<p class="p" style="mso-pagination: widow-orphan; text-align: justify; text-justify: inter-ideograph;" align="justify"><span style="mso-spacerun: 'yes'; font-family: 'Times New Roman'; mso-fareast-font-family: 宋体; font-size: 10.5000pt; mso-font-kerning: 0.0000pt;"><span dir="auto" style="vertical-align: inherit;"><span dir="auto" style="vertical-align: inherit;">免疫肿瘤学和精准医学领域正经历着翻天覆地的变化。过去那种单一生物标志物就能决定患者整个癌症治疗方案的时代已经一去不复返了。如今，要充分发挥靶向治疗和免疫疗法的治疗潜力，就需要对肿瘤微环境（TME）进行深入、多维度的理解。</span></span></span>

<p class="p" style="mso-pagination: widow-orphan; text-align: justify; text-justify: inter-ideograph;" align="justify"><span style="mso-spacerun: 'yes'; font-family: 'Times New Roman'; mso-fareast-font-family: 宋体; font-size: 10.5000pt; mso-font-kerning: 0.0000pt;"><span dir="auto" style="vertical-align: inherit;"><span dir="auto" style="vertical-align: inherit;">随着癌症生物学复杂性的日益凸显，研究人员越来越依赖</span></span></span><span class="15" style="font-family: 'Times New Roman'; color: #0000ff; font-size: 10.5pt;"><span dir="auto" style="vertical-align: inherit;"><span dir="auto" style="vertical-align: inherit;">先进的肿瘤分析技术，</span></span></span><span style="mso-spacerun: 'yes'; font-family: 'Times New Roman'; mso-fareast-font-family: 宋体; font-size: 10.5000pt; mso-font-kerning: 0.0000pt;"><span dir="auto" style="vertical-align: inherit;"><span dir="auto" style="vertical-align: inherit;">以识别可靶向的突变、了解免疫逃逸机制，并对患者群体进行分层以开展临床试验。这种整体性方法不再仅仅是一种选择，而是现代肿瘤学研究的基石。</span></span></span>

<h4 style="mso-pagination: widow-orphan; text-align: justify; text-justify: inter-ideograph;" align="justify"><span style="font-family: 'Times New Roman'; font-size: 10.5pt;"><span dir="auto" style="vertical-align: inherit;"><span dir="auto" style="vertical-align: inherit;">向多维肿瘤分析的转变</span></span></span></h4>
<p class="p" style="mso-pagination: widow-orphan; text-align: justify; text-justify: inter-ideograph;" align="justify"><span style="mso-spacerun: 'yes'; font-family: 'Times New Roman'; mso-fareast-font-family: 宋体; font-size: 10.5000pt; mso-font-kerning: 0.0000pt;"><span dir="auto" style="vertical-align: inherit;"><span dir="auto" style="vertical-align: inherit;">历史上，肿瘤学评估主要依赖于有限的免疫组织化学（IHC）或单基因聚合酶链式反应（PCR）检测。虽然这些方法能够有效识别</span></span></span><span style="font-family: 'Times New Roman'; font-size: 10.5pt;"><span dir="auto" style="vertical-align: inherit;"><span dir="auto" style="vertical-align: inherit;">HER2</span></span></span><span style="mso-spacerun: 'yes'; font-family: 'Times New Roman'; mso-fareast-font-family: 宋体; font-size: 10.5000pt; mso-font-kerning: 0.0000pt;"><span dir="auto" style="vertical-align: inherit;"><span dir="auto" style="vertical-align: inherit;">或</span></span></span><span style="font-family: 'Times New Roman'; font-size: 10.5pt;"><span dir="auto" style="vertical-align: inherit;"><span dir="auto" style="vertical-align: inherit;">EGFR</span></span></span><span style="mso-spacerun: 'yes'; font-family: 'Times New Roman'; mso-fareast-font-family: 宋体; font-size: 10.5000pt; mso-font-kerning: 0.0000pt;"><span dir="auto" style="vertical-align: inherit;"><span dir="auto" style="vertical-align: inherit;">等特定靶点，但它们往往无法全面反映肿瘤的基因组不稳定性及转录组图谱。</span></span></span>

<p class="p" style="mso-pagination: widow-orphan; text-align: justify; text-justify: inter-ideograph;" align="justify"><span style="mso-spacerun: 'yes'; font-family: 'Times New Roman'; mso-fareast-font-family: 宋体; font-size: 10.5000pt; mso-font-kerning: 0.0000pt;"><span dir="auto" style="vertical-align: inherit;"><span dir="auto" style="vertical-align: inherit;">肿瘤具有高度异质性。单次活​​检可能包含具有不同遗传特征的多种细胞亚群。全面的肿瘤分析通过大规模分析核酸（DNA和RNA）和蛋白质来解决这一问题，从而提供肿瘤遗传组成、表达谱及其与宿主免疫系统相互作用的全景图。</span></span></span>

<h4 style="mso-pagination: widow-orphan; text-align: justify; text-justify: inter-ideograph;" align="justify"><span style="font-family: 'Times New Roman'; font-size: 10.5pt;"><span dir="auto" style="vertical-align: inherit;"><span dir="auto" style="vertical-align: inherit;">利用基于NGS的肿瘤分析推动发现</span></span></span></h4>
<p class="p" style="mso-pagination: widow-orphan; text-align: justify; text-justify: inter-ideograph;" align="justify"><span style="mso-spacerun: 'yes'; font-family: 'Times New Roman'; mso-fareast-font-family: 宋体; font-size: 10.5000pt; mso-font-kerning: 0.0000pt;"><span dir="auto" style="vertical-align: inherit;"><span dir="auto" style="vertical-align: inherit;">引领这场诊断革命的是新一代测序（NGS）。NGS 极大地提升了我们分析癌症基因组的规模和速度。与以往逐个基因进行测序不同，NGS 可以同时对成百上千个基因，甚至整个外显子组/基因组进行测序。</span></span></span>

<p class="p" style="mso-pagination: widow-orphan; text-align: justify; text-justify: inter-ideograph;" align="justify"><span style="mso-spacerun: 'yes'; font-family: 'Times New Roman'; mso-fareast-font-family: 宋体; font-size: 10.5000pt; mso-font-kerning: 0.0000pt;"><span dir="auto" style="vertical-align: inherit;"><span dir="auto" style="vertical-align: inherit;">在免疫肿瘤学领域，</span></span></span><span class="15" style="font-family: 'Times New Roman'; color: #0000ff; font-size: 10.5pt;"><span dir="auto" style="vertical-align: inherit;"><span dir="auto" style="vertical-align: inherit;">基于新一代测序（NGS）的肿瘤谱分析</span></span></span><span style="mso-spacerun: 'yes'; font-family: 'Times New Roman'; mso-fareast-font-family: 宋体; font-size: 10.5000pt; mso-font-kerning: 0.0000pt;"><span dir="auto" style="vertical-align: inherit;"><span dir="auto" style="vertical-align: inherit;">至关重要。它是评估肿瘤突变负荷（TMB）和微卫星不稳定性（MSI）的主要工具&mdash;&mdash;TMB和MSI是预测免疫检查点抑制剂（ICI）疗效的两个关键生物标志物。此外，NGS还能检测罕见基因融合、拷贝数变异（CNV）和新型新抗原，这些对于开发个性化癌症疫苗和过继性细胞疗法（例如CAR-T疗法）至关重要。</span></span></span>

<p class="p" style="mso-pagination: widow-orphan; text-align: justify; text-justify: inter-ideograph;" align="justify"><span style="mso-spacerun: 'yes'; font-family: 'Times New Roman'; mso-fareast-font-family: 宋体; font-size: 10.5000pt; mso-font-kerning: 0.0000pt;"><span dir="auto" style="vertical-align: inherit;"><span dir="auto" style="vertical-align: inherit;">液体活检 NGS 的最新进展也使研究人员能够通过循环肿瘤 DNA (ctDNA) 无创地监测克隆演变和微小残留病灶 (MRD)，从而实时了解治疗耐药性。</span></span></span>

<h4 style="mso-pagination: widow-orphan; text-align: justify; text-justify: inter-ideograph;" align="justify"><span style="font-family: 'Times New Roman'; font-size: 10.5pt;"><span dir="auto" style="vertical-align: inherit;"><span dir="auto" style="vertical-align: inherit;">微阵列技术的协同作用</span></span></span></h4>
<p class="p" style="mso-pagination: widow-orphan; text-align: justify; text-justify: inter-ideograph;" align="justify"><span style="mso-spacerun: 'yes'; font-family: 'Times New Roman'; mso-fareast-font-family: 宋体; font-size: 10.5000pt; mso-font-kerning: 0.0000pt;"><span dir="auto" style="vertical-align: inherit;"><span dir="auto" style="vertical-align: inherit;">尽管新一代测序技术（NGS）在测序深度方面无可匹敌，但微阵列仍然是进行全面表达谱分析的强大而高效的工具。微阵列提供了一种高通量、经济高效的解决方案，可以同时分析数千个基因的表达水平。</span></span></span>

<p class="p" style="mso-pagination: widow-orphan; text-align: justify; text-justify: inter-ideograph;" align="justify"><span style="mso-spacerun: 'yes'; font-family: 'Times New Roman'; mso-fareast-font-family: 宋体; font-size: 10.5000pt; mso-font-kerning: 0.0000pt;"><span dir="auto" style="vertical-align: inherit;"><span dir="auto" style="vertical-align: inherit;">尤其是在临床前药物发现和大规模队列研究中，</span></span></span><span class="15" style="font-family: 'Times New Roman'; color: #0000ff; font-size: 10.5pt;"><span dir="auto" style="vertical-align: inherit;"><span dir="auto" style="vertical-align: inherit;">基于微阵列的肿瘤谱分析</span></span></span><span style="mso-spacerun: 'yes'; font-family: 'Times New Roman'; mso-fareast-font-family: 宋体; font-size: 10.5000pt; mso-font-kerning: 0.0000pt;"><span dir="auto" style="vertical-align: inherit;"><span dir="auto" style="vertical-align: inherit;">能够提供可靠的转录组特征数据。通过比较健康组织与恶性组织（或对特定药物有反应者与无反应者）的基因表达谱，研究人员可以识别新的治疗靶点和信号通路失调。除了基因表达分析外，专用微阵列还广泛用于DNA甲基化谱分析和单核苷酸多态性（SNP）基因分型，从而提供重要的表观遗传和遗传背景信息，与NGS数据形成互补。</span></span></span>

<h4 style="mso-pagination: widow-orphan; text-align: justify; text-justify: inter-ideograph;" align="justify"><span style="font-family: 'Times New Roman'; font-size: 10.5pt;"><span dir="auto" style="vertical-align: inherit;"><span dir="auto" style="vertical-align: inherit;">未来：多组学与人工智能的融合</span></span></span></h4>
<p class="p" style="mso-pagination: widow-orphan; text-align: justify; text-justify: inter-ideograph;" align="justify"><span style="mso-spacerun: 'yes'; font-family: 'Times New Roman'; mso-fareast-font-family: 宋体; font-size: 10.5000pt; mso-font-kerning: 0.0000pt;"><span dir="auto" style="vertical-align: inherit;"><span dir="auto" style="vertical-align: inherit;">肿瘤学研究的最新趋势是将这些不同的技术整合到一个统一的&ldquo;多组学&rdquo;方法中。通过将来自新一代测序（NGS）的基因组突变数据与来自微阵列的转录组和表观遗传数据相结合，研究人员可以构建高度精确的预测模型。</span></span></span>

<p class="p" style="mso-pagination: widow-orphan; text-align: justify; text-justify: inter-ideograph;" align="justify"><span style="mso-spacerun: 'yes'; font-family: 'Times New Roman'; mso-fareast-font-family: 宋体; font-size: 10.5000pt; mso-font-kerning: 0.0000pt;"><span dir="auto" style="vertical-align: inherit;"><span dir="auto" style="vertical-align: inherit;">此外，生成式人工智能和机器学习算法现在正被应用于这些庞大的数据集，以发现隐藏的生物网络并以前所未有的准确度预测患者的反应。</span></span></span>

<h4 style="mso-pagination: widow-orphan; text-align: justify; text-justify: inter-ideograph;" align="justify"><span style="font-family: 'Times New Roman'; font-size: 10.5pt;"><span dir="auto" style="vertical-align: inherit;"><span dir="auto" style="vertical-align: inherit;">加速您的免疫肿瘤学研究</span></span></span></h4>
<p class="p" style="mso-pagination: widow-orphan; text-align: justify; text-justify: inter-ideograph;" align="justify"><span style="mso-spacerun: 'yes'; font-family: 'Times New Roman'; mso-fareast-font-family: 宋体; font-size: 10.5000pt; mso-font-kerning: 0.0000pt;"><span dir="auto" style="vertical-align: inherit;"><span dir="auto" style="vertical-align: inherit;">肿瘤分子谱分析的复杂性不仅需要最先进的平台，还需要深厚的生物信息学专业知识。Creative Biolabs 提供端到端的肿瘤谱分析服务，可根据您的具体临床前研究需求量身定制。无论您是通过高通量 NGS 鉴定新型生物标志物，还是利用微阵列进行大规模基因表达分析，我们全面的技术组合都能加速您从发现到临床应用的进程。</span></span></span>

<p class="MsoNormal" style="text-align: justify; text-justify: inter-ideograph;" align="justify"><span style="mso-spacerun: 'yes'; font-family: 'Times New Roman'; mso-fareast-font-family: 宋体; font-size: 10.5000pt; mso-font-kerning: 1.0000pt;"> </span>