基于模式的（Silva）分类法是预测侵袭性HPV相关子宫颈内膜腺癌（HPVA）的结果已经成熟可再现的方法，因为这些肿瘤基本上是阶段相关的。以前的研究利用有针对性的测序已经表明，突变基因型和侵袭模式之间存在相关性。然而，没有使用全面的分子检测探索这种关联。针对454个基因的面板进行了大规模平行测序的侵袭性HPVA的临床病理学数据，包括侵袭模式（Silva A，B和C组）。与入侵模式相关的致病性改变、分子标志、肿瘤突变负担（TMB）和拷贝数改变（CNA）进行了相关性分析。共有45个侵袭性HPVA（11个模式A、17个模式B和17个模式C的肿瘤）。模式A的患者在没有涉及淋巴结或出现复发的情况下在I期就诊（对于随访时间超过2个月的患者）。B和C组的患者大多也呈I期，淋巴结为阴性，但复发的频率更高。17例B组和1例C组的HPVA有淋巴管内侵犯（LVI）。仅在Silva C型肿瘤（5/17）中检测到APOBEC突变标记，并且仅在破坏性侵袭性HPVA（模式B和C）中检测到有致病性的PIK3CA变化。当将病例分为低风险（没有LVI的A型和B型）和高风险（带LVI的B型和C型）时，发现高风险肿瘤富集于PIK3CA、ATRX和ERBB2的突变。低风险和高风险模式瘤之间的TMB存在统计学上的显着差异（p = 0.006），同时与APOBEC标记有关的C型瘤的TMB也存在显着差异（p = 0.002）。CNA的负荷从模式A增加到C。我们的研究进一步表明，HPVA中的关键分子事件与肿瘤形态的侵袭性质和侵袭性有关。带有LVI的B型肿瘤与C型肿瘤聚集在一起，而没有LVI的B型肿瘤在基因型上接近模式A。我们的研究为将Silva系统整合为低风险（A型 + B型没有LVI）和高风险（带LVI的B型和C型）提供了生物学基础。本文受版权保护。版权所有。

The pattern-based (Silva) classification of invasive HPV-associated endocervical adenocarcinomas (HPVA) is an established and reproducible method to predict outcomes for this otherwise stage-dependent group of tumors. Previous studies utilizing targeted sequencing have shown a correlation between mutational profiles and invasive pattern. However, such correlation has not been explored using comprehensive molecular testing.Clinicopathologic data including invasive pattern (Silva groups A, B, and C) was collected for a cohort of invasive HPVA, which previously underwent massive parallel sequencing using a panel covering 447 genes. Pathogenic alterations, molecular signatures, tumor mutational burden (TMB), and copy number alterations (CNA) were correlated with pattern of invasion.45 HPVA (11 pattern A, 17 pattern B and 17 pattern C tumors) were included. Patients with pattern A presented at stage I with no involved lymph nodes or evidence of recurrence (in those with > 2 months of follow-up). Patterns B and C patients also mostly presented at stage I with negative lymph nodes but had greater frequency of recurrence. 3/17 pattern B and 1/17 pattern C HPVAs harbored lymphovascular space invasion (LVI). APOBEC mutational signature was detected only in Silva pattern C tumors (5/17), and pathogenic PIK3CA changes were detected only in destructively invasive HPVA (patterns B and C). When cases were grouped as low-risk (pattern A and pattern B without LVI) and high-risk (pattern B with LVI and pattern C), high-risk tumors were enriched in mutations in PIK3CA, ATRX, and ERBB2. There was a statistically significant difference in TMB between low-risk and high-risk pattern tumors (p=0.006), as well as between Pattern C tumors with and without an APOBEC signature (p=0.002). CNA burden increased from pattern A to C.Our findings further indicate that key molecular events in HPVA correlate with the morphologic invasive properties of the tumor and their aggressiveness. Pattern B tumors with LVI clustered with pattern C tumors, whereas pattern B tumors without LVI approached pattern A genotypically. Our study provides a biologic foundation for consolidating the Silva system into low-risk (pattern A + B without LVI) and high-risk (pattern B with LVI and pattern C) categories.This article is protected by copyright. All rights reserved.