Stromal invasion pattern identifies patients at lowest risk of lymph node metastasis in HPV-associated endocervical adenocarcinomas, but is irrelevant in adenocarcinomas unassociated with HPV

Stolnicu, Simona; Bârsan, Iulia; Hoang, L.; Patel, Prusha; Terinte, Cristina; Pesci, Anna; Aviel‐Ronen, Sarit; Kiyokawa, Takako; Alvarado‐Cabrero, Isabel; Oliva, Esther; Park, K.J.; Abu-Rustum, N.R.; Pike, Malcolm C.; Soslow, Robert A.

doi:10.1016/j.ygyno.2018.04.570

Cited by 38 publications

(43 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Consistent with our results, a recent study showed that Pattern Classification is only suitable for HPVrelated ADCs. 21 Studies have provided increasing evidence that the predictive index of Pattern Classification correlates with LVSI, status of LN metastasis, tumour size, FIGO stage, tumour thickness or DOI, perineural invasion, and recurrence-free survival. 16,17 Invasion pattern as well as tumour size, DOI, LVSI, and LN metastasis have been reported to be independent predictors of recurrence-free and disease-specific survival in a multivariate analysis.…”

Section: Discussionmentioning

confidence: 99%

“…16,17 Invasion pattern as well as tumour size, DOI, LVSI, and LN metastasis have been reported to be independent predictors of recurrence-free and disease-specific survival in a multivariate analysis. 21 However, whether LN metastasis or LVSI is an independent predictor for overall survival remains controversial. Roma et al reported that LVSI is not an independent predictor of outcome if LN status is considered.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Expanded study on the risk of lymphovascular space invasion and lymph node metastasis of endocervical adenocarcinoma using Pattern Classification: a single-centre analysis of 213 cases

et al. 2019

View full text Add to dashboard Cite

A new three-tiered Pattern Classification system for usualtype endocervical adenocarcinomas (U-EACs) recommends using tumour invasive patterns rather than depth of invasion (DOI) and horizontal spread to categorise tumours. Tumours categorised by Pattern Classification are associated with lymph node (LN) metastasis and adverse outcomes. The aim of this study is to further explore the potential of Pattern Classification in surgical pathology practice. A total of 213 consecutive cases [201 U-EACs and 12 gastric-type adenocarcinomas (GACs)] diagnosed between 2006 and 2017 was retrospectively analysed. Clinicopathological data included age at diagnosis, DOI measurement, the status of lymphovascular space invasion (LVSI) and LN metastasis, and the number of LVSI foci, dissected and metastatic LNs. Immunostaining for CD34 and D2-40 was performed to identify LVSI in 14 challenging cases. Overall, mean age at diagnosis was 51 years (range 23-75). LVSI and LN metastasis occurred in 128 (60.1%, 128/213) and 42 (20.5%, 42/205) cases, respectively. Also, 28 (13.1%), 21 (9.9%), and 164 (77.0%) patients had pattern A, B, and C tumours, respectively. Patients with pattern C tumours had the oldest age at diagnosis (p=0.007), the highest incidence of LVSI and LN metastasis, and the highest DOI (p<0.001). Due to a highly heterogeneous growth pattern, pattern C U-EACs were stratified into four subgroups: C1, C2 and C3 corresponded to solid, extensive linear destructive, and band-like lymphocytic infiltrate growth patterns, respectively, and C4 included diffuse destructive, confluent, micropapillary and mixed growth pattern. C2 and C3 subgroup tumours had lower incidence of LVSI (20% and 40%, respectively) than the other two subgroups (p<0.001). None of the patients with C2 and C3 subgroup had LN metastasis and 3 LVSI foci. All GACs belonged to pattern C and had deeper stromal invasion (p=0.008), higher incidence of LN metastasis (p=0.001), and larger quantity of LVSI foci (p=0.008) and metastatic LNs (p=0.004) than those of pattern C U-ECAs. Number of LVSI foci were moderately positively correlated with LN metastasis status (p<0.001, g=0.489) or number of metastatic LNs (p<0.001, g=0.409). Our study further supports that Pattern Classification is a system easy to follow, which has a strong correlation to LVSI and an effective predictability for LN metastasis. Extensive linear destructive and band-like lymphocytic infiltrate growth patterns in pattern C U-EACs need to be recognised, as they behave less aggressively than that for the other growth pattern subgroups. Our study supports that Pattern Classification can be routinely applied to guide therapies for patients with U-EACs.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Expanded study on the risk of lymphovascular space invasion and lymph node metastasis of endocervical adenocarcinoma using Pattern Classification: a single-centre analysis of 213 cases

et al. 2019

View full text Add to dashboard Cite

show abstract

“…It should be emphasised that pattern classification applies only to HPV‐associated adenocarcinoma and not any of the non‐HPV subtypes. Two independent studies have shown that all non‐HPV‐associated adenocarcinomas were categorised as pattern C …”

Section: Classification Of Endocervical Adenocarcinomamentioning

confidence: 99%

Cervical adenocarcinoma: integration of HPV status, pattern of invasion, morphology and molecular markers into classification

Park

2019

Histopathology

View full text Add to dashboard Cite

Cervical adenocarcinoma is a heterogenous group of tumours with various aetiologies, molecular drivers, morphologies, response to treatment and prognosis. It has become evident that human papillomavirus (HPV) infection does not drive all adenocarcinomas, and appropriate classification is critical for patient management, especially in the era of the HPV vaccine and HPV‐only screening. Identified as one of the most important developments in gynaecological pathology during the past 50 years, the separation of cervical adenocarcinomas into HPV‐associated (HPVA) and HPV‐independent has resulted in a transformation of the classification system for cervical adenocarcinomas. HPVA has been traditionally subclassified by morphology, such as usual type (UEA), mucinous and villoglandular, etc. However, it has become evident that cell type‐based histomorphological classification is not clinically meaningful, and the newly proposed International Endocervical Adenocarcinoma Criteria and Classification (IECC) is a necessary and relevant break from this prior system. Non‐HPV‐associated adenocarcinomas can be divided by their distinct morphology and molecular genomics with very different responses to standard therapies and potential for future targeted therapies. These include gastric‐type, clear‐cell, mesonephric and endometrioid adenocarcinomas. So‐called ‘serous’ carcinomas of the cervix probably represent morphological variants of UEA or drop metastases from uterine or adnexal serous carcinomas, and the existence of true cervical serous carcinomas is in question. This review will discuss the advances since WHO 2014, and how HPV status, pattern of invasion as described by Silva and colleagues, histological features and molecular markers can be used to refine diagnosis and prognostication for patients with cervical adenocarcinoma.

show abstract

“…The validity of this new classi cation is supported by HPV status and, at present, by limited clinical data (8,9). In the present study, the following HPV tests were used: PCR, genotype, RNAscope, and immunochemistry (IHC) against p16 protein.…”

Section: Introductionmentioning

confidence: 90%

Prognostic nomogram for patients with invasive endocervical adenocarcinoma incorporating HPV E6/E7 mRNA in situ hybridization and clinical characteristics

Liu¹,

Chen²,

Yan³

et al. 2020

Preprint

View full text Add to dashboard Cite

Background: Human papillomavirus (HPV) E6/E7 mRNA in situ hybridization (HPV E6/E7 RNAscope) appears to be a sensitive and specific method. We aimed to examine the diagnostic and prognostic utility of this technique in endocervical adenocarcinoma (ECA) and build a useful prognostic nomogram model using this approach. Methods: The model was constructed from a retrospective study of 200 patients with ECA who had undergone surgery at Sun Yat-sen University Cancer Center between 2010 and 2014. The model's predictive efficiency and discriminative capability were defined by a concordance index (C-index) and calibration curve. Results: The overall sensitivity and specificity of HPV E6/E7 RNAscope for distinguishing HPV-associated adenocarcinoma (HPVA) from non HPV-associated adenocarcinoma (NHPVA) in the whole cohort were 75.8% and 80%, respectively, compared to 60.2% and 90.0% for p16 immunohistochemistry, 80.5% and 80.0% for HPV DNA, and 63.3% and 50% for HPV genotype. The independent factors derived from multivariable analysis of the whole cohort to predict overall survival (OS) were age, lymphovascular invasion (LVI), lymph node involvement (LNI), and HPV E6/E7 RNAscope, which were all incorporated into the nomogram with (nomogram B) or without (nomogram A) FIGO stage and treatment. The C-index of nomogram A for predicting OS was 0.825 (p = 0.002 and p < 0.001), which was significantly higher than the C-index for FIGO stage (0.653) and treatment (0.578). No significant difference occurred between nomograms A (0.825) and B (0.836). Furthermore, a risk stratification system was established to accurately stratify patients with ECA into two subgroups with significantly different prognosis. Conclusions: HPV E6/E7 RNAscope is highly specific for ECA, and the proposed nomogram using HPV E6/E7 RNAscope showed more accurate outcome in terms of prognosis in patients with ECA.

show abstract

Stromal invasion pattern identifies patients at lowest risk of lymph node metastasis in HPV-associated endocervical adenocarcinomas, but is irrelevant in adenocarcinomas unassociated with HPV

Abstract: Application of the Silva system is only relevant in HPVA cervical adenocarcinoma.

Cited by 38 publications

References 16 publications

Expanded study on the risk of lymphovascular space invasion and lymph node metastasis of endocervical adenocarcinoma using Pattern Classification: a single-centre analysis of 213 cases

Expanded study on the risk of lymphovascular space invasion and lymph node metastasis of endocervical adenocarcinoma using Pattern Classification: a single-centre analysis of 213 cases

Cervical adenocarcinoma: integration of HPV status, pattern of invasion, morphology and molecular markers into classification

Prognostic nomogram for patients with invasive endocervical adenocarcinoma incorporating HPV E6/E7 mRNA in situ hybridization and clinical characteristics

Contact Info

Product

Resources

About