvWpT5W+JEmLap8EA6jQxR18uniUP3AB5u49FXwQEMiN9Trmv+CCC0aNhyb77bffKLhA0IBGMRd1KnNdfOITn6iGFg934dhvUIkh0EHAI/B/Gl/RmHrmmWdKH/UgTJdpeFojH18q0SECAWwPFeq77rqr+mUyjnPsR/2uXVTO4gkQfPjhh9XQki7TLKKV7tdapdla5ZssGlisv6nBF428CAQcffTR1S9aS4ccckg1tFSOhA8++KAaWkLDmXM5Gsw8bRV5J/qBRniUu1/5yldKP4y7NkQ5Dxr2TU8NZDxRRh5h/U888USZnj4NO8qRxx57rJpyybjyJSMvE/wI9bTQ2smP6WeTbg5MW96MQ/nzk5/8ZJQn77zzztFNgl/4hV8ofUmSFtbw4jZRx8kanV593Iv+OPFnr/IHeZq+2hvL27Zt6SvWjI+P/PDFZ/CBJ5bFOH7DsOFZ/t/2wR+Ww+909Y8LzatxaTusAI/2JX9Bu61jmmEFe9n/Eek2bHSV/3eZpg3TMw3TMk+TmIau/uHG2KemeWMbmIb5ch6IfNFlmkXUZb+a0nWt0myt800+F5mvLs8Xy9J0In2jfAxN+YRjz7T1vMQ4yugYl8tNjltMUy9Pc57qKuefpjyBmCbKw7gusB2xDeSt2J/6vsd4tq+O32K9pEssmy7SQGsvlwWRzjkv1MuSOKbjpiE/1JE/Yvp6fqXOwHaAPucB002q00iSNA7XknkwV8EApmvqcuUsLujRcfHPQYN6F5WDXHmLjkoBy4tKb2xrUzdPmraPLtI4V2xi/+vyNIF0iAp8vYuKWJdp2kQlqqmLClo+TrlSlit39coa8v7Uu6gMdplmEXXZr6Z0Xas0W+t8kyvtcW4G1lmfP3eT8mCfjTuWTeVk5JM8Lnc0kOP4tE2Ty27kxl2ss4u2vEMXQYpcfiOvq6mL/cOk8qVt/TkNNBtt1+U47ohxcQ3sWt605Vu6yAdNv7HsRb5mSJL2Pa4n86DTVqxmY6MBmC/cbaiQxV1HOobrFUYqeFE54IIcd/p5UiAu/szH/xmO+cdVhKPCSgWC6eMOUXQsd57kbctdVIQQ+9BUsUWkR33fqODkRjvLqTewukzTpB7IyV1sB8tmmC5XsiNf5H2sIy/U8099/7tMs4gm7Vdbuq5Vmq1VvmHb4vemxuKkBl6XfNhXHLOmNKOLtG7LJ/VykePIsQjMV88jTcciyuX68ifJ6653bAuiQZ/LCPY557mYvp5/Y9vbypfIu2w307E9OZCs2SGNSetIe/rko5z2cW3JZUaX8obp4/d6F3kk1y3osy6WLUnSanBdmQeb+Ge4MWPxTnmHyeYaX7TnfdBhhXH0ril93l0dVgDLu6SSJEmSJM3SvLSv5+6vCcwaH6Ai8eniI1b5bxFLkiRJkrTR9SYYwBfHt27dOvrTV9iyZUt5UoC/XCBJkiRJUl/05jUBSZIkSZL2NV8TkCRJkiRJ+4TBAEmSJEmSesZggCRJkiRJPWMwQJIkSZKknjEYIEmSJElSzxgMkCRJkiSpZwwGSJIkSZLUMwYDJEmSJEnqGYMBkiRJkiT1jMEASZIkSZJ6xmCAJEmSJEk9YzBAkiRJkqSeMRggSZIkSVLPGAyQJEmSJKlnDAZIkiRJktQzBgMkSZIkSeoZgwGSJEmSJPWMwQBJkiRJknrGYIAkSZIkST1jMECSJEmSpJ4xGCBJkiRJUs8YDJAkSZIkqWcMBkiSJEmS1DMGAyRJkiRJ6hmDAZIkSZIk9YzBAEmSJEmSesZggCRJkiRJPWMwQJIkSZKknjEYIEmSJElSz8wsGHD++ecPNm3aVLrbbrutGrvk3nvvLeOZZhLmPeqoo8r0Bx544OCKK64YvPHGG9WvCqRJpDnp1MVzzz237DiRzvVjxbLi99wxL15++eXG36PjWI/z8MMPD4499tjR9Aw//vjj1a/jMV19XrYn4//1fWSdoUsaLKJ33nmnnCtx/Oh32a+m9Kofj67LnpQnYzlxftOdccYZo7yFpnXxf8ZrMtIyzhGORVecI5Hm9XM45496l48z+YbjGb9xnK+77rqJx47fc7lPxzrr53Zd23blvBn71NRF+qx0/ZqN+rHoev53mW/SNFFXqXfka0mSNoQ9HXScbJnTTz+9zEe3efPmPbt3765+2bNn+/btZTzTjLNt27bRMnLH/OGee+4p47Zu3VqN6Z9Iz9xNsmvXrr3miY40DU2/0+3cubP8Pm45dHlZdXHsmrrXX3+9mqpZl7yxY8eOxmki33VNg0W0ZcuWxv0i3dqQ5pyrTfORlqHLsrvkyVxG5I5tiOPftq5JZUffUd5SJk6bZpwT9TTP5xTqy80dxw6UD02/043Lg2hb/pFHHllN0awtP+Xtb8vfdHENWen6tfbaynny6Dhd5usyTVM5Rmf5I0laLa4n82DmrwkML6yD9957b/DAAw9UY7q7++67S394QSa1BsMKbhnOPvjgg9J///33S7+Prr322sGwYlO6rj766KPBsEIzGFbaS9oOG1+DYUW5/BZpmjFN7k444YQy/uijj97rN5YZTj311Gpob6yHbWbdzHf55ZdXvwwGjz32WDW0N+4433LLLWV42Ggv+YL5hw2ZwbnnnlvG4+qrry59lhvroB95aNo0WBTckX3xxRfLcOxb5A3Sre2uGuco5+qw0VPSgnQlffD1r3+99Lsuu0uefPLJJ0t/x44do+MHtuHtt98ud7Xr6+J4g3l9Qqjdq6++OnjqqadKesUx7IJ0Jf3zOVzHUwMci9zFOuLu+vPPP1/6jI/zc9jILuNeeuml0h8nzms6riEgT+anRtpEXonummuuqX4ZDN59991lv7H8OOfPOeec0sdq1q+1QVkS5XzUASgrQLlQf2IpdJlv2mXHNNE98cQT1S+SJC244YVtoo6TLTOsBJb5HnroodLnjsywYlV+G15YO0XXmYZu2JirxiwX68hdLHNYmVt2h4v1s5zYBnC3k7s9eX66fAeIafJyuGvE3bN5FOlKN61hBXp014xjFlayvDgubcetDdsQ62Nf2sR+xp28JrEs9qmrtjRYNMMGeNmHfH4NGzJlHB372STyeU77OH/pMO2yx+XJ+jycmzGOZca8eV2IaTg3NVmcj/V0nCTSedy5iDjX6DhuaDp2kXemLRdyHmrLu4j9HDdNXSx73F3/ruvX2uL8jnTP4prdli+7zNd12XHs29YlSdJK1a9B+8rMnww49NBDy53ZlTwdEHcVeUKA9/p4f6/trmY44IADSv+yyy4b3VUE62c5N9xwQ/k/d3jOOuuscldoeKFvvIPJ3QGmyct55JFHBieffPKGuCuZ34c88cQTSxoNG3+ju3tZTMdx4D3LtuNAusYd3wsvvLD0u/rBD35QDQ2W3eGv++lPf1r6PA2SvxnAdsd2/d//+39Ln3eEGR/T1L8rME0aLIq483rKKaeUPo444ohqqF3k8+OPP770wfmbrXTZTUhnkO68q/tLv/RL5f+MZ5mHHXZY+T/5KY5ZPnavvPJKNaR96aabbir9YWN8lBcuuuiickedY0eZwfnEnVjG3XjjjWWarh599NHSHzbURk8kjUN+4nzm3CdftZXVlBW33nprGb7kkktKv8m069faiPObfJWRn8bpMt+0y+ZJp7hOkJd9QkSStFGsy18ToPJHo5uKV1MjMjfW4mKLm2++edRI5xFNGvg0GOIRPh7VoyEPLup79uwZfRyOBsXO9LhoLCcqhvEY63nnnVceI2VdYDtfe+21MhyPRrMOlsEjozzqSoPx6aefLr9tNFSex1V0OA5UjCKoUpcbBlFxrn+EiUp6HY28eGyTYzWugRmvhNDQqAdqfud3fqcMx2P+bC/jA9MTzBkXVJqUBlobnOcECkGgjvOKxuJxxx1XxkUfxxxzTMk79DU/cvDv+uuvL30cdNBBg/vvv7+Up/kcvPjii8tvaCv3M8qOOMdvv/320u8qAsCnnXZaNWa5eC2GbSR40WQ169fGRF4m4ORrSpKkjWBdggFU/r72ta+Vite0TwfQSKcySYOcShvL+MIXvjC2MQfuaN5xxx2jr0dHQzPE3U/u+nCnm69cg7s/ISqBcVfg4IMPHlVq33rrrdJfZJdeeukoWLJjx45R+p599tnVFOX5lVHHcaCxhvieQ0aDPhoG8b5+F8xHAx00DiMwMwmBGbaJbcvvkmccT95FZ5r8TjrvVKNLGmg2CLqQjwgcEbyjzzlHHqOiTUCIYxJ5DhzzOEc/9alPlb72HcpYcIzyXfN8TlN2R/lNQDfK2kkI7DI9yB9nnnlmGW5DcDjOZQK3EWiijGgK7sVTAUwXAYps2vVr4+FGQeQpurjOYNx3bSRJWhTrEgwAd16oDFIBq3+crf5Bqri7H2gUcFF+9tlny/9zY64JDQki9zTcmbbJfvvtN2r40dgnWEBDI99FHmf//fevhjYGKrpReW5LM44DT1K04S4aaKzlinNucNPxEa8QjQbWyfrvuuuu6pd28SoIgZ54guBXfuVXSj/k48NHDnO/TZc0WASRJs8880zpY1LwDNHIjqdm8OGHH1ZDS1a67Dqe7iEQwDppxHFXmD6NStI+Ktock5/85CejvHPnnXeWxh1+4Rd+ofS1b1DORnn5la98pfQDTwBwHDmfKbvpvvOd75TfIjA7rtxn+IILLijDNMSbnhoYh8b9uNeUWH6c401PBax2/Vq9/JpQNqm86TLfSpfNtUySpI1k3YIB+emALg1uGom8352/6vujH/2oGhoMDjnkkGpoSVzEqaDyJXLQ0OAOERXNaOQFGq5sC49+5spoNHYQjaN4TSB3VG4XCXdhebqBpyBAP79PS3rHcSFIAu6m5Wno5/dnM36LpwXiVYFJugYCeI+TbY+7e3HHkeMV2xbfG4ht/8xnPlP6NBwjD+W8RDCoSxosopNOOqn0qeiyT4jXOtivuINbT9d4nPq+++4r5xNdvCpDoAxdlz1JvLNLYCjWz3GIBlrgmMXxoX/llVeWYZ4imBTc0XgcPwJqdJMaQU2++c1vlj5lQb2xHE9V/fCHPxwtu+s3Hro0xJmGvJv/3nv+HgjrfPDBB8sw6teLeKWBcieX+TAQMB/ya0IRaObYRN6iDEA9L3SZr+uyOfb5uhHTIgIKkiQttGHDdqKOky0zvJiW+epfXx5WHMt4OqZpwxf7Y7p6N6zAVVMt/9o5HcscN2+sc9jA3+u3YWNm2V8caJomunn6qnSkdVMX4v+x//y1hTxd7vgN7GPT73R8jTkj3RhPGkb6TTJsYO613OhYDvI2cDwwbOCPvvpf78gPYUv6KxC5i/zTJQ0WEenflj5NxzbSddzxjr+g0WXZmJQnOYZNv0UX51fTb6w/tkftmtKOrqkMjPQelwcinyAfvzw+RHnQ1MX627TlLzrKDOT8FfJ0udu2bVs1xZJ8zYj9zrqsX+ujrRzJx6EpL0w737TTcG2RJGk1uJ7Mg05bsZKN5YLKfPXKFo3IuKA2VSIzKm25QcfwpIpn/M68EXigz3iGubhjXKU3Gouob0N089QYaauw0IVIo5x+DOd9Yzn1Rn5ORzqOa/2Y0kCM35uOT5txDQYq5CHWn9dL+kceo2M/6tvOdrGOqNxHPsi6pMEiqqcP+14PcDSlK/ue04Ph+vHusuwueZLl5uXQ1fMXDbk4fvQ5ngYCusnpmrsoA0lH0pQuAnikfdM8dPnc4bgwLs+bMY7pI4/RxfnXNH2W56l35A9Egz72BWx7znfkXaari/yd5826rF/ro16G0yfv5TzUlBe6zNdlGoJeTMPvdF3zsCRJk3BdmQeb+Ge4MWPxCF6HyRYKj8bySPKwIjF6DJQ+j4kPKxXl/WVJkiRJktbSvLSv1+2bAfOKd0M5GHTxvnj+G+qSJEmSJG00vQ0G8JcJtm7duuxDcVu2bClPCizaxwElSZIkSZpGb18TkCRJkiRpvfmagCRJkiRJ2icMBkiSJEmS1DMGAyRJkiRJ6hmDAZIkSZIk9YzBAEmSJEmSesZggCRJkiRJPWMwQJIkSZKknjEYIEmSJElSzxgMkCRJkiSpZwwGSJIkSZLUMwYDJEmSJEnqGYMBkiRJkiT1jMEASZIkSZJ6xmCAJEmSJEk9YzBAkiRJkqSeMRggSZIkSVLPGAyQJEmSJKlnDAZIkiRJktQzBgMkSZIkSeoZgwGSJEmSJPWMwQBJkiRJknrGYIAkSZIkST1jMECSJEmSpJ4xGCBJkiRJUs8YDJAkSZIkqWcMBkiSJEmS1DMGAyRJkiRJ6hmDAZIkSZIk9YzBAEmSJEmSemYmwYAzzjhjsGnTptaO33H++eePxt12221lXLj33nvLeKYJBx544F7LqHv44YdH09C9/PLL1S/N3nnnncEVV1wxWvZRRx1VtoXxfUPaRTqQ/pOQRqQVaRbpzfHKaR7Hsd7Vjx/rPvbYY0e/M/z4449Xv7Z74403lh0/+vx/3PFj+2I9TV1935v2sb78LtPMu/o+TErH0GU+jmU+vhz/nE+YflJeUjekZf2cIG3HGXdOZLHMevfcc89VU6xs/WGl5QDqeYzhnH+afs/LbiurojMv7luTypBxmsqWXEZNyndMH7/VO/K3JEkLa08HHScbOf3008s8bR2/16fbvHnznt27d5fx2L59+7JpEdNGt2PHjuqXjx155JHLptm5c2f1S7MtW7Ysm75pPraNcbt27arGbCzsVz0dSP9Jtm7dumye6DgGIY5jvcvH9Z577mmchm5SmsexqXeXX355NcXeWGbTPNGxPaFL/ugyzbzbtm1b4z6wb+N0mY/ztGkajt3rr79epumSl9RNW37kWLUhrzbNQ5c1/U7X5XwYt36MKwcin7Rpy4dRjrXlQbrY9nHrp9uo5f8i6FKGtJlUPnfJd23lEx3bIEnStLiGzIOZPBnwxBNPsHelGzb6yjj6MY7fs+HFevDee+8NHnjggWrMeMMGQul///vfL/3A3anhxXv0+yTcVXjxxRfL8LBiULaN+YcX/jIusG346KOPSn+jefLJJ8s+kgbTGlakBrt37y4dxxGkYb5TiGGlfHT863nggw8+GAwb72U+fhtW/KpfJqc5d2WYnvmGlfXBsGJWxt99992l3+Too49eti10ed9PPfXU0uduEfmDZcY6YtpPfvKTnaeZd9whu+WWW8pwHKc4BuxbvkOWdZ3v61//eulzXpFPOM6kV/2c75qX1I40r5dpw4Zy+T/HKt8NbZLL6eia1Kc54YQTyvjVrJ9ygGmjHKBMCI899lg1tDeeDop8GHmI+SkPzj333DL+9ttvL/3Ig3RxnXjwwQdL/9JLLx3tT3TkazAt5Yb2ja5lSF2X8rlLvmM5MW90UbfhqQFJkhbW8KI2UcfJGnEHmPnp18VvDz30UOkPL9ijpwO4o1Ofj//T5Uh+TA/uBtd/H170q1/3xm8xHdtQl3/PHeOHFYdyt4BtjvHcgRhWOKq5l7AfeZro4s41289wTMOdUObZV2L7VrINcczoIt1j3DTLy8ePdJ5G5Cm6acR8cVwQ49ieNl2mmXfk2aY0Iy8yru3YdZmP/B3T5HMxztV8fmdNeUmTxR3ynK6cQ5PSkvH1+ZrEctqsdP1NYpvoxpUfkVcoj9s0rT/mo9xuQt6Ncrnp+qD1sdIyBPzGNNOUz13yXZ5m2muUJEngGjIP5uIDgoceemiJxnd9OuBXfuVXRnd1nn766dLnjlPcDY47u5NwNyvuQF5wwQXlHUTuAEyy3377lTsGjzzyyOipAXAH4qyzzip3qsB7itdee+3gtNNOK3eYuKtRxzrZ7ljOsGJR5rnuuuvK/xfJo48+Wvocm7hTGNineMeSOyn1u735nczLLrusLGNY4RocccQR1RSTkQd4ygHkp67YlpjvwgsvLH288MILpf/ss8+O3jflSYR8bLpMM+9eeeWV0h9WnEs/sD/jdJnv1VdfrYaWzrdw+OGHV0PNxuUltXvppZdK/5RTTil9THMOcR7Eech7023lYUzDsaacizv+q11/9oMf/KAaGozu8Df56U9/Wvrvv/9+2ebYtvxeeFwv7rjjjtJn/JtvvlmG40mGOq5FlMubN2/ufE3R2ltpGYKVlM9d8t1NN91U+pR9K83fkiTNg7n5awI33nhjqXTdeuutowrcOJdccknp/8Vf/EXpx+N8NLibLs5UAKKSSBcfieNx9WjMUBEmKECFklcIqHjsKYGbJTRO+T+Pi1JJeOihh0aPFu7evbuaajB4++23S/+ZZ54p/auuumpwzTXXlD7Yxrvuumv0SC0V1VgO68C4x9znEekZlep4JLcNQZQTTzxxFDRpQnp86UtfGk3TdvyyK6+8svTJR1/96lfLcBe5YpcrmxGgYXvZHjCOR5Ljg2hdptF0pslLmh2OAeXhuAApeZ5A3w033FCNmaz+oT7O7TrK33j0n0e4xzW4CAKA8js37Dknf+d3fqcME5AF41jnwQcfPLaM5RrEtQhf+9rXBgcddFAZ1mKZtnzuku9y8Pj6668vfUmSFtXcBAOobFHp4kLd5emAiNhT+aPBeP/995f/n3POOaXfFeslIMD7pXE3mWVSwR1n//33H7z11lulYR+Vy7q4O8bdKCoecVcq7lLFnVUqKYxjOTSSQTp0CYrMAxoL3M0HAZIzzzyzDIMgCEGO6O65557ql+XvAcc7mQRVYhqOAxWyLvh6ORU+AgHcBep6t4bKX1Tsrr766tKv46kOtovti6c7ItATukyjycblJc1OBD6jIyjJuYRvf/vbpY88DeVWPFm1lsFLzsmTTz65DFMm33zzzWV4Es47toltizIkzm2CzSwr9onyNs7T2IeMsikakhdddFHpa3F1KZ+75ru4jpNvfGpJkrTo5iYYACpd8XQAH/UZh8Ze3NGnIUjDkXnbPubz7rvvLqvI8rGojLv93K2vVyLbcCeMgEG+E1V32GGHlX4EF5566qnSuP3yl79cxo8TldZ5R+ONu4eg8TbpY0r1dK8jOMM0UUGPu37jjh/Hn8YIaUYgYJoPfcUTBjQO6g3POAYcx7gz+OlPf7r0Q5dp5l3k03qenxSM6jLfIYccUg0t3VELTef3tHlJe4sgWG7orCSoSCPnuOOOq/7XjHWdd9551f+WdFl//UN9nNshGmQ0xGmQUSZPcsABB5Q+TxjE+nmVLOPcZFlRjrz22mujoGz0sz//8z8vfbYhzmvtG9OUIXVdy+eu+Y4bDwSd8ZWvfKX0JUlaaMOK0UQdJ2s0bLCX+enXxW98jCfwwR7GDStoe83H//P0wwbDaBwdH68K9Wmb8FGhrVu3jv5k1O7qY37Mx/pDLIsPpjENXWw7y8DrDR/Jin1g+iax/UzH/PMg9oHjkJFGw4pV6WJ/cvoz3IT0Jd0C6VWfh2lYXyw3f5iO38aJ48V2xXGsi+2s58F8zJq2n3XHfPXjHtvVZZp5l9Mh8nM+tpGu9XTsOl+cB5EekZfa5ms6FuqmKf3zORLimERZxfnHsYhzkPFxjJg/xjEcZRX9LdWfbYvysuv6m+R8Eeusi2noYlujTGFcbBvXgrxO5svXArYz1pXHI+9DLE/7VpcypClvdCmfu+S7EHk58rskSSvF9WQezF0wAHHhr88X42J6Luwxjo6LeqhP2yQqkU1dbpDk7aFjmVHJaOpinbF/uWNZ0dBm+6MSUu+a0mtW2N6mbaCLbaUf42L/2radLipaTWlARyMijEvLfEzr+K1pnuiikpi3IcuNlKg8ZjkokTumj+3qMs0iaDtOcRzRlI5d5st5J3ecC5HuXfKSJhtXpsT5kM/3pvM7dywrGsTjyokI+HVZf5tx5QDLRFM5xPa1rTPK8bb9a2r8RXlP3tZ86FKGNOWNLuVzl3wH8lmMZ12SJK0G15N5MPNgQFxomyr08VtcuEO+gOeLblT4ciMr7gDVK25N09ZRiWD5ubHPcqJiG9i+mIY+lQLmzZUIhuv701aBoYtKKsuiQlqvzDal16ywvXnduYv0Jx3ZRrqofOV0q3ex/bF/MZ55WGYsAwwzTSyPdTD/pMZ0rpw1ddH4iDt9OY+wzpgu57E68kLc/aRr2q4u08y7OAaRD+lzbuXj1JaOk+ZD/TwjjTh+oUteUjfkPdIs0o+0rTfEI72jrOJ4cYzyceS45mME8kD9ONbL7y7rb5LLiXrH9oBlM0yX81h9nZyPuRzn93yOMty0TfnaU98v7VuTypC2vDGpfO6S75CfNqmXb5IkTYtryjzYxD/DjRmLD9t1mEwJ7yAec8wxZXhYYSnvsvLu7K//+q+X/w8rNuXjepIkSZKk/piX9vVcfUBwozqy+ksB/MUBAgE4/vjjS1+SJEmSpPVmMGBG+KL9jh07Rn/xIGzdurX82S7/JJEkSZIkaV/xNQFJkiRJktaJrwlIkiRJkqR9wmCAJEmSJEk9YzBAkiRJkqSeMRggSZIkSVLPGAyQJEmSJKlnDAZIkiRJktQzBgMkSZIkSeoZgwGSJEmSJPWMwQBJkiRJknrGYIAkSZIkST1jMECSJEmSpJ4xGCBJkiRJUs8YDJAkSZIkqWcMBkiSJEmS1DMGAyRJkiRJ6hmDAZIkSZIk9YzBAEmSJEmSesZggCRJkiRJPWMwQJIkSZKknjEYIEmSJElSzxgMkCRJkiSpZwwGSJIkSZLUMwYDJEmSJEnqGYMBkiRJkiT1jMEASZIkSZJ6xmCAJEmSJEk9YzBAkiRJkqSeMRggSZIkSVLPGAyQJEmSJKlnZhYMOP/88webNm0a3HbbbdWYweDAAw8s45577rlqTDfvvPNOWQ7z0r388svVL4MyHOObunvvvbeacsnDDz88OOOMM0a/H3vsscu2sS62ud6xf2B+/s8ys9jeo446qvy/aTtZ9hVXXLFsf9YD64vjQ8c2Pv7449Wv7brOx/GNdIl0asJ0kb70u6QD64tl05Huk+YjD8T0ucvHLPIY+xS/s+31ZbP+nH+Y/rrrrivzL7KVpCu6zMf/J+Wb+nIYrk+jbur5mDJmUv7kd6bL52NTubiWZXFd122omybvjCtzVrp+zV6XMqTJNPONyxv8Vl+OeUOStCHs6aDjZMucfvrpZb7t27dXY5aWQ7dz585qzGQ7duzYs3nz5tG89fl37dq17Ld6d88991RT7tlz+eWXN05D17ZNTdPSbd26tfz+0EMPjcbFMnbv3j3aZn4Hv8V09Y5pX3/99TLdrLGeenpGR1q36TIf+0265N/IB222bNmybNpJ+YL15Omjm5R+5MGm+fK21bc7OpYdxh3Dbdu2VVMtnpWma5f5uuSbtuXQTcoTWo582JSOnGvj1M/F6HK+5jjVj2U+PtOUxU26bEPdtHlnXJmzkvVr9rqUIU2mna8tb4zL15PytCRJbbiOzIO5f03g9ttvHxx33HGDYaO6GrPc0UcfTUou64YX8erXweDUU08tfZ4IuPvuu8vw5ZdfPhhWFMq0wwv9YNgoLOPHYZl5HSwP3C2I+W+66abSv+GGGwbvvffeYFi5KL/XxTJiO5n2scceK8Oz9sADD5T1HXnkkSUNhg340fZ//etfL/0mXeZ79dVXB0899dRgWEGamKak34svvliORVexnmHDvayf7RhW9sp2sX2TbN++fdkxfOKJJ6pflvA7y+W3YQOgjGPZ4fnnny999i2mY1vw0ksvlf4iWmm6dpmvS77hHEcsh47p8eCDD5a+JuPO9i233FKGI68PGz3l/5xrbXdEGc/viHIu8j/LY7lYq7K4SddtqJsm74wrc1a6fs1elzKkyTTzjcsbH330UZkv8kWUc/jggw9KX5KkhTW8uE3UcbJlhhfPMt9qnwwIzNN1/lg3TwKEGEf0fxpd1pm3Ld+FzvPkabIYl9NpluLuR15ffrqhzbTzRXrTrxtWysodG7phxWq0jHFpzDxN03GM29YT4ph0TWPWFcsdViSrsR8vJ6+Lu4aMy3ltkaw0XbvO1yXfxHBeTqT1tOdrn+W75Bl5mHFt+T/ycD7W485L/t/2Wx3LZLpJ58e02xCafm/KO5PKnJWuX7M362vWpLxRx3imZRqWJ0nSSuRr0b604T4gyLt9Tz75ZBm+8MILSx8x7rzzziv9aZ144omj9wXpshNOOGF0R+Haa68tfe5UMX6c/A7tYYcdVg3NVtz9Ov7440sfhx56aDXUbqXzNfnWt75V7th87WtfGxxxxBHV2PF46iDkdD388MOrock4NnH8eGKDvJIdWL0vevDBB5enSIYNg/KkQ7jooovK0x7kJd4ZZRncNWTcjTfeWE21WFaarl3n65Jv4k7uHXfcUfrchX3zzTfLcMyvyV555ZXSJ99m5NVx4qmWU045pfTR9bwcp60sbrLSbeiadyaVObNKA63erK9ZXa5H+bsz1AWY/qGHHmp88k+SpEUyN8GAaIhFN+ljU23iUX0qxJMa42vpc5/7XDW05JxzzqmG9hb7eNlll5X/05gc9wjtRsJHmWhAU4mncd2EClbOC7OocD3yyCOlUvfGG29UY/ZGQyYeFcZBBx00uP/++8sjoq+//npZBi6++OLym1bmtNNOK33Sk+MdwRgttqaymPM/n9t0+UNt0+qSd7qUOeqn1eQNPjZZDyhLkrRoNtSTAVzY407U1VdfXfprZWf1vmB0dfEOIg1FXH/99aU/DhUQGpu8u96XxuSf/dmflT4NhfXa52uuuWbZseObBiF/q+Hdd98tv9PQjyc9aGREYIr8dfLJJ5fh7du3l47jTVCHvyigleGpCtI7zh3OC56sAYEyLZ5ZlsVZl7yzL8ocLYaueePSSy8dXT/4Dgf5jacDzj777GoKSZIW09wEA6IhFh0X32lFo40K4ZlnnlmGA+PwzDPPlP5aio8PUUF49tlnyzgalG1PN8Q+vvbaa4Obb755XSuokQ7xMTx8+OGH1VC7lc5XF3fTL7jggtGdwcCdetKM9Mx5gf8fcsgh1VRLjx+HlXzAaVLe4lHR/Nh/rIMnAKgA3nXXXSXAQPed73yn/MbdpUW00nTtOl+XfEP+J02jDOC8iPmir8niVaNohIdJH7+LR6Nz2bjaD+a1lcVNHxlk3Eq3oUve6VLmzCINtDbiOM7imtUlb9SRnyNYzPVAkqRFtmGeDOBx73g8NB5PzS655JLSp6LM433xeDh3sJreH++KCiPLA+8cUrGNisIf//Efz12FMh6rve+++8q20eWvwoM04bUNutj+LvN1EXfwpkVlPSp38X4w2xnH/POf/3zpN207xzd/ST1X8KIBxXvVBB3AfPkr+vvvv3/pxzuoP/zhD0fLjve0F9VK07XrfF3zWz7/OA6xnKuuuqr0NRlf+g+RxyNQifiWAOUVjZ74O+knnXRS6VM2cizAX0QB5+u0r1tNKoubdN0GzlO2PfJLl7zTpcxZ6zTQ2ul67annjS7zdckbnCf1OkMEEbrML0nSXNvTQcfJlhlWPMt8+Uu+/L+pG/elZuZvmocuzzdsgJdxw4tz+TpwHeO2VF8XburatqFpWrphZaL8Hl+hHjaMyv8RXydmPL+D5ce8+1LejnrH31NGTvNIly7zoel3OvJDm5im7RiEtrxA2scxb9r2yIv1jvwQ4njVu7zsyGNN3bj9m3crTdcu83XJN23LIb01nba8HuUVYlzk2Vxe1bv8d9TbjhNdPncnlcVNumxDzktsC1aad2K62O6uaaD116UMacobXeZrEtNE3uD453lzZ96QJK0U15F5MLNgAJVP5osLM9oqW+MuzF0qoFTkYlxeXx3T8XsOCjA8bp62bWb/8nr5s15Z3m6wj/n/+xLbWk+DSEuwrew3HfsYJs2H+K3edQkGjMsHgXSlsRnzcBz4c1Chadv5PTfkmZ/l5H1jPpYVx5tpmCdPw3B9/U3LWkQrSVdMmg9d8lv9dyvZK8OxId9GPqZPQDIfszgXOHYh8n8cA45p/Rgwffxe76Yti5t02YbIa7G+leadmJ75Q5f1a9/ocu2p5w10ma8ups15g7ycl8P1jGVLkrRSXE/mwSb+GW7MWDx612EySZIkSZI0xry0rzfUXxOQJEmSJEmTGQyQJEmSJKlnDAZIkiRJktQzBgMkSZIkSeoZgwGSJEmSJPWMwQBJkiRJknrGYIAkSZIkST2zaU+HP3DI30GUJEmSJEmr16EZPnOdggGSJEmSJGnj8DUBSZIkSZJ6xmCAJEmSJEk9YzBAkiRJkqSeMRggSZIkSVLPGAyQJEmSJKlnDAZIkiRJktQzBgMkSZIkSeoZgwGSJEmSJPWMwQBJkiRJknrGYIAkSZIkST1jMECSJEmSpJ4xGCBJkiRJUs8YDJAkSZIkqWcMBkiSJEmS1CuDwf8PmghH01uKoeUAAAAASUVORK5CYII=)
4.5.2 The overall survival of HNSCC patients with high IL17C expression was significantly higher than that of patients with low expression.