Small cell carcinoma of the uterine cervix: a multi-institutional experience

Advancements in the Understanding of Small-Cell Neuroendocrine Cervical Cancer: Where We Stand and What Lies Ahead

Small-cell neuroendocrine cervical carcinoma (SCNCC) is a rare yet aggressive gynecological malignancy associated with dismal clinical outcomes. Its rarity has led to a limited number of retrospective studies and an absence of prospective research, posing significant challenges for evidence-based treatment approaches. As a result, most gynecologic oncology centers have limited experience with this tumor, emphasizing the urgent need for a comprehensive review and summary. This article systematically reviews the pathogenesis, immunohistochemical and molecular characteristics, prognostic factors, and clinical management of gynecologic SCNCC. We specifically focused on reviewing the distinct genomic characteristics of SCNCC identified via next-generation sequencing technologies, including loss of heterozygosity (LOH), somatic mutations, structural variations (SVs), and microRNA alterations. The identification of these actionable genomic events offers promise for discovering new molecular targets for drug development and enhancing therapeutic outcomes. Additionally, we delve deeper into key clinical challenges, such as determining the optimal treatment modality between chemoradiation and surgery for International Federation of Gynecology and Obstetrics (FIGO) stage I phase patients within a precision stratification framework, as well as the role of targeted therapy within the homologous recombination (HR) pathway, immune checkpoint inhibitors (ICIs), and prophylactic cranial irradiation (PCI) in the management of SCNCC. Finally, we anticipate the utilization of multiple SCNCC models, including cancer tissue-originated spheroid (CTOS) lines and patient-derived xenografts (PDXs), to decipher driver events and develop individualized therapeutic strategies for clinical application.

Quantitative proteomics analysis in small cell carcinoma of cervix reveals novel therapeutic targets

BACKGROUND

As a rare pathologic subtype, small cell carcinoma of the cervix (SCCC) is characterized by extensive aggressiveness and resistance to current therapies. To date, our knowledge of SCCC origin and progression is limited and sometimes even controversial. Herein, we explored the whole-protein expression profiles in a panel of SCCC cases, aiming to provide more evidence for the precise diagnosis and targeting therapy.

METHODS

Eighteen SCCC samples and six matched normal cervix tissues were collected from January 2013 to December 2017. Data independent acquisition mass spectrometry (DIA) was performed to discriminate the different proteins (DEPs) associated with SCCC. The expression of CDN2A and SYP in corresponding SCCC tissues was verified using immunohistochemistry. GO and KEGG enrichment analyses were used to identify the key DEPs related to SCCC development and tumor recurrence.

RESULTS

As a result, 1311 DEPs were identified in SCCC tissues (780 up-regulated and 531 down-regulated). In up-regulated DEPs, both GO analysis and KEGG analysis showed the most enriched were related to DNA replication (including nuclear DNA replication, DNA-dependent DNA replication, and cell cycle DNA replication), indicating the prosperous proliferation in SCCC. As for the down-regulated DEPs, GO analysis showed that the most enriched functions were associated with extracellular matrix collagen-containing extracellular matrix. KEGG analysis revealed that the DEPs were enriched in Complement and coagulation cascades, proteoglycans in cancer, and focal adhesion-related pathways. Down-regulation of these proteins could enhance the mobility of cancer cells and establish a favorable microenvironment for tumor metastasis, which might be accounted for the frequent local and distant metastasis in SCCC. Surprisingly, the blood vessels and circulatory system exhibit a down-regulation in SCCC, which might be partly responsible for its resistance to anti-angiogenic regimens. In the stratification analysis of early-stage tumors, a group of enzymes involved in the cancer metabolism was discriminated in these recurrence cases.

CONCLUSIONS

Using quantitative proteomics analysis, we first reported the whole-protein expression profiles in SCCC. Significant alterations were found in proteins associated with the enhancement of DNA replication and cellular motility. Besides the association with mitosis, a unique metabolic feature was detected in cases with tumor recurrence. These findings provided novel targets for disease surveillance and treatments, which warranted further validation in the future.

Prognostic value of apparent diffusion coefficient in neuroendocrine carcinomas of the uterine cervix

Objectives

This research was designed to examine the associations between the apparent diffusion coefficient (ADC) values and clinicopathological parameters, and to explore the prognostic value of ADC values in predicting the International Federation of Gynecology and Obstetrics (FIGO) stage and outcome of patients suffering from neuroendocrine carcinomas of the uterine cervix (NECCs).

Methods

This retrospective study included 83 patients with NECCs, who had undergone pre-treatment magnetic resonance imaging (MRI) between November 2002 and June 2019. The median follow-up period was 50.7 months. Regions of interest (ROIs) were drawn manually by two radiologists. ADC values in the lesions were calculated using the Functool software. These values were compared between different clinicopathological parameters groups. The Kaplan–Meier approach was adopted to forecast survival rates. Prognostic factors were decided by the Cox regression method.

Results

In the cohort of 83 patients, nine, 42, 23, and nine patients were in stage I, II, III, and IV, respectively. ADCmean, ADCmax, and ADCmin were greatly lower in stage IIB–IVB than in stage I–IIA tumours, as well as in tumours measuring ≥ 4 cm than in those < 4 cm. ADCmean, FIGO stage, and age at dianosis were independent prognostic variables for the 5-year overall survival (OS). ADCmin, FIGO stage, age at diagnosis and para-aortic lymph node metastasis were independent prognostic variables for the 5-year progression-free survival (PFS) in multivariate analysis. For surgically treated patients (n = 45), ADCmax was an independent prognostic parameter for both 5-year OS and 5-year PFS.

Conclusions

ADCmean, ADCmin, and ADCmax are independent prognostic factors for NECCs. ADC analysis could be useful in predicting the survival outcomes in patients with NECCs.

Cells with stem-like properties are associated with the development of HPV18-positive cervical cancer

The cellular origins of cervical cancer and the histological differentiation of human papillomavirus (HPV)-infected cells remain unexplained. To gain new insights into the carcinogenesis and histological differentiation of HPV-associated cervical cancer, we focused on cervical cancer with mixed histological types. We conducted genomic and transcriptomic analyses of cervical cancers with mixed histological types. The commonality of the cellular origins of these cancers was inferred using phylogenetic analysis and by assessing the HPV integration sites. Carcinogenesis was estimated by analyzing human gene expression profiles in different histological types. Among 42 cervical cancers with known HPV types, mixed histological types were detected in four cases, and three of them were HPV18-positive. Phylogenetic analysis of these three cases revealed that the different histological types had a common cell of origin. Moreover, the HPV-derived transcriptome and HPV integration sites were common among different histological types, suggesting that HPV integration could occur before differentiation into each histological type. Human gene expression profiles indicated that HPV18-positive cancer retained immunologically cold components with stem cell properties. Mixed cervical cancer has a common cellular origin among different histological types, and progenitor cells with stem-like properties may be associated with the development of HPV18-positive cervical cancer.

A Nomogram Model Based on Neuroendocrine Markers for Predicting the Prognosis of Neuroendocrine Carcinoma of Cervix

BACKGROUND

Combining traditional clinical parameters with neuroendocrine markers to construct a nomogram model to predict the postoperative recurrence of neuroendocrine carcinoma of cervix (NECC).

METHODS

A total of 257 patients were included in this study. Univariate and multivariate Cox regression analyses were used to establish a nomogram model in the training cohorts, which was further validated in the validation cohorts. The calibration curve was used to conduct the internal and external verification of the model.

RESULTS

Overall, 41 relapse cases were observed in the training (23 cases) and validation (18 cases) cohorts. The univariate analysis preliminarily showed that FIGO stage, stromal invasion, nerve invasion, lymph vascular space invasion, lymph node involvement, cervical-uterine junction invasion and CgA were correlated with NECC recurrence. The multivariate analysis further confirmed that FIGO stage (p = 0.023), stromal invasion (p = 0.002), lymph vascular space invasion (p = 0.039) and lymph node involvement (p = 0.00) were independent risk factors for NECC recurrence, which were ultimately included in the nomogram model. In addition, superior consistency indices were demonstrated in the training (0.863, 95% CI 0.784-0.942) and validation (0.884, 95% CI 0.758-1.010) cohorts.

CONCLUSIONS

The established nomogram model combining traditional clinical parameters with neuroendocrine markers can reliably and accurately predict the recurrence risks in NECC patients.

Cervical cancer heterogeneity: a constant battle against viruses and drugs

Cervical cancer is the first identified human papillomavirus (HPV) associated cancer and the most promising malignancy to be eliminated. However, the ever-changing virus subtypes and acquired multiple drug resistance continue to induce failure of tumor prevention and treatment. The exploration of cervical cancer heterogeneity is the crucial way to achieve effective prevention and precise treatment. Tumor heterogeneity exists in various aspects including the immune clearance of viruses, tumorigenesis, neoplasm recurrence, metastasis and drug resistance. Tumor development and drug resistance are often driven by potential gene amplification and deletion, not only somatic genomic alterations, but also copy number amplifications, histone modification and DNA methylation. Genomic rearrangements may occur by selection effects from chemotherapy or radiotherapy which exhibits genetic intra-tumor heterogeneity in advanced cervical cancers. The combined application of cervical cancer therapeutic vaccine and immune checkpoint inhibitors has become an effective strategy to address the heterogeneity of treatment. In this review, we will integrate classic and recently updated epidemiological data on vaccination rates, screening rates, incidence and mortality of cervical cancer patients worldwide aiming to understand the current situation of disease prevention and control and identify the direction of urgent efforts. Additionally, we will focus on the tumor environment to summarize the conditions of immune clearance and gene integration after different HPV infections and to explore the genomic factors of tumor heterogeneity. Finally, we will make a thorough inquiry into completed and ongoing phase III clinical trials in cervical cancer and summarize molecular mechanisms of drug resistance among chemotherapy, radiotherapy, biotherapy, and immunotherapy.

A Prognostic Nomogram for Predicting Overall Survival in Patients With Small-Cell Carcinoma of the Uterine Cervix: A SEER Population-Based Study

Background: This study aimed to develop a prognostic model based on the Surveillance, Epidemiology, and End Results (SEER) database to predict the overall survival (OS) of small cell carcinoma of the uterine cervix (SmCC). Methods: Between 1975 and 2016, a total of 401 patients were included, and their comprehensive sociodemographic and clinicopathological characteristics were collected. Univariate and multivariate Cox regression models were used to screen for independent prognostic factors. The identified factors were used to conduct a nomogram for predicting the OS of SmCC. The performance of the nomogram was determined using area under the receiver operating characteristic curve (AUC), concordance index (C-index), calibration curve, and decision curve analysis (DCA) metrics. Results: The median survival time of all patients was about 24 months (95% confidence interval [95% CI] [1.50-2.17]). Age (hazard ratio [HR] = 1.693 for 45-59 vs 21-34, 95% CI [1.140-2.513], P = .009; HR = 2.836 for 60-92 vs 21-34, 95% CI [1.851-4.345], P < .001), positive nodes (HR = 2.384, 95% CI [1.437-3.955], P < .001), regional nodes number ≥12 (HR = 0.500, 95% CI [0.282-0.886], P = .018), and treatment method (HR = 0.409 for surgery vs no, 95% CI [0.267-0.628], P < .001; HR = 0.649 for chemotherapy vs no, 95% CI [0.478-0.881)], P = .006) were independent factors of OS. Young patients who had surgical resection or chemotherapy, negative lymph nodes, and regional lymph nodes ≥12 had a longer survival time. These clinical factors were utilized to construct a nomogram for predicting OS. The AUC and C-index were higher than 0.7, indicating the good discriminating ability of the nomogram. The calibrations were all around the 45-degree line, indicating excellent consistency between the prediction of the model and actual observations. The DCA plots supported the clinical utility of the nomogram. Conclusion: The constructed nomogram is expected to help predict the prognosis of SmCC and guide patient treatment.

A real-world, population-based study of the trends for incidence and prognosis in high-grade neuroendocrine tumor of cervix

To explore the incidence and prognosis trends for high-grade cervical neuroendocrine tumor (HGCNET) and construct a nomogram to predict prognosis for HGCNET. Annual age-adjusted incidence of HGCNET from 1975 to 2015 was retrieved from the Surveillance, Epidemiology, and End Results program, the linear regression, poisson regression and annual percentage changes were used to assess the incidence trend. Also, trends for relative survival (RS) and overall survival (OS) in HGCNET patients from 1975 to 2015 were evaluated. From 1988 to 1975, 514 HGCNET patients were selected and divided into two cohorts with a ratio of 7:3. Nomogram to predict OS for these patients was constructed and validated. The incidence trend for HGCNET was unchanged in the past four decades (P = 0.734), but the proportion of HGCNET in diagnosed cervical cancer slightly increased from 0.9% in 1975 to 1.9% in 2015 (P < 0.001). The 5-year RS and OS for HGCNET in the study periods decreased steadily (RS: P = 0.009; OS: P = 0.008). Nomogram incorporating age, T stage, lymph-node positive, distant metastasis and surgery was constructed. The C-index of the nomogram was 0.716 (0.680-0.752), which was higher than the FIGO staging system. The incidence of HGCNET remained unchanged in the past four decades but the proportion of HGCNET has slightly increased. Besides, a steadily decreasing survival for HGCNET was observed in the study periods. A nomogram was constructed to better predict prognosis for HGCNET.

Effects of Perioperative Inflammatory Response in Cervical Cancer: Laparoscopic versus Open Surgery

There are few studies between postoperative neutrophil to lymphocyte ratio (NLR) and survival in cervical cancer. We compared postoperative changes in NLR according to surgical methods and analyzed the effect of these changes on 5-year mortality of cervical cancer patients. A total of 929 patients were assigned to either the laparoscopic radical hysterectomy (LRH) (n = 721) or open radical hysterectomy (ORH) (n = 208) group. Propensity score matching analysis compared the postoperative NLR changes between the two groups, and multivariate logistic regression analysis evaluated the association between NLR changes and 5-year mortality. Surgical outcomes between the two groups were also compared. In the LRH group, NLR changes at postoperative day (POD) 0 and POD 1 were significantly lower than in the ORH group after matching (NLR change at POD 0, 10.4 vs. 14.3, p < 0.001; NLR change at POD 1, 3.5 vs. 5.4, p < 0.001). In multivariate logistic regression analysis, postoperative NLR change was not associated with 5-year mortality (2nd quartile: OR 1.55, 95% CI 0.56–4.29, p = 0.401; 3rd quartile: OR 0.90, 95% CI 0.29–2.82, p = 0.869; 4th quartile: OR 1.40, 95% CI 0.48–3.61, p = 0.598), whereas preoperative NLR was associated with 5-year mortality (OR 1.23, 95% CI 1.06–1.43, p = 0.005). After matching, there were no significant differences in surgical outcomes between the two groups. There were significantly fewer postoperative changes of NLR in the LRH group. However, the extent of these NLR changes was not associated with 5-year mortality. By contrast, preoperative NLR was associated with 5-year mortality.